Baker, Rachel E., Wenchang Yang, Gabriel A Vecchi, and Saki Takahashi, July 2024: Increasing intensity of enterovirus outbreaks projected with climate change. Nature Communications, 15, 6466, DOI:10.1038/s41467-024-50936-3. Abstract
Pathogens of the enterovirus genus, including poliovirus and coxsackieviruses, typically circulate in the summer months suggesting a possible positive association between warmer weather and transmission. Here we evaluate the environmental and demographic drivers of enterovirus transmission, as well as the implications of climate change for future enterovirus circulation. We leverage pre-vaccination era data on polio in the US as well as data on two enterovirus A serotypes in China and Japan that are known to cause hand, foot, and mouth disease. Using mechanistic modeling and statistical approaches, we find that enterovirus transmission appears positively correlated with temperature although demographic factors, particularly the timing of school semesters, remain important. We use temperature projections from Coupled Model Intercomparison Project Phase 6 (CMIP6) to simulate future outbreaks under late 21st-century climate change for Chinese provinces. We find that outbreak size increases with climate change on average, though results differ across climate models depending on the degree of wintertime warming. In the worst-case scenario, we project peak outbreaks in some locations could increase by up to 40%.
Eusebi, Ryan, Gabriel A Vecchi, Ching-Yao Lai, and Mingjing Tong, January 2024: Realistic tropical cyclone wind and pressure fields can be reconstructed from sparse data using deep learning. Communications Earth and Environment, 5, 8, DOI:10.1038/s43247-023-01144-2. Abstract
Tropical cyclones are responsible for large-scale loss of life and property1,2,3,4, motivating accurate risk assessment and forecasting. These objectives require accurate reconstructions of storms’ wind and pressure fields which assimilate real-time observations5,6,7,8,9, but current methods used for these reconstructions remain computationally expensive and limited10. Here, we show that a physics-informed neural network11,12 can be a promising and computationally efficient algorithm for tropical cyclone data assimilation. Using synthetic training data sparsely sampled from hurricanes simulated in a forecast model, a physics-informed neural network is able to reconstruct full realistic 2- and 3-dimensional wind and pressure fields which capture key features of the cyclone. We also demonstrate how a set of sparse, real-time observations, can be used to accurately reconstruct Hurricane Ida. Our results highlight how recent advances in deep learning can augment data assimilation schemes. The methods are also general and can be applied to other flow problems.
Projections of future tropical cyclone frequency are uncertain, ranging from a slight increase to a considerable decrease according to climate models. Estimation of how much the Earth’s surface temperature warms in response to greenhouse gas increase, quantified by effective climate sensitivity, is also uncertain. These two uncertainties have historically been studied independently as they concern different scales: One quantifies the extreme weather and the other the mean climate. Here, we show that these two uncertainties are not independent and are both influenced by the response of tropical clouds to warming. Across climate models, we show an anticorrelation between shortwave cloud radiative feedback and changes in the frequency of seed vortices, a prevalent type of tropical cyclone precursors. We further show an anticorrelation between effective climate sensitivity and tropical cyclone frequency changes, suggesting that global tropical cyclone frequency tends to decrease more substantially in models with larger temperature increase.
This study investigates the relative roles of sea surface temperature–forced climate changes and weather variability in driving the observed eastward shift of Atlantic hurricane tracks over the period from 1970 to 2021. A 10-member initial condition ensemble with a ∼25-km horizontal resolution tropical cyclone permitting atmospheric model (GFDL AM2.5-C360) with identical sea surface temperature and radiative forcing time series was analyzed in conjunction with historical hurricane track observations. While a frequency increase was recovered by all the simulations, the observed multidecadal eastward shift in tracks was not robust across the ensemble members, indicating that it included a substantial contribution from weather-scale variability. A statistical model was developed to simulate expected storm tracks based on genesis location and steering flow, and it was used to conduct experiments testing the roles of changing genesis location and changing steering flow in producing the multidecadal weather-driven shifts in storm tracks. These experiments indicated that shifts in genesis location were a substantially larger driver of these multidecadal track changes than changes in steering flow. The substantial impact of weather on tracks indicates that there may be limited predictability for multidecadal track changes like those observed, although basinwide frequency has greater potential for prediction. Additionally, understanding changes in genesis location appears essential to understanding changes in track location.
Menemenlis, Sofia, Gabriel A Vecchi, Kun Gao, James A Smith, and Kai-Yuan Cheng, July 2024: Extreme rainfall risk in Hurricane Ida's extratropical stage: An analysis with convection-permitting ensemble hindcasts. Journal of the Atmospheric Sciences, 81(7), DOI:10.1175/JAS-D-23-0160.1. Abstract
The extratropical stage of Hurricane Ida (2021) brought extreme subdaily rainfall and devastating flooding to parts of eastern Pennsylvania, New Jersey, and New York. We investigate the predictability and character of this event using 31-member ensembles of perturbed initial condition hindcasts with the Tropical Atlantic version of GFDL’s System for High-resolution prediction on Earth-to-Local Domains (T-SHiELD), a ∼13-km global weather forecast model with a ∼3-km nested grid. At lead times of up to 4 days, the ensembles are able to capture the most extreme observed hourly and daily rainfall accumulations but are negatively biased in the spatial extent of heavy precipitation. Large intraensemble differences in the magnitudes and locations of simulated extremes suggest that although impacts were highly localized, risks were widespread. In Ida’s tropical stage, interensemble spread in extreme hourly rainfall is well predicted by large-scale moisture convergence; by contrast, in Ida’s extratropical stage, the most extreme rainfall is governed by mesoscale processes that exhibit chaotic and diverse forms across the ensembles. Our results are relevant to forecasting and communication in advance of extratropical transition and imply that flood preparedness efforts should account for the widespread possibility of severe localized impacts.
The climate simulation frontier of a global storm-resolving model (GSRM; or k-scale model because of its kilometer-scale horizontal resolution) is deployed for climate change simulations. The climate sensitivity, effective radiative forcing, and relative humidity changes are assessed in multiyear atmospheric GSRM simulations with perturbed sea-surface temperatures and/or carbon dioxide concentrations. Our comparisons to conventional climate model results can build confidence in the existing climate models or highlight important areas for additional research. This GSRM’s climate sensitivity is within the range of conventional climate models, although on the lower end as the result of neutral, rather than amplifying, shortwave feedbacks. Its radiative forcing from carbon dioxide is higher than conventional climate models, and this arises from a bias in climatological clouds and an explicitly simulated high-cloud adjustment. Last, the pattern and magnitude of relative humidity changes, simulated with greater fidelity via explicitly resolving convection, are notably similar to conventional climate models.
Yang, Wenchang, Elizabeth Wallace, Gabriel A Vecchi, Jeffrey P Donnelly, Julien Emile-Geay, Gregory J Hakim, Larry W Horowitz, Richard M Sullivan, Robert Tardif, Peter J Van Hengstum, and Tyler S Winkler, January 2024: Last millennium hurricane activity linked to endogenous climate variability. Nature Communications, 15, 816, DOI:10.1038/s41467-024-45112-6. Abstract
Despite increased Atlantic hurricane risk, projected trends in hurricane frequency in the warming climate are still highly uncertain, mainly due to short instrumental record that limits our understanding of hurricane activity and its relationship to climate. Here we extend the record to the last millennium using two independent estimates: a reconstruction from sedimentary paleohurricane records and a statistical model of hurricane activity using sea surface temperatures (SSTs). We find statistically significant agreement between the two estimates and the late 20th century hurricane frequency is within the range seen over the past millennium. Numerical simulations using a hurricane-permitting climate model suggest that hurricane activity was likely driven by endogenous climate variability and linked to anomalous SSTs of warm Atlantic and cold Pacific. Volcanic eruptions can induce peaks in hurricane activity, but such peaks would likely be too weak to be detected in the proxy record due to large endogenous variability.
The response of tropical cyclone (TC) frequency to sea surface warming is uncertain in climate models. We hypothesize that one source of uncertainty is the anomalies of large-scale atmospheric radiation in response to climate change, and whose influence on TC frequency is investigated. Given two atmospheric models with opposite TC frequency responses to uniform sea surface warming, we interchange their atmospheric radiation anomalies in experiments with prescribed radiative heating rates. The largest model discrepancy occurs in the western North Pacific, where the TC frequency tends to increase with anomalous large-scale ascent caused by prescribed positive radiation anomalies, while the TC frequency tends to decrease with anomalous large-scale descent caused by prescribed negative radiation anomalies. The model spread in TC frequency response is approximated by the model spread in the frequency response of pre-TC vortices (seeds), which is explained by changes in the large-scale circulation using a downscaling formula known as the seed propensity index. We further generalize the index to predict the influence of large-scale radiation anomalies on TC seed frequency. The results show that model spread in TC and seed frequency response can be reduced when constraining the large-scale radiation anomalies.
Schenkel, Benjamin A., Daniel Chavas, Ning Lin, Thomas R Knutson, Gabriel A Vecchi, and Alan Brammer, January 2023: North Atlantic tropical cyclone outer size and structure remain unchanged by the late twenty-first century. Journal of Climate, 36(2), DOI:10.1175/JCLI-D-22-0066.1359-382. Abstract
There is a lack of consensus on whether North Atlantic tropical cyclone (TC) outer size and structure (i.e., change in outer winds with increasing radius from the TC) will differ by the late twenty-first century. Hence, this work seeks to examine whether North Atlantic TC outer wind field size and structure will change by the late twenty-first century using multiple simulations under CMIP3 SRES A1B and CMIP5 RCP4.5 scenarios. Specifically, our analysis examines data from the GFDL High-Resolution Forecast-Oriented Low Ocean Resolution model (HiFLOR) and two versions of the GFDL hurricane model downscaling climate model output. Our results show that projected North Atlantic TC outer size and structure remain unchanged by the late twenty-first century within nearly all HiFLOR and GFDL hurricane model simulations. Moreover, no significant regional outer size differences exist in the North Atlantic within most HiFLOR and GFDL hurricane model simulations. No changes between the control and late-twenty-first-century simulations exist over the storm life cycle in nearly all simulations. For the simulation that shows significant decreases in TC outer size, the changes are attributed to reductions in storm lifetime and outer size growth rates. The absence of differences in outer size among most simulations is consistent with the process that controls the theoretical upper bound of storm size (i.e., Rhines scaling), which is thermodynamically invariant. However, the lack of complete consensus among simulations for many of these conclusions suggests nontrivial uncertainty in our results.
Smith, James A., Mary Lynn Baeck, Yibing Su, Maofeng Liu, and Gabriel A Vecchi, March 2023: Strange storms: Rainfall extremes from the remnants of Hurricane Ida (2021) in the northeastern US. Water Resources Research, 59(3), DOI:10.1029/2022WR033934. Abstract
On 1 September 2021, the remnants of Hurricane Ida transformed into a lethal variant of tropical cyclone in which unprecedented short-duration rainfall from clusters of supercells produced catastrophic flooding in watersheds of the Northeastern US. Short-duration rainfall extremes from Ida are examined through analyses of polarimetric radar fields and rain gauge observations. Rainfall estimates are constructed from a polarimetric rainfall algorithm that is grounded in specific differential phase shift (KDP) fields. Rainfall accumulations at multiple locations exceed 1000-year values for 1–3 hr time scales. Radar observations show that supercells are the principal agents of rainfall extremes. Record flood peaks occurred throughout the eastern Pennsylvania—New Jersey region; the peak discharge of the Elizabeth River is one of the most extreme in the eastern US, based on the ratio of the peak discharge to the sample 10-year flood at the gaging station. As with other tropical cyclones that have produced record flooding in the Northeastern US, Extratropical Transition was a key element of extreme rainfall and flooding from Ida. Tropical and extratropical elements of the storm system contributed to extremes of atmospheric water balance variables and Convective Available Potential Energy, providing the environment for extreme short-duration rainfall from supercells.
Zhang, Bosong, Brian J Soden, and Gabriel A Vecchi, February 2023: A vertically resolved analysis of radiative feedbacks on moist static energy variance in tropical cyclones. Journal of Climate, 36(4), DOI:10.1175/JCLI-D-22-0199.11125-1141. Abstract
A vertically resolved moist static energy (MSE) variance budget framework is used to diagnose processes associated with the development of tropical cyclones (TCs) in a general circulation model (GCM) under realistic boundary conditions. Previous studies have shown that interactions between radiation and MSE promote TC development. Here, we examine the vertical contributions of radiation and its interactions with MSE by performing several mechanism-denial experiments in which synoptic-scale radiative interactions are suppressed either in the boundary layer or in the free troposphere. Partly suppressing radiative interactions results in a reduction in global TC frequency. However, the magnitude of reduction and structure of the feedback depend on the intensity and structure of the TCs in these mechanism-denial experiments, indicating that both the magnitude and the vertical location of radiative interactions can impact global TC frequency. Using instantaneous 6-hourly outputs, an explicit computation reveals distinct spatial patterns of the advection term: the vertical component is positive in the mid- to upper troposphere, which reflects an upward transport of MSE by deep convection, whereas the horizontal component is positive in the boundary layer. These results illustrate the impact of the vertical distribution of radiative interactions and vertically varied contribution of the advection term in the development of TCs.
Tropical cyclone rapid intensification events often cause destructive hurricane landfalls because they are associated with the strongest storms and forecasts with the highest errors. Multi-decade observational datasets of tropical cyclone behavior have recently enabled documentation of upward trends in tropical cyclone rapid intensification in several basins. However, a robust anthropogenic signal in global intensification trends and the physical drivers of intensification trends have yet to be identified. To address these knowledge gaps, here we compare the observed trends in intensification and tropical cyclone environmental parameters to simulated natural variability in a high-resolution global climate model. In multiple basins and the global dataset, we detect a significant increase in intensification rates with a positive contribution from anthropogenic forcing. Furthermore, thermodynamic environments around tropical cyclones have become more favorable for intensification, and climate models show anthropogenic warming has significantly increased the probability of these changes.
The future projection of tropical cyclone frequency is highly uncertain. Recent multi-model studies showed that the model spread in tropical cyclones is correlated with the model spread in seeds, which are defined as convective weak vortices. However, it was unclear how the model spread is related to the large-scale circulation. Here we apply a downscaling theory recently developed using aquaplanet experiments to explain the seed frequency across four global atmospheric models having different parameterizations of convection and resolutions. The seed frequency has a larger model spread in response to uniform warming than to CO2 doubling or El Niño/La Niña-like sea surface temperature perturbations. Across all climate perturbations, the seed frequency is captured by the downscaling theory, expressed as a seed propensity index. The index highlights the connection between the tropical cyclone seeds and the climatological mean ascent pattern.
Jing, Renzhi, Ning Lin, Kerry A Emanuel, Gabriel A Vecchi, and Thomas R Knutson, December 2021: A comparison of tropical cyclone projections in a high-resolution global climate model and from downscaling by statistical and statistical-deterministic methods. Journal of Climate, 34(23), DOI:10.1175/JCLI-D-21-0071.1. Abstract
In this study, we investigate the response of tropical cyclones (TCs) to climate change by using the Princeton environment-dependent probabilistic tropical cyclone (PepC) model and a statistical-deterministic method to downscale TCs using environmental conditions obtained from the Geophysical Fluid Dynamics Laboratory (GFDL) High-Resolution Forecast-Oriented Low Ocean Resolution (HiFLOR) model, under the representative concentration pathway 4.5 (RCP4.5) emissions scenario for the North Atlantic Ocean basin. The downscaled TCs for the historical climate (1986–2005) are compared with those in the middle (2016–35) and late twenty-first century (2081–2100). The downscaled TCs are also compared with TCs explicitly simulated in HiFLOR. We show that, while significantly more storms are detected in HiFLOR toward the end of the twenty-first century, the statistical-deterministic model projects a moderate increase in TC frequency and PepC projects almost no increase in TC frequency. The changes in storm frequency in all three datasets are not significant in the mid-twenty-first century. All three project that storms will become more intense and the fraction of major hurricanes and category-5 storms will significantly increase in the future climates. However, HiFLOR projects the largest increase in intensity, and PepC projects the least. The results indicate that HiFLOR’s TC projection is more sensitive to climate change effects and that statistical models are less sensitive. Nevertheless, in all three datasets, storm intensification and frequency increase lead to relatively small changes in TC threat as measured by the return level of landfall intensity under the projected climate condition.
Knutson, Thomas R., Maya V Chung, Gabriel A Vecchi, Jingru Sun, Tsung-Lin Hsieh, and Adam J Smith, March 2021: ScienceBrief Review: Climate change is probably increasing the intensity of tropical cyclones [Le Quéré, Corrine, Peter Liss, and Piers Forster (ed.)] In Critical Issues in Climate Change Science, DOI:10.5281/zenodo.4570334. Abstract
Warming of the surface ocean from anthropogenic (human-induced) climate change is likely fuelling more powerful TCs. The destructive power of individual TCs through flooding is amplified by rising sea level, which very likely has a substantial contribution at the global scale from anthropogenic climate change. In addition, TC precipitation rates are projected to increase due to enhanced atmospheric moisture associated with anthropogenic global warming. The proportion of severe TCs (category 3 & 5) has increased, possibly due to anthropogenic climate change. This proportion of very intense TCs (category 4 & 5) is projected to increase, yet most climate model studies project the total number of TCs each year to decrease or remain approximately the same. Additional changes such as increasing rates of rapid intensification, the poleward migration of the latitude of maximum intensity, and a slowing of the forward motion of TCs have been observed in places, and these may be climate change signals emerging from natural variability. While there are challenges in attributing these past observed changes to anthropogenic forcing, models project that with global warming in coming decades some regions will experience increases in rapid intensification, a poleward migration of the latitude of maximum intensity or a slowing of the forward motion of TCs.
Atlantic hurricanes are a major hazard to life and property, and a topic of intense scientific interest. Historical changes in observing practices limit the utility of century-scale records of Atlantic major hurricane frequency. To evaluate past changes in frequency, we have here developed a homogenization method for Atlantic hurricane and major hurricane frequency over 1851–2019. We find that recorded century-scale increases in Atlantic hurricane and major hurricane frequency, and associated decrease in USA hurricanes strike fraction, are consistent with changes in observing practices and not likely a true climate trend. After homogenization, increases in basin-wide hurricane and major hurricane activity since the 1970s are not part of a century-scale increase, but a recovery from a deep minimum in the 1960s–1980s. We suggest internal (e.g., Atlantic multidecadal) climate variability and aerosol-induced mid-to-late-20th century major hurricane frequency reductions have probably masked century-scale greenhouse-gas warming contributions to North Atlantic major hurricane frequency.
Wang, Chenggong, Brian J Soden, Wenchang Yang, and Gabriel A Vecchi, February 2021: Compensation between cloud feedback and aerosol-cloud interaction in CMIP6 models. Geophysical Research Letters, 48(4), DOI:10.1029/2020GL091024. Abstract
The most recent generation of climate models (the 6th Phase of the Coupled Model Intercomparison Project) yields estimates of effective climate sensitivity (ECS) that are much higher than past generations due to a stronger amplification from cloud feedback. If plausible, these models require substantially larger greenhouse gas reductions to meet global warming targets. We show that models with a more positive cloud feedback also have a stronger cooling effect from aerosol-cloud interactions. These two effects offset each other during the historical period when both aerosols and greenhouse gases increase, allowing either more positive or neutral cloud feedback models to reproduce the observed global-mean temperature change. Since anthropogenic aerosols primarily concentrate in the Northern Hemisphere, strong aerosol-cloud interaction models produce an interhemispheric asymmetric warming. We show that the observed warming asymmetry during the mid to late 20th century is more consistent with low ECS (weak aerosol indirect effect) models.
Zhang, Bosong, Brian J Soden, Gabriel A Vecchi, and Wenchang Yang, November 2021: Investigating the causes and impacts of convective aggregation in a high resolution atmospheric GCM. Journal of Advances in Modeling Earth Systems, 13(11), DOI:10.1029/2021MS002675. Abstract
A ∼50 km resolution atmospheric general circulation model (GCM) is used to investigate the impact of radiative interactions on spatial organization of convection, the model's mean state, and extreme precipitation events in the presence of realistic boundary conditions. Mechanism-denial experiments are performed in which synoptic-scale feedbacks between radiation and dynamics are suppressed by overwriting the model-generated atmospheric radiative cooling rates with its monthly varying climatological values. When synoptic-scale radiative interactions are disabled, the annual mean circulation and precipitation remain almost unchanged, however tropical convection becomes less aggregated, with an increase in cloud fraction and relative humidity in the free troposphere but a decrease in both variables in the boundary layer. Changes in cloud fraction and relative humidity in the boundary layer exhibit more sensitivity to the presence of radiative interactions than variations in the degree of aggregation. The less aggregated state is associated with a decrease in the frequency of extreme precipitation events, coincident with a decrease in the dynamical contribution to the magnitude of extreme precipitation. At regional scales, the spatial contrast in radiative cooling between dry and moist regions diminishes when radiative interactions are suppressed, reducing the upgradient transport of energy, degree of aggregation, and frequency of extreme precipitation events. However, the mean width of the tropical rain belt remains almost unaffected when radiative interactions are disabled. These results offer insights into how radiation-circulation coupling affects the spatial organization of convection, distributions of clouds and humidity, and weather extremes.
Baker, Rachel E., Wenchang Yang, and Gabriel A Vecchi, et al., July 2020: Susceptible supply limits the role of climate in the early SARS-CoV-2 pandemic. Science, 369(6501), DOI:10.1126/science.abc2535315-319. Abstract
Preliminary evidence suggests that climate may modulate the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Yet it remains unclear whether seasonal and geographic variations in climate can substantially alter the pandemic trajectory, given that high susceptibility is a core driver. Here, we use a climate-dependent epidemic model to simulate the SARS-CoV-2 pandemic by probing different scenarios based on known coronavirus biology. We find that although variations in weather may be important for endemic infections, during the pandemic stage of an emerging pathogen, the climate drives only modest changes to pandemic size. A preliminary analysis of nonpharmaceutical control measures indicates that they may moderate the pandemic-climate interaction through susceptible depletion. Our findings suggest that without effective control measures, strong outbreaks are likely in more humid climates and summer weather will not substantially limit pandemic growth.
Bieli, M, Adam H Sobel, Suzana J Camargo, Hiroyuki Murakami, and Gabriel A Vecchi, April 2020: Application of the Cyclone Phase Space to Extratropical Transition in a Global Climate Model. Journal of Advances in Modeling Earth Systems, 12(4), DOI:10.1029/2019MS001878. Abstract
The authors analyze the global statistics of tropical cyclones (TCs) undergoing extratropical transition (ET) in the Forecast‐oriented Low Ocean Resolution version of CM2.5 with Flux Adjustment (FLOR‐FA). The Cyclone Phase Space (CPS) is used to diagnose ET. A simulation of the recent historical climate is analyzed and compared with data from the Japanese 55‐year Reanalysis (JRA‐55), and then a simulation of late 21st century climate under Representative Concentration Pathway 4.5 is compared to the historical simulation.
When CPS is applied to the FLOR‐FA output in the historical simulation, the results diverge from those obtained from JRA‐55 by having an unrealistic number of ET cases at low latitudes, due to the presence of strong local maxima in the upper‐level geopotential. These features mislead CPS into detecting a cold core where one is not present. The misdiagnosis is largely corrected by either replacing the maxima required by CPS with the 95th percentile values, smoothing the CPS trajectories in time, or both. Other climate models may contain grid‐scale structures akin to those in FLOR‐FA, and, when used for CPS analysis, require solutions such as those discussed here.
Comparisons of ET in the projected future climate with the historical climate show a number of changes that are robust to the details of the ET diagnosis, though few are statistically significant according to standard tests. Among them are an increase in the ET fraction and a reduction in the mean latitude at which ET occurs in the western North Pacific.
Camargo, Suzana J., C F Giulivi, Adam H Sobel, Allison A Wing, D Kim, Yumin Moon, Jeffrey D Strong, A Del Genio, M Kelley, Hiroyuki Murakami, Kevin A Reed, E Scoccimarro, Gabriel A Vecchi, Michael F Wehner, Colin M Zarzycki, and Ming Zhao, June 2020: Characteristics of model tropical cyclone climatology and the large-scale environment. Journal of Climate, 33(11), DOI:10.1175/JCLI-D-19-0500.1. Abstract
Here we explore the relationship between the global climatological characteristics of tropical cyclones (TCs) in climate models and the modeled large-scale environment across a large number of models. We consider the climatology of TCs in 30 climate models with a wide range of horizontal resolutions. We examine if there is a systematic relationship between the climatological diagnostics for the TC activity (number of tropical cyclones (NTC) and accumulated cyclone energy (ACE)) by hemisphere in the models and the environmental fields usually associated with TC activity, when examined across a large number of models. For low-resolution models, there is no association between a conducive environment and TC activity, when integrated over space (tropical hemisphere) and time (all years of the simulation). As the model resolution increases, for a couple of variables, in particular vertical wind shear there is a statistically significant relationship in between the models’ TC characteristics and the environmental characteristics, but in most cases the relationship is either non-existent or the opposite of what is expected based on observations. It is important to stress that these results do not imply that there is no relationship between individual models’ environmental fields and their TC activity by basin with respect to intraseasonal or interannual variability or due to climate change. However, it is clear that when examined across many models, the models’ mean state does not have a consistent relationship with the models’ mean TC activity. Therefore, other processes associated with model physics, dynamical core, and resolution determine the climatological TC activity in climate models.
A diagnostic framework is developed to explain the response of tropical cyclones (TCs) to climate in high-resolution global atmospheric models having different complexity of boundary conditions. The framework uses vortex dynamics to identify the large-scale control on the evolution of TC precursors—first non-rotating convective clusters and then weakly rotating seeds. In experiments with perturbed sea surface temperature (SST) and CO2 concentration from the historical values, the response of TCs follows the response of seeds. The distribution of seeds is explained by the distribution of the non-rotating convective clusters multiplied by a probability that they transition to seeds. The distribution of convective clusters is constrained by the large-scale vertical velocity and is verified in aquaplanet experiments with shifting Inter tropical Convergence Zones. The probability of transition to seeds is constrained by the large-scale vorticity via an analytical function, representing the relative importance between vortex stretching and vorticity advection, and is verified in aquaplanet experiments with uniform SST. The consistency between seed and TC responses breaks down substantially when the realistic SST is perturbed such that the spatial gradient is significantly enhanced or reduced. In such cases, the difference between the responses is explained by a change in the ventilation index, which influences the fraction of seeds that develop into TCs. The proposed TC-climate relationship serves as a framework to explain the diversity of TC projection across models and forcing scenarios.
The semi-arid African Sahel region is highly sensitive to changes in monsoon precipitation, as much of the region’s workforce is employed in the agricultural industry (Hamro-Drotz and Programme 2011). Thus, studying the response of rainfall and aridity in this region to radiative perturbations is a matter of pressing humanitarian relevance. In addition, there is evidence to suggest that spatially asymmetric volcanic aerosols produce different hydroclimatic responses based on their hemispheric symmetry, both globally and in the Sahel. We use two different climate models, GFDL’s FLOR model (Vecchi et al. in J Clim 27(21):7994–8016, 2014) and NCAR’s CESM 1.1 model (Otto-Bliesner et al. in Bull Am Meteorol Soc 97(5):735–754, 2016), to characterize the response of rainfall in the Sahel to large volcanic eruptions based on the meridional symmetry of the volcanic eruptions. We find that in both the FLOR experiments simulating three large twentieth century eruptions and in the CESM Last Millennium Ensemble simulations of 46 historic volcanic eruptions, asymmetric Northern Hemisphere cooling causes a subsequent drying response in the Sahel, and Southern Hemisphere cooling causes a wetting, or “greening” response. Symmetric volcanic eruptions have a relatively small effect on rainfall in the Sahel. We also find that the FLOR results show a consistent response in the annual rainfall cycle in the Sahel for all three of the eruptions analyzed, with a reduction in rainfall in early summer followed by an increased rainfall in late summer. The annual cycle response of rainfall in the Sahel from the CESM experiments is different, in that the SH eruptions cause a rainfall maximum in August, NH eruptions cause a rainfall minimum in September, and symmetric eruptions show a slight increase in August and a decrease in October. Our results highlight the need for accurate meridional structures in historic volcanic forcing data used for climate models as well as the need for further study on regional effects of hemispherically asymmetric radiative forcing, especially as they might pertain to aerosol geoengineering.
Positive precipitation biases over western North America have remained a pervasive problem in the current generation of coupled global climate models. These biases are substantially reduced, however, in a version of the Geophysical Fluid Dynamics Laboratory Forecast-oriented Low Ocean Resolution (FLOR) coupled climate model with systematic sea surface temperature (SST) biases artificially corrected through flux adjustment. This study examines how the SST biases in the Atlantic and Pacific Oceans contribute to the North American precipitation biases. Experiments with the FLOR model in which SST biases are removed in the Atlantic and Pacific are carried out to determine the contribution of SST errors in each basin to precipitation statistics over North America. Tropical and North Pacific SST biases have a strong impact on northern North American precipitation, while tropical Atlantic SST biases have a dominant impact on precipitation biases in southern North America, including the western United States. Most notably, negative SST biases in the tropical Atlantic in boreal winter induce an anomalously strong Aleutian low and a southward bias in the North Pacific storm track. In boreal summer, the negative SST biases induce a strengthened North Atlantic Subtropical High and Great Plains low-level jet. Each of these impacts contributes to positive annual mean precipitation biases over western North America. Both North Pacific and North Atlantic SST biases induce SST biases in remote basins through dynamical pathways, so a complete attribution of the effects of SST biases on precipitation must account for both the local and remote impacts.
Moon, Yumin, D Kim, Suzana J Camargo, Allison A Wing, Adam H Sobel, Hiroyuki Murakami, Kevin A Reed, E Scoccimarro, Gabriel A Vecchi, Michael F Wehner, Colin M Zarzycki, and Ming Zhao, February 2020: Azimuthally averaged wind and thermodynamic structures of tropical cyclones in global climate models and their sensitivity to horizontal resolution. Journal of Climate, 33(4), DOI:10.1175/JCLI-D-19-0172.1. Abstract
Characteristics of tropical cyclones (TCs) in global climate models (GCMs) are known to be influenced by details of the model configurations, including horizontal resolution and parameterization schemes. Understanding model-to-model differences in TC characteristics is a prerequisite for reducing uncertainty in future TC activity projections by GCMs. This study performs a process-level examination of TC structures in eight GCM simulations that span a range of horizontal resolutions from 1° to 0.25°. A recently developed set of process-oriented diagnostics is used to examine the azimuthally averaged wind and thermodynamic structures of the GCM-simulated TCs.
Results indicate that the inner-core wind structures of simulated TCs are more strongly constrained by the horizontal resolutions of the models than are the thermodynamic structures of those TCs. As expected, the structures of TC circulations become more realistic with smaller horizontal grid spacing, such that the radii of maximum wind (RMW) become smaller, and the maximum vertical velocities occur off the center. However, the RMWs are still too large, especially at higher intensities, and there are rising motions occurring at the storm centers, inconsistently with observations. The distributions of precipitation, moisture, radiative and surface turbulent heat fluxes around TCs are diverse, even across models with similar horizontal resolutions. At the same horizontal resolution, models that produce greater rainfall in the inner-core regions tend to simulate stronger TCs. When TCs are weak, the radial gradient of net column radiative flux convergence is comparable to that of surface turbulent heat fluxes, emphasizing the importance of cloud-radiative feedbacks during the early developmental phases of TCs.
Ng, Chin Ho J., and Gabriel A Vecchi, May 2020: Large-scale environmental controls on the seasonal statistics of rapidly intensifying North Atlantic tropical cyclones. Climate Dynamics, 54(9-10), DOI:10.1007/s00382-020-05207-4. Abstract
This study is concerned with the connections between the large-scale environment and the seasonal occurrence of rapid intensification (RI) of North Atlantic tropical cyclones. Physically-motivated statistical analysis using observations and reanalysis products suggests that for tropical cyclones over the open tropical North Atlantic, the interannual variability of the probability of storms undergoing RI is influenced by seasonal large-scale atmospheric and oceanic variables, but not so for storms over the Gulf of Mexico and western Caribbean Sea. We suggest that this differentiated response is due to the former region exhibiting a strong negative correlation between the seasonal anomalies of vertical wind shear and potential intensity. Differences in the mean climatology and subseasonal variations of the large-scale environment in these regions appear to play an insignificant role in the distinctive seasonal environmental controls on RI. We suggest that the interannual correlation of vertical wind shear and potential intensity is an indicator of seasonal predictability of tropical cyclone activity (including RI) across the tropics .
Most present forecast systems for estuaries predict conditions for only a few days into the future. However, there are many reasons to expect that skillful estuarine forecasts are possible for longer time periods, including increasingly skillful extended atmospheric forecasts, the potential for lasting impacts of atmospheric forcing on estuarine conditions, and the predictability of tidal cycles. In this study, we test whether skillful estuarine forecasts are possible for up to 35 days into the future by combining an estuarine model of Chesapeake Bay with 35‐day atmospheric forecasts from an operational weather model. When compared with both a hindcast simulation from the same estuarine model and with observations, the estuarine forecasts for surface water temperature are skillful up to about two weeks into the future, and the forecasts for bottom temperature, surface and bottom salinity, and density stratification are skillful for all or the majority of the forecast period. Bottom oxygen forecasts are skillful when compared to the model hindcast, but not when compared with observations. We also find that skill for all variables in the estuary can be improved by taking the mean of multiple estuarine forecasts driven by an ensemble of atmospheric forecasts. Finally, we examine the forecasts in detail using two case studies of extreme events, and we discuss opportunities for improving the forecast skill.
Zhang, Wei, Gabriele Villarini, and Gabriel A Vecchi, August 2020: The East Asian Subtropical Jet Stream and Atlantic Tropical Cyclones. Geophysical Research Letters, 47(15), DOI:10.1029/2020GL088851. Abstract
Atlantic tropical cyclones (TCs) can cause significant societal and economic impacts, as 2019's Dorian serves to remind us of these storms' destructiveness. Decades of effort to understand and predict Atlantic TC activity have improved seasonal forecast skill, but large uncertainties still remain, in part due to an incomplete understanding of the drivers of TC variability. Here we identify an association between the East Asian Subtropical Jet Stream (EASJ) during July–October and the frequency of Atlantic TCs (wind speed ≥34 knot) and hurricanes (wind speed ≥64 knot) during August–November based on observations for 1980–2018. This strong association is tied to the impacts of EASJ on a stationary Rossby wave train emanating from East Asia and the tropical Pacific to the North Atlantic, leading to changes in vertical wind shear in the Atlantic Main Development Region (80–20°W, 10–20°N).
Tropical cyclones that rapidly intensify are typically associated with the highest forecast errors and cause a disproportionate amount of human and financial losses. Therefore, it is crucial to understand if, and why, there are observed upward trends in tropical cyclone intensification rates. Here, we utilize two observational datasets to calculate 24-hour wind speed changes over the period 1982–2009. We compare the observed trends to natural variability in bias-corrected, high-resolution, global coupled model experiments that accurately simulate the climatological distribution of tropical cyclone intensification. Both observed datasets show significant increases in tropical cyclone intensification rates in the Atlantic basin that are highly unusual compared to model-based estimates of internal climate variations. Our results suggest a detectable increase of Atlantic intensification rates with a positive contribution from anthropogenic forcing and reveal a need for more reliable data before detecting a robust trend at the global scale.
Seasonal predictions of Arctic sea ice on regional spatial scales are a pressing need for a broad group of stakeholders, however, most assessments of predictability and forecast skill to date have focused on pan-Arctic sea–ice extent (SIE). In this work, we present the first direct comparison of perfect model (PM) and operational (OP) seasonal prediction skill for regional Arctic SIE within a common dynamical prediction system. This assessment is based on two complementary suites of seasonal prediction ensemble experiments performed with a global coupled climate model. First, we present a suite of PM predictability experiments with start dates spanning the calendar year, which are used to quantify the potential regional SIE prediction skill of this system. Second, we assess the system’s OP prediction skill for detrended regional SIE using a suite of retrospective initialized seasonal forecasts spanning 1981–2016. In nearly all Arctic regions and for all target months, we find a substantial skill gap between PM and OP predictions of regional SIE. The PM experiments reveal that regional winter SIE is potentially predictable at lead times beyond 12 months, substantially longer than the skill of their OP counterparts. Both the OP and PM predictions display a spring prediction skill barrier for regional summer SIE forecasts, indicating a fundamental predictability limit for summer regional predictions. We find that a similar barrier exists for pan-Arctic sea–ice volume predictions, but is not present for predictions of pan-Arctic SIE. The skill gap identified in this work indicates a promising potential for future improvements in regional SIE predictions.
Mediterranean hurricanes (Medicanes) are intense cyclones that acquire tropical characteristics, associated with extreme winds and rainfall, thus posing a serious natural hazard to populated areas along Mediterranean coasts. Understanding how Medicanes will change with global warming remains, however, a challenge, because coarse resolution and/or the lack of atmosphere‐ocean coupling limit the reliability of numerical simulations. Here we investigate the Medicanes' response to global warming using a recently developed 25‐km global coupled climate model, which features a realistic representation of Medicanes in present climate conditions. It is found that despite a decrease in frequency, Medicanes potentially become more hazardous in the late century, lasting longer and producing stronger winds and rainfall. These changes are associated with a more robust hurricane‐like structure and are mainly confined to autumn. Thus, continued anthropogenic warming will increase the risks associated with Medicanes even in an intermediate scenario (Representative Concentration Pathway, RCP4.5), with potential natural and socioeconomic consequences.
Solar geoengineering (SG) has the potential to restore average surface temperatures by increasing planetary albedo1–4, but this could reduce precipitation5–7. Thus, although SG might reduce globally aggregated risks, it may increase climate risks for some regions8–10. Here, using the high-resolution forecast-oriented low ocean resolution (HiFLOR) model—which resolves tropical cyclones and has an improved representation of present-day precipitation extremes11,12—alongside 12 models from the Geoengineering Model Intercomparison Project (GeoMIP), we analyse the fraction of locations that see their local climate change exacerbated or moderated by SG. Rather than restoring temperatures, we assume that SG is applied to halve the warming produced by doubling CO2 (half-SG). In HiFLOR, half-SG offsets most of the CO2-induced increase of simulated tropical cyclone intensity. Moreover, neither temperature, water availability, extreme temperature nor extreme precipitation are exacerbated under half-SG when averaged over any Intergovernmental Panel on Climate Change (IPCC) Special Report on Extremes (SREX) region. Indeed, for both extreme precipitation and water availability, less than 0.4% of the ice-free land surface sees exacerbation. Thus, while concerns about the inequality of solar geoengineering impacts are appropriate, the quantitative extent of inequality may be overstated13.
The Caribbean low-level jet (CLLJ) is an important component of the atmospheric circulation over the Intra-Americas Sea (IAS) which impacts the weather and climate both locally and remotely. It influences the rainfall variability in the Caribbean, Central America, northern South America, the tropical Pacific and the continental Unites States through the transport of moisture. We make use of high-resolution coupled and uncoupled models from the Geophysical Fluid Dynamics Laboratory (GFDL) to investigate the simulation of the CLLJ and its teleconnections and further compare with low-resolution models. The high-resolution coupled model FLOR shows improvements in the simulation of the CLLJ and its teleconnections with rainfall and SST over the IAS compared to the low-resolution coupled model CM2.1. The CLLJ is better represented in uncoupled models (AM2.1 and AM2.5) forced with observed sea-surface temperatures (SSTs), emphasizing the role of SSTs in the simulation of the CLLJ. Further, we determine the forecast skill for observed rainfall using both high- and low-resolution predictions of rainfall and SSTs for the July–August–September season. We determine the role of statistical correction of model biases, coupling and horizontal resolution on the forecast skill. Statistical correction dramatically improves area-averaged forecast skill. But the analysis of spatial distribution in skill indicates that the improvement in skill after statistical correction is region dependent. Forecast skill is sensitive to coupling in parts of the Caribbean, Central and northern South America, and it is mostly insensitive over North America. Comparison of forecast skill between high and low-resolution coupled models does not show any dramatic difference. However, uncoupled models show improvement in the area-averaged skill in the high-resolution atmospheric model compared to lower resolution model. Understanding and improving the forecast skill over the IAS has important implications for highly vulnerable nations in the region.
Recent climate modeling studies point to an increase in tropical cyclone rainfall rates in response to climate warming. These studies indicate that the percentage increase in tropical cyclone rainfall rates often outpaces the increase in saturation specific humidity expected from the Clausius-Clapeyron relation (~7% °C−1). We explore the change in tropical cyclone rainfall rates over all oceans under global warming using a high-resolution climate model with the ability to simulate the entire intensity spectrum of tropical cyclones. Consistent with previous results, we find a robust increase of tropical cyclone rainfall rates. The percentage increase for inner-core tropical cyclone rainfall rates in our model is markedly larger than the Clausius-Clapeyron rate. However, when the impact of storm intensity is excluded, the rainfall rate increase shows a much better match with the Clausius-Clapeyron rate, suggesting that the “super Clausius-Clapeyron” scaling of rainfall rates with temperature increase is due to the warming-induced increase of tropical cyclone intensity. The increase of tropical cyclone intensity and environmental water vapor, in combination, explain the tropical cyclone rainfall rate increase under global warming.
This study explores the impact of El Niño and La Niña events on precipitation and circulation in East Asia. The results are based on statistical analysis of various observational datasets and Geophysical Fluid Dynamics Laboratory’s (GFDL’s) global climate model experiments. Multiple observational datasets and certain models show that in the southeastern coast of China, precipitation exhibits a nonlinear response to Central Pacific sea surface temperature anomalies during boreal deep fall/early winter. Higher mean rainfall is observed during both El Niño and La Niña events compared to the ENSO-Neutral phase, by an amount of approximately 0.4–0.5 mm/day on average per oC change. We argue that, in October to December, while the precipitation increases during El Niño are the result of anomalous onshore moisture fluxes, those during La Niña are driven by the persistence of terrestrial moisture anomalies resulting from earlier excess rainfall in this region. This is consistent with the nonlinear extreme rainfall behavior in coastal southeastern China, which increases during both ENSO phases and becomes more severe during El Niño than La Niña events.
Scaife, Adam A., L Ferranti, Oscar Alves, Panos Athanasiadis, J Baehr, M Dequé, T Dippe, Nick Dunstone, D Fereday, Richard G Gudgel, R J Greatbatch, Leon Hermanson, Yukiko Imada, S Jain, Arun Kumar, C MacLachlan, William J Merryfield, Wolfgang A Müller, Hong-Li Ren, Doug Smith, Yuhei Takaya, Gabriel A Vecchi, and Xiaosong Yang, February 2019: Tropical rainfall predictions from multiple seasonal forecast systems. International Journal of Climatology, 39(2), DOI:10.1002/joc.5855. Abstract
We quantify seasonal prediction skill of tropical winter rainfall in 14 climate forecast systems. High levels of seasonal prediction skill exist for year‐to‐year rainfall variability in all tropical ocean basins. The tropical East Pacific is the most skilful region, with very high correlation scores, and the tropical West Pacific is also highly skilful. Predictions of tropical Atlantic and Indian Ocean rainfall show lower but statistically significant scores.
We compare prediction skill (measured against observed variability) with model predictability (using single forecasts as surrogate observations). Model predictability matches prediction skill in some regions but it is generally greater, especially over the Indian Ocean. We also find significant inter‐basin connections in both observed and predicted rainfall. Teleconnections between basins due to El Niño–Southern Oscillation (ENSO) appear to be reproduced in multi‐model predictions and are responsible for much of the prediction skill. They also explain the relative magnitude of inter‐annual variability, the relative magnitude of predictable rainfall signals and the ranking of prediction skill across different basins.
These seasonal tropical rainfall predictions exhibit a severe wet bias, often in excess of 20% of mean rainfall. However, we find little direct relationship between bias and prediction skill. Our results suggest that future prediction systems would be best improved through better model representation of inter‐basin rainfall connections as these are strongly related to prediction skill, particularly in the Indian and West Pacific regions. Finally, we show that predictions of tropical rainfall alone can generate highly skilful forecasts of the main modes of extratropical circulation via linear relationships that might provide a useful tool to interpret real‐time forecasts.
Slater, L J., Gabriele Villarini, A Allen Bradley, and Gabriel A Vecchi, December 2019: A dynamical statistical framework for seasonal streamflow forecasting in an agricultural watershed. Climate Dynamics, 53(12), DOI:10.1007/s00382-017-3794-7. Abstract
The state of Iowa in the US Midwest is regularly affected by major floods and has seen a notable increase in agricultural land cover over the twentieth century. We present a novel statistical-dynamical approach for probabilistic seasonal streamflow forecasting using land cover and General Circulation Model (GCM) precipitation forecasts. Low to high flows are modelled and forecast for the Raccoon River at Van Meter, a 8900 km2 catchment located in central-western Iowa. Statistical model fits for each streamflow quantile (from seasonal minimum to maximum; predictands) are based on observed basin-averaged total seasonal precipitation, annual row crop (corn and soybean) production acreage, and observed precipitation from the month preceding each season (to characterize antecedent wetness conditions) (predictors). Model fits improve when including agricultural land cover and antecedent precipitation as predictors, as opposed to just precipitation. Using the dynamically-updated relationship between predictand and predictors every year, forecasts are computed from 1 to 10 months ahead of every season based on annual row crop acreage from the previous year (persistence forecast) and the monthly precipitation forecasts from eight GCMs of the North American Multi-Model Ensemble (NMME). The skill of our forecast streamflow is assessed in deterministic and probabilistic terms for all initialization months, flow quantiles, and seasons. Overall, the system produces relatively skillful streamflow forecasts from low to high flows, but the skill does not decrease uniformly with initialization time, suggesting that improvements can be gained by using different predictors for specific seasons and flow quantiles.
van Oldenborgh, G J., E Mitchell-Larson, and Gabriel A Vecchi, et al., November 2019: Cold waves are getting milder in the northern midlatitudes. Environmental Research Letters, 14(11), DOI:10.1088/1748-9326/ab4867. Abstract
The strong two-day cold wave in the midwestern United States in January 2019 again ignited the discussion as to whether cold waves are getting more severe or not as a result of Arctic amplification due to climate change. Assessing the evolution of cold waves in the northern hemisphere midlatitudes in the observations has been difficult because the variability of cold waves is large compared to anthropogenic warming. In order to detect changes in cold spells, two complementary ways to optimise the signal-to-noise ratio are employed: multi-decadal series at individual stations, and for shorter time periods by using spatially aggregated measures. Global warming is now strong enough to make trends clear at individual stations when considering long enough (>50 yr) records of daily minimum and maximum temperature. Calculating the land area that has temperatures below the 1-in-10 year return value (defined over 1951–1980) enables us to investigate trends over a shorter time horizon. The long-term station data have strong decreases everywhere in the lowest minimum temperature. Warming trends in the lowest maximum temperature are smaller over most of the Northern Hemisphere, with dataset-dependent indications of possible negative trends in parts of the United States and Mexico. Considering the area experiencing cold waves over the last decades, the most notable feature is a sharp decline of this area since the 1980s. The natural variability is still so large that it is possible to arbitrarily select starting dates after the decline for which the trend is slightly positive in smaller regions like North America or Europe. However, these values are within uncertainties compatible with a steady decline and have differing starting dates in North America and Europe. An analysis of the entire northern midlatitudes confirms the steady decrease in severity and frequency of cold waves over the last decades in the observations.
Responses of tropical cyclones (TCs) to CO2 doubling are explored using coupled global climate models (GCMs) with increasingly refined atmospheric/land horizontal grids (~ 200 km, ~ 50 km and ~ 25 km). The three models exhibit similar changes in background climate fields thought to regulate TC activity, such as relative sea surface temperature (SST), potential intensity, and wind shear. However, global TC frequency decreases substantially in the 50 km model, while the 25 km model shows no significant change. The ~ 25 km model also has a substantial and spatially-ubiquitous increase of Category 3–4–5 hurricanes. Idealized perturbation experiments are performed to understand the TC response. Each model’s transient fully-coupled 2 × CO2 TC activity response is largely recovered by “time-slice” experiments using time-invariant SST perturbations added to each model’s own SST climatology. The TC response to SST forcing depends on each model’s background climatological SST biases: removing these biases leads to a global TC intensity increase in the ~ 50 km model, and a global TC frequency increase in the ~ 25 km model, in response to CO2-induced warming patterns and CO2 doubling. Isolated CO2 doubling leads to a significant TC frequency decrease, while isolated uniform SST warming leads to a significant global TC frequency increase; the ~ 25 km model has a greater tendency for frequency increase. Global TC frequency responds to both (1) changes in TC “seeds”, which increase due to warming (more so in the ~ 25 km model) and decrease due to higher CO2 concentrations, and (2) less efficient development of these“seeds” into TCs, largely due to the nonlinear relation between temperature and saturation specific humidity.
Villarini, Gabriele, B Luitel, and Gabriel A Vecchi, et al., December 2019: Multi-model ensemble forecasting of North Atlantic tropical cyclone activity. Climate Dynamics, 53(12), DOI:10.1007/s00382-016-3369-z. Abstract
North Atlantic tropical cyclones (TCs) and hurricanes are responsible for a large number of fatalities and economic damage. Skillful seasonal predictions of the North Atlantic TC activity can provide basic information critical to our improved preparedness. This study focuses on the development of statistical–dynamical seasonal forecasting systems for different quantities related to the frequency and intensity of North Atlantic TCs. These models use only tropical Atlantic and tropical mean sea surface temperatures (SSTs) to describe the variability exhibited by the observational records because they reflect the importance of both local and non-local effects on the genesis and development of TCs in the North Atlantic basin. A set of retrospective forecasts of SSTs by six experimental seasonal-to-interannual prediction systems from the North American Multi-Model Ensemble are used as covariates. The retrospective forecasts are performed over the period 1982–2015. The skill of these statistical–dynamical models is quantified for different quantities (basin-wide number of tropical storms and hurricanes, power dissipation index and accumulated cyclone energy) for forecasts initialized as early as November of the year prior to the season to forecast. The results of this work show that it is possible to obtain skillful retrospective forecasts of North Atlantic TC activity with a long lead time. Moreover, probabilistic forecasts of North Atlantic TC activity for the 2016 season are provided.
Wing, Allison A., Suzana J Camargo, Adam H Sobel, D Kim, Yumin Moon, Hiroyuki Murakami, Kevin A Reed, Gabriel A Vecchi, Michael F Wehner, Colin M Zarzycki, and Ming Zhao, September 2019: Moist static energy budget analysis of tropical cyclone intensification in high-resolution climate models. Journal of Climate, 32(18), DOI:10.1175/JCLI-D-18-0599.1. Abstract
Tropical cyclone intensification processes are explored in six high-resolution climate models. The analysis framework employs process-oriented diagnostics that focus on how convection, moisture, clouds and related processes are coupled. These diagnostics include budgets of column moist static energy and the spatial variance of column moist static energy, where the column integral is performed between fixed pressure levels. The latter allows for the quantification of the different feedback processes responsible for the amplification of moist static energy anomalies associated with the organization of convection and cyclone spin-up, including surface flux feedbacks and cloud-radiative feedbacks. Tropical cyclones (TCs) are tracked in the climate model simulations and the analysis is applied along the individual tracks and composited over many TCs. Two methods of compositing are employed: a composite over all TC snapshots in a given intensity range, and a composite over all TC snapshots at the same stage in the TC life cycle (same time relative to the time of lifetime maximum intensity for each storm). The radiative feedback contributes to TC development in all models, especially in storms of weaker intensity or earlier stages of development. Notably, the surface flux feedback is stronger in models that simulate more intense TCs. This indicates that the representation of the interaction between spatially varying surface fluxes and the developing TC is responsible for at least part of the inter-model spread in TC simulation.
Explosive volcanic eruptions have large climate impacts, and can serve as observable tests of the climatic response to radiative forcing. Using a high resolution climate model, we contrast the climate responses to Pinatubo, with symmetric forcing, and those to Santa Maria and Agung, which had meridionally asymmetric forcing. Although Pinatubo had larger global‐mean forcing, asymmetric forcing strongly shifts the latitude of tropical rainfall features, leading to larger local precipitation/TC changes. For example, North Atlantic TC activity over is enhanced/reduced by SH‐forcing (Agung)/NH‐forcing (Santa Maria), but changes little in response to the Pinatubo forcing. Moreover, the transient climate sensitivity estimated from the response to Santa Maria is 20% larger than that from Pinatubo or Agung. This spread in climatic impacts of volcanoes needs to be considered when evaluating the role of volcanoes in global and regional climate, and serves to contextualize the well‐observed response to Pinatubo.
This study examines the performance of the Geophysical Fluid Dynamics Laboratory Forecast-Oriented Low Ocean Resolution version of CM2.5 (FLOR; ~ 50-km mesh) and high-resolution FLOR (HiFLOR; ~ 25-km mesh) in reproducing the climatology and interannual variability in rainfall associated with tropical cyclones (TCs) in both sea surface temperature (SST)-nudging and seasonal-forecast experiments. Overall, HiFLOR outperforms FLOR in capturing the observed climatology of TC rainfall, particularly in East Asia, North America and Australia. In general, both FLOR and HiFLOR underestimate the observed TC rainfall in the coastal regions along the Bay of Bengal, connected to their failure to accurately simulate the bimodal structure of the TC genesis seasonality. A crucial factor in capturing the climatology of TC rainfall by the models is the simulation of the climatology of spatial TC density. Overall, while HiFLOR leads to a better characterization of the areas affected by TC rainfall, the SST-nudging and seasonal-forecast experiments with both models show limited skill in reproducing the year-to-year variation in TC rainfall. Ensemble-based estimates from these models indicate low potential skill for year-to-year variations in TC rainfall, yet the models show lower skill than this. Therefore, the low skill for interannual TC rainfall in these models reflects both a fundamental limit on predictability/reproducibility of seasonal TC rainfall as well as shortcomings in the models.
Zhang, Wei, Gabriele Villarini, and Gabriel A Vecchi, December 2019: Impacts of the Pacific meridional mode on rainfall over the maritime continent and australia: potential for seasonal predictions. Climate Dynamics, 53(12), DOI:10.1007/s00382-017-3652-7. Abstract
The skill of monthly sea surface temperature (SST) anomaly predictions for large marine ecosystems (LMEs) in coastal regions of the United States and Canada is assessed using simulations from the climate models in the North American Multimodel Ensemble (NMME). The forecasts based on the full ensemble are generally more skillful than predictions from even the best single model. The improvement in skill is particularly noteworthy for probability forecasts that categorize SST anomalies into upper (warm) and lower (cold) terciles. The ensemble provides a better estimate of the full range of forecast values than any individual model, thereby correcting for the systematic over-confidence (under-dispersion) of predictions from an individual model. Probability forecasts, including tercile predictions from the NMME, are used frequently in seasonal forecasts for atmospheric variables and may have many uses in marine resource management.
As one of the first global coupled climate models to simulate and predict category 4 and 5 (Saffir–Simpson scale) tropical cyclones (TCs) and their interannual variations, the High-Resolution Forecast-Oriented Low Ocean Resolution (HiFLOR) model at the Geophysical Fluid Dynamics Laboratory (GFDL) represents a novel source of insight on how the entire TC intensification distribution could be transformed due to climate change. In this study, three 70-year HiFLOR experiments are performed to identify the effects of climate change on TC intensity and intensification. For each of the experiments, sea surface temperature (SST) is nudged to different climatological targets and atmospheric radiative forcing is specified, allowing us to explore the sensitivity of TCs to these conditions.
First, a control experiment, which uses prescribed climatological ocean and radiative forcing based on observations during the years 1986-2005, is compared to two observational records and evaluated for its ability to capture the mean TC behavior during these years. The simulated intensification distributions as well as the percentage of TCs that become major hurricanes show similarities with observations. The control experiment is then compared to two 21st century experiments, in which the climatological SSTs from the control experiment are perturbed by multimodel projected SST anomalies and atmospheric radiative forcing from either 2016-2035 or 2081-2100 (RCP4.5 scenario). The frequency, intensity, and intensification distribution of TCs all shift to higher values as the 21st century progresses. HiFLOR’s unique response to climate change and fidelity in simulating the present climate lays the groundwork for future studies involving models of this type.
An observing system simulation experiment (OSSE) using an ensemble coupled data assimilation system was designed to investigate the impact of deep ocean Argo profile assimilation in a biased numerical climate system. Based on the modern Argo observational array and an artificial extension to full depth, “observations” drawn from one coupled general circulation model (CM2.0) were assimilated into another model (CM2.1). Our results showed that coupled data assimilation with simultaneous atmospheric and oceanic constraints plays a significant role in preventing deep ocean drift. However, the extension of the Argo array to full depth did not significantly improve the quality of the oceanic climate estimation within the bias magnitude in the twin experiment. Even in the “identical” twin experiment for the deep Argo array from the same model (CM2.1) with the assimilation model, no significant changes were shown in the deep ocean, such as in the Atlantic meridional overturning circulation and the Antarctic bottom water cell. The small ensemble spread and corresponding weak constraints by the deep Argo profiles with medium spatial and temporal resolution may explain why the deep Argo profiles did not improve the deep ocean features in the assimilation system. Additional studies using different assimilation methods with improved spatial and temporal resolution of the deep Argo array are necessary in order to more thoroughly understand the impact of the deep Argo array on the assimilation system.
The past few years have seen a growing investment in the development of global eddy‐resolving ocean models, but the impact of incorporating such high ocean resolution on precipitation responses to CO2 forcing has yet to be investigated. This study analyzes precipitation changes from a suite of GFDL models incorporating eddy‐resolving (0.1o), eddy‐permitting (0.25o) and eddy‐parameterizing (1o) ocean models. The incorporation of eddy resolution does not challenge the large‐scale structure of precipitation changes but results in substantial regional differences, particularly over ocean. These oceanic differences are primarily driven by the pattern of SST changes with greater sensitivity in lower latitudes. The largest impact of ocean resolution on SST changes occurs in eddy rich regions (e.g., boundary currents and the Southern Ocean), where impact on precipitation changes is also found to various degrees. In the Gulf Stream region where previous studies found considerable impact of eddy resolution on the simulation of climatological precipitation, we do not find such impact from the GFDL models but we do find substantial impact on precipitation changes. The eddy‐parameterizing model projects a banded structure common to the CMIP5 models, whereas the higher‐resolution models project a poleward shift of precipitation maxima associated with an enhanced Gulf Stream warming. Over land, precipitation changes are generally not very sensitive to ocean resolution. In eastern North America adjacent to the Gulf Stream region, moderate differences are found between resolutions. We discuss the mechanisms of land differences, which arise through the simulation of both climatological SST and SST changes.
The driving of tropical precipitation by variability of the underlying sea surface temperature (SST) plays a critical role in the atmospheric general circulation. To assess the precipitation sensitivity to SST variability, it is necessary to observe and understand the relationship between precipitation and SST. However, the precipitation – SST relationships from any coupled atmosphere-ocean system can be difficult to interpret due to the challenge of disentangling the SST-forced atmospheric response and the atmospheric intrinsic variability. This study demonstrates that the two components can be isolated using uncoupled atmosphere-only simulations, which extract the former when driven by time-varying SSTs and the latter when driven by climatological SSTs. With a simple framework that linearly combines the two types of uncoupled simulations, the coupled precipitation – SST relationships are successfully reproduced. Such a framework can be a useful tool for quantitatively diagnosing tropical air-sea interactions.
The precipitation sensitivity to SST variability is investigated with the use of uncoupled simulations with prescribed SST anomalies, where the influence of atmospheric intrinsic variability on SST is deactivated. Through a focus on local precipitation – SST relationships, the precipitation sensitivity to local SST variability is determined to be predominantly controlled by the local background SST. In addition, the strength of the precipitation response increases monotonically with the local background SST, with a very sharp growth at high SSTs. These findings are supported by basic principles of moist static stability, from which a simple formula for precipitation sensitivity to local SST variability is derived.
Mountain snowpack in the western United States provides a natural reservoir for cold season precipitation; variations in snowpack influence warm season water supply, wildfire risk, ecology, and industries like agriculture dependent on snow and downstream water availability. Efforts to understand snowpack variability have predominantly been focused on either weekly (weather) or decadal to centennial (climate variability and change) timescales. We focus on a timescale between these ranges by demonstrating that a global climate model suite can provide snowpack predictions 8 months in advance. The predictions from climate models outperform statistical methods from observations alone. Our results show that seasonal hydroclimate predictions are possible and highlight areas for future prediction system improvements.
This study proposes a set of process-oriented diagnostics with the aim of understanding how model physics and numerics control the representation of tropical cyclones (TCs), especially their intensity distribution, in GCMs. Three simulations are made using two 50-km GCMs developed at NOAA’s Geophysical Fluid Dynamics Laboratory. The two models are forced with fixed sea surface temperature (AM2.5 and HiRAM), and in the third simulation the AM2.5 model is coupled to an ocean GCM (FLOR).
The frequency distributions of maximum surface wind near TC centers show that HiRAM tends to develop stronger TCs than the other models do. Large-scale environmental parameters, such as potential intensity, do not explain the differences between HiRAM and the other models. It is found that HiRAM produces a greater amount of precipitation near the TC center, suggesting that associated greater diabatic heating enables TCs to become stronger in HiRAM. HiRAM also shows a greater contrast in relative humidity and surface latent heat flux between the inner and outer regions of TCs.
Various fields are composited on precipitation percentiles to reveal the essential character of the interaction among convection, moisture, and surface heat flux. Results show that the moisture sensitivity of convection is higher in HiRAM than in the other model simulations. HiRAM also exhibits a stronger feedback from surface latent heat flux to convection via near-surface wind speed in heavy rain rate regimes. The results emphasize that the moisture-convection coupling and the surface heat flux feedback are critical processes that affect the intensity of TCs in GCMs.
Unprecedented high intensity flooding induced by extreme precipitation was reported over Chennai in India during November-December of 2015, which led to extensive damage to human life and property. It is of utmost importance to determine the odds of occurrence of such extreme floods in future and the related climate phenomena, for planning and mitigation purposes. Here, we make use of a suite of simulations from GFDL high-resolution coupled climate models to investigate the odds of occurrence of extreme floods induced by extreme precipitation over Chennai and the role of radiative forcing and/or large-scale SST forcing in enhancing the probability of such events in future. Climate of 20th century experiments with large ensembles suggest that the radiative forcing may not enhance the probability of extreme floods over Chennai. Doubling of CO2 experiments also fail to show evidence for increase of such events in a global warming scenario. Further, this study explores the role of SST forcing from the Indian and Pacific Oceans on the odds of occurrence of Chennai-like floods. Neither an El Niño nor La Niña enhances the probability of extreme floods over Chennai. However, warm Bay of Bengal tends to increase the odds of occurrence of extreme Chennai-like floods. The atmospheric condition such as a tropical depression over Bay of Bengal favoring the transport of moisture from warm Bay of Bengal is conducive for intense precipitation.
Li, Shan, Shaoqing Zhang, Zhengyu Liu, Lv Lu, J Zhu, X-F Zhang, Xinrong Wu, Ming Zhao, and Gabriel A Vecchi, et al., April 2018: Estimating Convection Parameters in the GFDL CM2.1 Model Using Ensemble Data Assimilation. Journal of Advances in Modeling Earth Systems, 10(4), DOI:10.1002/2017MS001222. Abstract
Parametric uncertainty in convection parameterization is one major source of model errors that cause model climate drift. Convection parameter tuning has been widely studied in atmospheric models to help mitigate the problem. However, in a fully coupled general circulation model (CGCM), convection parameters which impact the ocean as well as the climate simulation may have different optimal values. This study explores the possibility of estimating convection parameters with an ensemble coupled data assimilation method in a CGCM. Impacts of the convection parameter estimation on climate analysis and forecast are analyzed. In a twin experiment framework, five convection parameters in the GFDL coupled model CM2.1 are estimated individually and simultaneously under both perfect and imperfect model regimes. Results show that the ensemble data assimilation method can help reduce the bias in convection parameters. With estimated convection parameters, the analyses and forecasts for both the atmosphere and the ocean are generally improved. It is also found that information in low latitudes is relatively more important for estimating convection parameters. This study further suggests that when important parameters in appropriate physical parameterizations are identified, incorporating their estimation into traditional ensemble data assimilation procedure could improve the final analysis and climate prediction.
Landfalling tropical cyclone (TC) rainfall is an important element of inland flood hazards in the eastern United States. The projection of landfalling TC rainfall under anthropogenic warming provides insight to future flood risks. This study examines the frequency of landfalling TCs and associated rainfall using the GFDL Forecast-oriented Low Ocean Resolution (FLOR) climate model through comparisons with observed TC track and rainfall over the July–November 1979–2005 seasons. The projection of landfalling TC frequency and rainfall under the representative concentration pathway (RCP) 4.5 scenario for the late twenty-first century is explored, including an assessment of the impacts of extratropical transition (ET). In most regions of the southeastern United States, competition between increased storm rain rate and decreased storm frequency dominates the change of annual TC rainfall, and rainfall from ET and non-ET storms. In the northeastern United States, a prominent feature is the striking increase of ET storm frequency but with tropical characteristics (i.e., prior to the ET phase), a key element of increased rainfall. The storm-centered rainfall composite analyses show the greatest increase at radius a few hundred kilometers from the storm centers. Over both ocean and land, the increase of rainfall within 500 km from the storm center exceeds the Clausius-Clapeyron scaling for TC-phase storms. Similar results are found in the front-left quadrant of ET-phase storms. Future work involving explorations of multiple models (e.g., higher atmospheric resolution version of FLOR) for TC rainfall projection is expected to add more robustness to projection results.
Extratropical transition can extend the threat of tropical cyclones into the mid‐latitudes, and modify it through expansion of rainfall and wind fields. Despite the scientific and socioeconomic interest, the seasonal forecast of extratropical transition has received little attention. The GFDL High‐Resolution Forecast‐Oriented Low Ocean Resolution (FLOR) model (HiFLOR) shows skill in seasonal forecasts of tropical cyclone frequency as well as major hurricanes. A July‐initialized twelve‐member ensemble retrospective seasonal forecast experiment with HiFLOR in the North Atlantic is conducted, representing one of the very first attempts to predict the extratropical transition activity months in advance. HiFLOR exhibits retrospective skill in seasonal forecasts of basin‐wide and regional ET activity relative to best track and reanalysis data. In contrast, the skill of HiFLOR in predictions of non‐ET activity is limited. Future work targeted at improved predictions of non‐ET storms provides a path for enhanced TC activity forecasting.
Luitel, B, Gabriele Villarini, and Gabriel A Vecchi, January 2018: Verification of the skill of numerical weather prediction models in forecasting rainfall from U.S. landfalling tropical cyclones. Journal of Hydrology, 556, DOI:10.1016/j.jhydrol.2016.09.019. Abstract
The goal of this study is the evaluation of the skill of five state-of-the-art numerical weather prediction (NWP) systems [European Centre for Medium-Range Weather Forecasts (ECMWF), UK Met Office (UKMO), National Centers for Environmental Prediction (NCEP), China Meteorological Administration (CMA), and Canadian Meteorological Center (CMC)] in forecasting rainfall from North Atlantic tropical cyclones (TCs). Analyses focus on 15 North Atlantic TCs that made landfall along the U.S. coast over the 2007–2012 period. As reference data we use gridded rainfall provided by the Climate Prediction Center (CPC). We consider forecast lead-times up to five days. To benchmark the skill of these models, we consider rainfall estimates from one radar-based (Stage IV) and four satellite-based [Tropical Rainfall Measuring Mission - Multi-satellite Precipitation Analysis (TMPA, both real-time and research version); Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN); the CPC MORPHing Technique (CMORPH)] rainfall products. Daily and storm total rainfall fields from each of these remote sensing products are compared to the reference data to obtain information about the range of errors we can expect from “observational data.” The skill of the NWP models is quantified: (1) by visual examination of the distribution of the errors in storm total rainfall for the different lead-times, and numerical examination of the first three moments of the error distribution; (2) relative to climatology at the daily scale. Considering these skill metrics, we conclude that the NWP models can provide skillful forecasts of TC rainfall with lead-times up to 48 h, without a consistently best or worst NWP model.
Schenkel, Benjamin A., Ning Lin, Daniel Chavas, and Gabriel A Vecchi, et al., October 2018: Lifetime Evolution of Outer Tropical Cyclone Size and Structure as Diagnosed from Reanalysis and Climate Model Data. Journal of Climate, 31(19), DOI:10.1175/JCLI-D-17-0630.1. Abstract
The present study examines the lifetime evolution of outer tropical cyclone (TC) size and structure in the North Atlantic (NA) and western North Pacific (WNP). The metric for outer TC size is the radius at which the azimuthal-mean 10-m azimuthal wind equals 8 m s−1 (r8) derived from the NCEP Climate Forecast System Reanalysis (CFSR) and GFDL High-Resolution Forecast-Oriented Low Ocean Resolution model (HiFLOR). Radial profiles of the azimuthal-mean 10-m azimuthal wind are also analyzed to demonstrate that the results are robust across a broad range of wind radii. The analysis shows that most TCs in both basins are characterized by: 1) minimum lifetime r8 at genesis, 2) subsequent substantial increases in r8 as the TC wind field expands, 3) peak r8 values occurring near or after the midpoint of TC lifetime, and 4) nontrivial decreases in r8 and outer winds during the latter part of TC lifetime. Compared to the NA, WNP TCs are systematically larger up until the end of their lifetime, exhibit r8 growth and decay rates that are larger in magnitude, and are characterized by an earlier onset of lifetime maximum r8 near their lifetime midpoint. In both basins, the TCs exhibiting the largest r8 increases are the longest-lived, especially those that traverse the longest distances (i.e., recurving TCs). Finally, analysis of TCs undergoing extratropical transition (ET) shows that NA TCs exhibit negligible changes in r8 during ET, while WNP ET cases either show r8 decreases (CFSR) or negligible changes in r8 (HiFLOR).
Strong, Jeffrey D., Gabriel A Vecchi, and Paul Ginoux, May 2018: The Climatological Effect of Saharan Dust on Global Tropical Cyclones in a Fully Coupled GCM. Journal of Geophysical Research: Atmospheres, 123(10), DOI:10.1029/2017JD027808. Abstract
Climate in the tropical North Atlantic and West Africa is known to be sensitive to both the atmospheric burden and optical properties of aerosolized mineral dust. We investigate the global climatic response to an idealized perturbation in atmospheric burden of Saharan‐born mineral dust, comparable to the observed changes between the 1960's and 1980's, using simulations with the high resolution, fully coupled GFDL Climate Model 2.5, Forecast‐oriented Low Ocean Resolution version, across a range of realistic optical properties, with a specific focus on tropical cyclones. The direct radiative response at the top of the atmosphere (ToA) and at the surface along with regional hydrologic and thermodynamic responses are in agreement with previous studies, depending largely on the amount of aerosol absorption versus scattering. In all simulations, dust causes a decrease in tropical cyclone activity across the North Atlantic Ocean, as determined by a tropical cyclone tracking scheme, with the largest response occurring in the most absorbing and scattering optical regimes. These changes are partially corroborated by common local genesis potential indices. However, no clear‐cut explanation can be developed upon inspection of their constituent variables. There are also non‐negligible anomalies in the North Pacific and Indian Oceans in these simulations. A relationship between accumulated cyclone energy and ToA radiative flux anomalies is used to explain the North Atlantic anomalies, while analogy to known climate variations can help us understand the far‐field response to the dust forcing.
Floods in the Mississippi basin can have large negative societal, natural and economic impacts. Understanding the drivers of floods, now and in the future, is relevant for risk management and infrastructure-planning purposes. We investigate the drivers of 100-year return Lower-Mississippi River floods using a global coupled climate model with an integrated surface-water module. The model provides 3400 years of physically consistent data from a static climate, in contrast to available observational data (relatively short records, incomplete land-surface data, transient climate). In the months preceding the model’s 100-year floods, as indicated by extreme monthly discharge, above-average rain and snowfall lead to moist subsurface conditions and the build up of snowpack, making the river system prone to these major flooding events. The melt water from snowpack in the northern Missouri and Upper Mississippi catchments primes the river system, sensitizing it to subsequent above-average precipitation in the Ohio and Tennessee catchments. An ensemble of transient-forcing experiments is used to investigate the impacts of past and projected anthropogenic climate change on extreme floods. There is no statistically significant projected trend in the occurrence of 100-year floods in the model ensemble, despite significant increases in extreme precipitation, significant decreases in extreme snowmelt, and significant decreases in less extreme floods. The results emphasize the importance of considering the fully-coupled land-atmosphere system for extreme floods. This initial analysis provides avenues for further investigation, including comparison to characteristics of less extreme floods, the sensitivity to model configuration, the role of human water management, and implications for future flood-risk management.
The Geophysical Fluid Dynamics Laboratory (GFDL) has recently developed two global coupled GCMs, FLOR and HiFLOR, which are now being utilized for climate research and seasonal predictions. Compared to their predecessor CM2.1, the new versions have improved ocean/atmosphere physics and numerics, and refinement of the atmospheric horizontal grid from 220 km (CM2.1) to 55 km (FLOR) and 26 km (HiFLOR). Both FLOR and HiFLOR demonstrate greatly improved simulations of the tropical Pacific annual‐mean climatology, with FLOR practically eliminating any equatorial cold bias in sea surface temperature. An additional model experiment (LOAR1) using FLOR's ocean/atmosphere physics, but with the atmospheric grid coarsened toward that of CM2.1, is used to further isolate the impacts of the refined atmospheric grid versus the improved physics and numerics. The improved ocean/atmosphere formulations are found to produce more realistic tropical Pacific patterns of sea surface temperature and rainfall, surface heat fluxes, ocean mixed layer depths, surface currents, and tropical instability wave (TIW) activity; enhance the near‐surface equatorial upwelling; and reduce the inter‐centennial warm drift of the tropical Pacific upper ocean. The atmospheric grid refinement further improves these features, and also improves the tropical Pacific surface wind stress, implied Ekman and Sverdrup transports, subsurface temperature and salinity structure, and heat advection in the equatorial upper ocean. The results highlight the importance of nonlocal air‐sea interactions in the tropical Pacific climate system, including the influence of off‐equatorial surface fluxes on the equatorial annual‐mean state. Implications are discussed for improving future simulations, observations, and predictions of tropical Pacific climate.
A “typical” El Niño leads to wet (dry) wintertime anomalies over the southern (northern) half of the Western United States (WUS). However, during the strong El Niño of 2015/16, the WUS winter precipitation pattern was roughly opposite to this canonical (average of the record) anomaly pattern. To understand why this happened, and whether it was predictable, we use a suite of high-resolution seasonal prediction experiments with coupled climate models. We find that the unusual 2015/16 precipitation pattern was predictable at zero-lead time horizon when the ocean/atmosphere/land components were initialized with observations. However, when the ocean alone is initialized the coupled model fails to predict the 2015/16 pattern, although ocean initial conditions alone can reproduce the observed WUS precipitation during the 1997/98 strong El Niño. Further observational analysis shows that the amplitudes of the El Niño induced tropical circulation anomalies during 2015/16 were weakened by about 50% relative to those of 1997/98. This was caused by relative cold (warm) anomalies in the eastern (western) tropical Pacific suppressing (enhancing) deep convection anomalies in the eastern (western) tropical Pacific during 2015/16. The reduced El Niño teleconnection led to a weakening of the subtropical westerly jet over the southeast North Pacific and southern WUS, resulting in the unusual 2015/16 winter precipitation pattern over the WUS. This study highlights the importance of initial conditions not only in the ocean, but in the land and atmosphere as well, for predicting the unusual El Niño teleconnection and its influence on the winter WUS precipitation anomalies during 2015/16.
This study examines the impacts of the Pacific Meridional Mode (PMM) on North Atlantic tropical cyclones (TCs) making landfall along the coastal US, Caribbean Islands and Mexico, and provides insights on the underlying physical mechanisms using observations and model simulations. There is a statistically significant time-lagged association between spring PMM and the August–October US and Caribbean landfalling TCs. Specifically, the positive (negative) spring PMM events tend to be followed by fewer (more) TCs affecting the coastal US (especially over the Gulf of Mexico and Florida) and the Caribbean Islands. This lagged association is mainly caused by the lagged impacts of PMM on the El Niño Southern Oscillation (ENSO), and the subsequent impacts of ENSO on TC frequency and landfalls. Positive (negative) PMM events are largely followed by El Niño (La Niña) events, which lead to less (more) TC geneses close to the US coast (i.e., the Gulf of Mexico and the Caribbean Sea); this also leads to easterly (westerly) steering flow in the vicinity of the US and Caribbean coast, which is unfavorable (favorable) to TC landfall across the Gulf of Mexico, Florida and Caribbean Islands. Perturbation simulations with the state-of-the-art Geophysical Fluid Dynamics Laboratory Forecast-oriented Low Ocean Resolution Version of CM2.5 (FLOR) support the linkage between PMM and TC landfall activity. The time-lagged impacts of spring PMM on TC landfalling activity results in a new predictor to forecast seasonal TC landfall activity along the US (especially over the Gulf of Mexico and Florida) and Caribbean coastal regions.
Over the 1997-2014 period, the mean frequency of western North Pacific (WNP) tropical cyclones (TCs) was markedly lower (~18%) than the period 1980-1996. Here we show that these changes were driven by an intensification of the vertical wind shear in the southeastern/eastern WNP tied to the changes in the Walker circulation, which arose primarily in response to the enhanced sea surface temperature (SST) warming in the North Atlantic, while the SST anomalies associated with the negative phase of the Pacific Decadal Oscillation (PDO) in the tropical Pacific and the anthropogenic forcing play only secondary roles. These results are based on observations and experiments using the Geophysical Fluid Dynamics Laboratory (GFDL) Forecast-oriented Low-ocean Resolution Coupled Climate Model (FLOR) coupled climate model. The present study suggests a crucial role of the North Atlantic SST in causing decadal changes to WNP TC frequency.
Due to its persistence on seasonal timescales, Arctic sea-ice thickness (SIT) is a potential source of predictability for summer sea-ice extent (SIE). New satellite observations of SIT represent an opportunity to harness this potential predictability via improved thickness initialization in seasonal forecast systems. In this work, the evolution of Arctic sea-ice volume anomalies is studied using a 700-year control integration and a suite of initialized ensemble forecasts from a fully-coupled global climate model. Our analysis is focused on the September sea-ice zone, as this is the region where thickness anomalies have the potential to impact the SIE minimum. The primary finding of this paper is that, in addition to a general decay with time, sea-ice volume anomalies display a summer enhancement, in which anomalies tend to grow between the months of May and July. This summer enhancement is relatively symmetric for positive and negative volume anomalies and peaks in July regardless of the initial month. Analysis of the surface energy budget reveals that the summer volume anomaly enhancement is driven by a positive feedback between the SIT state and the surface albedo. The SIT state affects surface albedo through changes in the sea-ice concentration field, melt-onset date, snow coverage, and ice-thickness distribution, yielding an anomaly in the total absorbed shortwave radiation between May and August, which enhances the existing SIT anomaly. This phenomenon highlights the crucial importance of accurate SIT initialization and representation of ice-albedo feedback processes in seasonal forecast systems.
Recent Arctic sea ice seasonal prediction efforts and forecast skill assessments have primarily focused on pan-Arctic sea-ice extent (SIE). In this work, we move towards stakeholder-relevant spatial scales, investigating the regional forecast skill of Arctic sea ice in a Geophysical Fluid Dynamics Laboratory (GFDL) seasonal prediction system. Using a suite of retrospective initialized forecasts spanning 1981–2015 made with a coupled atmosphere-ocean-sea ice-land model, we show that predictions of detrended regional SIE are skillful at lead times up to 11 months. Regional prediction skill is highly region and target month dependent, and generically exceeds the skill of an anomaly persistence forecast. We show for the first time that initializing the ocean subsurface in a seasonal prediction system can yield significant regional skill for winter SIE. Similarly, as suggested by previous work, we find that sea-ice thickness initial conditions provide a crucial source of skill for regional summer SIE.
The relationship between the North Atlantic Oscillation (NAO) and Atlantic sea surface temperature (SST) variability is investigated using models and observations. Coupled climate models are used in which the ocean component is either a fully dynamic ocean, or a slab ocean with no resolved ocean heat transport. On time scales less than ten years NAO variations drive a tripole pattern of SST anomalies in both observations and models. This SST pattern is a direct response of the ocean mixed layer to turbulent surface heat flux anomalies associated with the NAO.
On time scales longer than ten years a similar relationship exists between the NAO and the tripole pattern of SST anomalies in models with a slab ocean. A different relationship exists both for the observations and for models with a dynamic ocean. In these models a positive (negative) NAO anomaly leads, after a decadal-scale lag, to a monopole pattern of warming (cooling) that resembles the Atlantic Multidecadal Oscillation (AMO), although with smaller than observed amplitudes of tropical SST anomalies. Ocean dynamics are critical to this decadal scale response in the models. The simulated Atlantic Meridional Overturning Circulation (AMOC) strengthens (weakens) in response to a prolonged positive (negative) phase of the NAO, thereby enhancing (decreasing) poleward heat transport, leading to broad scale warming (cooling).
We use additional simulations in which heat flux anomalies derived from observed NAO variations from 1901 to 2014 are applied to the ocean component of coupled models. We show that ocean dynamics allow models to reproduce important aspects of the observed AMO, mainly in the subpolar gyre.
There is large uncertainty in the simulation of transient climate sensitivity. This study aims to understand how such uncertainty is related to the simulation of the base climate by comparing two simulations with the same model but in which CO2 is increased from either a preindustrial (1860) or a present-day (1990) control simulation. This allows different base climate ocean circulations that are representative of those in current climate models to be imposed upon a single model. As a result, the model projects different transient climate sensitivities that are comparable to the multimodel spread. The greater warming in the 1990-start run occurs primarily at high latitudes and particularly over regions of oceanic convection. In the 1990-start run, ocean overturning circulations are initially weaker and weaken less from CO2 forcing. As a consequence, there are smaller reductions in the poleward ocean heat transport, leading to less tropical ocean heat storage and less moderated high-latitude surface warming. This process is evident in both hemispheres, with changes in the Atlantic meridional overturning circulation and the Antarctic Bottom Water formation dominating the warming differences in each hemisphere. The high-latitude warming in the 1990-start run is enhanced through albedo and cloud feedbacks, resulting in a smaller ocean heat uptake efficacy. The results highlight the importance of improving the base climate ocean circulation in order to provide a reasonable starting point for assessments of past climate change and the projection of future climate change.
This study explores the role of the stratosphere as a source of seasonal predictability of surface climate over Northern Hemisphere extra-tropics both in the observations and climate model predictions. A suite of numerical experiments, including climate simulations and retrospective forecasts, are set up to isolate the role of the stratosphere in seasonal predictive skill of extra-tropical near surface land temperature. We show that most of the lead-0 month spring predictive skill of land temperature over extra-tropics, particularly over northern Eurasia, stems from stratospheric initialization. We further reveal that this predictive skill of extra-tropical land temperature arises from skillful prediction of the Arctic Oscillation (AO). The dynamical connection between the stratosphere and troposphere is also demonstrated by the significant correlation between the stratospheric polar vortex and sea level pressure anomalies, as well as the migration of the stratospheric zonal wind anomalies to the lower troposphere.
Khouakhi, A, Gabriele Villarini, and Gabriel A Vecchi, January 2017: Contribution of tropical cyclones to rainfall at the global scale. Journal of Climate, 30(1), DOI:10.1175/JCLI-D-16-0298.1. Abstract
This study quantifies the relative contribution of tropical cyclones (TCs) to annual, seasonal and extreme rainfall, and examines the connection between El Niño–Southern Oscillation (ENSO) and the occurrence of extreme TC-induced rainfall across the globe. We use historical six-hour best track TC datasets and daily precipitation data from 18607 global rain gauges with at least 25 complete years of data between 1970 and 2014. The highest TC-induced rainfall totals occur in eastern Asia (>400 mm/year) and northeastern Australia (>200mm/year), followed by the southeastern United States and along the coast of the Gulf of Mexico (100 to 150 mm/year). Fractionally, TCs account for 35% to 50% of the mean annual rainfall in northwestern Australia, southeastern China, the northern Philippines and Baja California, Mexico. Seasonally, between 40% and 50% of TC-induced rain is recorded along the western coast of Australia and in islands of the south Indian Ocean in the austral summer, and in eastern Asia and Mexico in boreal summer and fall. In terms of extremes, using annual maximum and peak-over-threshold approaches, we find the highest proportions of TC-induced rainfall in East Asia, followed by Australia and North-Central America, with fractional contributions generally decreasing as one moves inland from the coast. The relationship between TC-induced extreme rainfall and ENSO reveals that TC-induced extreme rainfall tends to occur more frequently in Australia and along the U.S. East Coast during La Niña, and along eastern Asia and the northwestern Pacific islands during El Niño.
Liu, Maofeng, Gabriel A Vecchi, James A Smith, and Hiroyuki Murakami, April 2017: The Present-Day Simulation and Twenty-First-Century Projection of the Climatology of Extratropical Transition in the North Atlantic. Journal of Climate, 30(8), DOI:10.1175/JCLI-D-16-0352.1. Abstract
This study explores the simulations and 21st century projections of extratropical transition (ET) of tropical cyclones (TCs) in the North Atlantic, with a newly developed global climate model: the Forecast-oriented Low Ocean Resolution (FLOR) version of the Geophysical Fluid Dynamics Laboratory (GFDL) Coupled Model version 2.5 (CM2.5). FLOR exhibits good skill in simulating present-day ET properties (e.g., Cyclone Phase Space parameters). A version of FLOR in which sea surface temperature (SST) biases are artificially corrected through flux-adjustment (FLOR-FA) shows much improved simulation of ET activity (e.g., annual ET number). This result is largely attributable to better simulation of basinwide TC activity which is strongly dependent on larger-scale climate simulation. FLOR-FA is also used to explore changes of ET activity in the 21st century under the representative concentration pathway (RCP) 4.5 scenario. We find a contrasting pattern in which regional TC density increases in the eastern North Atlantic and decreases in the western North Atlantic, probably due to changes in the TC genesis location. The increasing TC frequency in the eastern Atlantic is dominated by increased ET cases. The increased density of TCs undergoing ET in the eastern subtropics of the Atlantic shows two propagation paths: one moves northwest towards the northeast coast of the United States and the other moves northeast toward Western Europe, implying increased TC-related risks in these regions. A more TC-favorable future climate, evident in the projected changes of SST and vertical wind shear, is hypothesized to favor the increased ET occurrence in the eastern North Atlantic.
This study proposes an integrated diagnostic framework based on atmospheric circulation regime spatial patterns and frequencies of occurrence to facilitate the identification of model systematic errors across multiple timescales. To illustrate the approach, three sets of 32-year-long simulations are analyzed for northeastern North America and for the March-May season using the Geophysical Fluid Dynamics Laboratory’s Low Ocean-Atmosphere Resolution (LOAR) and Forecast-oriented Low Ocean Resolution (FLOR) coupled models; the main difference between these two models is the horizontal resolution of the atmospheric model used. Regime-dependent biases are explored in the light of different atmospheric horizontal resolutions and under different nudging approaches. It is found that both models exhibit a fair representation of the observed circulation regime spatial patterns and frequencies of occurrence, although some biases are present independently of the horizontal resolution or the nudging approach, and are associated with a misrepresentation of troughs centered north of the Great Lakes, and deep coastal troughs. Moreover, the intra-seasonal occurrence of certain model regimes is delayed with respect to observations. On the other hand, inter-experiment differences in the mean frequencies of occurrence of the simulated weather types, and their variability across multiple timescales, tend to be negligible. This result suggests that low-resolution models could be of potential use to diagnose and predict physical variables via their simulated weather type characteristics.
Given knowledge at the time, the recent 2015–2016 zika virus (ZIKV) epidemic probably could not have been predicted. Without the prior knowledge of ZIKV being already present in South America, and given the lack of understanding of key epidemiologic processes and long-term records of ZIKV cases in the continent, the best related prediction could be carried out for the potential risk of a generic Aedes-borne disease epidemic. Here we use a recently published two-vector basic reproduction number model to assess the predictability of the conditions conducive to epidemics of diseases like zika, chikungunya, or dengue, transmitted by the independent or concurrent presence of Aedes aegypti and Aedes albopictus. We compare the potential risk of transmission forcing the model with the observed climate and with state-of-the-art operational forecasts from the North American Multi Model Ensemble (NMME), finding that the predictive skill of this new seasonal forecast system is highest for multiple countries in Latin America and the Caribbean during the December-February and March-May seasons, and slightly lower—but still of potential use to decision-makers—for the rest of the year. In particular, we find that above-normal suitable conditions for the occurrence of the zika epidemic at the beginning of 2015 could have been successfully predicted at least 1 month in advance for several zika hotspots, and in particular for Northeast Brazil: the heart of the epidemic. Nonetheless, the initiation and spread of an epidemic depends on the effect of multiple factors beyond climate conditions, and thus this type of approach must be considered as a guide and not as a formal predictive tool of vector-borne epidemics.
The 2015 hurricane season in the Eastern and Central Pacific Oceans (EPO and CPO), particularly around Hawaii, was extremely active – including a record number of tropical cyclones (TCs) and the first instance of three simultaneous Category 4 hurricanes in the EPO and CPO. A strong El Niño developed during the 2015 boreal summer season, and was attributed by some to be the cause of the extreme number of TCs. However, according to a suite of targeted high-resolution model experiments, the extreme 2015 EPO and CPO hurricane season was not primarily induced by the 2015 El Niño’s tropical Pacific warming, but by warming in the subtropical Pacific Ocean. This warming is not typical of El Niño, but rather the “Pacific Meridional Mode (PMM)” superimposed on long-term anthropogenic warming. Although the likelihood of such an extreme year depends on the phase of natural variability, the coupled GCM projects an increase in the frequency of such extremely active TC years over the next few decades for the EPO, CPO, and Hawaii due enhanced subtropical Pacific warming from anthropogenic greenhouse forcing.
In 2014 and 2015, post-monsoon extremely severe cyclonic storms (ESCS)—defined by the WMO as tropical storms with lifetime maximum winds greater than 46 m s−1—were first observed over the Arabian Sea (ARB), causing widespread damage. However, it is unknown to what extent this abrupt increase in post-monsoon ESCSs can be linked to anthropogenic warming, natural variability, or stochastic behaviour. Here, using a suite of high-resolution global coupled model experiments that accurately simulate the climatological distribution of ESCSs, we show that anthropogenic forcing has likely increased the probability of late-season ECSCs occurring in the ARB since the preindustrial era. However, the specific timing of observed late-season ESCSs in 2014 and 2015 was likely due to stochastic processes. It is further shown that natural variability played a minimal role in the observed increase of ESCSs. Thus, continued anthropogenic forcing will further amplify the risk of cyclones in the ARB, with corresponding socio-economic implications.
Future changes in the North American monsoon, a circulation system that brings abundant summer rains to vast areas of the North American Southwest1, 2, could have significant consequences for regional water resources3. How this monsoon will change with increasing greenhouse gases, however, remains unclear4, 5, 6, not least because coarse horizontal resolution and systematic sea-surface temperature biases limit the reliability of its numerical model simulations5, 7. Here we investigate the monsoon response to increased atmospheric carbon dioxide (CO2) concentrations using a 50-km-resolution global climate model which features a realistic representation of the monsoon climatology and its synoptic-scale variability8. It is found that the monsoon response to CO2 doubling is sensitive to sea-surface temperature biases. When minimizing these biases, the model projects a robust reduction in monsoonal precipitation over the southwestern United States, contrasting with previous multi-model assessments4, 9. Most of this precipitation decline can be attributed to increased atmospheric stability, and hence weakened convection, caused by uniform sea-surface warming. These results suggest improved adaptation measures, particularly water resource planning, will be required to cope with projected reductions in monsoon rainfall in the American Southwest.
Salvi, K, Gabriele Villarini, and Gabriel A Vecchi, October 2017: High resolution decadal precipitation predictions over the continental United States for impacts assessment. Journal of Hydrology, 553, DOI:10.1016/j.jhydrol.2017.07.043. Abstract
Unprecedented alterations in precipitation characteristics over the last century and especially in the last two decades have posed serious socio-economic problems to society in terms of hydro-meteorological extremes, in particular flooding and droughts. The origin of these alterations has its roots in changing climatic conditions; however, its threatening implications can only be dealt with through meticulous planning that is based on realistic and skillful decadal precipitation predictions (DPPs). Skillful DPPs represent a very challenging prospect because of the complexities associated with precipitation predictions. Because of the limited skill and coarse spatial resolution, the DPPs provided by General Circulation Models (GCMs) fail to be directly applicable for impact assessment. Here, we focus on nine GCMs and quantify the seasonally and regionally averaged skill in DPPs over the continental United States. We address the problems pertaining to the limited skill and resolution by applying linear and kernel regression-based statistical downscaling approaches. For both the approaches, statistical relationships established over the calibration period (1961–1990) are applied to the retrospective and near future decadal predictions by GCMs to obtain DPPs at ∼4 km resolution. The skill is quantified across different metrics that evaluate potential skill, biases, long-term statistical properties, and uncertainty. Both the statistical approaches show improvements with respect to the raw GCM data, particularly in terms of the long-term statistical properties and uncertainty, irrespective of lead time. The outcome of the study is monthly DPPs from nine GCMs with 4-km spatial resolution, which can be used as a key input for impacts assessments.
Salvi, K, Gabriele Villarini, and Gabriel A Vecchi, et al., November 2017: Decadal temperature predictions over the continental United States: Analysis and Enhancement. Climate Dynamics, 49(9-10), DOI:10.1007/s00382-017-3532-1. Abstract
Increases in global temperature over recent decades and the projected acceleration in warming trends over the 21 century have resulted in a strong need to obtain information about future temperature conditions. Hence, skillful decadal temperature predictions (DTPs) can have profound societal and economic benefits through informed planning and response. However, skillful and actionable DTPs are extremely challenging to achieve. Even though general circulation models (GCMs) provide decadal predictions of different climate variables, the direct use of GCM data for regional-scale impacts assessment is not encouraged because of the limited skill they possibly exhibit and their coarse spatial resolution. Here, we focus on 14 GCMs and evaluate seasonally and regionally averaged skills in DTPs over the continental United States. Moreover, we address the limitations in skill and spatial resolution in the GCM outputs using two data-driven approaches: (1) quantile-based bias correction and (2) linear regression-based statistical downscaling. For both the approaches, statistical parameters/relationships, established over the calibration period (1961–1990) are applied to retrospective and near future decadal predictions by GCMs to obtain DTPs at ‘4 km’ resolution. Predictions are assessed using different evaluation metrics, long-term statistical properties, and uncertainty in terms of the range of predictions. Both the approaches adopted here show improvements with respect to the raw GCM data, particularly in terms of the long-term statistical properties and uncertainty, irrespective of lead time. The outcome of the study is monthly DTPs from 14 GCMs with a spatial resolution of 4 km, which can be used as a key input for impacts assessments.
Tommasi, Desiree, Charles A Stock, A J Hobday, R Methot, Isaac C Kaplan, J P Eveson, Kirstin Holsman, Timothy J Miller, Sarah K Gaichas, Marion Gehlen, A Pershing, Gabriel A Vecchi, Rym Msadek, Thomas L Delworth, C M Eakin, Melissa A Haltuch, Roland Séférian, C M Spillman, J R Hartog, Samantha A Siedlecki, Jameal F Samhouri, Barbara A Muhling, R G Asch, Malin L Pinsky, Vincent S Saba, Sarah B Kapnick, and Carlos F Gaitán, et al., March 2017: Managing living marine resources in a dynamic environment: The role of seasonal to decadal climate forecasts. Progress in Oceanography, 152, DOI:10.1016/j.pocean.2016.12.011. Abstract
Recent developments in global dynamical climate prediction systems have allowed for skillful predictions of climate variables relevant to living marine resources (LMRs) at a scale useful to understanding and managing LMRs. Such predictions present opportunities for improved LMR management and industry operations, as well as new research avenues in fisheries science. LMRs respond to climate variability via changes in physiology and behavior. For species and systems where climate-fisheries links are well established, forecasted LMR responses can lead to anticipatory and more effective decisions, benefitting both managers and stakeholders. Here, we provide an overview of climate prediction systems and advances in seasonal to decadal prediction of marine-resource relevant environmental variables. We then describe a range of climate-sensitive LMR decisions that can be taken at lead-times of months to decades, before highlighting a range of pioneering case studies using climate predictions to inform LMR decisions. The success of these case studies suggests that many additional applications are possible. Progress, however, is limited by observational and modeling challenges. Priority developments include strengthening of the mechanistic linkages between climate and marine resource responses, development of LMR models able to explicitly represent such responses, integration of climate driven LMR dynamics in the multi-driver context within which marine resources exist, and improved prediction of ecosystem-relevant variables at the fine regional scales at which most marine resource decisions are made. While there are fundamental limits to predictability, continued advances in these areas have considerable potential to make LMR managers and industry decision more resilient to climate variability and help sustain valuable resources. Concerted dialog between scientists, LMR managers and industry is essential to realizing this potential.
Tommasi, Desiree, Charles A Stock, Kathleen Pegion, and Gabriel A Vecchi, et al., March 2017: Improved management of small pelagic fisheries through seasonal climate prediction. Ecological Applications, 27(2), DOI:10.1002/eap.1458. Abstract
Populations of small pelagic fish are strongly influenced by climate. The inability of managers to anticipate environment-driven fluctuations in stock productivity or distribution can lead to overfishing and stock collapses, inflexible management regulations inducing shifts in the functional response to human predators, lost opportunities to harvest populations, bankruptcies in the fishing industry, and loss of resilience in the human food supply. Recent advances in dynamical global climate prediction systems allow for sea surface temperature (SST) anomaly predictions at a seasonal scale over many shelf ecosystems. Here we assess the utility of SST predictions at this “fishery relevant” scale to inform management, using Pacific sardine as a case study. The value of SST anomaly predictions to management was quantified under four harvest guidelines (HGs) differing in their level of integration of SST data and predictions. The HG that incorporated stock biomass forecasts informed by skillful SST predictions led to increases in stock biomass and yield, and reductions in the probability of yield and biomass falling below socioeconomic or ecologically acceptable levels. However, to mitigate the risk of collapse in the event of an erroneous forecast, it was important to combine such forecast-informed harvest controls with additional harvest restrictions at low biomass.
Decisions made by fishers and fisheries managers are informed by climate and fisheries observations that now often span more than 50 years. Multi-annual climate forecasts could further inform such decisions if they were skillful in predicting future conditions relative to the 50-year scope of past variability. We demonstrate that an existing multi-annual prediction system skillfully forecasts the probability of next year, the next 1–3 years, and the next 1–10 years being warmer or cooler than the 50-year average at the surface in coastal ecosystems. Probabilistic forecasts of upper and lower seas surface temperature (SST) terciles over the next 3 or 10 years from the GFDL CM 2.1 10-member ensemble global prediction system showed significant improvements in skill over the use of a 50-year climatology for most Large Marine Ecosystems (LMEs) in the North Atlantic, the western Pacific, and Indian oceans. Through a comparison of the forecast skill of initialized and uninitialized hindcasts, we demonstrate that this skill is largely due to the predictable signature of radiative forcing changes over the 50-year timescale rather than prediction of evolving modes of climate variability. North Atlantic LMEs stood out as the only coastal regions where initialization significantly contributed to SST prediction skill at the 1 to 10 year scale.
van der Wiel, Karin, Sarah B Kapnick, G J van Oldenborgh, K Whan, S Philip, Gabriel A Vecchi, R K Singh, J Arrighi, and H Cullen, February 2017: Rapid attribution of the August 2016 flood-inducing extreme precipitation in south Louisiana to climate change. Hydrology and Earth System Sciences, 21(2), DOI:10.5194/hess-21-897-2017. Abstract
A stationary low pressure system and elevated levels of precipitable water provided a nearly continuous source of precipitation over Louisiana, United States (U.S.) starting around 10 August, 2016. Precipitation was heaviest in the region broadly encompassing the city of Baton Rouge, with a three-day maximum found at a station in Livingston, LA (east of Baton Rouge) from 12–14 August, 2016 (648.3 mm, 25.5 inches). The intense precipitation was followed by inland flash flooding and river flooding and in subsequent days produced additional backwater flooding. On 16 August, Louisiana officials reported that 30,000 people had been rescued, nearly 10,600 people had slept in shelters on the night of 14 August, and at least 60,600 homes had been impacted to varying degrees. As of 17 August, the floods were reported to have killed at least thirteen people. As the disaster was unfolding, the Red Cross called the flooding the worst natural disaster in the U.S. since Super Storm Sandy made landfall in New Jersey on 24 October, 2012. Before the floodwaters had receded, the media began questioning whether this extreme event was caused by anthropogenic climate change. To provide the necessary analysis to understand the potential role of anthropogenic climate change, a rapid attribution analysis was launched in real-time using the best readily available observational data and high-resolution global climate model simulations.
The objective of this study is to show the possibility of performing rapid attribution studies when both observational and model data, and analysis methods are readily available upon the start. It is the authors aspiration that the results be used to guide further studies of the devastating precipitation and flooding event. Here we present a first estimate of how anthropogenic climate change has affected the likelihood of a comparable extreme precipitation event in the Central U.S. Gulf Coast. While the flooding event of interest triggering this study occurred in south Louisiana, for the purposes of our analysis, we have defined an extreme precipitation event by taking the spatial maximum of annual 3-day inland maximum precipitation over the region: 29–31º N, 85–95º W, which we refer to as the Central U.S. Gulf Coast. Using observational data, we find that the observed local return time of the 12–14 August precipitation event in 2016 is about 550 years (95 % confidence interval (C.I.): 450–1450). The probability for an event like this to happen anywhere in the region is presently 1 in 30 years (C.I. 11–110). We estimate that these probabilities and the intensity of extreme precipitation events of this return time have increased since 1900. A Central U.S. Gulf Coast extreme precipitation event has effectively become more likely in 2016 than it was in 1900. The global climate models tell a similar story, with the regional probability of 3-day extreme precipitation increasing due to anthropogenic climate change by a factor of more than a factor 1.4 in the most accurate analyses. The magnitude of the shift in probabilities is greater in the 25 km (higher resolution) climate model than in the 50 km model. The evidence for a relation to El Niño half a year earlier is equivocal, with some analyses showing a positive connection and others none.
Climate change has been shown to impact the mean climate state and climate extremes. Though climate extremes have the potential to disrupt society, extreme conditions are rare by definition. In contrast, mild weather occurs frequently and many human activities are built around it. We provide a global analysis of mild weather based on simple criteria and explore changes in response to radiative forcing. We find a slight global mean decrease in the annual number of mild days projected both in the near future (−4 days per year, 2016–2035) and at the end of this century (−10 days per year, 2081–2100). Projected seasonal and regional redistributions of mild days are substantially greater. These changes are larger than the interannual variability of mild weather caused by El Niño–Southern Oscillation. Finally, we show an observed global decrease in the recent past, and that observed regional changes in mild weather resemble projections.
Temperature variability in the North Atlantic Ocean is the result of many competing physical processes, but the relative roles of these processes is a source of contention. Here, scientists present two perspectives on the debate.
The TAO/TRITON array is the cornerstone of the tropical Pacific and ENSO observing system. Motivated by the recent rapid decline of the TAO/TRITON array, the potential utility of TAO/TRITON was assessed for ENSO monitoring and prediction. The analysis focused on the period when observations from Argo floats were also available. We coordinated observing system experiments (OSEs) using the global ocean data assimilation system (GODAS) from the National Centers for Environmental Prediction and the ensemble coupled data assimilation (ECDA) from the Geophysical Fluid Dynamics Laboratory for the period 2004–2011. Four OSE simulations were conducted with inclusion of different subsets of in situ profiles: all profiles (XBT, moorings, Argo), all except the moorings, all except the Argo and no profiles. For evaluation of the OSE simulations, we examined the mean bias, standard deviation difference, root-mean-square difference (RMSD) and anomaly correlation against observations and objective analyses. Without assimilation of in situ observations, both GODAS and ECDA had large mean biases and RMSD in all variables. Assimilation of all in situ data significantly reduced mean biases and RMSD in all variables except zonal current at the equator. For GODAS, the mooring data is critical in constraining temperature in the eastern and northwestern tropical Pacific, while for ECDA both the mooring and Argo data is needed in constraining temperature in the western tropical Pacific. The Argo data is critical in constraining temperature in off-equatorial regions for both GODAS and ECDA. For constraining salinity, sea surface height and surface current analysis, the influence of Argo data was more pronounced. In addition, the salinity data from the TRITON buoys played an important role in constraining salinity in the western Pacific. GODAS was more sensitive to withholding Argo data in off-equatorial regions than ECDA because it relied on local observations to correct model biases and there were few XBT profiles in those regions. The results suggest that multiple ocean data assimilation systems should be used to assess sensitivity of ocean analyses to changes in the distribution of ocean observations to get more robust results that can guide the design of future tropical Pacific observing systems.
This study examines the year-to-year modulation of the western North Pacific (WNP) tropical cyclones (TC) activity by the Atlantic Meridional Mode (AMM) using both observations and the Geophysical Fluid Dynamics Laboratory Forecast-oriented Low Ocean Resolution Version of CM2.5 (FLOR) global coupled model. 1. The positive (negative) AMM phase suppresses (enhances) WNP TC activity in observations. The anomalous occurrence of WNP TCs results mainly from changes in TC genesis in the southeastern part of the WNP. 2. The observed responses of WNP TC activity to the AMM are connected to the anomalous zonal vertical wind shear (ZVWS) caused by AMM-induced changes to the Walker circulation. During the positive AMM phase, the warming in the North Atlantic induces strong descending flow in the tropical eastern and central Pacific, which intensifies the Walker cell in the WNP. The intensified Walker cell is responsible for the suppressed (enhanced) TC genesis in the eastern (western) part of the WNP by strengthening (weakening) ZVWS. 3. The observed WNPTC–AMM linkage is examined by the long-term control and idealized perturbations experiment with FLOR-FA. A suite of sensitivity experiments strongly corroborate the observed WNPTC–AMM linkage and underlying physical mechanisms.
This study attempts to improve the prediction of western North Pacific (WNP) and East Asia (EA) landfalling tropical cyclones (TCs) using modes of large-scale climate variability [e.g., the Pacific meridional mode (PMM), the Atlantic meridional mode (AMM), and North Atlantic sea surface temperature anomalies (NASST)] as predictors in a hybrid statistical–dynamical scheme, based on dynamical model forecasts with the GFDL Forecast-Oriented Low Ocean Resolution version of CM2.5 with flux adjustments (FLOR-FA). Overall, the predictive skill of the hybrid model for the WNP TC frequency increases from lead month 5 (initialized in January) to lead month 0 (initialized in June) in terms of correlation coefficient and root-mean-square error (RMSE). The hybrid model outperforms FLOR-FA in predicting WNP TC frequency for all lead months. The predictive skill of the hybrid model improves as the forecast lead time decreases, with values of the correlation coefficient increasing from 0.56 for forecasts initialized in January to 0.69 in June. The hybrid models for landfalling TCs over the entire East Asian (EEA) coast and its three subregions [i.e., southern EA (SEA), middle EA (MEA), and northern EA (NEA)] dramatically outperform FLOR-FA. The correlation coefficient between predicted and observed TC landfall over SEA increases from 0.52 for forecasts initialized in January to 0.64 in June. The hybrid models substantially reduce the RMSE of landfalling TCs over SEA and EEA compared with FLOR-FA. This study suggests that the PMM and NASST/AMM can be used to improve statistical/hybrid forecast models for the frequencies of WNP or East Asia landfalling TCs.
This study explores the potential predictability of the Southern Ocean (SO) climate on decadal timescales as represented in the GFDL CM2.1 model using prognostic methods. We conduct perfect model predictability experiments starting from ten different initial states, and show potentially predictable variations of Antarctic bottom water formation (AABW) rates on time scales as long as twenty years. The associated Weddell Sea (WS) subsurface temperatures and Antarctic sea ice have comparable potential predictability as the AABW cell. The predictability of sea surface temperature (SST) variations over the WS and the SO is somewhat smaller, with predictable scales out to a decade. This reduced predictability is likely associated with stronger damping from air-sea interaction. As a complement to our perfect predictability study, we also make hindcasts of SO decadal variability using the GFDL CM2.1 decadal prediction system. Significant predictive skill for SO SST on multi-year time scales is found in the hindcast system. The success of the hindcasts, especially in reproducing observed surface cooling trends, is largely due to initializing the state of the AABW cell. A weak state of the AABW cell leads to cooler surface conditions and more extensive sea ice. Although there are considerable uncertainties regarding the observational data used to initialize the hindcasts, the consistency between the perfect model experiments and the decadal hindcasts at least gives us some indication as to where and to what extent skillful decadal SO forecasts might be possible.
Zhang, Wei, Gabriele Villarini, and Gabriel A Vecchi, April 2017: Impacts of the Pacific Meridional Mode on June-August Precipitation in the Amazon River Basin. Quarterly Journal of the Royal Meteorological Society, 143(705), DOI:10.1002/qj.3053. Abstract
This study examines the impacts of the Pacific Meridional Mode (PMM) on Amazon precipitation during the June-August months using observations and several experiments with the National Oceanic and Atmospheric Administration/Geophysical Fluid Dynamics Laboratory (NOAA/GFDL) Forecast-oriented Low Ocean Resolution Version of CM2.5 (FLOR). We find that the positive (negative) PMM can lead to precipitation surplus (deficit) using both observations and climate simulations with FLOR. The impacts of PMM on Amazon precipitation during June-August are induced by the forcing of sea surface temperature (SST) anomalies associated with PMM. Positive PMM can force the baroclinic Gill responses to the heat source in the Pacific with two low-level cyclones (anticyclones) located west (east) of the heating source. The anomalous low-level anticyclone and high-level cyclone located in the Amazon region are associated with low-level moisture moisture transport from the Atlantic. There is significant positive correlation between the PMM index and moisture flux convergence in most part of the Amazon basin, with negative correlation in its northwestern part. Such physical mechanisms underlying the linkage between PMM and the Amazon precipitation are supported by both the 500-year control experiment and a suite of perturbation experiments with FLOR.
Zhao, Y, X Deng, Shaoqing Zhang, Zhengyu Liu, C Liu, and Gabriel A Vecchi, et al., November 2017: Impact of Optimal Observational Time Window on Coupled Data Assimilation: Simulation with a Simple Climate Model. Nonlinear Processes in Geophysics, 24(4), DOI:10.5194/npg-24-681-2017. Abstract
Climate signals are the results of interactions of multiple time scale media such as the atmosphere and ocean in the coupled earth system. Coupled data assimilation (CDA) pursues balanced and coherent climate analysis and prediction initialization by incorporating observations from multiple media into a coupled model. In practice, an observational time window (OTW) is usually used to collect measured data for an assimilation cycle to increase observational samples. Given different time scales of characteristic variability in different media, what are the optimal OTWs for the coupled media so that climate signals can be most accurately recovered by CDA? With a simple coupled model that simulates typical scale interactions in the climate system, we address this issue here. Results show that required by retrieval of characteristic variability of each coupled medium, an optimal OTW determined from the de-correlation time scale provides maximal observational information that best fits characteristic variability of the medium during the data blending process. Maintaining correct scale interactions, the resulted CDA improves the analysis of climate signals greatly. The simple model results provide a guideline when the real observations are assimilated into a coupled general circulation model for improving climate analysis and prediction initialization by accurately recovering important characteristic variability such as sub-diurnal in the atmosphere and diurnal in the ocean.
Arid Extratropical Asia (AEA) is bisected at the wetter Tianshan Mountains (a northern offshoot of the Tibetan Plateau) into East and West Deserts, each with unique climatological characteristics. The East Deserts (~ 75 – 115°E, ~ 35 – 55°N) have a summer precipitation maximum, and the West Deserts (~ 45 – 75°E, ~ 35 – 55°N) have a winter-spring precipitation maximum. A new high-resolution (50 km atmosphere/land) global coupled climate model is run with the Tianshan Mountains removed to determine whether these mountains are responsible for the climatological East-West differentiation of AEA. Multi-centennial simulations for the Control and NoTianshan runs highlight statistically significant effects of the Tianshan. Overall, the Tianshan are found to enhance the precipitation seasonality gradient across AEA, mostly through altering the East Deserts. The Tianshan dramatically change the precipitation seasonality of the Taklimakan Desert directly to its east (the driest part of AEA), by blocking West winter precipitation, enhancing subsidence over this region, and increasing East summer precipitation. The Tianshan increase East summer precipitation through two mechanisms: 1) orographic precipitation which is greatest on the eastern edge of the Tianshan in summer, and 2) remote enhancement of the East Asian Summer Monsoon through alteration of the larger-scale seasonal mean atmospheric circulation. The decrease in East winter precipitation also generates remote warming of the Altai and Kunlun Mountains, northeast and southeast of the Tianshan respectively, due to reduction of snow cover and corresponding albedo decrease.
Pronounced climate changes have occurred since the 1970s, including rapid loss of Arctic sea ice1, large-scale warming2 and increased tropical storm activity3 in the Atlantic. Anthropogenic radiative forcing is likely to have played a major role in these changes4, but the relative influence of anthropogenic forcing and natural variability is not well established. The above changes have also occurred during a period in which the North Atlantic Oscillation has shown marked multidecadal variations5. Here we investigate the role of the North Atlantic Oscillation in these rapid changes through its influence on the Atlantic meridional overturning circulation and ocean heat transport. We use climate models to show that observed multidecadal variations of the North Atlantic Oscillation can induce multidecadal variations in the Atlantic meridional overturning circulation and poleward ocean heat transport in the Atlantic, extending to the Arctic. Our results suggest that these variations have contributed to the rapid loss of Arctic sea ice, Northern Hemisphere warming, and changing Atlantic tropical storm activity, especially in the late 1990s and early 2000s. These multidecadal variations are superimposed on long-term anthropogenic forcing trends that are the dominant factor in long-term Arctic sea ice loss and hemispheric warming.
Han, R, H Wang, Zeng-Zhen Hu, Arun Kumar, W Li, L Long, J-K E Schemm, P Peng, Wanqui Wang, D Si, X Jia, Ming Zhao, and Gabriel A Vecchi, et al., September 2016: An assessment of multi-model simulations for the variability of western North Pacific tropical cyclones and its association with ENSO. Journal of Climate, 29(18), DOI:10.1175/JCLI-D-15-0720.1. Abstract
An assessment of simulations of the interannual variability of tropical cyclones (TCs) over the western North Pacific (WNP) and its association with El Niño–Southern Oscillation (ENSO), as well as a subsequent diagnosis for possible causes of model biases generated from simulated large scale climate conditions, are documented in the paper. The model experiments are carried out by the Hurricane Work Group under the U.S. Climate Variability and Predictability Research Program (CLIVAR) using five global climate models (GCMs) with a total of 16 ensemble members forced by the observed sea surface temperature, and spanning the 28-yr period from 1982 to 2009. The results show GISS and GFDL model ensemble means best simulate the interannual variability of TCs and the multi-model ensemble mean (MME) follows. Also, the MME has the closest climate mean annual number of WNP TCs and the smallest root-mean-square error to the observation.
Most GCMs can simulate the interannual variability of WNP TCs well, with stronger TC activities during two types of El Niño, namely eastern Pacific (EP) and central Pacific (CP) El Niño, and weaker activity during La Niña. However, none of the models capture the differences in TC activity between EP and CP El Niño as shown in observations. The inability of models to distinguish the differences in TC activities between the two types of El Niño events may be due to the bias of the models in response to the shift of tropical heating associated with CP El Niño.
This study investigates the roles of radiative forcing, sea surface temperatures (SSTs), and atmospheric and land initial conditions in the summer warming episodes of the United States. The summer warming episodes are defined as the significantly above normal (1983-2012) June-August 2-m temperature anomalies, and are referred to as heat waves in this study. Two contrasting cases, the summers of 2006 and 2012, are explored in detail to illustrate the distinct roles of SSTs, direct radiative forcing, and atmospheric and land initial conditions in driving U.S. summer heat waves. For 2012, simulations with the GFDL atmospheric general circulation model reveal that SSTs play a critical role. Further sensitivity experiments reveal the contributions of uniform global SST warming, SSTs in individual ocean basins and direct radiative forcing to the geographic distribution and magnitudes of warm temperature anomalies. In contrast, for 2006, the atmospheric and land initial conditions are key drivers. The atmospheric (land) initial conditions play a major (minor) role in the central and northwestern (eastern) U.S.. Due to changes in radiative forcing, the probability of areal-averaged summer temperature anomalies over U.S. exceeding the observed 2012 anomaly increases with time over the early 21st century. La Niña (El Niño) events tend to increase (reduce) the occurrence rate of heat waves. The temperatures over the central U.S. are mostly influenced by El Niño/La Niña, with the central tropical Pacific playing a more important role than the eastern tropical Pacific. Thus, atmospheric and land initial conditions, SSTs and radiative forcing are all important drivers of, and sources of predictability for U.S. summer heat waves.
Kossin, James, Kerry A Emanuel, and Gabriel A Vecchi, June 2016: Comment on 'Roles of interbasin frequency changes in the poleward shifts of the maximum intensity location of tropical cyclones'. Environmental Research Letters, 11(6), DOI:10.1088/1748-9326/11/6/068001.
Tropical cyclone (TC) activity in the North Pacific and North Atlantic Oceans is known to be affected by the El Niño Southern Oscillation (ENSO). This study uses GFDL FLOR model, which has relatively high-resolution in the atmosphere, as a tool to investigate the sensitivity of TC activity to the strength of ENSO events. We show that TCs exhibit a non-linear response to the strength of ENSO in the tropical eastern North Pacific (ENP) but a quasi-linear response in the tropical western North Pacific (WNP) and tropical North Atlantic. Specifically, stronger El Niño results in disproportionate inhibition of TCs in the ENP and North Atlantic, and leads to an eastward shift in the location of TCs in the southeast of the WNP. However, the character of the response of TCs in the Pacific is insensitive to the amplitude of La Niña events. The eastward shift of TCs in the southeast of the WNP in response to a strong El Niño is due to an eastward shift of the convection and of the associated environmental conditions favorable for TCs. The inhibition of TC activity in the ENP and Atlantic during El Niño is attributed to the increase in the number of days with strong vertical wind shear during stronger El Niño events. These results are further substantiated with coupled model experiments. Understanding of the impact of strong ENSO on TC activity is important for present and future climate as the frequency of occurrence of extreme ENSO events is projected to increase in future.
Retrospective seasonal forecasts of North Atlantic tropical cyclone (TC) activity over the period 1980–2014 are conducted using a GFDL high-resolution coupled climate model [Forecast-Oriented Low Ocean Resolution (FLOR)]. The focus is on basin-total TC and U.S. landfall frequency. The correlations between observed and model predicted basin-total TC counts range from 0.4 to 0.6 depending on the month of the initial forecast. The correlation values for U.S. landfalling activity based on individual TCs tracked from the model are smaller and between 0.1 and 0.4. Given the limited skill from the model, statistical methods are used to complement the dynamical seasonal TC prediction from the FLOR model. Observed and predicted TC tracks were classified into four groups using fuzzy c-mean clustering to evaluate the model’s predictability in observed classification of TC tracks. Analyses revealed that the FLOR model has the highest skill in predicting TC frequency for the cluster of TCs that tracks through the Caribbean and the Gulf of Mexico.
New hybrid models are developed to improve the prediction of observed basin-total TC and landfall TC frequencies. These models use large-scale climate predictors from the FLOR model as predictors for generalized linear models. The hybrid models show considerable improvements in the skill in predicting the basin-total TC frequencies relative to the dynamical model. The new hybrid model shows correlation coefficients as high as 0.75 for basinwide TC counts from the first two lead months and retains values around 0.50 even at the 6-month lead forecast. The hybrid model also shows comparable or higher skill in forecasting U.S. landfalling TCs relative to the dynamical predictions. The correlation coefficient is about 0.5 for the 2–5-month lead times.
Skillful seasonal forecasting of tropical cyclone (TC; wind speed ≥17.5 m s−1) activity is challenging, even more so when the focus is on major hurricanes (wind speed ≥49.4 m s−1), the most intense hurricanes (Category 4–5; wind speed ≥58.1 m s−1), and landfalling TCs. Here we show that a 25-km resolution global coupled model (HiFLOR) developed at the Geophysical Fluid Dynamics Laboratory (GFDL) has improved skill in predicting the frequencies of major hurricanes and Category 4–5 hurricanes in the North Atlantic, and landfalling TCs over the United States and Caribbean Islands a few months in advance, relative to its 50-km resolution predecessor climate model (FLOR). HiFLOR also shows significant skill in predicting Category 4–5 hurricanes in the western North Pacific and eastern North Pacific, while both models show comparable skills in predicting basin-total and landfalling TC frequency in the basins. The improved skillful forecasts of basin-total TCs, major hurricanes, and Category 4–5 hurricane activity in the North Atlantic by HiFLOR are obtained mainly by improved representation of the TCs and their response to climate from the increased horizontal resolution, rather than improvements in large-scale parameters.
The impact of atmosphere and ocean horizontal resolution on the climatology of North American Monsoon Gulf of California (GoC) moisture surges is examined in a suite of global circulation models (CM2.1, FLOR, CM2.5, CM2.6, HiFLOR) developed at the Geophysical Fluid Dynamics Laboratory (GFDL). These models feature essentially the same physical parameterizations, but differ in horizontal resolution in either the atmosphere (≃200, 50 and 25 km) or the ocean (≃1°, 0.25°, 0.1°). Increasing horizontal atmospheric resolution from 200 km to 50 km results in a drastic improvement in the model’s capability of accurately simulating surge events. The climatological near-surface flow and moisture and precipitation anomalies associated with GoC surges are overall satisfactorily simulated in all higher-resolution models. The number of surge events agrees well with reanalyses but models tend to underestimate July-August surge-related precipitation and overestimate September surge-related rainfall in the southwestern United States. Large-scale controls supporting the development of GoC surges, such as tropical easterly waves (TEWs), tropical cyclones (TCs) and trans-Pacific Rossby wave trains (RWTs), are also well captured, although models tend to underestimate the TEW/TC magnitude and number. Near-surface GoC surge features and their large-scale forcings (TEWs, TCs, RWTs) do not appear to be substantially affected by a finer representation of the GoC at higher ocean resolution. However, the substantial reduction of the eastern Pacific warm sea surface temperature bias through flux adjustment in the FLOR model leads to an overall improvement of tropical-extratropical controls on GoC moisture surges and the seasonal cycle of precipitation in the southwestern United States.
The Intergovernmental Panel on Climate Change (IPCC) fifth assessment of projected global and regional ocean temperature change is based on global climate models that have coarse (∼100-km) ocean and atmosphere resolutions. In the Northwest Atlantic, the ensemble of global climate models has a warm bias in sea surface temperature due to a misrepresentation of the Gulf Stream position; thus, existing climate change projections are based on unrealistic regional ocean circulation. Here we compare simulations and an atmospheric CO2 doubling response from four global climate models of varying ocean and atmosphere resolution. We find that the highest resolution climate model (∼10-km ocean, ∼50-km atmosphere) resolves Northwest Atlantic circulation and water mass distribution most accurately. The CO2 doubling response from this model shows that upper-ocean (0-300 m) temperature in the Northwest Atlantic Shelf warms at a rate nearly twice as fast as the coarser models and nearly three times faster than the global average. This enhanced warming is accompanied by an increase in salinity due to a change in water mass distribution that is related to a retreat of the Labrador Current and a northerly shift of the Gulf Stream. Both observations and the climate model demonstrate a robust relationship between a weakening Atlantic Meridional Overturning Circulation (AMOC) and an increase in the proportion of Warm-Temperate Slope Water entering the Northwest Atlantic Shelf. Therefore, prior climate change projections for the Northwest Atlantic may be far too conservative. These results point to the need to improve simulations of basin and regional-scale ocean circulation.
Tian, D, Ming Pan, Liwei Jia, Gabriel A Vecchi, and Eric F Wood, July 2016: Assessing GFDL High-Resolution Climate Model Water and Energy Budgets from AMIP simulations over Africa. Journal of Geophysical Research: Atmospheres, 121(14), DOI:10.1002/2016JD025068. Abstract
This study assessed surface water and energy budgets in Atmospheric Model Intercomparison Project (AMIP) simulations of a coupled atmosphere-land model developed by Geophysical Fluid Dynamics Laboratory [Atmospheric General Circulation Model (AM2.5)]. The AM2.5 water and energy budget variables were compared with four reanalyses datasets and an observational-based reference, the Variable Infiltration Capacity model simulations forced by Princeton Global Meteorological Forcing (PGF/VIC) over 20-year period during 1991-2010 in nine African river basins. Results showed that AM2.5 have closed water and energy budgets. However, the discrepancies between AM2.5 and other datasets were notable in terms of their long-term averages. For the water budget, the AM2.5 mostly overestimated precipitation, evapotranspiration, and runoff compared to PGF/VIC and reanalyses. The AM2.5, reanalyses, and PGF/VIC showed similar seasonal cycles but discrepant amplitudes. For the energy budget, while the AM2.5 has relatively consistent net radiation with other datasets, it generally showed higher latent heat, lower sensible heat, and lower Bowen ratio than reanalyses and PGF/VIC. In addition, the AM2.5 water and energy budgets terms mostly had the smallest interannual variability compared to both reanalyses and PGF/VIC. The spatial differences of long-term mean precipitation, runoff, evapotranspiration, and latent heat between AM2.5 and other datasets were reasonably small in dry regions. On average, AM2.5 is closer to PGF/VIC than R2 and 20CR are to PGF/VIC, but is not as close as MERRA and CFSR to PGF/VIC. The bias in AM2.5 water and energy budget terms may be associated with the excessive wet surface and parameterization of moisture advection from ocean to land.
Precipitation extremes have a widespread impact on societies and ecosystems; it is therefore important to understand current and future patterns of extreme precipitation. Here, a set of new global coupled climate models with varying atmospheric resolution has been used to investigate the ability of these models to reproduce observed patterns of precipitation extremes and to investigate changes in these extremes in response to increased atmospheric CO2 concentrations. The atmospheric resolution was increased from 2°×2° grid cells (typical resolution in the CMIP5 archive) to 0.25°×.25° (tropical cyclone-permitting). Analysis has been confined to the contiguous United States (CONUS). It is shown that, for these models, integrating at higher atmospheric resolution improves all aspects of simulated extreme precipitation: spatial patterns, intensities and seasonal timing. In response to 2×CO2 concentrations, all models show a mean intensification of precipitation rates during extreme events of approximately 3-4% K−1. However, projected regional patterns of changes in extremes are dependent on model resolution. For example, the highest-resolution models show increased precipitation rates during extreme events in the hurricane season in the CONUS southeast, this increase is not found in the low-resolution model. These results emphasize that, for the study of extreme precipitation there is a minimum model resolution that is needed to capture the weather phenomena generating the extremes. Finally, the observed record and historical model experiments were used to investigate changes in the recent past. In part because of large intrinsic variability, no evidence was found for changes in extreme precipitation attributable to climate change in the available observed record.
This study investigates the association between the Pacific Meridional Mode (PMM) and tropical cyclone (TC) activity in the western North Pacific (WNP). It is found that the positive PMM phase favors the occurrence of TCs in the WNP while the negative PMM phase inhibits the occurrence of TCs there. Observed relationships are consistent with those from a long-term pre-industrial control experiment (1000 years) of a high-resolution TC-resolving Geophysical Fluid Dynamics Laboratory (GFDL) Forecast-oriented Low Ocean Resolution (FLOR) coupled climate model. The diagnostic relationship between the PMM and TCs in observations and the model is further supported by sensitivity experiments with FLOR. The modulation of TC genesis by the PMM is primarily through the anomalous zonal vertical wind shear (ZVWS) changes in the WNP, especially in the southeastern WNP. The anomalous ZVWS can be attributed to the responses of the atmosphere to the anomalous warming in the northwestern part of the PMM pattern during the positive PMM phase, which resembles a classic Matsuno-Gill pattern. Such influences on TC genesis are strengthened by a cyclonic flow over the WNP. The significant relationship between TCs and the PMM identified here may provide a useful reference for seasonal forecasting of TCs and interpreting changes in TC activity in the WNP.
This study aims to assess whether, and the extent to which, an increase in atmospheric resolution in versions of the Geophysical Fluid Dynamics Laboratory (GFDL) High-Resolution Forecast-oriented Low Ocean Resolution Version of CM2.5 (FLOR) with 50 km and HiFLOR with 25 km improves the simulation of the El Niño Southern Oscillation-tropical cyclone (ENSO-TC) connections in the western North Pacific (WNP). HiFLOR simulates better ENSO-TC connections in the WNP including TC track density, genesis and landfall than FLOR in both long-term control experiments and sea surface temperature (SST)- and sea surface salinity (SSS)-restoring historical runs (1971-2012). Restoring experiments are performed with SSS and SST restored to observational estimates of climatological SSS and interannually-varying monthly SST. In the control experiments of HiFLOR, an improved simulation of the Walker circulation arising from more realistic SST and precipitation is largely responsible for its better performance in simulating ENSO-TC connections in the WNP. In the SST-restoring experiments of HiFLOR, more realistic Walker circulation and steering flow during El Niño/La Niña are responsible for the improved simulation of ENSO-TC connections in the WNP. The improved simulation of ENSO-TC connections with HiFLOR arises from a better representation of SST and better responses of environmental large-scale circulation to SST anomalies associated with El Niño/La Niña. A better representation of ENSO-TC connections in HiFLOR can benefit the seasonal forecasting of TC genesis, track and landfall, improve our understanding of the interannual variation of TC activity, and provide better projection of TC activity under climate change.
Zhang, Wei, Gabriele Villarini, Gabriel A Vecchi, Hiroyuki Murakami, and Richard G Gudgel, June 2016: Statistical-dynamical seasonal forecast of western North Pacific and East Asia landfalling tropical cyclones using the high-resolution GFDL FLOR coupled model. Journal of Advances in Modeling Earth Systems, 8(2), DOI:10.1002/2015MS000607. Abstract
This study examines the seasonal prediction of western North Pacific [WNP) and East Asia landfalling tropical cyclones (TCs) using the Geophysical Fluid Dynamics Laboratory(GFDL) Forecast-oriented Low Ocean Resolution version of CM2.5 with Flux Adjustment (FLOR-FA) and finite-mixture-model (FMM)-based statistical cluster analysis. Using the FMM-based cluster analysis, seven clusters are identified from the historical and FLOR-FA-predicted TC tracks for the period 1980–2013. FLOR-FA has significant skill in predicting year-to-year variations in the frequency of TCs within clusters 1 (recurving TCs) and 5 (straight-moving TCs). By building Poisson regression models for each cluster using key predictors (i.e., sea surface temperature, 500 hPa geopotential height, and zonal vertical wind shear), the predictive skill for almost all the clusters at all initialization months improves with respect to the dynamic prediction. The prediction of total WNP TC frequency made by combining hybrid predictions for each of the seven clusters in the hybrid model shows skill higher than what achieved using the TC frequency directly from FLOR-FA initialized from March to July. However, the hybrid predictions for total WNP TC frequency initialized from January to February exhibit lower skill than FLOR-FA. The prediction of TC landfall over East Asia made by combining the hybrid models of TC frequency in each cluster and its landfall rate over East Asia also outperforms FLOR-FA for all initialization months January through July.
This study aims to assess the connections between the El Niño Southern Oscillation (ENSO) and tropical cyclones near Guam (GuamTC) using the state-of-the-art Geophysical Fluid Dynamics Laboratory (GFDL) Forecast-oriented Low Ocean Resolution Version of CM2.5 (FLOR). In observations, more (less) GuamTCs occur in El Niño (La Niña) years and the ENSO-GuamTC connections arise from TC genesis locations in ENSO phases. The observed ENSO-GuamTC connections are realistically simulated in the two control experiments that use two versions of FLOR, the standard version and another with flux adjustments (FLOR-FA). The ENSO-GuamTC connections in FLOR-FA are closer to observations than those in FLOR because of a better representation of TC genesis during ENSO phases. The physical mechanisms underlying the observed ENSO-GuamTC connections are further supported in the long-term control experiments with FLOR/FLOR-FA. The ENSO-GuamTC connections in sea surface temperature (SST)- and sea surface salinity (SSS)-restoring experiments with FLOR 1990 strongly resemble the observations, suggesting the ENSO-GuamTC connections arise substantially from the forcing of SST. The prediction skill of FLOR-FA for GuamTC frequency is quite promising in terms of correlation and root mean square error and is higher than that of FLOR for the period 1980-2014. This study shows the capability of global climate models (FLOR/FLOR-FA) in simulating the linkage between ENSO and TC activity near a highly localized region (i.e., Guam) and in predicting the frequency of TCs at the sub-basin scale.
Observed austral summertime (November through April) rainfall in southeastern South America (SESA)—including northern Argentina, Uruguay, southern Brazil and Paraguay—has exhibited substantial low-frequency variations with a multi-decadal moistening trend during the 20th century and a subsequent decadal drying trend during the current century. Understanding the mechanisms responsible for these variations is essential for predicting long-term rainfall changes. Here with a suite of attribution experiments using a pair of high-resolution global climate models—GFDL CM2.5 and FLOR_FA, we investigate the causes of these regional rainfall variations. Both models reproduce the 20th-century moistening trend, albeit with a weaker magnitude than observed, in response to the radiative forcing associated with increasing greenhouse gases. The increasing greenhouse gases drive tropical expansion; consequently, the subtropical dry branch of Hadley cell moves away from SESA, leading to the rainfall increase. The amplitude discrepancy between the observed and simulated rainfall changes suggests a possible underestimation by the models of the atmospheric response to the radiative forcing, as well as an important role for low-frequency internal variability in the observed moistening trend. Over the current century, increasing greenhouse gases drive a continuous SESA rainfall increase in the models. However, the observed decadal rainfall decline is largely (~60%) reproduced in response to the observed Pacific trade wind strengthening, which is likely associated with natural Pacific decadal variability. These results suggest that the recent summertime rainfall decline in SESA is temporary and the positive trend will resume in response to both increasing greenhouse gases and a return of Pacific trade winds to normal conditions.
Cai, Wenju, Guojian Wang, Agus Santoso, Michael J McPhaden, L Wu, Fei-Fei Jin, Axel Timmermann, Matthew Collins, Gabriel A Vecchi, Matthieu Lengaigne, Matthew H England, D Dommenget, Ken Takahashi, and Eric Guilyardi, February 2015: Increased frequency of extreme La Niña events under greenhouse warming. Nature Climate Change, 5(2), DOI:10.1038/nclimate2492. Abstract
The El Niño/Southern Oscillation is Earth’s most prominent source of interannual climate variability, alternating irregularly between El Niño and La Niña, and resulting in global disruption of weather patterns, ecosystems, fisheries and agriculture1, 2, 3, 4, 5. The 1998–1999 extreme La Niña event that followed the 1997–1998 extreme El Niño event6 switched extreme El Niño-induced severe droughts to devastating floods in western Pacific countries, and vice versa in the southwestern United States4, 7. During extreme La Niña events, cold sea surface conditions develop in the central Pacific8, 9, creating an enhanced temperature gradient from the Maritime continent to the central Pacific. Recent studies have revealed robust changes in El Niño characteristics in response to simulated future greenhouse warming10, 11, 12, but how La Niña will change remains unclear. Here we present climate modelling evidence, from simulations conducted for the Coupled Model Intercomparison Project phase 5 (ref. 13), for a near doubling in the frequency of future extreme La Niña events, from one in every 23 years to one in every 13 years. This occurs because projected faster mean warming of the Maritime continent than the central Pacific, enhanced upper ocean vertical temperature gradients, and increased frequency of extreme El Niño events are conducive to development of the extreme La Niña events. Approximately 75% of the increase occurs in years following extreme El Niño events, thus projecting more frequent swings between opposite extremes from one year to the next.
Cai, Wenju, Agus Santoso, Guojian Wang, S-W Yeh, S I An, K M Cobb, Matthew Collins, Eric Guilyardi, Fei-Fei Jin, Jong-Seong Kug, Matthieu Lengaigne, Michael J McPhaden, Ken Takahashi, Axel Timmermann, Gabriel A Vecchi, M Watanabe, and L Wu, September 2015: ENSO and greenhouse warming. Nature Climate Change, 5(9), DOI:10.1038/nclimate2743. Abstract
The El Niño/Southern Oscillation (ENSO) is the dominant climate phenomenon affecting extreme weather conditions worldwide. Its response to greenhouse warming has challenged scientists for decades, despite model agreement on projected changes in mean state. Recent studies have provided new insights into the elusive links between changes in ENSO and in the mean state of the Pacific climate. The projected slow-down in Walker circulation is expected to weaken equatorial Pacific Ocean currents, boosting the occurrences of eastward-propagating warm surface anomalies that characterize observed extreme El Niño events. Accelerated equatorial Pacific warming, particularly in the east, is expected to induce extreme rainfall in the eastern equatorial Pacific and extreme equatorward swings of the Pacific convergence zones, both of which are features of extreme El Niño. The frequency of extreme La Niña is also expected to increase in response to more extreme El Niños, an accelerated maritime continent warming and surface-intensified ocean warming. ENSO-related catastrophic weather events are thus likely to occur more frequently with unabated greenhouse-gas emissions. But model biases and recent observed strengthening of the Walker circulation highlight the need for further testing as new models, observations and insights become available.
Choi, Kityan, Gabriel A Vecchi, and Andrew T Wittenberg, November 2015: Nonlinear zonal wind response to ENSO in the CMIP5 models: Roles of the zonal and meridional shift of the ITCZ/SPCZ and the simulated climatological precipitation. Journal of Climate, 28(21), DOI:10.1175/JCLI-D-15-0211.1. Abstract
The observed equatorial Pacific zonal wind response during El Niño tends to be stronger than during La Niña. Most global coupled climate models in CMIP5 exhibit such nonlinearity, yet weaker than observed. The wind response nonlinearity can be reproduced by driving a linear shallow-water atmospheric model with a model’s or the observed precipitation anomalies, which can be decomposed into two main components: the zonal and meridional redistribution of the climatological precipitation. Both redistributions contribute comparably to the total rainfall anomalies while the zonal redistribution plays the dominant role in the zonal wind response.
The meridional redistribution component plays an indirect role in the nonlinear wind response by limiting the zonal redistribution during La Niña and thus enhancing the nonlinearity in the wind response significantly. During La Niña, the poleward movement of the ITCZ/SPCZ reduces the equatorial zonal mean precipitation available for the zonal redistribution and its resulting zonal wind response. Conversely, during El Niño, the equatorward movement of the ITCZ and SPCZ do not limit the zonal redistribution of precipitation.
The linear equatorial zonal wind response to ENSO is found to have a significant linear correlation with the equatorial central Pacific climatological precipitation and SST among the CMIP5 models. However, no linear correlation is found between the nonlinear equatorial zonal wind response and the climatological precipitation.
Portions of western North America have experienced prolonged drought over the last decade. This drought has occurred at the same time as the global warming hiatus – a decadal period with little increase in global mean surface temperature. We use climate models and observational analyses to clarify the dual role of recent tropical Pacific changes in driving both the global warming hiatus and North American drought. When we insert observed tropical Pacific wind stress anomalies into coupled models, the simulations produce persistent negative sea surface temperature anomalies in the eastern tropical Pacific, a hiatus in global warming, and drought over North America driven by SST-induced atmospheric circulation anomalies. In our simulations the tropical wind anomalies account for 92% of the simulated North American drought during the recent decade, with 8% from anthropogenic radiative forcing changes. This suggests that anthropogenic radiative forcing is not the dominant driver of the current drought, unless the wind changes themselves are driven by anthropogenic radiative forcing. The anomalous tropical winds could also originate from coupled interactions in the tropical Pacific or from forcing outside the tropical Pacific. The model experiments suggest that if the tropical winds were to return to climatological conditions, then the recent tendency toward North American drought would diminish. Alternatively, if the tropical winds were to persist, then the impact on North American drought would continue; however, the impact of the enhanced Pacific easterlies on global temperature diminishes after a decade or two due to a surface reemergence of warmer water that was initially subducted into the ocean interior.
Dwyer, John, Suzana J Camargo, Adam H Sobel, M Biasutti, Kerry A Emanuel, Gabriel A Vecchi, Ming Zhao, and Michael K Tippett, August 2015: Projected Twenty-First-Century Changes in the Length of the Tropical Cyclone Season. Journal of Climate, 28(15), DOI:10.1175/JCLI-D-14-00686.1. Abstract
This study investigates projected changes in the length of the tropical cyclone season due to greenhouse gas increases. Two sets of simulations are analyzed, both of which capture the relevant features of the observed annual cycle of tropical cyclones in the recent historical record. Both sets use output from the general circulation models (GCMs) of the CMIP3 or CMIP5 suites. In one set, downscaling is performed by randomly seeding incipient vortices into the large-scale atmospheric conditions simulated by each GCM and simulating the vortices’ evolution in an axisymmetric dynamical tropical cyclone model; in the other, the GCMs’ sea surface temperature (SST) is used as the boundary condition of a high-resolution, global atmospheric model (HIRAM). The downscaling model projects a longer season (in the late 21st century compared to the 20th) in most basins when using CMIP5 data, but a slightly shorter season using CMIP3. HIRAM with either CMIP3 or CMIP5 SST anomalies projects a shorter tropical cyclone season in most basins. Season length is measured by the number of consecutive days that the mean cyclone count is greater than a fixed threshold, but other metrics give consistent results. The projected season length changes are also consistent with the large-scale changes, as measured by a genesis index of tropical cyclones. The season length changes are mostly explained by an idealized year-round multiplicative change in tropical cyclone frequency, but additional changes in the transition months also contribute.
The response of the equatorial Pacific Ocean’s seasonal cycle to orbital forcing is explored using idealized simulations with a coupled atmosphere-ocean GCM, in which eccentricity, obliquity, and longitude of the perihelion are altered while other boundary conditions are maintained at preindustrial levels. The importance of ocean dynamics in the climate response is investigated using additional simulations with a slab ocean version of the model. Precession is found to substantially influence the equatorial Pacific seasonal cycle through both thermodynamic and dynamic mechanisms while changes in obliquity have only a small effect. In the precession experiments, western equatorial Pacific SSTs respond in a direct thermodynamic manner to changes in insolation, while the eastern equatorial Pacific is first affected by the propagation of thermocline temperature anomalies from the west. These thermocline signals result from zonal wind anomalies associated with changes in the strength of subtropical anticyclones and shifts in the regions of convection in the western equatorial Pacific. The redistribution of heat from these thermocline signals, aided by the direct thermodynamic effect of insolation anomalies, results in large changes to the strength and timing of the eastern equatorial Pacific seasonal cycle. A comparison of 10 CMIP5 mid-Holocene experiments, in which the primary forcing is due to precession, shows that this response is relatively robust across models. Because equatorial Pacific SST anomalies have local climate impacts as well as non-local impacts through teleconnections, these results may be important to understanding paleoclimate variations both inside and outside of the tropical Pacific.
This study demonstrates skillful seasonal prediction of 2m air temperature and precipitation over land in a new high-resolution climate model developed by Geophysical Fluid Dynamics Laboratory, and explores the possible sources of the skill. We employ a statistical optimization approach to identify the most predictable components of seasonal mean temperature and precipitation over land, and demonstrate the predictive skill of these components. First, we show improved skill of the high-resolution model over the previous lower-resolution model in seasonal prediction of NINO3.4 index and other aspects of interest. Then we measure the skill of temperature and precipitation in the high-resolution model for boreal winter and summer, and diagnose the sources of the skill. Lastly, we reconstruct predictions using a few most predictable components to yield more skillful predictions than the raw model predictions. Over three decades of hindcasts, we find that the two most predictable components of temperature are characterized by a component that is likely due to changes in external radiative forcing in boreal winter and summer, and an ENSO-related pattern in boreal winter. The most predictable components of precipitation in both seasons are very likely ENSO-related. These components of temperature and precipitation can be predicted with significant correlation skill at least 9 months in advance. The reconstructed predictions using only the first few predictable components from the model show considerably better skill relative to observations than raw model predictions. This study shows that the use of refined statistical analysis and a high-resolution dynamical model leads to significant skill in seasonal predictions of 2m air temperature and precipitation over land.
Global projections of intense tropical cyclone activity are derived from the Geophysical Fluid Dynamics Laboratory (GFDL) HiRAM (50 km grid) atmospheric model and the GFDL Hurricane Model using a two-stage downscaling procedure. First, tropical cyclone genesis is simulated globally using the HiRAM atmospheric model. Each storm is then downscaled into the GFDL Hurricane Model, with horizontal grid-spacing near the storm of 6 km, and including ocean coupling (e.g., ‘cold wake’ generation). Simulations are performed using observed sea surface temperatures (SSTs) (1980-2008); for a “control run” with 20 repeating seasonal cycles; and for a late 21st century projection using an altered SST seasonal cycle obtained from a CMIP5/RCP4.5 multi-model ensemble. In general agreement with most previous studies, projections with this framework indicate fewer tropical cyclones globally in a warmer late-21st-century climate, but also an increase in average cyclone intensity, precipitation rates, and in the number and occurrence-days of very intense category 4-5 storms. While these changes are apparent in the globally averaged tropical cyclone statistics, they are not necessarily present in each individual basin. The inter-basin variation of changes in most of the tropical cyclone metrics we examined is directly correlated to the variation in magnitude of SST increases between the basins. Finally, the framework is shown capable of reproducing both the observed global distribution of outer storm size--albeit with a slight high bias--and its inter-basin variability. Projected median size is found to remain nearly constant globally, with increases in most basins offset by decreases in the Northwest Pacific.
This study investigates the seasonality of the relationship between the Great Plains low-level jet (GPLLJ) and the Pacific Ocean from spring to summer, using observational analysis and coupled model experiments. The observed GPLLJ and El Niño-Southern Oscillation (ENSO) relation undergoes seasonal changes with a stronger GPLLJ associated with La Niña in boreal spring and El Niño in boreal summer. The ability of the GFDL FLOR global coupled climate model, which has the high-resolution atmospheric and land components, to simulate the observed seasonality in the GPLLJ-ENSO relationship is assessed. The importance of simulating the magnitude and phase-locking of ENSO accurately in order to better simulate its seasonal teleconnections with the Intra-Americas Seas (IAS) is demonstrated. This study explores the mechanisms for seasonal changes in the GPLLJ-ENSO relation in model and observations. It is hypothesized that ENSO affects the GPLLJ variability through the Caribbean low-level jet (CLLJ) during the summer and spring seasons. These results suggest that climate models with improved ENSO variability would advance our ability to simulate and predict seasonal variations of the GPLLJ and their associated impacts on the United States.
Little, Christopher M., R Horton, Robert E Kopp, M Oppenheimer, Gabriel A Vecchi, and Gabriele Villarini, December 2015: Joint projections of US East Coast sea level and storm surge. Nature Climate Change, 5(12), DOI:10.1038/nclimate2801. Abstract
Future coastal flood risk will be strongly influenced by sea-level rise (SLR) and changes in the frequency and intensity of tropical cyclones. These two factors are generally considered independently. Here, we assess twenty-first century changes in the coastal hazard for the US East Coast using a flood index (FI) that accounts for changes in flood duration and magnitude driven by SLR and changes in power dissipation index (PDI, an integrated measure of tropical cyclone intensity, frequency and duration). Sea-level rise and PDI are derived from representative concentration pathway (RCP) simulations of 15 atmosphere–ocean general circulation models (AOGCMs). By 2080–2099, projected changes in the FI relative to 1986–2005 are substantial and positively skewed: a 10th–90th percentile range 4–75 times higher for RCP 2.6 and 35–350 times higher for RCP 8.5. High-end FI projections are driven by three AOGCMs that project the largest increases in SLR, PDI and upper ocean temperatures. Changes in PDI are particularly influential if their intra-model correlation with SLR is included, increasing the RCP 8.5 90th percentile FI by a further 25%. Sea-level rise from other, possibly correlated, climate processes (for example, ice sheet and glacier mass changes) will further increase coastal flood risk and should be accounted for in comprehensive assessments.
We review past, present and future North Atlantic hurricane activity based on analysis of observational records and models projections. When adjusted for likely missed tropical cyclones, the observational record does not show any significant increase or decrease of North Atlantic hurricane frequency. Downscaling results for most available CMIP5 models show a decrease or little change in overall frequency of tropical storms and hurricanes, although in the Atlantic basin, previous studies by other investigators report a wider range of change (+/−60%). Some model projections of late 21st century hurricane activity indicate an increase in frequency of the strongest storms (category 4–5 hurricanes). The projected increase is substantial (+100% per century) in the CMIP3 ensemble model downscaling, but much smaller (+40%) and only marginally significant in the CMIP5 ensemble model downscaling. Rainfall rates in the inner core of the hurricanes are projected to increase with potentially a substantial damage impact. The largest source of uncertainty in predicting changes in Atlantic tropical storms activity over the first half of the 21st century arises from the internal variability of the climate system. Nonetheless, some of these natural fluctuations appear to be predictable beyond seasonal time scale. We review recent predictability assessment results based on two CMIP5 models. Initializing these models with observational estimates leads to encouraging results in predicting multi-year variations in North Atlantic hurricane frequency. However the short record and the persistent character of the time series limits the ability to confidently predict North Atlantic hurricane activity for now. Remaining model biases, despite the tremendous improvement over the recent decades, and the changing observational system make it an ongoing challenge to simulate past hurricane activity and project or predict its future behavior.
A new high-resolution Geophysical Fluid Dynamics Laboratory (GFDL) coupled model (HiFLOR) has been developed and used to investigate potential skill in simulation and prediction of tropical cyclone (TC) activity. HiFLOR comprises of high-resolution (~25-km mesh) atmosphere and land components and a more moderate-resolution (~100-km mesh) sea ice and ocean components. HiFLOR was developed from the Forecast Oriented Low Resolution Ocean model (FLOR) by decreasing the horizontal grid spacing of the atmospheric component from 50-km to 25-km, while leaving most of the sub-gridscale physical parameterizations unchanged. Compared with FLOR, HiFLOR yields a more realistic simulation of the structure, global distribution, and seasonal and interannual variations of TCs, and a comparable simulation of storm-induced cold wakes and TC-genesis modulation induced by the Madden Julian Oscillation (MJO). Moreover, HiFLOR is able to simulate and predict extremely intense TCs (categories 4 and 5) and their interannual variations, which represents the first time a global coupled model has been able to simulate such extremely intense TCs in a multi-century simulation, sea surface temperature restoring simulations, and retrospective seasonal predictions.
Santoso, Agus, Wenju Cai, Matthew Collins, Michael J McPhaden, Fei-Fei Jin, Eric Guilyardi, Gabriel A Vecchi, D Dommenget, and Guojian Wang, November 2015: ENSO Extremes and Diversity: Dynamics, Teleconnections, and Impacts. Bulletin of the American Meteorological Society, 96(11), DOI:10.1175/BAMS-D-15-00141.1.
Sea surface temperature (SST) anomalies are often both leading indicators and important drivers of marine resource fluctuations. Assessment of the skill of SST anomaly forecasts within coastal ecosystems accounting for the majority of global fish yields, however, has been minimal. This reflects coarse global forecast system resolution and past emphasis on the predictability of ocean basin-scale SST variations. This paper assesses monthly to inter-annual SST anomaly predictions in coastal “Large Marine Ecosystems” (LMEs). We begin with an analysis of 7 well-observed LMEs adjacent to the United States and then examine how mechanisms responsible for prediction skill in these systems are reflected in predictions for LMEs globally. Historical SST anomaly estimates from the 1/4o daily Optimal Interpolation Sea Surface Temperature reanalysis (OISST.v2) were first found to be highly consistent with in-situ measurements for 6 of the 7 U.S. LMEs. Thirty years of retrospective forecasts from climate forecast systems developed at NOAA’s Geophysical Fluid Dynamics Laboratory (CM2.5-FLOR) and the National Center for Environmental Prediction (CFSv2) were then assessed against OISST.v2. Forecast skill varied widely by LME, initialization month, and lead but there were many cases of high skill that also exceeded that of a persistence forecast, some at leads greater than 6 months. Mechanisms underlying skill above persistence included accurate simulation of a) seasonal transitions between less predictable locally generated and more predictable basin-scale SST variability; b) seasonal transitions between different basin-scale influences; c) propagation of SST anomalies across seasons through sea ice; and d) re-emergence of previous anomalies upon the breakdown of summer stratification. Globally, significant skill above persistence across many tropical systems arises via mechanisms a) and b). Combinations of all four mechanisms contribute to less prevalent but nonetheless significant skill in extratropical systems. While continued refinement of global climate forecast systems and observations are needed to improve coastal SST anomaly prediction and extend predictions to other ecosystem relevant variables (e.g., salinity), present skill warrants close examination of forecasts for marine resource applications.
This study examines the climate response in West Africa and the tropical Atlantic to an idealized aerosol radiative forcing from Saharan-born mineral dust, comparable to the observed changes between the 1960s and 1990s, using simulations with the fully coupled GFDL Climate Model 2.1 (CM2.1) for two optical property regimes: more absorbing (ABS) and more scattering (SCT) dust. For both regimes dust induces significant regional reductions in radiative flux at the surface (approximately –30 W m−2). At the top of the atmosphere (ToA) dust in the two simulations produces a radiative flux anomaly of opposite sign (+30 W m−2 in the ABS-case and –20 W m−2 in the SCT-case). These differences result in opposing regional hydrologic and thermodynamic effects of dust. The ABS-forced simulations show an increase in the West African monsoon due to dust whereas in the SCT-forced simulations dust causes a decrease in the monsoon. This is due to moist enthalpy changes throughout the atmospheric column over West Africa creating either horizontal divergence or convergence near the surface, respectively. In the tropical North Atlantic, dust acts to cool the ocean surface. However, in the subsurface the ABS-forced simulations show a decrease in upper ocean heat content while the SCT-forced simulations show an increase in upper ocean heat content. The peak differences primarily arise from the wind stress curl response to a shift in the Atlantic ITCZ and associated mixed layer depth anomalies. Changes to upper ocean currents are also found to be important in transporting energy across the equator.
Walsh, Kevin J., Suzana J Camargo, Gabriel A Vecchi, A S Daloz, J B Elsner, Kerry A Emanuel, M Horn, Y-K Lim, Malcolm J Roberts, Christina M Patricola, E Scoccimarro, Adam H Sobel, S E Strazzo, Gabriele Villarini, Michael F Wehner, Ming Zhao, James Kossin, T LaRow, K Oouchi, S D Schubert, H Wang, Julio T Bacmeister, P Chang, F Chauvin, Christiane Jablonowski, Arun Kumar, and Hiroyuki Murakami, et al., July 2015: Hurricanes and climate: the U.S. CLIVAR working group on hurricanes. Bulletin of the American Meteorological Society, 96(6), DOI:10.1175/BAMS-D-13-00242.1. Abstract
While a quantitative climate theory of tropical cyclone formation remains elusive, considerable progress has been made recently in our ability to simulate tropical cyclone climatologies and understand the relationship between climate and tropical cyclone formation. Climate models are now able to simulate a realistic rate of global tropical cyclone formation, although simulation of the Atlantic tropical cyclone climatology remains challenging unless horizontal resolutions finer than 50 km are employed. This article summarizes published research from the idealized experiments of the Hurricane Working Group of U.S. CLIVAR (CLImate VARiability and predictability of the ocean-atmosphere system). This work, combined with results from other model simulations, has strengthened relationships between tropical cyclone formation rates and climate variables such as mid-tropospheric vertical velocity, with decreased climatological vertical velocities leading to decreased tropical cyclone formation. Systematic differences are shown between experiments in which only sea surface temperature is increased versus experiments where only atmospheric carbon dioxide is increased, with the carbon dioxide experiments more likely to demonstrate the decrease in tropical cyclone numbers previously shown to be a common response of climate models in a warmer climate. Experiments where the two effects are combined also show decreases in numbers, but these tend to be less for models that demonstrate a strong tropical cyclone response to increased sea surface temperatures. Further experiments are proposed that may improve our understanding of the relationship between climate and tropical cyclone formation, including experiments with two-way interaction between the ocean and the atmosphere and variations in atmospheric aerosols.
While tropical cyclone (TC) prediction, in particular TC genesis, remains very challenging, accurate prediction of TCs is critical for timely preparedness and mitigation. Using a new version of the Geophysical Fluid Dynamics Laboratory (GFDL) coupled model, the authors studied the predictability of two destructive landfall TCs, Hurricane Sandy in 2012 and Super Typhoon Haiyan in 2013. Results demonstrate that the geneses of these two TCs are highly predictable with the maximum prediction lead-time reaching 11 days. The “beyond weather time scale” predictability of tropical cyclogenesis is primarily attributed to the model’s skillful prediction of the intraseasonal Madden-Julian Oscillation (MJO) and the westward propagation of easterly waves. Meanwhile, the landfall location and time can be predicted one week ahead for Sandy’s U.S landfall, and two weeks ahead for Haiyan’s landing in the Philippines. The success in predicting Sandy and Haiyan, together with low false alarms, indicates the potential using the GFDL coupled model for operational extended-range predictions of TCs.
Based on a new version of the Geophysical Fluid Dynamics Laboratory (GFDL) coupled model, the Madden-Julian Oscillation (MJO) prediction skill in boreal wintertime (November-April) is evaluated by analyzing 11 years (2003-2013) of hindcast experiments. The initial conditions are obtained by applying a simple nudging technique towards observations. Using the real-time multivariate MJO (RMM) index as a predictand, we demonstrated that the MJO prediction skill can reach out to 27 days before the anomaly correlation coefficient (ACC) decreases to 0.5. The MJO forecast skill also shows relatively larger contrasts between target strong and weak cases (32 vs 7 days) than that between initially strong and weak cases (29 vs 24 days). Meanwhile, the strong dependence on target phases is found, as opposed to the relative skill independence from different initial phases. The MJO prediction skill is also shown to be about 29 days during DYNAMO/CINDY (Dynamics of the MJO/Cooperative Indian Ocean Experiment on Intraseasonal Variability in Year 2011) field campaign period. This model’s potential predictability, the upper bound of prediction skill, extends out to 42 days, revealing a considerable unutilized predictability and a great potential for improving current MJO prediction.
Regional information on climate change is urgently needed but often deemed unreliable. To achieve credible regional climate projections, it is essential to understand underlying physical processes, reduce model biases and evaluate their impact on projections, and adequately account for internal variability. In the tropics, where atmospheric internal variability is small compared with the forced change, advancing our understanding of the coupling between long-term changes in upper-ocean temperature and the atmospheric circulation will help most to narrow the uncertainty. In the extratropics, relatively large internal variability introduces substantial uncertainty, while exacerbating risks associated with extreme events. Large ensemble simulations are essential to estimate the probabilistic distribution of climate change on regional scales. Regional models inherit atmospheric circulation uncertainty from global models and do not automatically solve the problem of regional climate change. We conclude that the current priority is to understand and reduce uncertainties on scales greater than 100 km to aid assessments at finer scales.
The seasonal predictability of extratropical storm tracks in Geophysical Fluid Dynamics Laboratory (GFDL)’s high-resolution climate model has been investigated using an average predictability time analysis. The leading predictable components of extratropical storm tracks are ENSO-related spatial pattern for both boreal winter and summer, and the second predictable components are mostly due to changes in external radiative forcing and multidecadal oceanic variability. These two predictable components for both seasons show significant correlation skill for all leads from 0 to 9 months, while the skill of predicting the boreal winter storm track is consistently higher than that of the austral winter. The predictable components of extratropical storm tracks are dynamically consistent with the predictable components of the upper troposphere jet flow for both seasons. Over the region with strong storm track signals in North America, the model is able to predict the changes in statistics of extremes connected to storm track changes (e.g., extreme low and high sea level pressure and extreme 2m air temperature) in response to different ENSO phases. These results point towards the possibility of providing skillful seasonal predictions of the statistics of extratropical extremes over land using high-resolution coupled models.
Yang, Y, Shang-Ping Xie, L Wu, Yu Kosaka, Ngar-Cheung Lau, and Gabriel A Vecchi, October 2015: Seasonality and Predictability of the Indian Ocean Dipole Mode: ENSO Forcing and Internal Variability. Journal of Climate, 28(20), DOI:10.1175/JCLI-D-15-0078.1. Abstract
This study evaluates the relative contributions to the Indian Ocean Dipole (IOD) mode of interannual variability from the El Niño-Southern Oscillation (ENSO) forcing and ocean-atmosphere feedbacks internal to the Indian Ocean. The ENSO forcing and internal variability is extracted by conducting a 10-member coupled simulation for 1950-2012 where sea surface temperature (SST) is restored to the observed anomalies over the tropical Pacific but interactive with the atmosphere over the rest of the world ocean. In these experiments, the ensemble mean is due to ENSO forcing and the inter-member difference arises from internal variability of the climate system independent of ENSO. These elements contribute one third and two thirds of the total IOD variance, respectively. Both types of IOD variability develop into an east-west dipole pattern due to Bjerknes feedback and peak in September-November. The ENSO forced and internal IOD modes differ in several important ways. The forced IOD mode develops in August with a broad meridional pattern, and eventually evolves into the Indian Ocean Basin mode; while the internal IOD mode grows earlier in June, is more confined to the equator and decays rapidly after October. The internal IOD mode is more skewed than the ENSO forced response. The destructive interference of ENSO forcing and internal variability can explain early-terminating IOD events, referred to IOD-like perturbations that fail to grow during boreal summer.
Our results have implications for predictability. Internal variability, as represented by pre-season sea surface height anomalies off Sumatra, contributes to predictability considerably. Including this indicator of internal variability, together with ENSO, improves the predictability of IOD.
Cai, Wenju, S Borlace, Matthieu Lengaigne, P van Rensch, Matthew Collins, and Gabriel A Vecchi, et al., February 2014: Increasing frequency of extreme El Niño events due to greenhouse warming. Nature Climate Change, 4(2), DOI:10.1038/nclimate2100. Abstract
El Niño events are a prominent feature of climate variability with global climatic impacts. The 1997/98 episode, often referred to as ‘the climate event of the twentieth century, and the 1982/83 extreme El Niño3, featured a pronounced eastward extension of the west Pacific warm pool and development of atmospheric convection, and hence a huge rainfall increase, in the usually cold and dry equatorial eastern Pacific. Such a massive reorganization of atmospheric convection, which we define as an extreme El Niño, severely disrupted global weather patterns, affecting ecosystems agriculture, tropical cyclones, drought, bushfires, floods and other extreme weather events worldwide. Potential future changes in such extreme El Niño occurrences could have profound socio-economic consequences. Here we present climate modelling evidence for a doubling in the occurrences in the future in response to greenhouse warming. We estimate the change by aggregating results from climate models in the Coupled Model Intercomparison Project phases 3 (CMIP3; ref. 10) and 5 (CMIP5; ref. 11) multi-model databases, and a perturbed physics ensemble. The increased frequency arises from a projected surface warming over the eastern equatorial Pacific that occurs faster than in the surrounding ocean waters facilitating more occurrences of atmospheric convection in the eastern equatorial region.
Camargo, Suzana J., Michael K Tippett, Adam H Sobel, Gabriel A Vecchi, and Ming Zhao, December 2014: Testing the performance of tropical cyclone genesis indices in future climates using the HIRAM model. Journal of Climate, 27(24), DOI:10.1175/JCLI-D-13-00505.1. Abstract
Tropical cyclone genesis indices (TCGIs) are functions of the large-scale environment which are designed to be proxies for the probability of tropical cyclone (TC) genesis. While the performance of TCGIs in the current climate can be assessed by direct comparison to TC observations, their ability to represent future TC activity based on projections of the large-scale environment cannot. Here we examine the performance of TCGIs in high-resolution atmospheric model simulations forced with sea surface temperatures (SST) of future, warmer, climate scenarios. We investigate whether the TCGIs derived for the present climate can, when computed from large-scale fields taken from future climate simulations, capture the simulated global mean decreases in TC frequency. The TCGIs differ in their choice of environmental predictors, and several choices of predictors perform well in the present climate. However, some TCGIs which perform well in the present climate do not accurately reproduce the simulated future decrease in TC frequency. This decrease is captured when the humidity predictor is the column saturation deficit rather than relative humidity. Using saturation deficit with relative SST as the other thermodynamic predictor over-predicts the TC frequency decrease, while using potential intensity in place of relative SST as the other thermodynamic predictor gives a good prediction of the decrease’s magnitude. These positive results appear to depend on the spatial and seasonal patterns in the imposed SST changes; none of the indices capture correctly the frequency decrease in simulations with spatially uniform climate forcings, whether a globally uniform increase in SST of 2K, or a doubling of CO2 with no change in SST.
There have been few attempts to quantify errors in various objective analyzed (OA) fields, even though they have potential uncertainties associated with data handling and mapping methods. Here, we compare five different OA fields (EN3, GFDL, IPRC, JAMSTEC, and SIO) for 2008–2011. The variability and linear trends of the upper ocean temperature are very similar in every ocean basin, but the mean values are different from each other. This discrepancy is evident, especially around the southern ocean (± 0.07 °C in the Antarctic Ocean) where Argo observations are still sparse, which is related to different first-guess climatologies and decorrelation length scales applied to individual OA products. In the subpolar North Atlantic, detailed spatial anomalous patterns are also different. Along the boundary current areas, substantial warming (salting) anomalies with respect to WOA09 climatology are depicted by GFDL, IPRC, and SIO. By comparing with statistical bin-averaged fields and data assimilation products, we confirm that this anomalous pattern is robust, but it could be exaggerated when we calculate the anomalies with WOA09 climatology or other OA fields showing a relatively weak horizontal gradient across the boundary current regions.
Chiodi, A M., D E Harrison, and Gabriel A Vecchi, May 2014: Subseasonal atmospheric variability and El Niño waveguide warming; observed effects of the Madden-Julian Oscillation and Westerly Wind Events. Journal of Climate, 27(10), DOI:10.1175/JCLI-D-13-00547.1. Abstract
Westerly Wind Events (WWEs) have previously been shown to initiate equatorial Pacific waveguide warming. The relationship between WWE and Madden-Julian Oscillation (MJO) activity, and the role of MJO events in initiating waveguide warming is reconsidered here, over the 1986-2010 period. WWEs are identified in observations of near surface zonal winds using an objective scheme. MJO events are defined using a widely used index, and 64 are identified that occur when the El Niño-Southern Oscillation (ENSO) is in its neutral-state. 43 of these MJO events have one or more embedded WWEs and 21 have not.
We examine the evolution of sea surface temperature anomaly over the equatorial Pacific waveguide following the westerly surface wind phase of the MJO over the western equatorial Pacific. We find waveguide warming for the MJO+WWE events in similar magnitudes as following the WWEs not embedded in an MJO. There is very little statistically significant waveguide warming following MJO events that do not contain an embedded WWE. The observed SSTA changes are well reproduced in an ocean general circulation model forced with the respective composite wind stress anomalies. Further, we find that the occurrence of an MJO event does not significantly affect the likelihood that a WWE will occur. These results extend and confirm the results of Vecchi (2000) with a near doubling of the period of study. We suggest that understanding the sources and predictability of tropical Pacific Westerly Wind Events remains essential to improving predictions of the onset of El Niño events.
Hawkins, E, B Anderson, N S Diffenbaugh, I Mahlstein, Richard A Betts, Gabriele Hegerl, M Joshi, Reto Knutti, D McNeall, S Solomon, Rowan Sutton, J Syktus, and Gabriel A Vecchi, July 2014: Uncertainties in the timing of unprecedented climates. Nature, 511(7507), DOI:10.1038/nature13523. Abstract
The question of when the signal of climate change will emerge from the background noise of climate variability—the ‘time of emergence’—is potentially important for adaptation planning. Mora et al.1 presented precise projections of the time of emergence of unprecedented regional climates. However, their methodology produces artificially early dates at which specific regions will permanently experience unprecedented climates and artificially low uncertainty in those dates everywhere. This overconfidence could impair the effectiveness of climate risk management decisions.
Kessler, William S., Tong Lee, Matthew Collins, Eric Guilyardi, D Chen, Andrew T Wittenberg, Gabriel A Vecchi, William G Large, and D Anderson, January 2014: White Paper #3 -- ENSO research: The overarching science drivers and requirements for observations In Report of the Tropical Pacific Observing System 2020 (TPOS 2020) Workshop, Volume II, La Jolla, CA, WMO and Intergovernmental Oceanographic Commission, 27-30.
Global tropical cyclone (TC) activity is simulated by the Geophysical Fluid Dynamics Laboratory (GFDL) CM2.5, which is a fully coupled global climate model with horizontal resolution of about 50km for atmosphere and 25 km for ocean. The present climate simulation shows fairly realistic global TC frequency, seasonal cycle, and geographical distribution. The model has some notable biases in regional TC activity, including simulating too few TCs in the North Atlantic. The regional biases in TC activity are associated with simulation biases in the large-scale environment such as sea surface temperature, vertical wind shear, and vertical velocity. Despite these biases, the model simulates the large-scale variations of TC activity induced by El Nino/Southern Oscillation fairly realistically.
The response of TC activity in the model to global warming is investigated by comparing the present climate with a CO2 doubling experiment. Globally, TC frequency decreases (-19%) while the intensity increases (+2.7%) in response to CO2 doubling, consistent with previous studies. The average TC lifetime decreases by -4.6%, while the TC size and rainfall increase by about 3% and 12%, respectively. These changes are generally reproduced across the different basins in terms of the sign of the change, although the percent changes vary from basin to basin and within individual basins. For the Atlantic basin, although there is an overall reduction in frequency from CO2 doubling, the warmed climate exhibits increased interannual hurricane frequency variability so that the simulated Atlantic TC activity is enhanced more during unusually warm years in the CO2-warmed climate relative to that in unusually warm years in the control climate.
Kirtman, Ben P., Arlene M Fiore, and Gabriel A Vecchi, et al., March 2014: Near-term climate change: Projections and predictability In Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, 953-1028.
Kossin, James, Kerry A Emanuel, and Gabriel A Vecchi, May 2014: The poleward migration of the location of tropical cyclone maximum intensity. Nature, 509(7500), DOI:10.1038/nature13278. Abstract
Temporally inconsistent and potentially unreliable global historical data hinder the detection of trends in tropical cyclone activity. This limits our confidence in evaluating proposed linkages between observed trends in tropical cyclones and in the environment. Here we mitigate this difficulty by focusing on a metric that is comparatively insensitive to past data uncertainty, and identify a pronounced poleward migration in the average latitude at which tropical cyclones have achieved their lifetime-maximum intensity over the past 30 years. The poleward trends are evident in the global historical data in both the Northern and the Southern hemispheres, with rates of 53 and 62 kilometres per decade, respectively, and are statistically significant. When considered together, the trends in each hemisphere depict a global-average migration of tropical cyclone activity away from the tropics at a rate of about one degree of latitude per decade, which lies within the range of estimates of the observed expansion of the tropics over the same period6. The global migration remains evident and statistically significant under a formal data homogenization procedure, and is unlikely to be a data artefact. The migration away from the tropics is apparently linked to marked changes in the mean meridional structure of environmental vertical wind shear and potential intensity, and can plausibly be linked to tropical expansion, which is thought to have anthropogenic contributions.
This paper provides an update on research in the relatively new and fast moving field of decadal climate prediction, and addresses the use of decadal climate predictions not only for potential users of such information but also for improving our understanding of processes in the climate system. External forcing influences the predictions throughout, but their contributions to predictive skill become dominant after most of the improved skill from initialization with observations vanishes after about six to nine years. Recent multi-model results suggest that there is relatively more decadal predictive skill in the North Atlantic, western Pacific, and Indian Oceans than in other regions of the world oceans. Aspects of decadal variability of SSTs, like the mid-1970s shift in the Pacific, the mid-1990s shift in the northern North Atlantic and western Pacific, and the early-2000s hiatus, are better represented in initialized hindcasts compared to uninitialized simulations. There is evidence of higher skill in initialized multi-model ensemble decadal hindcasts than in single model results, with multi-model initialized predictions for near term climate showing somewhat less global warming than uninitialized simulations. Some decadal hindcasts have shown statistically reliable predictions of surface temperature over various land and ocean regions for lead times of up to 6–9 years, but this needs to be investigated in a wider set of models. As in the early days of El Niño-Southern Oscillation (ENSO) prediction, improvements to models will reduce the need for bias adjustment, and increase the reliability, and thus usefulness, of decadal climate predictions in the future.
Decadal prediction experiments were conducted as part of CMIP5 using the GFDL-CM2.1 forecast system. The abrupt warming of the North Atlantic subpolar gyre (SPG) that was observed in the mid 1990s is considered as a case study to evaluate our forecast capabilities and better understand the reasons for the observed changes. Initializing the CM2.1 coupled system produces high skill in retrospectively predicting the mid-90s shift, which is not captured by the uninitialized forecasts. All the hindcasts initialized in the early 90s show a warming of the SPG, however, only the ensemble mean hindcasts initialized in 1995 and 1996 are able to reproduce the observed abrupt warming and the associated decrease and contraction of the SPG. Examination of the physical mechanisms responsible for the successful retrospective predictions indicates that initializing the ocean is key to predict the mid 90s warming. The successful initialized forecasts show an increased Atlantic Meridional Overturning Circulation and North Atlantic current transport, which drive an increased advection of warm saline subtropical waters northward, leading to a westward shift of the subpolar front and subsequently a warming and spin down of the SPG. Significant seasonal climate impacts are predicted as the SPG warms, including a reduced sea-ice concentration over the Arctic, an enhanced warming over central US during summer and fall, and a northward shift of the mean ITCZ. These climate anomalies are similar to those observed during a warm phase of the Atlantic Multidecadal Oscillation, which is encouraging for future predictions of North Atlantic climate.
We present seasonal predictions of Arctic sea ice extent (SIE) over the 1982-2013 period using two suites of retrospective forecasts initialized from a fully coupled ocean-atmosphere-sea ice assimilation system. High skill scores are found in predicting year-to-year fluctuations of Arctic SIE, with significant correlations up to 7 month ahead for September detrended anomalies. Predictions over the recent era, which coincides with an improved observational coverage, outperform the earlier period for most target months. We find, however, a degradation of skill in September during the last decade, a period of sea ice thinning in observations. The two prediction models, CM2.1 and FLOR, share very similar ocean and ice component and initialization but differ by their atmospheric component. FLOR has improved climatological atmospheric circulation and sea ice mean state but its skill is overall similar to CM2.1 for most seasons, which suggests a key role for initial conditions in predicting seasonal SIE fluctuations.
Scoccimarro, E, Silvio Gualdi, Gabriele Villarini, Gabriel A Vecchi, and Ming Zhao, et al., June 2014: Intense Precipitation Events Associated with Landfalling Tropical Cyclones in response to a Warmer Climate and increased CO2. Journal of Climate, 27(12), DOI:10.1175/JCLI-D-14-00065.1. Abstract
In this work the authors investigate possible changes in the intensity of rainfall events associated with tropical cyclones (TCs) under idealized forcing scenarios, including a uniformly warmer climate, with a special focus on landfalling storms. A new set of experiments designed within the U.S. Climate Variability and Predictability (CLIVAR) Hurricane Working Group allows disentangling the relative role of changes in atmospheric carbon dioxide from that played by sea surface temperature (SST) in changing the amount of precipitation associated with TCs in a warmer world. Compared to the present-day simulation, an increase in TC precipitation was found under the scenarios involving SST increases. On the other hand, in a CO2-doubling-only scenario, the changes in TC rainfall are small and it was found that, on average, TC rainfall tends to decrease compared to the present-day climate. The results of this study highlight the contribution of landfalling TCs to the projected increase in the precipitation changes affecting the tropical coastal regions.
In our original paper (Vecchi et al., 2013, hereafter V13) we stated “the skill in the initialized forecasts comes in large part from the persistence of the mid-1990s shift by the initialized forecasts, rather than from predicting its evolution”. Smith et al (2013, hereafter S13) challenge that assertion, contending that DePreSys was able to make a successful retrospective forecast of that shift. We stand by our original assertion, and present additional analyses using output from DePreSys retrospective forecasts to support our assessment.
Tropical cyclones (TCs) are a hazard to life and property (1, 2), as was tragically apparent following Super Typhoon Haiyan's landfall in the Philippines in 2013 and Hurricane/extratropical system Sandy's landfall in the New York tri-state area in 2012. Yet TCs also provide vital water, sometimes relieving drought (3). Predictions of the path and intensity of individual TCs are usually sufficiently good several days in advance that action can be taken. In contrast, predictions of seasonal TC activity months in advance must still be made more regionally relevant to produce information that can be acted on, for example, to improve storm preparedness.
Tropical cyclones (TCs) are a hazard to life and property and a prominent element of the global climate system, therefore understanding and predicting TC location, intensity and frequency is of both societal and scientific significance. Methodologies exist to predict basin-wide, seasonally-aggregated TC activity months, seasons and even years in advance. We show that a newly developed high-resolution global climate model can produce skillful forecasts of seasonal TC activity on spatial scales finer than basin-wide, from months and seasons in advance of the TC season. The climate model used here is targeted at predicting regional climate and the statistics of weather extremes on seasonal to decadal timescales, and is comprised of high-resolution (50km×50km) atmosphere and land components, and more moderate resolution (~100km) sea ice and ocean components. The simulation of TC climatology and interannual variations in this climate model is substantially improved by correcting systematic ocean biases through “flux-adjustment.” We perform a suite of 12-month duration retrospective forecasts over the 1981-2012 period, after initializing the climate model to observationally-constrained conditions at the start of each forecast period – using both the standard and flux-adjusted versions of the model. The standard and flux-adjusted forecasts exhibit equivalent skill at predicting Northern Hemisphere TC season sea surface temperature, but the flux-adjusted model exhibits substantially improved basin-wide and regional TC activity forecasts, highlighting the role of systematic biases in limiting the quality of TC forecasts. These results suggest that dynamical forecasts of seasonally-aggregated regional TC activity months in advance are feasible.
Villarini, Gabriele, R Goska, James A Smith, and Gabriel A Vecchi, September 2014: North Atlantic Tropical Cyclones and U.S. Flooding. Bulletin of the American Meteorological Society, 95(9), DOI:10.1175/BAMS-D-13-00060.1. Abstract
Riverine flooding associated with North Atlantic tropical cyclones (TCs) is responsible for large societal and economic impacts. The effects of TC flooding are not limited to the coastal regions, but affect large areas away from the coast, and often away from the center of the storm. Despite these important repercussions, inland TC flooding has received relatively little attention in the scientific literature, although there has been growing media attention following Hurricanes Irene (2011) and Sandy (2012). Based on discharge data from 1981 to 2011, we provide a climatological view of inland flooding associated with TCs, leveraging on the wealth of discharge measurements collected, archived, and disseminated by the U.S. Geological Survey (USGS). Florida and the eastern seaboard of the United States (from South Carolina to Maine and Vermont) are the areas that are the most susceptible to TC flooding, with typical TC flood peaks that are two to six times larger than the local 10-year flood peak, causing major flooding. We also identify a secondary swath of extensive TC-induced flooding in the central United States. These results indicate that flooding from TCs is not solely a coastal phenomenon, but affects much larger areas of the United States, as far inland as Illinois, Wisconsin and Michigan. Moreover, we highlight the dependence of the frequency and magnitude of TC flood peaks on large scale climate indices, and highlight the role played by the North Atlantic Oscillation and the El Niño-Southern Oscillation phenomenon (ENSO), suggesting potential sources of extended-range predictability.
Heavy rainfall and flooding associated with tropical cyclones (TCs) are responsible for a large number of fatalities and economic damage worldwide. Despite their large socio-economic impacts, research into heavy rainfall and flooding associated with TCs has received limited attention to date, and still represents a major challenge. Our capability to adapt to future changes in heavy rainfall and flooding associated with TCs is inextricably linked to and informed by our understanding of the sensitivity of TC rainfall to likely future forcing mechanisms. Here we use a set of idealized high-resolution atmospheric model experiments produced as part of the U.S. CLIVAR Hurricane Working Group activity to examine TC response to idealized global-scale perturbations: the doubling of CO2, uniform 2K increases in global sea surface temperature (SST), and their combined impact. As a preliminary but key step, daily rainfall patterns of composite TCs within climate model outputs are first compared and contrasted to the observational records. To assess similarities and differences across different regions in response to the warming scenarios, analyses are performed at the global and hemispheric scales and in six global TC ocean basins. The results indicate a reduction in TC daily precipitation rates in the doubling CO2 scenario (on the order of 5% globally), and an increase in TC rainfall rates associated with a uniform increase of 2K in SST (both alone and in combination with CO2 doubling; on the order of 10-20% globally).
Wang, H, L Long, Arun Kumar, Wanqui Wang, J-K E Shemm, Ming Zhao, and Gabriel A Vecchi, et al., August 2014: How well do global climate models simulate the variability of Atlantic tropical cyclones associated with ENSO?Journal of Climate, 27(15), DOI:10.1175/JCLI-D-13-00625.1. Abstract
The variability of Atlantic tropical cyclones (TCs) associated with El Niño–Southern Oscillation (ENSO) in model simulations is assessed and compared with observations. The model experiments are 28-yr simulations forced with the observed sea surface temperature from 1982 to 2009. The simulations were coordinated by the U.S. CLIVAR Hurricane Working Group and conducted with five global climate models (GCMs) with a total of 16 ensemble members. The model performance is evaluated based on both individual model ensemble means and multi-model ensemble mean. The latter has the highest anomaly correlation (0.86) for the interannual variability of TCs. Previous observational studies show a strong association between ENSO and Atlantic TC activity, as well as distinctions during eastern Pacific (EP) and central Pacific (CP) El Niño events. The analysis of track density and TC origin indicates that each model has different mean biases. Overall, the GCMs simulate the variability of Atlantic TCs well with weaker activity during EP El Niño and stronger activity during La Niña. For CP El Niño, there is a slight increase in the number of TCs as compared with EP El Niño. However, the spatial distribution of track density and TC origin is less consistent among the models. Particularly, there is no indication of increasing TC activity over the U.S. southeast coastal region during CP El Niño as in observations. The difference between the models and observations is likely due to the bias of the models in response to the shift of tropical heating associated with CP El Niño, as well as the model bias in the mean circulation.
Observations and climate simulations exhibit epochs of extreme El Niño/Southern Oscillation (ENSO) behavior that can persist for decades. Previous studies have revealed a wide range of ENSO responses to forcings from greenhouse gases, aerosols, and orbital variations – but they have also shown that interdecadal modulation of ENSO can arise even without such forcings. The present study examines the predictability of this intrinsically-generated component of ENSO modulation, using a 4000-year unforced control run from a global coupled GCM (GFDL-CM2.1) with a fairly realistic representation of ENSO. Extreme ENSO epochs from the unforced simulation are reforecast using the same (“perfect”) model, but slightly-perturbed initial conditions. These 40-member reforecast ensembles display potential predictability of the ENSO trajectory, extending up to several years ahead. However, no decadal-scale predictability of ENSO behavior is found. This indicates that multidecadal epochs of extreme ENSO behavior can arise not only intrinsically, but delicately, and entirely at random. Previous work had shown that CM2.1 generates strong, reasonably-realistic, decadally-predictable high-latitude climate signals, as well as tropical and extratropical decadal signals that interact with ENSO. However, those slow variations appear not to lend significant decadal predictability to this model’s ENSO behavior, at least in the absence of external forcings. While the potential implications of these results are sobering for decadal predictability, they also suggest an expedited approach to model evaluation and development – in which large ensembles of short runs are executed in parallel, to quickly and robustly evaluate simulations of ENSO. Further implications are discussed for decadal prediction, attribution of past and future ENSO variations, and societal vulnerability.
The El Niño/Southern Oscillation (ENSO) exhibits well-known asymmetries: (1) warm events are stronger than cold events; (2) strong warm events are more likely to be followed by cold events than vice versa; and (3) cold events are more persistent than warm events. Coupled GCM simulations, however, continue to underestimate many of these observed features.
To shed light on these asymmetries, we begin with a widely-used delayed-oscillator conceptual model for ENSO, and modify it so that wind stress anomalies depend more strongly on SSTAs during warm conditions - as is observed. We then explore the impact of this nonlinearity on three dynamical regimes for ENSO: self-sustained oscillations, stochastically driven oscillations, and self-sustained oscillations interrupted by stochastic forcings. In all three regimes, the nonlinear air-sea coupling preferentially strengthens the feedbacks (both positive and delayed negative) during the ENSO warm phase – producing El Niños that grow to larger amplitude and overshoot more rapidly and consistently into the opposite phase, than do the La Niñas. Finally, we apply the modified oscillator to observational records, and to control simulations from two global coupled ocean-atmosphere-land-ice models (GFDL-CM2.1 and GFDL-CM2.5), to elucidate the causes of their differing asymmetries.
We examine the change in tropical cyclone (TC) tracks that result from projected changes in the large-scale steering flow and genesis location due to increasing greenhouse gases. Tracks are first simulated using a Beta and Advection Model (BAM) and NCEP-NCAR Reanalysis winds for all TCs that formed in the North Atlantic main development region (MDR) for the period 1950-2010. Changes in genesis location and large-scale steering flow are then estimated from an ensemble mean of 17 CMIP3 models for the A1b emissions scenario. The BAM simulations are then repeated with these changes to estimate how the TC tracks would respond to increased greenhouse gases. As the climate warms, the models project a weakening of the subtropical easterlies as well as an eastward shift in genesis location. This results in a statistically significant decrease in straight-moving (westward) storm tracks of 5.5% and an increase in recurving (open ocean) tracks of 5.5%. These track changes decrease TC counts over the Southern Gulf of Mexico and Caribbean by 1-1.5 per decade and increase TC counts over the central Atlantic by 1-1.5 per decade. Changes in the large-scale steering flow account for a vast majority of the projected changes in TC trajectories.
DiNezio, P, Gabriel A Vecchi, and A C Clement, June 2013: Detectability of Changes in the Walker Circulation in Response to Global Warming. Journal of Climate, 26(12), DOI:10.1175/JCLI-D-12-00531.1. Abstract
Changes in the gradients in sea level pressure (SLP) and sea surface temperature (SST) along the equatorial Pacific are analyzed in observations and 101 numerical experiments performed with 37 climate models participating the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5). The ensemble of numerical experiments simulates changes in the Earth's climate during the 1870-2004 period in response to changes in natural (solar variations, volcanoes) and anthropogenic (well-mixed greenhouse gases, ozone, direct aerosol forcing, and land use) radiative forcings. A reduction in the zonal SLP gradient is present in observational records, and is the typical response of the ensemble; yet only 26 out of the 101 "all forcing" historical experiments are able to simulate a reduced SLP gradient within 95% statistical confidence of the observed value. The multi-model response indicates a reduction of the Walker circulation to 'historical' forcings an order of magnitude smaller than the observed value. There are multiple, non-exclusive interpretations of these results: i) the observed trend may not be entirely forced, and includes a substantial component from internal variability; ii) there are problems with the observational record that lead to a spuriously large trend; iii) the strength of the Walker circulation, as measured by the zonal SLP gradient, may be less sensitive to external forcing in models than in the real climate system. Analysis of a subset of experiments suggests that greenhouse gases act to weaken the circulation, but aerosol forcing drives a strengthening of the circulation, which appears to be overestimated by the models, resulting in a muted response to the combined anthropogenic forcings.
Response of climate conditions in the Atlantic Hurricane Main Development Region (MDR) to doubling of atmospheric CO2 has been explored, using the new high-resolution coupled Climate Model version 2.5 developed at the Geophysical Fluid Dynamics Laboratory (GFDL-CM2.5). In the annual mean, the SST in the MDR warms by about 2°C in the CO2 doubling run relative to the Control run, the trade winds become weaker in the northern tropical Atlantic, and the rainfall increases over the ITCZ and its northern region. The amplitude of the annual cycle of the SST over the MDR is not significantly changed by CO2 doubling. However, we find that the interannual variations show significant responses to CO2 doubling: the seasonal maximum peak of the interannual variations of the SST over the MDR is about 25% stronger than in the Control run. The enhancement of the interannual variations of the SST in the MDR is due to changes in effectiveness of the Wind-Evaporation-SST (WES) positive feedback: WES remains a positive feedback until boreal early summer in the CO2 doubling run. The enhancement of the interannual variability of the SST over the MDR in boreal early summer due to CO2 doubling could lead to serious damages associated with the Atlantic Hurricane count and drought (or flood) in the Sahel and South America in a future climate.
Twenty-first-century projections of Atlantic climate change are downscaled to explore the robustness of potential changes in hurricane activity. Multimodel ensembles using the phase 3 of the Coupled Model Intercomparison Project (CMIP3)/Special Report on Emissions Scenarios A1B (SRES A1B; late-twenty-first century) and phase 5 of the Coupled Model Intercomparison Project (CMIP5)/representative concentration pathway 4.5 (RCP4.5; early- and late-twenty-first century) scenarios are examined. Ten individual CMIP3 models are downscaled to assess the spread of results among the CMIP3 (but not the CMIP5) models. Downscaling simulations are compared for 18-km grid regional and 50-km grid global models. Storm cases from the regional model are further downscaled into the Geophysical Fluid Dynamics Laboratory (GFDL) hurricane model (9-km inner grid spacing, with ocean coupling) to simulate intense hurricanes at a finer resolution.
A significant reduction in tropical storm frequency is projected for the CMIP3 (−27%), CMIP5-early (−20%) and CMIP5-late (−23%) ensembles and for 5 of the 10 individual CMIP3 models. Lifetime maximum hurricane intensity increases significantly in the high-resolution experiments—by 4%–6% for CMIP3 and CMIP5 ensembles. A significant increase (+87%) in the frequency of very intense (categories 4 and 5) hurricanes (winds ≥ 59 m s−1) is projected using CMIP3, but smaller, only marginally significant increases are projected (+45% and +39%) for the CMIP5-early and CMIP5-late scenarios. Hurricane rainfall rates increase robustly for the CMIP3 and CMIP5 scenarios. For the late-twenty-first century, this increase amounts to +20% to +30% in the model hurricane’s inner core, with a smaller increase (~10%) for averaging radii of 200 km or larger. The fractional increase in precipitation at large radii (200–400 km) approximates that expected from environmental water vapor content scaling, while increases for the inner core exceed this level.
Kosaka, Yu, Shang-Ping Xie, Ngar-Cheung Lau, and Gabriel A Vecchi, May 2013: Origin of seasonal predictability for summer climate over the Northwestern Pacific. Proceedings of the National Academy of Sciences, 110(19), DOI:10.1073/pnas.1215582110. Abstract
Summer climate in the Northwestern Pacific (NWP) displays large year-to-year variability, affecting densely populated Southeast and East Asia by impacting precipitation, temperature, and tropical cyclones. The Pacific–Japan (PJ) teleconnection pattern provides a crucial link of high predictability from the tropics to East Asia. Using coupled climate model experiments, we show that the PJ pattern is the atmospheric manifestation of an air–sea coupled mode spanning the Indo-NWP warm pool. The PJ pattern forces the Indian Ocean (IO) via a westward propagating atmospheric Rossby wave. In response, IO sea surface temperature feeds back and reinforces the PJ pattern via a tropospheric Kelvin wave. Ocean coupling increases both the amplitude and temporal persistence of the PJ pattern. Cross-correlation of ocean–atmospheric anomalies confirms the coupled nature of this PJIO mode. The ocean–atmosphere feedback explains why the last echoes of El Niño–Southern Oscillation are found in the IO-NWP in the form of the PJIO mode. We demonstrate that the PJIO mode is indeed highly predictable; a characteristic that can enable benefits to society.
Impacts of tropical temperature changes in the upper troposphere (UT) and the tropical tropopause layer (TTL) on tropical cyclone (TC) activity are explored. UT and lower TTL cooling both lead to an overall increase in potential intensity (PI), while temperatures 70hPa and higher have negligible effect. Idealized experiments with a high-resolution global model show that lower temperatures in the UT are associated with increases in global and North Atlantic TC frequency, but modeled TC frequency changes are not significantly affected by TTL temperature changes nor do they scale directly with PI.
Future projections of hurricane activity have been made with models that simulate the recent upward Atlantic TC trends while assuming or simulating very different tropical temperature trends. Recent Atlantic TC trends have been simulated by: i) high-resolution global models with nearly moist-adiabatic warming profiles, and ii) regional TC downscaling systems that impose the very strong UT and TTL trends of the NCEP Reanalysis, an outlier among observational estimates. Impact of these differences in temperature trends on TC activity is comparable to observed TC changes, affecting assessments of the connection between hurricanes and climate. Therefore, understanding the character of and mechanisms behind changes in UT and TTL temperature is important to understanding past and projecting future TC activity changes. We conclude that the UT and TTL temperature trends in NCEP are unlikely to be accurate, and likely drive spuriously positive TC and PI trends, and an inflated connection between absolute surface temperature warming and TC activity increases.
Retrospective predictions of multi-year North Atlantic hurricane frequency are explored, by applying a hybrid statistical-dynamical forecast system to initialized and non-initialized multi-year forecasts of tropical Atlantic and tropical mean sea surface temperatures (SSTs) from two global climate model forecast systems. By accounting for impacts of initialization and radiative forcing, retrospective predictions of five-year mean and nine-year mean tropical Atlantic hurricane frequency show significant correlation relative to a null hypothesis of zero correlation. The retrospective correlations are increased in a two-model average forecast and by using a lagged-ensemble approach, with the two-model ensemble decadal forecasts hurricane frequency over 1961-2011 yielding correlation coefficients that approach 0.9.
These encouraging retrospective multi-year hurricane predictions, however, should be interpreted with care: although initialized forecasts have higher nominal skill than uninitialized ones, the relatively short record and large autocorrelation of the time series limits our confidence in distinguishing between the skill due to external forcing and that added by initialization. The nominal increase in correlation in the initialized forecasts relative to the uninitialized experiments is due to improved representation of the multi-year tropical Atlantic SST anomalies. The skill in the initialized forecasts comes in large part from the persistence of a mid-1990s shift by the initialized forecasts, rather than from predicting its evolution. Predicting shifts like that observed in 1994-1995 remains a critical issue for the success of multi-year forecasts of Atlantic hurricane frequency. The retrospective forecasts highlight the possibility that changes in observing system impact forecast performance.
Villarini, Gabriele, James A Smith, and Gabriel A Vecchi, January 2013: Changing Frequency of Heavy Rainfall Over the Central United States. Journal of Climate, 26(1), DOI:10.1175/JCLI-D-12-00043.1. Abstract
Records of daily rainfall accumulations from 447 rain gage stations over the central United States (Minnesota, Wisconsin, Michigan, Iowa, Illinois, Indiana, Missouri, Kentucky, Tennessee, Arkansas, Louisiana, Alabama, and Mississippi) are used to assess past changes in the frequency of heavy rainfall. Each station has a record of at least 50 years, and the data cover most of the twentieth century and the first decade of the twenty-first century. Analyses are performed using a peaks-over-threshold approach, and, for each station, the 95th percentile is used as threshold. Because of the count nature of the data and to account for both abrupt and slowly varying changes in the heavy rainfall distribution, we use segmented regression to detect change-points at unknown points in time. The presence of trends is assessed by means of a Poisson regression model, in which we examine whether the rate of occurrence parameter is a linear function of time (by means of a logarithmic link function). Our results point to increasing trends in heavy rainfall over the northern part of our domain. Examination of the surface temperature record suggests that these increasing trends occur over the area with largest increasing trends in temperature and, consequently, with an increase in atmospheric water vapor.
Villarini, Gabriele, and Gabriel A Vecchi, May 2013: Projected Increases in North Atlantic Tropical Cyclone Intensity from CMIP5 Models. Journal of Climate, 26(10), DOI:10.1175/JCLI-D-12-00441.1. Abstract
Tropical cyclones—particularly intense ones—are a hazard to life and property, so an assessment of the changes in North Atlantic tropical cyclone intensity has important socioeconomic implications. In this study, the authors focus on the seasonally integrated power dissipation index (PDI) as a metric to project changes in tropical cyclone intensity. Based on a recently developed statistical model, this study examines projections in North Atlantic PDI using output from 17 state-of-the-art global climate models and three radiative forcing scenarios. Overall, the authors find that North Atlantic PDI is projected to increase with respect to the 1986–2005 period across all scenarios. The difference between the PDI projections and those of the number of North Atlantic tropical cyclones, which are not projected to increase significantly, indicates an intensification of North Atlantic tropical cyclones in response to both greenhouse gas (GHG) increases and aerosol changes over the current century. At the end of the twenty-first century, the magnitude of these increases shows a positive dependence on projected GHG forcing. The projected intensification is significantly enhanced by non-GHG (primarily aerosol) forcing in the first half of the twenty-first century.
Villarini, Gabriele, and Gabriel A Vecchi, June 2013: Multiseason Lead Forecast of the North Atlantic Power Dissipation Index (PDI) and Accumulated Cyclone Energy (ACE). Journal of Climate, 26(11), DOI:10.1175/JCLI-D-12-00448.1. Abstract
By considering the intensity, duration, and frequency of tropical cyclones, the power dissipation index (PDI) and accumulated cyclone energy (ACE) are concise metrics routinely used to assess tropical storm activity. This study focuses on the development of a hybrid statistical–dynamical seasonal forecasting system for the North Atlantic Ocean’s PDI and ACE over the period 1982–2011. The statistical model uses only tropical Atlantic and tropical mean sea surface temperatures (SSTs) to describe the variability exhibited by the observational record, reflecting the role of both local and nonlocal effects on the genesis and development of tropical cyclones in the North Atlantic basin. SSTs are predicted using a 10-member ensemble of the Geophysical Fluid Dynamics Laboratory Climate Model, version 2.1 (GFDL CM2.1), an experimental dynamical seasonal-to-interannual prediction system. To assess prediction skill, a set of retrospective predictions is initialized for each month from November to April, over the years 1981–2011. The skill assessment indicates that it is possible to make skillful predictions of ACE and PDI starting from November of the previous year: skillful predictions of the seasonally integrated North Atlantic tropical cyclone activity for the coming season could be made even while the current one is still under way. Probabilistic predictions for the 2012 North Atlantic tropical cyclone season are presented.
The decadal predictability of sea surface temperature (SST) and 2m air temperature (T2m) in Geophysical Fluid Dynamics Laboratory (GFDL)'s decadal hindcasts, which are part of the Fifth Coupled Model Intercomparison Project experiments, has been investigated using an average predictability time (APT) analysis. Comparison of retrospective forecasts initialized using the GFDL's Ensemble Coupled Data Assimilation system with uninitialized historical forcing simulations using the same model, allows identification of internal multidecadal pattern (IMP) for SST and T2m. The IMP of SST is characterized by an inter-hemisphere dipole, with warm anomalies centered in the North Atlantic subpolar gyre region and North Pacific subpolar gyre region, and cold anomalies centered in the Antarctic Circumpolar Current region. The IMP of T2m is characterized by a general bi-polar seesaw, with warm anomalies centered in Greenland, and cold anomalies centered in Antarctica. The retrospective prediction skill of the initialized system, verified against independent observations, indicates that the IMP of SST may be predictable up to 4 (10) year lead time at 95% (90%) significance level, and the IMP of T2m may be predictable up to 2 (10) years at 95% (90%) significance level. The initialization of multidecadal variations of northward oceanic heat transport in the North Atlantic significantly improves the predictive skill of the IMP. The dominant roles of oceanic internal dynamics in decadal prediction are further elucidated by fixed-forcing experiments, in which radiative forcing is returned to 1961 values. These results point towards the possibility of meaningful decadal climate outlooks using dynamical coupled models, if they are appropriately initialized from a sustained climate observing system.
Identifying the prime drivers of the twentieth-century multidecadal variability in the Atlantic Ocean is crucial for predicting how the Atlantic will evolve in the coming decades and the resulting broad impacts on weather and precipitation patterns around the globe. Recently Booth et al (2012) showed that the HadGEM2-ES climate model closely reproduces the observed multidecadal variations of area-averaged North Atlantic sea surface temperature in the 20th century. The multidecadal variations simulated in HadGEM2-ES are primarily driven by aerosol indirect effects that modify net surface shortwave radiation. On the basis of these results, Booth et al (2012) concluded that aerosols are a prime driver of twentieth-century North Atlantic climate variability. However, here it is shown that there are major discrepancies between the HadGEM2-ES simulations and observations in the North Atlantic upper ocean heat content, in the spatial pattern of multidecadal SST changes within and outside the North Atlantic, and in the subpolar North Atlantic sea surface salinity. These discrepancies may be strongly influenced by, and indeed in large part caused by, aerosol effects. It is also shown that the aerosol effects simulated in HadGEM2-ES cannot account for the observed anti-correlation between detrended multidecadal surface and subsurface temperature variations in the tropical North Atlantic. These discrepancies cast considerable doubt on the claim that aerosol forcing drives the bulk of this multidecadal variability.
Zhao, Ming, Isaac M Held, and Gabriel A Vecchi, et al., September 2013: Robust direct effect of increasing atmospheric CO2 concentration on global tropical cyclone frequency: a multi-model inter-comparison. U.S. CLIVAR Variations, 11(3), 17-23.
We present results for simulated climate and climate change from a newly developed high-resolution global climate model (GFDL CM2.5). The GFDL CM2.5 model has an atmospheric resolution of approximately 50 Km in the horizontal, with 32 vertical levels. The horizontal resolution in the ocean ranges from 28 Km in the tropics to 8 Km at high latitudes, with 50 vertical levels. This resolution allows the explicit simulation of some mesoscale eddies in the ocean, particularly at lower latitudes.
We present analyses based on the output of a 280 year control simulation; we also present results based on a 140 year simulation in which atmospheric CO2 increases at 1% per year until doubling after 70 years.
Results are compared to the GFDL CM2.1 climate model, which has somewhat similar physics but coarser resolution. The simulated climate in CM2.5 shows marked improvement over many regions, especially the tropics, including a reduction in the double ITCZ and an improved simulation of ENSO. Regional precipitation features are much improved. The Indian monsoon and Amazonian rainfall are also substantially more realistic in CM2.5.
The response of CM2.5 to a doubling of atmospheric CO2 has many features in common with CM2.1, with some notable differences. For example, rainfall changes over the Mediterranean appear to be tightly linked to topography in CM2.5, in contrast to CM2.1 where the response is more spatially homogeneous. In addition, in CM2.5 the near-surface ocean warms substantially in the high latitudes of the Southern Ocean, in contrast to simulations using CM2.1.
Climate model experiments are analyzed to elucidate if and how the changes in mean climate in response to doubling of atmospheric CO2 (2xCO2) influence ENSO. The processes involved the development, transition, and decay of simulated ENSO events are quantified through a multi-model heat budget analysis. The simulated changes in ENSO amplitude in response to 2xCO2 are directly related to changes in the anomalous ocean heat flux convergence during the development, transition, and decay of ENSO events. This consistency relationship results from the Bjerknes feedback and cannot be used to attribute the changes in ENSO. In order to avoid a circular argument, we compute the anomalous heat flux convergence due to the interaction of the ENSO anomalies in the pre-industrial climate with the 2xCO2 changes in mean climate. The weakening of the Walker circulation and the increased thermal stratification, both robust features of the mean climate response to 2xCO2, play opposing roles in ENSO - mean climate interactions. Weaker upwelling in response to a weaker Walker circulation drives a reduction in thermocline-driven ocean heat flux convergence (i.e., thermocline feedback), and thus reduces the ENSO amplitude. Conversely, a stronger zonal subsurface temperature gradient, associated with the increased thermal stratification, drives an increase in zonal current-induced ocean heat flux convergence (i.e., zonal advection feedback), and thus increases the ENSO amplitude. These opposing processes explain the lack of model agreement in whether ENSO is going to weaken or strengthen in response to increasing greenhouse gases, but also why ENSO appears to be relatively insensitive to 2xCO2 in most models.
Using two fully coupled ocean-atmosphere models of CM2.1 (the Climate Model version 2.1 developed at the Geophysical Fluid Dynamics Laboratory) and CM2.5 (a new high-resolution climate model based on CM2.1), the characteristics and sources of SST and precipitation biases associated with the Atlantic ITCZ have been investigated.
CM2.5 has an improved simulation of the annual mean and the annual cycle of the rainfall over the Sahel and the northern South America, while CM2.1 shows excessive Sahel rainfall and lack of northern South America rainfall in boreal summer. This marked improvement in CM2.5 is due to not only high-resolved orography, but also a significant reduction of biases in the seasonal meridional migration of the ITCZ. In particular, the seasonal northward migration of the ITCZ in boreal summer is coupled to the seasonal variation of the SST and a subsurface doming of the thermocline in the northeastern tropical Atlantic, known as the Guinea Dome. Improvements in the ITCZ allow for better representation of the coupled processes that are important for an abrupt seasonally phase-locked decay of the interannual SST anomaly in the northern tropical Atlantic.
Nevertheless, the differences between CM2.5 and CM2.1 were not sufficient to reduce the warm SST biases in the eastern equatorial region and Angola-Benguela Area. The weak bias of southerly winds along the southwestern African coast associated with the excessive southward migration bias of the ITCZ may be a key to improve the warm SST biases there.
Matei et al. (Reports, 6 January 2012, p. 76) claim to show skillful multiyear predictions of the
Atlantic Meridional Overturning Circulation (AMOC). However, these claims are not justified,
primarily because the predictions of AMOC transport do not outperform simple reference forecasts
based on climatological annual cycles. Accordingly, there is no justification for the "confident"
prediction of a stable AMOC through 2014.
Villarini, Gabriele, and Gabriel A Vecchi, January 2012: North Atlantic Power Dissipation Index (PDI) and Accumulated Cyclone Energy (ACE): Statistical modeling and sensitivity to sea surface temperature changes. Journal of Climate, 25(2), DOI:10.1175/JCLI-D-11-00146.1. Abstract
This study focuses on the statistical modeling of the Power Dissipation Index (PDI) and Accumulated Cyclone Energy (ACE) for the North Atlantic basin over the period 1949-2008, which are metrics routinely used to assess tropical storm activity, and their sensitivity to sea surface temperature (SST) changes. To describe the variability exhibited by the data, four different statistical distributions are considered (gamma, Gumbel, lognormal, and Weibull), and tropical Atlantic and tropical mean SSTs are used as predictors. Model selection, both in terms of significant covariates and their functional relation to the parameters of the statistical distribution, is performed using two penalty criteria. Two different SST data sets are considered (UK Met Offices HadISSTv1 and NOAAs Extended Reconstructed ERSSTv3b) to examine the sensitivity of the results to the input data.
The statistical models presented in this study are able to well describe the variability in the observations according to several goodness-of-fit diagnostics. Both tropical Atlantic and tropical mean SSTs are significant predictors, independently of the SST input data, penalty criterion, and tropical storm activity metric. The application of these models to centennial reconstructions and seasonal forecasting is illustrated.
The sensitivity of North Atlantic tropical cyclone frequency, duration, and intensity is examined for both uniform and non-uniform SST changes. Under uniform SST warming, these results indicate that there is a modest sensitivity of intensity, and a decrease in tropical storm and hurricane frequencies. On the other hand, increases of tropical Atlantic SST relative to the tropical mean SST suggest an increase in intensity and frequency of North Atlantic tropical storms and hurricanes.
Villarini, Gabriele, Gabriel A Vecchi, and James A Smith, January 2012: U.S. landfalling and North Atlantic hurricanes: Statistical modeling of their frequencies and ratios. Monthly Weather Review, 140(1), DOI:10.1175/MWR-D-11-00063.1. Abstract
Time series of US landfalling and North Atlantic hurricane counts and their ratios over the period 1878–2008 are modeled using tropical Atlantic sea surface temperature (SST), tropical mean SST, North Atlantic Oscillation (NAO), and Southern Oscillation Index (SOI). Two SST input data are employed to examine the uncertainties in the reconstructed SST data on the modeling results. Due to the likely undercount of recorded hurricanes in the earliest part of the record, we consider both the uncorrected hurricane record (HURDAT), and a time series with a recently proposed undercount correction.
Modeling of the count data is performed using a conditional Poisson regression model, in which the rate of occurrence can depend linearly or nonlinearly on the climate indices. Model selection is performed following a stepwise approach and using two penalty criteria. These results do not allow identifying a single “best” model due to the different model configurations (different SST data, corrected versus uncorrected datasets, penalty criteria). Despite the lack of an objectively identified unique final model, we recommend a set of models in which the parameter of the Poisson distribution depends linearly on tropical Atlantic and tropical mean SSTs.
Modeling of the fractions of North Atlantic hurricanes making US landfall is performed using a binomial regression model. Similar to the count data, it is not possible to identify a single “best” model, but different model configurations are obtained depending on the SST data, undercount correction, and penalty criterion. These results suggest that these fractions are controlled by local (related to the NAO) and remote (SOI and tropical mean SST) effects.
Villarini, Gabriele, and Gabriel A Vecchi, August 2012: Twenty-first-century projections of North Atlantic tropical storms from CMIP5 models. Nature Climate Change, 2(8), DOI:10.1038/nclimate1530. Abstract
Assessing potential changes in North Atlantic (NA) tropical storm (TS) activity this century is of paramount societal and economic significance, and the topic of intense scientific research1. We explore projections of NA TS changes over the twenty-first century by applying a statistical downscaling methodology2, 3 to a suite of experiments with the latest state-of-the-art global coupled climate models4. We also apply a methodology5 to partition the dominant sources of uncertainty in the TS projections. We find that over the first half of the twenty-first century radiative forcing changes act to increase NA TS frequency; this increase arises from radiative forcings other than increasing CO2 (probably aerosols). However, NA TS trends over the entire twenty-first century are of ambiguous sign. We find that for NA TS frequency, in contrast to sea surface temperature (SST), the largest uncertainties are driven by the chaotic nature of the climate system and by the climate response to radiative forcing. These results highlight the need to better understand the processes controlling patterns of SST change in response to radiative forcing and internal climate variability to constrain estimates of future NA TS activity. Coordinated experiments isolating forcing agents in projections should improve our understanding, and would enable better assessment of future TS activity.
The response of the Walker circulation to Last Glacial Maximum (LGM) forcing
is analyzed using an ensemble of six coordinated coupled climate model experiments.
The tropical atmospheric overturning circulation strengthens in all models in a manner
that is dictated by the response of the hydrological cycle to tropical cooling. This
response arises from the same mechanism that has been found to explain the weakening
of the tropical circulation in response to anthropogenic global warming, but with opposite
sign. Analysis of the model differences shows that the ascending branch of the Walker
circulation strengthens via this mechanism, but vertical motion also weakens over areas
of the Maritime Continent exposed due to lower sea level. Each model exhibits a
different balance between these two mechanisms, and the result is a Pacific Walker
circulation response that is not robust. Further, even those models that simulate a stronger
Walker circulation during the LGM do not simulate clear patterns of surface cooling,
such as La Niña-like cooling or enhanced equatorial cooling, as proposed by previous
studies. In contrast, the changes in the Walker circulation have a robust and distinctive
signature on the tilt of the equatorial thermocline, as expected from zonal momentum
balance. The changes in the Walker circulation also have a clear signature on the spatial
pattern of the precipitation changes. A reduction of the east-west salinity contrast in the
Indian Ocean is related to the precipitation changes resulting from a weakening of the
Indian Walker circulation. These results indicate that proxies of thermocline depth and
sea surface salinity can be used to detect actual LGM changes in the Pacific and Indian
Walker circulations, respectively and help constrain the sensitivity of the Walker
circulation to tropical cooling.
Air pollution (ozone and particulate matter in surface air) is strongly linked to synoptic weather and thus is likely sensitive to climate change. In order to isolate the responses of air pollutant transport and wet removal to a warming climate, we examine a simple carbon monoxide (CO)–like tracer (COt) and a soluble version (SAt), both with the 2001 CO emissions, in simulations with the GFDL chemistry-climate model (AM3) for present (1981-2000) and future (2081-2100) climates. In 2081-2100, projected reductions in lower tropospheric ventilation and wet deposition exacerbate surface air pollution as evidenced by higher surface COt and SAt concentrations. However, the average horizontal general circulation patterns in 2081-2100 are similar to 1981-2000, so the spatial distribution of COt changes little. Precipitation is an important factor controlling soluble pollutant wet removal, but the total global precipitation change alone does not necessarily indicate the sign of the soluble pollutant response to climate change. Over certain latitudinal bands, however, the annual wet deposition change can be explained mainly by the simulated changes in large-scale (LS) precipitation. In regions such as North America, differences in the seasonality of LS precipitation and tracer burdens contribute to an apparent inconsistency of changes in annual wet deposition versus annual precipitation. As a step towards an ultimate goal of developing a simple index that can be applied to infer changes in soluble pollutants directly from changes in precipitation fields as projected by physical climate models, we explore here a “Diagnosed Precipitation Impact” (DPI) index. This index captures the sign and magnitude (within 50%) of the relative annual mean changes in the global wet deposition of the soluble pollutant. DPI can only be usefully applied in climate models in which LS precipitation dominates wet deposition and horizontal transport patterns change little as climate warms. Our findings support the need for tighter emission regulations, for both soluble and insoluble pollutants, to obtain a desired level of air quality as climate warms.
Kirtman, Ben P., and Gabriel A Vecchi, 2011: Why climate modelers should worry about atmospheric and oceanic weather In The Global Monsoon System: Research and Forecast, 2nd Edition, Singapore, World Scientific, 511-523.
The influence of oceanic changes on tropical cyclone activity is investigated using observational estimates of Sea Surface Temperature (SST), air-sea fluxes and ocean subsurface thermal structure over the period 1998–2007. SST conditions are examined before, during, and after the passage of tropical cyclones, through Lagrangian composites along cyclone tracks across all ocean basins, with particular focus on the North Atlantic. We explore the influence of translation speed by separating tropical cyclones according to the translation speed divided by the coriolis parameter. On average for tropical cyclones up to category 2, SST cooling becomes larger as cyclone intensity increases, peaking at 1.8K in the North Atlantic. Beyond category 2 hurricanes, however, the cooling no longer follows an increasing monotonic relationship with intensity. In the North Atlantic, the cooling for stronger hurricanes decreases, while in other ocean basins the cyclone-induced cooling does not significantly differ from Category 2 to Category 5 tropical cyclones, with the exception of the South Pacific. Since the SST response is non-monotonic, with stronger cyclones producing more cooling up to category 2, but producing less or approximately equal cooling for categories 3–5, the observations indicate that oceanic feedbacks can inhibit intensification of cyclones. This result implies that large-scale oceanic conditions are important for tropical cyclone intensity, since they control oceanic sensitivity to atmospheric forcing. Ocean sub-surface thermal data provides additional support for this dependence, showing weaker upper ocean stratification for stronger tropical cyclones. Intensification is suppressed due to negative ocean feedback when stratification favors large SST cooling, but the ability of tropical cyclones to intensify is not inhibited when stratification is weak and cyclone-induced SST cooling is small. Thus, after accounting for tropical cyclone translation speeds and latitudes, it is argued that reduced cooling under extreme tropical cyclones is the manifestation of oceanic conditions on the ability of tropical cyclones to intensify.
Lloyd, I D., Timothy Marchok, and Gabriel A Vecchi, November 2011: Diagnostics comparing sea surface temperature feedbacks from operational hurricane forecasts to observations. Journal of Advances in Modeling Earth Systems, 3, M11002, DOI:10.1029/2011MS000075. Abstract
This paper examines the ability of recent versions of the Geophysical Fluid Dynamics Laboratory
Operational Hurricane Forecast Model (GHM) to reproduce the observed relationship between hurricane
intensity and hurricane-induced Sea Surface Temperature (SST) cooling. The analysis was performed by
taking a Lagrangian composite of all hurricanes in the North Atlantic from 1998–2009 in observations and
2005–2009 for the GHM. A marked improvement in the intensity-SST relationship for the GHM compared
to observations was found between the years 2005 and 2006–2009 due to the introduction of warm-core
eddies, a representation of the loop current, and changes to the drag coefficient parameterization for bulk
turbulent flux computation. A Conceptual Hurricane Intensity Model illustrates the essential steady-state
characteristics of the intensity-SST relationship and is explained by two coupled equations for the
atmosphere and ocean. The conceptual model qualitatively matches observations and the 2006–2009 period
in the GHM, and presents supporting evidence for the conclusion that weaker upper oceanic thermal
stratification in the Gulf of Mexico, caused by the introduction of the loop current and warm core eddies, is
crucial to explaining the observed SST-intensity pattern. The diagnostics proposed by the conceptual model
offer an independent set of metrics for comparing operational hurricane forecast models to observations.
We assess the vertical distribution of cloud feedbacks in coupled climate models, taking care to distinguish between cloud feedbacks and a change in cloud forcing. We show that the effect of cloud changes on the longwave fluxes provides a strong positive feedback that is broadly consistent across models. In contrast, the effect of cloud changes on the shortwave fluxes ranges from a modest negative to a strong positive feedback, and is responsible for most of the intermodel spread in net cloud feedback. The feedback from high clouds is positive in all models, and is consistent with that anticipated by the Proportionately Higher Anvil Temperature hypothesis over the tropics. In contrast, low cloud cover is responsible for roughly three-quarters of the difference in global mean net cloud feedback among models, with the largest contributions from regions associated with low-level subtropical marine cloud systems.
The study of climate impacts on Living Marine Resources (LMRs) has increased rapidly in recent years with the availability of climate model simulations contributed to the assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Collaboration between climate and LMR scientists and shared understanding of critical challenges for such applications are essential for developing robust projections of climate impacts on LMRs. This paper assesses present approaches for generating projections of climate impacts on LMRs using IPCC-class climate models, recommends practices that should be followed for these applications, and identifies priority developments that could improve current projections. Understanding of the climate system and its representation within climate models has progressed to a point where many climate model outputs can now be used effectively to make LMR projections. However, uncertainty in climate model projections (particularly biases and inter-model spread at regional to local scales), coarse climate model resolution, and the uncertainty and potential complexity of the mechanisms underlying the response of LMRs to climate limit the robustness and precision of LMR projections. A variety of techniques including the analysis of multi-model ensembles, bias corrections, and statistical and dynamical downscaling can ameliorate some limitations, though the assumptions underlying these approaches and the sensitivity of results to their application must be assessed for each application. Developments in LMR science that could improve current projections of climate impacts on LMRs include improved understanding of the multi-scale mechanisms that link climate and LMRs and better representations of these mechanisms within more holistic LMR models. These developments require a strong baseline of field and laboratory observations including long time-series and measurements over the broad range of spatial and temporal scales over which LMRs and climate interact. Priority developments for IPCC-class climate models include improved model accuracy (particularly at regional and local scales), inter-annual to decadal-scale predictions, and the continued development of earth system models capable of simulating the evolution of both the physical climate system and biosphere. Efforts to address these issues should occur in parallel and be informed by the continued application of existing climate and LMR models.
Skillfully predicting North Atlantic hurricane activity months in advance is of potential
societal significance and a useful test of our understanding of the factors controlling
hurricane activity. We describe a statistical-dynamical hurricane forecasting system,
based on a statistical hurricane model, with explicit uncertainty estimates, built from a
suite of high-resolution global atmospheric dynamical model integrations spanning a
broad range of climate states. The statistical model uses two climate predictors: the sea
surface temperature (SST) in the tropical North Atlantic and SST averaged over the
global tropics. The choice of predictors is motivated by physical considerations, results of
high-resolution hurricane modeling and of statistical modeling of the observed record.
The statistical hurricane model is applied to a suite of initialized dynamical global
climate model forecasts of SST to predict North Atlantic hurricane frequency, which
peaks in the August-October season, from different starting dates. Retrospective forecasts
of the 1982-2009 period indicate that skillful predictions can be made from as early as
November of the previous year – that is, skillful forecasts for the coming North Atlantic
hurricane season could be made as the current one is closing. Based on forecasts
initialized between November 2009 and March 2010, the model system predicts that the
upcoming 2010 North Atlantic hurricane season will likely be more active than the 1982-
2009 climatology, with the forecasts initialized in March 2010 predicting an expected
hurricane count of eight and a 50% probability of counts between six (the 1966-2009
median) and nine.
In this study we assess the impact of imperfect sampling in the pre-satellite era (between
1878 and 1965) on North Atlantic hurricane activity measures, and on the long-term
trends in those measures. Our results suggest that a substantial upward adjustment of
hurricane counts is needed prior to 1965 to account for likely ‘missed’ hurricanes due to
sparse density of reporting ship traffic. After adjusting for our estimate of ‘missed’
hurricanes in the basin, the long-term (1878-2008) trend in hurricane counts changes
from significantly positive to no significant change (with a nominally negative trend).
The adjusted hurricane count record is more strongly connected to the difference between
main development region (MDR) sea surface temperature (SST) and tropical-mean SST,
than with MDR SST. Our results do not support the notion that the warming of the
tropical North Atlantic due to anthropogenic greenhouse gas emissions has caused
Atlantic hurricane frequency to increase.
The impact of future anthropogenic forcing on the frequency of tropical storms in the North Atlantic basin has been the subject of intensive investigation. However, whether the number of North Atlantic tropical storms will increase or decrease in a warmer climate is still heavily debated and a consensus has yet to be reached. To shed light on this issue, the authors use a recently developed statistical model, in which the frequency of North Atlantic tropical storms is modeled by a conditional Poisson distribution with rate of occurrence parameter that is a function of tropical Atlantic and mean tropical sea surface temperatures (SSTs). It is shown how the disagreement among dynamical modeling projections of late-twenty-first-century tropical storm frequency can be largely explained by differences in large-scale SST patterns from the different climate model projections used in these studies. The results do not support the notion of large (~200%) increases in tropical storm frequency in the North Atlantic basin over the twenty-first century in response to increasing greenhouse gases (GHGs). Because the statistical model is computationally inexpensive, it is used to examine the impact of different climate models and climate change scenarios on the frequency of North Atlantic tropical storms. The authors estimate that the dominant drivers of uncertainty in projections of tropical storm frequency over the twenty-first century are internal climate variations and systematic intermodel differences in the response of SST patterns to increasing GHGs. Relative to them, uncertainties in total GHG emissions or other climate forcings, within the scenarios explored here, represent a minor source of uncertainty in tropical storm frequency projections. These results suggest that reducing uncertainty in future projections of North Atlantic tropical storm frequency may depend as critically on reducing the uncertainty in the sensitivity of tropical Atlantic warming relative to the tropical mean, in response to GHG increase, as on improving dynamical or statistical downscaling techniques. Moreover, the large uncertainties on century-scale trends that are due to internal climate variability are likely to remain irreducible for the foreseeable future.
As a further illustration of the statistical model’s utility, the authors model projected changes in U.S. landfalling tropical storm activity under a variety of different climate change scenarios and climate models. These results are similar to those for the overall number of North Atlantic tropical storms, and do not point to a large increase in U.S. landfalling tropical storms over the twenty-first century in response to increasing GHGs.
Villarini, Gabriele, Gabriel A Vecchi, Thomas R Knutson, and James A Smith, May 2011: Is the recorded increase in short duration North Atlantic tropical storms spurious?Journal of Geophysical Research: Atmospheres, 116, D10114, DOI:10.1029/2010JD015493. Abstract
The number of North Atlantic tropical storms lasting two days or less exhibits a
very large increase starting from the middle of the twentieth century. Still lacking are
quantitative analyses to assess whether this behavior is more likely associated with
climate variability or with changes in the observational system. By using statisti-
cal methods combined with the current understanding of the physical processes, we
provide further supporting evidence that the trend in North Atlantic tropical storms
lasting two days or less is likely to be spurious. These results imply that studies ex-
amining trends in the frequency of North Atlantic tropical storms from the nineteenth
century should focus on storms of duration greater than about two days.
Villarini, Gabriele, James A Smith, Mary Lynn Baeck, Timothy Marchok, and Gabriel A Vecchi, December 2011: Characterization of rainfall distribution and flooding associated with U.S. landfalling tropical cyclones: Analyses of hurricanes Frances, Ivan, and Jeanne (2004). Journal of Geophysical Research: Atmospheres, 116, D23116, DOI:10.1029/2011JD016175. Abstract
Rainfall and flooding associated with landfalling tropical cyclones are examined through empirical analyses of three hurricanes (Frances, Ivan, and Jeanne) that affected large portions of the eastern U.S. during September 2004. Three rainfall products are considered for the analyses: NLDAS, Stage IV, and TMPA. Each of these products has strengths and weaknesses related to their spatio-temporal resolution and accuracy in estimating rainfall. Based on our analyses, we recommend using the Stage IV product when studying rainfall distribution in landfalling tropical cyclones due to its fine spatial and temporal resolutions (about 4-km and hourly) and accuracy, and the capability of estimating rainfall up to 150 km from the coast. Lagrangian analyses of rainfall distribution relative to the track of the storm are developed to represent evolution of the temporal and spatial structure of rainfall. Analyses highlight the profound changes in rainfall distribution near landfall, the changing contributions to the rainfall field from eyewall convection, inner rain bands and outer rain bands, and the key role of orographic amplification of rainfall. We also present new methods for examining spatial extreme of flooding from tropical cyclones and illustrate the links between evolving rainfall structure and spatial extent of flooding.
Several recent models suggest that the frequency of Atlantic tropical cyclones could decrease as the climate warms. However, these models are unable to reproduce storms of category 3 or higher intensity. We explored the influence of future global warming on Atlantic hurricanes with a downscaling strategy by using an operational hurricane-prediction model that produces a realistic distribution of intense hurricane activity for present-day conditions. The model projects nearly a doubling of the frequency of category 4 and 5 storms by the end of the 21st century, despite a decrease in the overall frequency of tropical cyclones, when the downscaling is based on the ensemble mean of 18 global climate-change projections. The largest increase is projected to occur in the Western Atlantic, north of 20°N.
Based on independent observations, we estimate the sea level budget and linear trends for individual ocean basins and the world ocean during 2004–2007. Even though it is confirmed that the seasonal variation of global sea level is balanced by the different sea level components (total sea level change from satellite altimetry equals to the sum of the steric height contribution obtained by Argo profiles and any variability in ocean mass observed from GRACE), basin-scale sea level budgets show very different characteristics. Sea level budgets over the South Pacific and Antarctic Ocean maintain a good balance both on seasonal to interannual time scales. Meanwhile, only the satellite altimeter data exhibits a large 4-year trend over the South Indian Ocean. This basin significantly impacts the magnitude of the disagreement for the global sea level budget. Large differences among the 3 different gravity fields related to the hydrologic signals in the Atlantic and Indian Ocean could be one of the major causes of the imbalance in the global sea level budget.
Collins, Matthew, Gabriel A Vecchi, and Andrew T Wittenberg, et al., June 2010: The impact of global warming on the tropical Pacific and El Niño Prepared on behalf of the CLIVAR Pacific Panel. Nature Geoscience, 3(6), DOI:10.1038/ngeo868. Abstract
The El Niño–Southern Oscillation (ENSO) is a naturally occurring fluctuation that originates in the tropical Pacific region and affects ecosystems, agriculture, freshwater supplies, hurricanes and other severe weather events worldwide. Under the influence of global warming, the mean climate of the Pacific region will probably undergo significant changes. The tropical easterly trade winds are expected to weaken; surface ocean temperatures are expected to warm fastest near the equator and more slowly farther away; the equatorial thermocline that marks the transition between the wind-mixed upper ocean and deeper layers is expected to shoal; and the temperature gradients across the thermocline are expected to become steeper. Year-to-year ENSO variability is controlled by a delicate balance of amplifying and damping feedbacks, and one or more of the physical processes that are responsible for determining the characteristics of ENSO will probably be modified by climate change. Therefore, despite considerable progress in our understanding of the impact of climate change on many of the processes that contribute to El Niño variability, it is not yet possible to say whether ENSO activity will be enhanced or damped, or if the frequency of events will change.
DiNezio, P, A C Clement, and Gabriel A Vecchi, April 2010: Reconciling differing views of tropical Pacific climate change. EOS, 91(16), 141-142. PDF
Because ocean color alters the absorption of sunlight, it can produce changes in sea surface temperatures with further impacts on atmospheric circulation. These changes can project onto fields previously recognized to alter the distribution of tropical cyclones. If the North Pacific subtropical gyre contained no absorbing and scattering materials, the result would be to reduce subtropical cyclone activity in the subtropical Northwest Pacific by 2/3, while concentrating cyclone tracks along the equator. Predicting tropical cyclone activity using coupled models may thus require consideration of the details of how heat moves into the upper thermocline as well as biogeochemical cycling.
Records of Atlantic basin tropical cyclones (TCs) since the late nineteenth century indicate a very large upward trend in storm frequency. This increase in documented TCs has been previously interpreted as resulting from anthropogenic climate change. However, improvements in observing and recording practices provide an alternative interpretation for these changes: recent studies suggest that the number of potentially missed TCs is sufficient to explain a large part of the recorded increase in TC counts. This study explores the influence of another factor—TC duration—on observed changes in TC frequency, using a widely used Atlantic hurricane database (HURDAT). It is found that the occurrence of short-lived storms (duration of 2 days or less) in the database has increased dramatically, from less than one per year in the late nineteenth–early twentieth century to about five per year since about 2000, while medium- to long-lived storms have increased little, if at all. Thus, the previously documented increase in total TC frequency since the late nineteenth century in the database is primarily due to an increase in very short-lived TCs.
The authors also undertake a sampling study based upon the distribution of ship observations, which provides quantitative estimates of the frequency of missed TCs, focusing just on the moderate to long-lived systems with durations exceeding 2 days in the raw HURDAT. Upon adding the estimated numbers of missed TCs, the time series of moderate to long-lived Atlantic TCs show substantial multidecadal variability, but neither time series exhibits a significant trend since the late nineteenth century, with a nominal decrease in the adjusted time series.
Thus, to understand the source of the century-scale increase in Atlantic TC counts in HURDAT, one must explain the relatively monotonic increase in very short-duration storms since the late nineteenth century. While it is possible that the recorded increase in short-duration TCs represents a real climate signal, the authors consider that it is more plausible that the increase arises primarily from improvements in the quantity and quality of observations, along with enhanced interpretation techniques. These have allowed National Hurricane Center forecasters to better monitor and detect initial TC formation, and thus incorporate increasing numbers of very short-lived systems into the TC database.
Lengaigne, Matthieu, and Gabriel A Vecchi, August 2010: Contrasting the termination of moderate and extreme El Niño events in coupled general circulation models. Climate Dynamics, 35(2-3), DOI:10.1007/s00382-009-0562-3. Abstract
As in the observed record, the termination of El Niño in the coupled IPCC-AR4 climate models involves meridional processes tied to the seasonal cycle. These meridional processes both precondition the termination of El Niño events in general and lead to a peculiar termination of extreme El Niño events (such as those of 1982–83 and 1997–98), in which the eastern equatorial Pacific warm sea surface temperature anomalies (SSTA) persist well into boreal spring/early-summer. The mechanisms controlling the peculiar termination of extreme El Niño events, which involves to the development of an equatorially centred intertropical convergence zone, are consistent across the four models that exhibit extreme El Niños and observational record, suggesting that this peculiar termination represents a general feature of extreme El Niños. Further, due to their unusual termination, extreme El Niños exhibit an apparent eastward propagation of their SSTA, which can strongly influence estimates of the apparent propagation of ENSO over multi-decadal periods. Interpreting these propagation changes as evidence of changes in the underlying dynamical feedbacks behind El Niño could therefore be misleading, given the strong influence of a single extreme event.
Lloyd, I D., and Gabriel A Vecchi, February 2010: Submonthly Indian Ocean cooling events and their interaction with large-scale conditions. Journal of Climate, 23(3), DOI:10.1175/2009JCLI3067.1. Abstract
The Indian Ocean exhibits strong variability on a number of time scales, including prominent intraseasonal variations in both the atmosphere and ocean. Of particular interest is the south tropical Indian Ocean thermocline ridge, a region located between 12° and 5°S, which exhibits prominent variability in sea surface temperature (SST) due to dominant winds that raise the thermocline and shoal the mixed layer. In this paper, submonthly (less than 30 day) cooling events in the thermocline ridge region are diagnosed with observations and models, and are related to large-scale conditions in the Indo-Pacific region. Observations from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) satellite were used to identify 16 cooling events in the period 1998–2007, which on average cannot be fully accounted for by air–sea enthalpy fluxes. Analysis of observations and a hierarchy of models, including two coupled global climate models (GFDL CM2.1 and GFDL CM2.4), indicates that ocean dynamical changes are important to the cooling events. For extreme cooling events (above 2.5 standard deviations), air–sea enthalpy fluxes account for approximately 50% of the SST signature, and oceanic processes cannot in general be neglected. For weaker cooling events (1.5–2.5 standard deviations), air–sea enthalpy fluxes account for a larger fraction of the SST signature. Furthermore, it is found that cooling events are preconditioned by large-scale, low-frequency changes in the coupled ocean–atmosphere system. When the thermocline is unusually shallow in the thermocline ridge region, cooling events are more likely to occur and are stronger; these large-scale conditions are more (less) likely during La Niña (El Niño/Indian Ocean dipole) events. Strong cooling events are associated with changes in atmospheric convection, which resemble the Madden–Julian oscillation, in both observations and the models.
Seager, Richard, and Gabriel A Vecchi, December 2010: Greenhouse warming and the 21st century hydroclimate of southwestern North America. Proceedings of the National Academy of Sciences, 107(50), DOI:10.1073/pnas.0910856107. Abstract
Climate models robustly predict that the climate of southwestern
North America, defined as from the western Great Plains to the
Pacific Ocean and from the Oregon border to southern Mexico,
will dry throughout the current century as a consequence of rising
greenhouse gases. This regional drying is part of a general
drying of the subtropics and poleward expansion of the subtropical
dry zones. It is shown that the drying is driven by a reduction
of of winter season precipitation associated with a poleward
broadening of the North Pacific storm track and increased moisture
divergence by transient eddies. Observations to date cannot
confirm that this transition to a drier climate is already underway
due to the presence of large amplitude decadal variations of presumed
natural origin but it is anticipated that the anthropogenic
drying will reach the amplitude of natural decadal variability by
mid-century. In addition to this drop in total precipitation warming
is already causing a decline in mountain snow mass and an
advance of spring snow melt disrupting the natural water storage
systems that are part of the regions water supply system. Uncertainties
in how radiative forcing will impact the tropical Pacific
climate system create uncertainties in the amplitude of drying in
southwest North America with a La Niña-like response creating a
worst case scenario of greater drying.
Seager, Richard, N Naik, and Gabriel A Vecchi, September 2010: Thermodynamic and dynamic mechanisms for large-scale changes in the hydrological cycle in response to global warming. Journal of Climate, 23(17), DOI:10.1175/2010JCLI3655.1. Abstract
The mechanisms of changes in the large-scale hydrological cycle projected by 15 models participating in the
Coupled Model Intercomparison Project phase 3 and used for the Intergovernmental Panel on Climate
Change’s Fourth Assessment Report are analyzed by computing differences between 2046 and 2065 and 1961
and 2000. The contributions to changes in precipitation minus evaporation, P2E, caused thermodynamically
by changes in specific humidity, dynamically by changes in circulation, and by changes in moisture transports
by transient eddies are evaluated. The thermodynamic and dynamic contributions are further separated into
advective and divergent components. The nonthermodynamic contributions are then related to changes in the
mean and transient circulation. The projected change in P 2 E involves an intensification of the existing
pattern of P2E with wet areas [the intertropical convergence zone (ITCZ) and mid- to high latitudes] getting
wetter and arid and semiarid regions of the subtropics getting drier. In addition, the subtropical dry zones
expand poleward. The accentuation of the twentieth-century pattern of P2E is in part explained by increases
in specific humidity via both advection and divergence terms. Weakening of the tropical divergent circulation
partially opposes the thermodynamic contribution by creating a tendency to decreased P2E in the ITCZ and
to increased P2E in the descending branches of the Walker and Hadley cells. The changing mean circulation
also causes decreased P 2 E on the poleward flanks of the subtropics because the descending branch of the
Hadley Cell expands and the midlatitude meridional circulation cell shifts poleward. Subtropical drying and
poleward moistening are also contributed to by an increase in poleward moisture transport by transient
eddies. The thermodynamic contribution to changing P 2 E, arising from increased specific humidity, is
almost entirely accounted for by atmospheric warming under fixed relative humidity.
El Niño and La Niña comprise the dominant mode of tropical climate variability: the El Niño and Southern Oscillation (ENSO) phenomenon. ENSO variations influence climate, ecosystems, and societies around the globe. It is, therefore, of great interest to understand the character of past and future ENSO variations. In this brief review, we explore our current understanding of these issues. The amplitude and character of ENSO have been observed to exhibit substantial variations on timescales of decades to centuries; many of these changes over the past millennium resemble those that arise from internally generated climate variations in an unforced climate model. ENSO activity and characteristics have been found to depend on the state of the tropical Pacific climate system, which is expected to change in the 21st century in response to changes in radiative forcing (including increased greenhouse gases) and internal climate variability. However, the extent and character of the response of ENSO to increased in greenhouse gases are still a topic of considerable research, and given the results published to date, we cannot yet rule out possibilities of an increase, decrease, or no change in ENSO activity arising from increases in CO2. Yet we are fairly confident that ENSO variations will continue to occur and influence global climate in the coming decades and centuries. Changes in continental climate, however, could alter the remote impacts of El Niño and La Niña.
Villarini, Gabriele, Gabriel A Vecchi, and James A Smith, July 2010: Modeling the dependence of tropical storm counts in the North Atlantic basin on climate indices. Monthly Weather Review, 138(7), DOI:10.1175/2010MWR3315.1. Abstract
The authors analyze and model time series of annual counts of tropical storms lasting more than 2 days in
the North Atlantic basin and U.S. landfalling tropical storms over the period 1878–2008 in relation to different
climate indices. The climate indices considered are the tropical Atlantic sea surface temperature (SST),
tropical mean SST, the North Atlantic Oscillation (NAO), and the Southern Oscillation index (SOI). Given
the uncertainties associated with a possible tropical storm undercount in the presatellite era, two different
time series of counts for the North Atlantic basin are employed: one is the original (uncorrected) tropical
storm record maintained by the National Hurricane Center and the other one is with a correction for the
estimated undercount associated with a changing observation network. Two different SST time series are
considered: the Met Office’s HadISSTv1 and NOAA’s Extended Reconstructed SST.
Given the nature of the data (counts), a Poisson regression model is adopted. The selection of statistically
significant covariates is performed by penalizing models for adding extra parameters and two penalty functions
are used. Depending on the penalty function, slightly different models, both in terms of covariates and
dependence of themodel’s parameter, are obtained, showing that there is not a ‘‘single best’’model.Moreover,
results are sensitive to the undercount correction and the SST time series.
Suggestions concerning the model to use are provided, driven by both the outcomes of the statistical
analyses and the current understanding of the underlying physical processes responsible for the genesis,
development, and tracks of tropical storms in the North Atlantic basin. Although no single model is unequivocally
superior to the others, the authors suggest a very parsimonious family ofmodels using as covariates
tropical Atlantic and tropical mean SSTs.
Spatial variations in sea surface temperature (SST) and rainfall changes over the tropics are investigated based on ensemble simulations for the first half of the twenty-first century under the greenhouse gas (GHG) emission scenario A1B with coupled ocean–atmosphere general circulation models of the Geophysical Fluid Dynamics Laboratory (GFDL) and National Center for Atmospheric Research (NCAR). Despite a GHG increase that is nearly uniform in space, pronounced patterns emerge in both SST and precipitation. Regional differences in SST warming can be as large as the tropical-mean warming. Specifically, the tropical Pacific warming features a conspicuous maximum along the equator and a minimum in the southeast subtropics. The former is associated with westerly wind anomalies whereas the latter is linked to intensified southeast trade winds, suggestive of wind–evaporation–SST feedback. There is a tendency for a greater warming in the northern subtropics than in the southern subtropics in accordance with asymmetries in trade wind changes. Over the equatorial Indian Ocean, surface wind anomalies are easterly, the thermocline shoals, and the warming is reduced in the east, indicative of Bjerknes feedback. In the midlatitudes, ocean circulation changes generate narrow banded structures in SST warming. The warming is negatively correlated with wind speed change over the tropics and positively correlated with ocean heat transport change in the northern extratropics. A diagnostic method based on the ocean mixed layer heat budget is developed to investigate mechanisms for SST pattern formation.
Tropical precipitation changes are positively correlated with spatial deviations of SST warming from the tropical mean. In particular, the equatorial maximum in SST warming over the Pacific anchors a band of pronounced rainfall increase. The gross moist instability follows closely relative SST change as equatorial wave adjustments flatten upper-tropospheric warming. The comparison with atmospheric simulations in response to a spatially uniform SST warming illustrates the importance of SST patterns for rainfall change, an effect overlooked in current discussion of precipitation response to global warming. Implications for the global and regional response of tropical cyclones are discussed.
Retrospective predictions of seasonal hurricane activity in the Atlantic and
East Pacific are generated using an atmospheric model with 50km horizontal resolution and
simply persisting sea surface temperature (SST) anomalies from June through the hurricane
season. Using an ensemble of 5 realizations for each year between 1982 and 2008, the
correlations of the model mean with observations of basin-wide hurricane frequency are 0.69
in the North Atlantic and 0.58 in the East Pacific. In the North Atlantic, a significant part of the
degradation in skill as compared to a model forced with observed SSTs during the hurricane
season (correlation 0.78) can be explained by the change from June through the hurricane
season in one parameter, the difference between the SST in the main development region and
the tropical mean SST. In fact, simple linear regression models with this one predictor perform
nearly as well as the full dynamical model for basin-wide hurricane frequency in both the
East Pacific and the North Atlantic. The implication is that the quality of seasonal forecasts
based on a coupled atmosphere-ocean model will depend in large part on the model’s ability
to predict the evolution of this difference between main development region SST and tropical
mean SST.
Zheng, Xiao-Tong, Shang-Ping Xie, Gabriel A Vecchi, Q Liu, and J Hafner, March 2010: Indian Ocean dipole response to global warming: Analysis of ocean-atmospheric feedbacks in a coupled model. Journal of Climate, 23(5), DOI:10.1175/2009JCLI3326.1. Abstract
Low-frequency modulation of and change under global warming in the Indian
Ocean Dipole (IOD) mode is investigated based on a pair of long simulations with a
coupled ocean-atmosphere general circulation model, one under constant climate forcing
and one forced by increasing greenhouse gas concentrations. In the unforced simulation,
IOD variance displays slow modulation significant in amplitude. It is found that the mean
thermocline depth in the eastern equatorial Indian Ocean (EEIO) is important for the slow
modulation, skewness and ENSO-correlation of IOD. IOD variance increases as the
EEIO thermocline shoals and thermocline feedback strengthens.
In the global warming simulation, the Walker circulation slows down with easterly
wind changes in the equatorial Indian Ocean. The thermocline shoals in the EEIO.
Thermocline feedback intensifies but surprisingly IOD variance does not. Zonal wind
anomalies associated with IOD are found to weaken, likely due to increased static
stability of the troposphere in global warming. Linear model experiments confirm this
stability effect to reduce circulation response to a sea surface temperature dipole. The
opposing changes in thermocline and atmospheric feedbacks result in little change in IOD
variance but the shoaling thermocline weakens IOD skewness. Little change under global
warming in IOD variance in the model suggests that the apparent intensification of IOD
activity for the recent decades is likely part of natural, chaotic modulation of the
ocean-atmosphere system.
The climate response of the equatorial Pacific to increased greenhouse gases is investigated using numerical experiments from 11 climate models participating in the Intergovernmental Panel on Climate Change’s Fourth Assessment Report. Multimodel mean climate responses to CO2 doubling are identified and related to changes in the heat budget of the surface layer. Weaker ocean surface currents driven by a slowing down of the Walker circulation reduce ocean dynamical cooling throughout the equatorial Pacific. The combined anomalous ocean dynamical plus radiative heating from CO2 is balanced by different processes in the western and eastern basins: Cloud cover feedbacks and evaporation balance the heating over the warm pool, while increased cooling by ocean vertical heat transport balances the warming over the cold tongue. This increased cooling by vertical ocean heat transport arises from increased near-surface thermal stratification, despite a reduction in vertical velocity. The stratification response is found to be a permanent feature of the equilibrium climate potentially linked to both thermodynamical and dynamical changes within the equatorial Pacific. Briefly stated, ocean dynamical changes act to reduce (enhance) the net heating in the east (west). This explains why the models simulate enhanced equatorial warming, rather than El Niño–like warming, in response to a weaker Walker circulation. To conclude, the implications for detecting these signals in the modern observational record are discussed.
Harrison, D E., A M Chiodi, and Gabriel A Vecchi, November 2009: Effects of surface forcing on the seasonal cycle of the eastern equatorial Pacific. Journal of Marine Research, 67(6), 701-729. Abstract PDF
The roles of zonal and meridional wind stress and of surface heat flux in the seasonal cycle of sea surface temperature (SST) are examined with a primitive equation (PE) model of the tropical Pacific Ocean. While a variety of previous numerical and observational studies have examined the seasonal cycle of SST in the eastern tropical Pacific, it is noteworthy that different mechanisms have been invoked as primary in each case and different conclusions have been reached regarding the relative importance of the various components of surface forcing. Here, we perform a series of numerical experiments in which different components of the surface forcing are eliminated and the resulting upper ocean variability is compared with that of the climatological experiment. The model used for these experiments reproduces a realistic climatological seasonal cycle, in which SST emerges as an independent quantity. We find that the different cases all produce qualitatively reasonable seasonal cycles of SST, though only the most complete model is also able to reproduce the seasonal cycle of near surface currents, tropical instability waves (TIWs), and net surface heat fluxes consistent with historical observations. These results indicate that simply reproducing a qualitatively accurate seasonal cycle of SST does not necessarily allow meaningful conclusions to be made about the relative importance of the different components of surface forcing. The results described here also suggest that a model simulation must at least reproduce all the documented near surface kinematic features of the equatorial Pacific cold tongue region reasonably well, before accurate inferences can be made from model experiments. This provides useful guidelines to current efforts to develop and evaluate more complex fully coupled air-sea models and shows that results for simple or intermediate ocean models that do not have this level of fidelity to the observations will be difficult to interpret.
McPhaden, Michael J., and Gabriel A Vecchi, et al., February 2009: Ocean-atmosphere interactions during cyclone Nargis. EOS, 90(7), 53-60. PDF
A global atmospheric model with roughly 50 km horizontal grid spacing is used to simulate the interannual variability of tropical cyclones using observed sea surface temperatures (SSTs) as the lower boundary condition. The model's convective parameterization is based on a closure for shallow convection, with much of the deep convection allowed to occur on resolved scales. Four realizations of the period 1981–2005 are generated. The correlation of yearly Atlantic hurricane counts with observations is greater than 0.8 when the model is averaged over the four realizations, supporting the view that the random part of this annual Atlantic hurricane frequency (the part not predictable given the SSTs) is relatively small (< 2 hurricanes/yr). Correlations with observations are lower in the East, West and South Pacific (roughly 0.6, 0.5 and 0.3) and insignificant in the Indian ocean. The model trends in Northern Hemisphere basin-wide frequency are consistent with the observed trends in the IBTrACS database. The model generates an upward trend of hurricane frequency in the Atlantic and downward trends in the East and West Pacific over this time frame. The model produces a negative trend in the Southern Hemisphere that is larger than that in the IBTrACS.
The same model is used to simulate the response to the SST anomalies generated by coupled models in the CMIP3 archive, using the late 21st century in the A1B scenario. Results are presented for SST anomalies computed by averaging over 18 CMIP3 models and from individual realizations from three models. A modest reduction of global and Southern Hemisphere hurricane frequency is obtained in each case, but the results in individual Northern Hemisphere basins differ among the models. The vertical shear in the Atlantic Main Development Region (MDR) and the difference between the MDR SST and the tropical mean SST are well correlated with the model's Atlantic storm frequency, both for interannual variability and for the intermodel spread in global warming projections.
Increasing sea surface temperatures in the tropical Atlantic Ocean and measures of Atlantic hurricane activity have been reported to be strongly correlated since at least 1950 (refs 1, 2, 3, 4, 5), raising concerns that future greenhouse-gas-induced warming6 could lead to pronounced increases in hurricane activity. Models that explicitly simulate hurricanes are needed to study the influence of warming ocean temperatures on Atlantic hurricane activity, complementing empirical approaches. Our regional climate model of the Atlantic basin reproduces the observed rise in hurricane counts between 1980 and 2006, along with much of the interannual variability, when forced with observed sea surface temperatures and atmospheric conditions7. Here we assess, in our model system7, the changes in large-scale climate that are projected to occur by the end of the twenty-first century by an ensemble of global climate models8, and find that Atlantic hurricane and tropical storm frequencies are reduced. At the same time, near-storm rainfall rates increase substantially. Our results do not support the notion of large increasing trends in either tropical storm or hurricane frequency driven by increases in atmospheric greenhouse-gas concentrations.
We explore the predictability of the sea surface temperature anomalies associated with the Indian Ocean Dipole/Zonal Mode (IODZM) at a three-season lead, within the Geophysical Fluid Dynamics Laboratory (GFDL) coupled general circulation model (CGCM). In both control simulations and retrospective forecasts of the 1990's in the CGCM, we find that the occurrence of some IODZM events is preconditioned by oceanic conditions and potentially predictable three seasons in advance, while other IODZM events appear to be triggered by weather noise and have low predictability. The results highlight the necessity for future studies to distinguish periods when the IODZM is more or less predictable and search for its precursory pattern in the ocean.
In this study, an estimate of the expected
number of Atlantic tropical cyclones (TCs) that were missed by the observing
system in the presatellite era (between 1878 and 1965) is developed. The
significance of trends in both number and duration since 1878 is assessed
and these results are related to estimated changes in sea surface
temperature (SST) over the “main development region” (“MDR”). The
sensitivity of the estimate of missed TCs to underlying assumptions is
examined. According to the base case adjustment used in this study, the
annual number of TCs has exhibited multidecadal variability that has
strongly covaried with multidecadal variations in MDR SST, as has been noted
previously. However, the linear trend in TC counts (1878–2006) is notably
smaller than the linear trend in MDR SST, when both time series are
normalized to have the same variance in their 5-yr running mean series.
Using the base case adjustment for missed TCs leads to an 1878–2006 trend in
the number of TCs that is weakly positive, though not statistically
significant, with p ~ 0.2. The estimated trend for 1900–2006 is
highly significant (+~ 4.2 storms century−1) according to the
results of this study. The 1900–2006 trend is strongly influenced by a
minimum in 1910–30, perhaps artificially enhancing significance, whereas the
1878–2006 trend depends critically on high values in the late 1800s, where
uncertainties are larger than during the 1900s. The trend in average TC
duration (1878–2006) is negative and highly significant. Thus, the evidence
for a significant increase in Atlantic storm activity over the most recent
125 yr is mixed, even though MDR SST has warmed significantly. The
decreasing duration result is unexpected and merits additional exploration;
duration statistics are more uncertain than those of storm counts. As TC
formation, development, and track depend on a number of environmental
factors, of which regional SST is only one, much work remains to be done to
clarify the relationship between anthropogenic climate warming, the
large-scale tropical environment, and Atlantic TC activity.
Vecchi, Gabriel A., A C Clement, and Brian J Soden, February 2008: Examining the tropical Pacific's response to global warming. EOS, 89(9), 81, 83. PDF
Alternative interpretations of the relationship between sea surface temperature and hurricane activity imply vastly different future Atlantic hurricane activity.
A consistent weakening and poleward expansion of the Hadley circulation is diagnosed in the climate change simulations of the IPCC AR4 project. Associated with this widening is a poleward expansion of the subtropical dry zone. Simple scaling analysis supports the notion that the poleward extent of the Hadley cell is set by the location where the thermally driven jet first becomes baroclinically unstable. The expansion of the Hadley cell is caused by an increase in the subtropical static stability, which pushes poleward the baroclinic instability zone and hence the outer boundary of the Hadley cell.
How anthropogenic climate change will affect hydroclimate in the arid regions of southwestern North America has implications for the allocation of water resources and the course of regional development. Here we show that there is a broad consensus among climate models that this region will dry in the 21st century and that the transition to a more arid climate should already be under way. If these models are correct, the levels of aridity of the recent multiyear drought or the Dust Bowl and the 1950s droughts will become the new climatology of the American Southwest within a time frame of years to decades.
Song, Qian, Gabriel A Vecchi, and Anthony Rosati, June 2007: The role of Indonesian throughflow in the Indo-Pacific climate variability in the GFDL coupled climate model. Journal of Climate, 20(11), DOI:10.1175/JCLI4133.1. Abstract
The impacts of the Indonesian Throughflow (ITF) on the tropical Indo–Pacific climate, particularly on the character of interannual variability, are explored using a coupled general circulation model (CGCM). A pair of CGCM experiments—a control experiment with an open ITF and a perturbation experiment in which the ITF is artificially closed—is integrated for 200 model years, with the 1990 values of trace gases. The closure of the ITF results in changes to the mean oceanic and atmospheric conditions throughout the tropical Indo–Pacific domain as follows: surface temperatures in the eastern tropical Pacific (Indian) Ocean warm (cool), the near-equatorial Pacific (Indian) thermocline flattens (shoals), Indo–Pacific warm-pool precipitation shifts eastward, and there are relaxed trade winds over the tropical Pacific and anomalous surface easterlies over the equatorial Indian Ocean. The character of the oceanic changes is similar to that described by ocean-only model experiments, though the amplitude of many features in the tropical Indo–Pacific is amplified in the CGCM experiments.
In addition to the mean-state changes, the character of tropical Indo–Pacific interannual variability is substantially modified. Interannual variability in the equatorial Pacific and the eastern tropical Indian Ocean is substantially intensified by the closure of the ITF. In addition to becoming more energetic, El Niño–Southern Oscillation (ENSO) exhibits a shorter time scale of variability and becomes more skewed toward its warm phase (stronger and more frequent warm events). The structure of warm ENSO events changes; the anomalies of sea surface temperature (SST), precipitation, and surface westerly winds are shifted to the east and the meridional extent of surface westerly anomalies is larger.
In the eastern tropical Indian Ocean, the interannual SST variability off the coast of Java–Sumatra is noticeably amplified by the occurrence of much stronger cooling events. Closing the ITF shoals the eastern tropical Indian Ocean thermocline, which results in stronger cooling events through enhanced atmosphere–thermocline coupled feedbacks. Changes to the interannual variability caused by the ITF closure rectify into mean-state changes in tropical Indo–Pacific conditions. The modified Indo–Pacific interannual variability projects onto the mean-state differences between the ITF open and closed scenarios, rectifying into mean-state differences. These results suggest that CGCMs need to reasonably simulate the ITF in order to successfully represent not just the mean climate, but its variations as well.
The interannual variability of the Indian Ocean, with particular focus on the Indian Ocean dipole/zonal mode (IODZM), is investigated in a 250-yr simulation of the GFDL coupled global general circulation model (CGCM). The CGCM successfully reproduces many fundamental characteristics of the climate system of the Indian Ocean. The character of the IODZM is explored, as are relationships between positive IODZM and El Niño events, through a composite analysis. The IODZM events in the CGCM grow through feedbacks between heat-content anomalies and SST-related atmospheric anomalies, particularly in the eastern tropical Indian Ocean. The composite IODZM events that co-occur with El Niño have stronger anomalies and a sharper east–west SSTA contrast than those that occur without El Niño. IODZM events, whether or not they occur with El Niño, are preceded by distinctive Indo-Pacific warm pool anomaly patterns in boreal spring: in the central Indian Ocean easterly surface winds, and in the western equatorial Pacific an eastward shift of deep convection, westerly surface winds, and warm sea surface temperature. However, delayed onsets of the anomaly patterns (e.g., boreal summer) are often not followed by IODZM events. The same anomaly patterns often precede El Niño, suggesting that the warm pool conditions favorable for both IODZM and El Niño are similar. Given that IODZM events can occur without El Niño, it is proposed that the observed IODZM–El Niño relation arises because the IODZM and El Niño are both large-scale phenomena in which variations of the Indo-Pacific warm pool deep convection plays a central role. Yet each phenomenon has its own dynamics and life cycle, allowing each to develop without the other.
The CGCM integration also shows substantial decadal modulation of the occurrence of IODZM events, which is found to be not in phase with that of El Niño events. There is a weak, though significant, negative correlation between the two. Moreover, the statistical relationship between the IODZM and El Niño displays strong decadal variability.
To help understand possible impacts of anthropogenic greenhouse warming on hurricane activity, we assess model-projected changes in large-scale environmental factors tied to variations in hurricane statistics. This study focuses on vertical wind shear (Vs) over the tropical Atlantic during hurricane season, the increase of which has been historically associated with diminished hurricane activity and intensity. A suite of state-of-the-art global climate model experiments is used to project changes in Vs over the 21st century. Substantial increases in tropical Atlantic and East Pacific shear are robust features of these experiments, and are shown to be connected to the model-projected decrease in the Pacific Walker circulation. The relative changes in shear are found to be comparable to those of other large-scale environmental parameters associated with Atlantic hurricane activity. The influence of these Vs changes should be incorporated into projections of long-term hurricane activity.
An integrated in situ Indian Ocean observing system (IndOOS) is simulated using a high-resolution ocean general circulation model (OGCM) with daily mean forcing, including an estimate of subdaily oceanic variability derived from observations. The inclusion of subdaily noise is fundamental to the results; in the mixed layer it is parameterized as Gaussian noise with an rms of 0.1°C; below the mixed layer a Gaussian interface displacement with an rms of 7 m is used. The focus of this assessment is on the ability of an IndOOS—comprising a 3° × 3° Argo profiling float array, a series of frequently repeated XBT lines, and an array of moored buoys—to observe the interannual and subseasonal variability of subsurface Indian Ocean temperature. The simulated IndOOS captures much of the OGCM interannual subsurface temperature variability.
A fully deployed Argo array with 10-day sampling interval is able to capture a significant part of the Indian Ocean interannual temperature variability; a 5-day sampling interval degrades its ability to capture variability. The proposed moored buoy array and frequently repeated XBT lines provide complementary information in key regions, particularly the Java/Sumatra and Somali upwelling and equatorial regions. Since the subdaily noise is of the same order as the subseasonal signal and since much of the variability is submonthly, a 5-day sampling interval does not drastically enhance the ability of Argo to capture the OGCM subseasonal variability. However, as sampling intervals are decreased, there is enhanced divergence of the Argo floats, diminished ability to quality control data, and a decreased lifetime of the floats; these factors argue against attempting to resolve subseasonal variability with Argo by shortening the sampling interval. A moored array is essential to capturing the subseasonal and near-equatorial variability in the model, and the proposed moored buoy locations span the region of strong subseasonal variability. On the whole, the proposed IndOOS significantly enhances the ability to capture both interannual and subseasonal variability in the Indian Ocean.
This study examines the response of the tropical atmospheric and oceanic circulation to increasing
greenhouse gases using a coordinated set of twenty-first-century climate model experiments performed for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). The strength
of the atmospheric overturning circulation decreases as the climate warms in all IPCC AR4 models, in a
manner consistent with the thermodynamic scaling arguments of Held and Soden. The weakening occurs
preferentially in the zonally asymmetric (i.e., Walker) rather than zonal-mean (i.e., Hadley) component of
the tropical circulation and is shown to induce substantial changes to the thermal structure and circulation
of the tropical oceans. Evidence suggests that the overall circulation weakens by decreasing the frequency
of strong updrafts and increasing the frequency of weak updrafts, although the robustness of this behavior
across all models cannot be confirmed because of the lack of data. As the climate warms, changes in both
the atmospheric and ocean circulation over the tropical Pacific Ocean resemble “El Niño–like” conditions;
however, the mechanisms are shown to be distinct from those of El Niño and are reproduced in both mixed
layer and full ocean dynamics coupled climate models. The character of the Indian Ocean response to global
warming resembles that of Indian Ocean dipole mode events. The consensus of model results presented
here is also consistent with recently detected changes in sea level pressure since the mid–nineteenth century.
The
response of tropical cyclone activity to global warming is widely debated.
It is often assumed that warmer sea surface temperatures provide a more
favourable environment for the development and intensification of tropical
cyclones, but cyclone genesis and intensity are also affected by the
vertical thermodynamic properties of the atmosphere. Here we use climate
models and observational reconstructions to explore the relationship between
changes in sea surface temperature and tropical cyclone 'potential
intensity'—a measure that provides an upper bound on cyclone intensity and
can also reflect the likelihood of cyclone development. We find that changes
in local sea surface temperature are inadequate for characterizing even the
sign of changes in potential intensity, but that long-term changes in
potential intensity are closely related to the regional structure of
warming; regions that warm more than the tropical average are characterized
by increased potential intensity, and vice versa. We use this relationship
to reconstruct changes in potential intensity over the twentieth century
from observational reconstructions of sea surface temperature. We find that,
even though tropical Atlantic sea surface temperatures are currently at a
historical high, Atlantic potential intensity probably peaked in the 1930s
and 1950s, and recent values are near the historical average. Our results
indicate that—per unit local sea surface temperature change—the response of
tropical cyclone activity to natural climate variations, which tend to
involve localized changes in sea surface temperature, may be larger than the
response to the more uniform patterns of greenhouse-gas-induced warming.
The current generation of coupled climate models run at the Geophysical Fluid Dynamics Laboratory (GFDL) as part of the Climate Change Science Program contains ocean components that differ in almost every respect from those contained in previous generations of GFDL climate models. This paper summarizes the new physical features of the models and examines the simulations that they produce. Of the two new coupled climate model versions 2.1 (CM2.1) and 2.0 (CM2.0), the CM2.1 model represents a major improvement over CM2.0 in most of the major oceanic features examined, with strikingly lower drifts in hydrographic fields such as temperature and salinity, more realistic ventilation of the deep ocean, and currents that are closer to their observed values. Regional analysis of the differences between the models highlights the importance of wind stress in determining the circulation, particularly in the Southern Ocean. At present, major errors in both models are associated with Northern Hemisphere Mode Waters and outflows from overflows, particularly the Mediterranean Sea and Red Sea.
The mechanisms that drove zonal wind stress (τx) changes in the near-equatorial Pacific at the end of the extreme 1997–98 El Niño event are explored using a global atmospheric general circulation model. The analysis focuses on three features of the τx evolution between October 1997 and May 1998 that were fundamental in driving the oceanic changes at the end of this El Niño event: (i) the southward shift of near-date-line surface zonal wind stress (τx) anomalies beginning November 1997, (ii) the disappearance of the easterly τx from the eastern equatorial Pacific (EEqP) in February 1998, and (iii) the reappearance of easterly τx in the EEqP in May 1998. It is shown that these wind changes represent the deterministic response of the atmosphere to the observed sea surface temperature (SST) field, resulting from changes in the meridional structure of atmospheric convective anomalies in response to the seasonally phase-locked meridional movement of the warmest SST.
The southward shift of the near-date-line τx anomalies at the end of this El Niño event was controlled by the seasonal movement of the warmest SST south of the equator, which—both directly and through its influence on the atmospheric response to changes in SST anomaly—brought the convective anomalies from being centered about the equator to being centered south of the equator. The disappearance (reappearance) of easterly EEqP τx has only been evident in extreme El Niño events and has been associated with the development (northward retreat) of an equatorial intertropical convergence zone (ITCZ). The disappearance/return of EEqP easterly τx arises in the AGCM as the deterministic response to changes in the SST field, tied principally to the changes in climatological SST (given time-invariant extreme El Niño SSTA) and not to changes in the underlying SSTA field. The disappearance (return) of EEqP easterly τx in late boreal winter (late boreal spring) is a characteristic atmospheric response to idealized extreme El Niño SST anomalies; this suggests that the distinctive termination of the 1997–98 El Niño event is that to be expected for extreme El Niño events.
Vecchi, Gabriel A., and D E Harrison, 2006: The termination of the 1997–98 El Niño. Part I: Mechanisms of oceanic change. Journal of Climate, 19(12), DOI:10.1175/JCLI3776.1. Abstract
The 1997–98 El Niño was both unusually strong and terminated unusually. Warm eastern equatorial Pacific (EEqP) sea surface temperature anomalies (SSTAs) exceeded 4°C at the event peak and lasted well into boreal spring of 1998, even though subsurface temperatures began cooling in December 1997. The oceanic processes that controlled this unusual termination are explored here and can be characterized by three features: (i) eastward propagating equatorial Pacific thermocline (Ztc) shoaling beginning in the central Pacific in November 1997; (ii) persistent warm EEqP SSTA between December 1997 and May 1998, despite strong EEqP Ztc shoaling (and subsurface cooling); and (iii) an abrupt cooling of EEqP SSTA in early May 1998 that exceeded 4°C within two weeks.
It is shown here that these changes can be understood in terms of the oceanic response to changes to the meridional structure of the near-equatorial zonal wind field. Equatorial near-date-line westerly wind anomalies greatly decreased in late 1997, associated with a southward shift of convective and wind anomalies. In the EEqP, equatorial easterlies disappeared (reappeared) in late January (early May) 1998, driving the springtime extension (abrupt termination) of this El Niño event. The authors suggest that the wind changes arise from fundamentally meridional processes and are tied to the annual cycle of insolation.
Since the mid-nineteenth century the Earth's surface has warmed1, 2, 3, and models indicate that human activities have caused part of the warming by altering the radiative balance of the atmosphere1, 3. Simple theories suggest that global warming will reduce the strength of the mean tropical atmospheric circulation4, 5. An important aspect of this tropical circulation is a large-scale zonal (east–west) overturning of air across the equatorial Pacific Ocean—driven by convection to the west and subsidence to the east—known as the Walker circulation6. Here we explore changes in tropical Pacific circulation since the mid-nineteenth century using observations and a suite of global climate model experiments. Observed Indo-Pacific sea level pressure reveals a weakening of the Walker circulation. The size of this trend is consistent with theoretical predictions, is accurately reproduced by climate model simulations and, within the climate models, is largely due to anthropogenic forcing. The climate model indicates that the weakened surface winds have altered the thermal structure and circulation of the tropical Pacific Ocean. These results support model projections of further weakening of tropical atmospheric circulation during the twenty-first century4, 5, 7.
We explore the extent to which stochastic atmospheric variability was fundamental to development of extreme sea surface temperature anomalies (SSTAs) during the 1997–8 El Niño. The observed western equatorial Pacific westerly zonal stress anomalies (τ a x ), which appeared between Nov. 1996 and May 1997 as a series of episodic bursts, were largely reproducible by an atmospheric general circulation model (AGCM) ensemble forced with observed SST. Retrospective forecasts using a hybrid coupled model (HCM) indicate that coupling only the part of τ a x linearly related to large-scale tropical Pacific SSTA is insufficient to capture the observed 1997 warming; but, accounting in the HCM for all the τ a x that was connected to SST, recovers most of the strong SSTA warming. The AGCM-estimated range of stochastic τ a x forcing induces substantial dispersion in the forecasts, but does not obscure the large-scale warming in most HCM ensemble members.
The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) with the capability of measuring sea surface temperature (SST) in the presence of clouds, has been providing an unprecedented view of tropical basin-scale SST variability. In this paper, an assessment of the accuracy of the SST derived from TMI over the Bay of Bengal using in situ data collected from moored buoys and research ships, is presented. The authors find that TMI captures the evolution of the SST of the bay on seasonal time scales with reasonable accuracy. The mean difference between the SST from TMI and buoys is less than 0.1°C, and the rms difference is about 0.6°C. The time scales of the intraseasonal variation of the TMI SST are realistic. However, the amplitude of the SST variation on the intraseasonal scale is overestimated by a factor of about 1.3 when compared to buoy data. It is observed that the SST derived from TMI tends to be lower during periods with deep convection or winds stronger than 10 m s−1, or both. There is better agreement during weak conditions of convection/wind. This leads to a cold bias during convectively active periods when running average SST time series are constructed from SSTs retrieved from the TMI.
Vecchi, Gabriel A., and N A Bond, 2004: The Madden-Julian Oscillation (MJO) and northern high latitude wintertime surface air temperatures. Geophysical Research Letters, 31, L04104, DOI:10.1029/2003GL018645. Abstract
The Madden-Julian Oscillation (MJO) is the primary mode of large-scale intraseasonal variability in the tropics. Recent work has connected the MJO to atmospheric variability in mid-latitudes. We focus on relationships between the MJO and wintertime surface air temperatures in the Northern Hemisphere high latitudes. The MJO is diagnosed using principal EOF of 850 hPa zonal winds from the NCEP/NCAR Reanalysis for 1979–2002. Station data are used for surface air temperature in Alaska, Canada, the former U.S.S.R., Greenland, and Iceland. The phase of the MJO has a substantial systematic and spatially coherent effect on intraseasonal variability in wintertime surface air temperature through the global Arctic. Composites of geopotential height and specific humidity suggest that radiative and advective effects are important in the observed connections. These statistical connections may be useful for wintertime temperature forecasts. The mechanisms connecting intraseasonal tropical variability with polar and sub-polar variability bear examination.
Vecchi, Gabriel A., and D E Harrison, 2004: Interannual Indian rainfall variability and Indian Ocean sea surface temperature anomalies In Earth Climate: The Ocean-Atmosphere Interaction, Geophysical Monograph 147, Washington, DC, American Geophysical Union, 247-260. Abstract
It is shown that interannual variations in Indian continental rainfall during the southwest monsoon can be usefully represented by two regional rainfall indices. India rainfall is concentrated in two regions, each with strong mean and variance in precipitation: the Western Ghats (WG) and the Ganges-Mahanadi Basin (GB) region. Interannual variability of rainfall averaged over each of the two regions (WG and GB) is uncorrelated; however, the rainfall over these two regions together explains 90% of the interannual variance of All-India rainfall (AIR).
The lack of correlation between WG and GB rainfall suggests that different mechanisms may account for their variability. During the period 1982-2001, rainfall variability over each of these two regions exhibits distinct relationships to Indian Ocean SST: warm SSTA over the western Arabian Sea at the monsoon onset is associated with increased WG rainfall (r = 0.77), while cool SSTA off of Java and Sumatra is associated with increased GB rainfall (r = -0.55). The connection between SSTA and AIR is considerably weaker, and represents the superposition of that associated with each region. We find the relationship with WG rainfall is robust, while that with GB results from a single exceptional year. Each region also exhibits distinct relationships to El Nińo SSTA indices.
The western Arabian Sea exhibits strong spatial variability in sea surface temperature (SST) during the southwest monsoon, with changes in SST that can exceed 5°C over 200 km. Exploration of satellite-based and in situ data shows a strong connection between mesoscale SST features and changes in the atmospheric boundary layer. The fundamental relationship is that of weak (strong) wind velocities overlying cold (warm) SST features. There are also coherent changes in other near-surface meteorological parameters, such as the air–sea temperature difference and relative humidity—indicating changes in the stability of the planetary boundary layer over the mesoscale SST features. These relationships are similar to those recently reported over the equatorial Pacific tropical instability wave region.
This observed covariability of atmospheric boundary layer structure and SST results in variations of the surface heat and moisture fluxes; latent heat flux is modified by changes in relative humidity (principally through the temperature dependence of saturation specific humidity), wind speed, and boundary layer stability over the cold filaments. The nonlinear dependence of latent heat flux on the three parameters leads to a net enhancement of latent heat flux from the mesoscale features, as compared to that computed using spatially averaged parameters.
Additionally, the spatial structure of the heat-flux variability will tend to dampen the mesoscale SST features. The mesoscale wind variability results in strong wind stress curl patterns on the same spatial scales as the oceanic features. The resulting Ekman pumping variations may play an important role in the evolution of the ocean eddy fields in this region. Further examination of the processes controlling the observed covariability, and the oceanic and atmospheric response to the coupling should therefore be undertaken.
doi: 10.1175/1520-0442(2004)017<1213:OCITWA>2.0.CO;2
