Bloch-Johnson, Jonah, Maria A A Rugenstein, Marc J Alessi, Cristian Proistosescu, Ming Zhao, Bosong Zhang, Andrew I L Williams, Jonathan M Gregory, Jason N S Cole, Yue Dong, Margaret L Duffy, Sarah M Kang, and Chen Zhou, February 2024: The Green's Function Model Intercomparison Project (GFMIP) protocol. Journal of Advances in Modeling Earth Systems, 16(2), DOI:10.1029/2023MS003700. Abstract
The atmospheric Green's function method is a technique for modeling the response of the atmosphere to changes in the spatial field of surface temperature. While early studies applied this method to changes in atmospheric circulation, it has also become an important tool to understand changes in radiative feedbacks due to evolving patterns of warming, a phenomenon called the “pattern effect.” To better study this method, this paper presents a protocol for creating atmospheric Green's functions to serve as the basis for a model intercomparison project, GFMIP. The protocol has been developed using a series of sensitivity tests performed with the HadAM3 atmosphere-only general circulation model, along with existing and new simulations from other models. Our preliminary results have uncovered nonlinearities in the response of the atmosphere to surface temperature changes, including an asymmetrical response to warming versus cooling patch perturbations, and a change in the dependence of the response on the magnitude and size of the patches. These nonlinearities suggest that the pattern effect may depend on the heterogeneity of warming as well as its location. These experiments have also revealed tradeoffs in experimental design between patch size, perturbation strength, and the length of control and patch simulations. The protocol chosen on the basis of these experiments balances scientific utility with the simulation time and setup required by the Green's function approach. Running these simulations will further our understanding of many aspects of atmospheric response, from the pattern effect and radiative feedbacks to changes in circulation, cloudiness, and precipitation.
Dogar, Muhammad M., Masatomo Fujiwara, Ming Zhao, Masamichi Ohba, and Yu Kosaka, January 2024: ENSO and NAO linkage to strong volcanism and associated post-volcanic high-latitude winter warming. Geophysical Research Letters, 51(1), DOI:10.1029/2023GL106114. Abstract
High-latitude winter warming was observed following strong tropical volcanism, which has long been believed to be due to the volcanic-induced positive North Atlantic Oscillation (NAO) phase. However, recent works argue that this warming is caused by El Niño–Southern Oscillation (ENSO) variability instead of volcanoes. Moreover, some studies further argue that El Niño and volcanoes work together to produce this post-volcanic NAO winter warming. To better understand these arguments on post-volcanic high-latitude winter warming, we conducted ENSO-preconditioned volcanic experiments. Our simulations strongly suggest that the post-eruption Eurasian winter warming is caused by a post-eruption positive NAO phase and not by coexisting ENSO-preconditioned variability. Additionally, we find that the El Niño-preconditioned volcanic eruption enhances the El Niño phase; however, the neutral and La Niña-preconditioned eruptions do not lead to an ENSO–like response. These findings are helpful to better understand volcanic-induced circulation impacts and have important implications for the interpretation of model results and post-volcanic prediction.
Atmospheric rivers (ARs) play important roles in various extreme weather events across the US. While AR features in western US have been extensively studied, there remains limited understanding of their variability in the eastern US (EUS). Using both observations and a state-of-the-art climate model, we find a significant increase (~10% dec−1) in winter AR frequency in the EUS during the past four decades. This trend is closely linked to recent changes in the Pacific/North America (PNA) teleconnection pattern, accompanied by a poleward shift of the mid-latitude jet stream. We further reveal a strong correlation (R = 0.8; P < 0.001) between interannual variations in AR occurrence and the PNA index. This linkage has been verified in various model simulations. A statistical model, built on this linkage, has proven effective in predicting the AR frequency using the PNA index at both monthly and seasonal scales. These promising results have important implications for addressing concerns related to AR-associated extreme precipitation and flooding in this region.
Gentile, Emanuele S., Ming Zhao, Vincent E Larson, Colin M Zarzycki, and Zhihong Tan, May 2024: The effect of coupling between CLUBB turbulence scheme and surface momentum flux on global wind simulations. Journal of Advances in Modeling Earth Systems, 16(5), DOI:10.1029/2024MS004295. Abstract
The higher-order turbulence scheme, Cloud Layers Unified by Binormals (CLUBB), is known for effectively simulating the transition from cumulus to stratocumulus clouds within leading atmospheric climate models. This study investigates an underexplored aspect of CLUBB: its capacity to simulate near-surface winds and the Planetary Boundary Layer (PBL), with a particular focus on its coupling with surface momentum flux. Using the GFDL atmospheric climate model (AM4), we examine two distinct coupling strategies, distinguished by their handling of surface momentum flux during the CLUBB's stability-driven substepping performed at each atmospheric time step. The static coupling maintains a constant surface momentum flux, while the dynamic coupling adjusts the surface momentum flux at each CLUBB substep based on the CLUBB-computed zonal and meridional wind speed tendencies. Our 30-year present-day climate simulations (1980–2010) show that static coupling overestimates 10-m wind speeds compared to both control AM4 simulations and reanalysis, particularly over the Southern Ocean (SO) and other midlatitude ocean regions. Conversely, dynamic coupling corrects the static coupling 10-m winds biases in the midlatitude regions, resulting in CLUBB simulations achieving there an excellent agreement with AM4 simulations. Furthermore, analysis of PBL vertical profiles over the SO reveals that dynamic coupling reduces downward momentum transport, consistent with the found wind-speed reductions. Instead, near the tropics, dynamic coupling results in minimal changes in near-surface wind speeds and associated turbulent momentum transport structure. Notably, the wind turning angle serves as a valuable qualitative metric for assessing the impact of changes in surface momentum flux representation on global circulation patterns.
Precipitation changes in full response to CO2 increase are widely studied but confidence in future projections remains low. Mechanistic understanding of the direct radiative effect of CO2 on precipitation changes, independent from CO2-induced SST changes, is therefore necessary. Utilizing global atmospheric models, we identify robust summer precipitation decreases across North America in response to direct CO2 forcing. We find that spatial distribution of CO2 forcing at land surface is likely shaped by climatological distribution of water vapor and clouds. This, coupled with local feedback processes, changes in convection, and moisture supply resulting from CO2-induced circulation changes, could determine North American hydroclimate changes. In central North America, increasing CO2 may decrease summertime precipitation by warming the surface and inducing dry advection into the region to reduce moisture supply. Meanwhile, for the southwest and the east, CO2-induced shift of subtropical highs generates wet advection, which might mitigate the drying effect from warming.
We present a variable-resolution global chemistry-climate model (AM4VR) developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) for research at the nexus of US climate and air quality extremes. AM4VR has a horizontal resolution of 13 km over the US, allowing it to resolve urban-to-rural chemical regimes, mesoscale convective systems, and land-surface heterogeneity. With the resolution gradually reducing to 100 km over the Indian Ocean, we achieve multi-decadal simulations driven by observed sea surface temperatures at 50% of the computational cost for a 25-km uniform-resolution grid. In contrast with GFDL's AM4.1 contributing to the sixth Coupled Model Intercomparison Project at 100 km resolution, AM4VR features much improved US climate mean patterns and variability. In particular, AM4VR shows improved representation of: precipitation seasonal-to-diurnal cycles and extremes, notably reducing the central US dry-and-warm bias; western US snowpack and summer drought, with implications for wildfires; and the North American monsoon, affecting dust storms. AM4VR exhibits excellent representation of winter precipitation, summer drought, and air pollution meteorology in California with complex terrain, enabling skillful prediction of both extreme summer ozone pollution and winter haze events in the Central Valley. AM4VR also provides vast improvements in the process-level representations of biogenic volatile organic compound emissions, interactive dust emissions from land, and removal of air pollutants by terrestrial ecosystems. We highlight the value of increased model resolution in representing climate–air quality interactions through land-biosphere feedbacks. AM4VR offers a novel opportunity to study global dimensions to US air quality, especially the role of Earth system feedbacks in a changing climate.
Zhang, Bosong, Leo J Donner, Ming Zhao, and Zhihong Tan, September 2024: Improved precipitation diurnal cycle in GFDL climate models with non-equilibrium convection. Journal of Advances in Modeling Earth Systems, 16(9), DOI:10.1029/2024MS004315. Abstract
Most global climate models with convective parameterization have trouble in simulating the observed diurnal cycle of convection. Maximum precipitation usually happens too early during summertime, especially over land. Observational analyses indicate that deep convection over land cannot keep pace with rapid variations in convective available potential energy, which is largely controlled by boundary-layer forcing. In this study, a new convective closure in which shallow and deep convection interact strongly, out of equilibrium, is implemented in atmosphere-only and ocean-atmosphere coupled models. The diurnal cycles of convection in both simulations are significantly improved with small changes to their mean states. The new closure shifts maximum precipitation over land later by about three hours. Compared to satellite observations, the diurnal phase biases are reduced by half. Shallow convection to some extent equilibrates rapid changes in the boundary layer at subdiurnal time scales. Relaxed quasi-equilibrium for convective available potential energy holds in significant measure as a result. Future model improvement will focus on the remaining biases in the diurnal cycle, which may be further reduced by including stochastic entrainment and cold pools.
Zhao, Ming, May 2024: Cloud radiative effects associated with daily weather regimes. Geophysical Research Letters, 51(10), DOI:10.1029/2024GL109090. Abstract
Using high temporal resolution satellite observations and reanalysis data, we classify daily weather into distinct regimes and quantify their associated cloud radiative effect (CRE) to better understand the roles of various weather systems in affecting Earth's top-of-atmosphere radiation budget. These regimes include non-precipitation, drizzle, wet non-storm, and storm days, which encompass atmospheric rivers (AR), tropical storms (TS), and mesoscale convection systems (MCS). We find that precipitation (wet) days account for roughly 80% (60%) of global longwave (LW) and shortwave (SW) CREs due to their large frequency and high intensity in CRE. Despite being rare globally (13%), AR, TS, and MCS days together account for 32% of global LW CRE and 27% of SW CRE due to their higher intensity in LW and SW CRE. These results enhance our understanding of how various weather systems, particularly severe storms, influence Earth's radiative balance, and will help to better constrain climate models.
Zhao, Ming, and Thomas R Knutson, June 2024: Crucial role of sea surface temperature warming patterns in near-term high-impact weather and climate projection. npj Climate and Atmospheric Science, 7, 130, DOI:10.1038/s41612-024-00681-7. Abstract
Recent studies indicate that virtually all global climate models (GCMs) have had difficulty simulating sea surface temperature (SST) trend patterns over the past four decades. GCMs produce enhanced warming in the eastern Equatorial Pacific (EPAC) and Southern Ocean (SO) warming, while observations show intensified warming in the Indo-Pacific Warm Pool (IPWP) and slight cooling in the eastern EPAC and SO. Using Geophysical Fluid Dynamics Laboratory’s latest higher resolution atmospheric model and coupled prediction system, we show the model biases in SST trend pattern have profound implications for near-term projections of high-impact storm statistics, including the frequency of atmospheric rivers (AR), tropical storms (TS) and mesoscale convection systems (MCS), as well as for hydrological and climate sensitivity. If the future SST warming pattern continues to resemble the observed pattern from the past few decades rather than the GCM simulated/predicted patterns, our results suggest (1) a drastically different future projection of high-impact storms and their associated hydroclimate changes, especially over the Western Hemisphere, (2) a stronger global hydrological sensitivity, and (3) substantially less global warming due to stronger negative feedback and lower climate sensitivity. The roles of SST trend patterns over the EPAC, IPWP, SO, and the North Atlantic tropical cyclone Main Development Region (AMDR) are isolated, quantified, and used to understand the simulated differences. Specifically, SST trend patterns in the EPAC and AMDR are crucial for modeled differences in AR and MCS frequency, while those in the IPWP and AMDR are essential for differences in TS frequency over the North Atlantic.
Chang, Chuan-Chieh, Zhuo Wang, Mingfang Ting, and Ming Zhao, February 2023: Summertime subtropical stationary waves in the northern hemisphere: Variability, forcing mechanisms, and impacts on tropical cyclone activity. Journal of Climate, 36(3), DOI:10.1175/JCLI-D-22-0233.1753-773. Abstract
The interannual variability of summertime subtropical stationary waves, the forcing mechanisms, and their connections to regional tropical cyclone (TC) variability are investigated in this study. Two indices are identified to characterize the interannual variability of subtropical stationary waves: the longitudinal displacement of the zonal wavenumber-1 component (WN1) and the intensity change of the zonal wavenumber-2 component (WN2). These two indices are strongly anticorrelated and offer simple metrics to depict the interannual variability of subtropical stationary waves. Furthermore, the longitudinal displacement of the WN1 is significantly correlated with the variability of TC activity over the North Pacific and North Atlantic, and its influences on regional TC activity can be explained by variations in vertical wind shear, tropospheric humidity, and the frequency of Rossby wave breaking. The subtropical stationary waves are strongly related to precipitation anomalies over different oceanic regions, implying the possible impacts of low-frequency climate modes. Semi-idealized experiments using the Community Earth System Model version 2 (CESM2) show that the longitude of the WN1 is strongly modulated by ENSO, as well as SST anomalies over the Atlantic main development region and the central North Pacific. Further diagnosis using a baroclinic stationary wave model demonstrates the dominant role of diabatic heating in driving the interannual variability of stationary waves and confirms the impacts of different air–sea coupled modes on subtropical stationary waves. Overall, subtropical stationary waves provide a unified framework to understand the impacts of various forcing agents, such as ENSO, the Atlantic meridional mode, and extratropical Rossby wave breaking, on TC activity over the North Atlantic and North Pacific.
Dogar, Muhammad M., Leon Hermanson, Adam A Scaife, Daniele Visioni, Ming Zhao, Ibrahim Hoteit, Hans-F Graf, Muhammad Ahmad Dogar, Mansour Almazroui, and Masatomo Fujiwara, January 2023: A review of El Niño Southern Oscillation linkage to strong volcanic eruptions and post-volcanic winter warming. Earth Systems and Environment, 7, DOI:10.1007/s41748-022-00331-z15-42. Abstract
Understanding the influence of volcanism on ENSO and associated climatic impacts is of great scientific and social importance. Although many studies on the volcano–ENSO nexus are available, a thorough review of ENSO sensitivity to explosive eruptions is still missing. Therefore, this study aims to provide an in-depth assessment of the ENSO response to volcanism. Most past studies suggest an emerging consensus in models, with the vast majority showing an El Niño-like SST response during the eruption year and a La Niña-like response a few years later. RCP8.5-based climate model projections also suggest strong El Niño conditions and significant monsoonal rainfall reduction following strong tropical volcanism. However, some studies involving climate reconstructions and model simulations still raise concerns about the ENSO–volcano link and suggest a weak ENSO response to volcanism. This happens because ENSO response to volcanism seems very sensitive to reconstruction methods, ENSO preconditioning, eruption timing, position and amplitude. We noticed that some response mechanisms are still unclear, for instance, how the tropical volcanic forcing with nearly uniform radiative cooling projects onto ENSO when coincidental ENSO events are underway. Moreover, there are very less observational and proxy records for assessing the extratropical volcanism impact on ENSO. Nevertheless, model-based studies suggest that Northern (Southern) Hemispheric extratropical eruptions may lead to an El Niño (La Niña)-like response. We further noticed that the origin of post-eruption winter warming is still elusive; however, recent findings suggest that the large-scale circulation changes concurrently occurring during volcanism are the potential source of high-latitude winter warming. Existing uncertainties in the simulated ENSO response to volcanism could be reduced by considering a synchronized modeling approach with large ensembles.
Accurate representation of mesoscale scale convective systems (MCSs) in climate models is of vital importance to understanding global energy, water cycles, and extreme weather. In this study, we evaluate the simulated MCS features over the United States from the newly developed GFDL global high-resolution (∼50 km) AM4 model by comparing them with the observations during spring to early summer (April–June) and late summer (July–August). The results show that the spatial distribution and seasonality of occurrence and genesis frequency of MCSs are reasonably simulated over the central United States in both seasons. The model reliably reproduces the observed features of MCS duration, translation speed, and size over the central United States, as well as the favorable large-scale circulation pattern associated with MCS development over the central United States during spring and early summer. However, the model misrepresents the amplitude and the phase of the diurnal cycle of MCSs during both seasons. In addition, the spatial distribution of occurrence and genesis frequency of MCSs over the eastern United States is substantially overestimated, with larger biases in early spring and summer. Furthermore, while large-scale circulation patterns are reasonably simulated in spring and early summer, they are misrepresented in the model during summer. Finally, we examine MCS-related precipitation, finding that the model overestimates MCS-related precipitation during spring and early summer, but this bias is insufficient to explain the significant dry bias observed in total precipitation over the central United States. Nonetheless, the dry biases in MCS-associated precipitation during late summer likely contribute to the overall precipitation deficit in the model.
Falasca, Fabrizio, Andrew Brettin, Laure Zanna, Stephen M Griffies, Jianjun Yin, and Ming Zhao, June 2023: Exploring the nonstationarity of coastal sea level probability distributions. Environmental Data Science, 2, e16, DOI:10.1017/eds.2023.10. Abstract
Studies agree on a significant global mean sea level rise in the 20th century and its recent 21st century acceleration in the satellite record. At regional scale, the evolution of sea level probability distributions is often assumed to be dominated by changes in the mean. However, a quantification of changes in distributional shapes in a changing climate is currently missing. To this end, we propose a novel framework quantifying significant changes in probability distributions from time series data. The framework first quantifies linear trends in quantiles through quantile regression. Quantile slopes are then projected onto a set of four orthogonal polynomials quantifying how such changes can be explained by independent shifts in the first four statistical moments. The framework proposed is theoretically founded, general, and can be applied to any climate observable with close-to-linear changes in distributions. We focus on observations and a coupled climate model (GFDL-CM4). In the historical period, trends in coastal daily sea level have been driven mainly by changes in the mean and can therefore be explained by a shift of the distribution with no change in shape. In the modeled world, robust changes in higher order moments emerge with increasing concentration. Such changes are driven in part by ocean circulation alone and get amplified by sea level pressure fluctuations, with possible consequences for sea level extremes attribution studies.
Gentile, Emanuele S., Ming Zhao, and Kevin Hodges, December 2023: Poleward intensification of midlatitude extreme winds under warmer climate. npj Climate and Atmospheric Science, 6, 219, DOI:10.1038/s41612-023-00540-x. Abstract
Our study investigates the global impact of midlatitude cyclones on extreme wind speed events in both hemispheres under a warmer climate. Using the latest version of the high-resolution ≈ 50 km grid-spacing atmospheric climate model AM4, developed by the Geophysical Fluid Dynamics Laboratory, we conducted simulations covering the 71-years period 1949–2019 for both the present-day climate and an idealised future global warming climate scenario with a homogeneous Sea Surface Temperature (SST) increase by 2 K. Our findings reveal that extreme near-surface wind speeds increase by up to 3% K−1 towards the poles while decrease by a similar amount in the lower midlatitudes. When considering only extreme wind speed events objectively attributed to midlatitude cyclones, we observe a migration by the same amount towards higher latitudes both in percentage per degree SST warming and absolute value. The total number of midlatitude cyclones decreases by roughly 4%, but the proportion of cyclone-associated extreme wind speed events increases by 10% in a warmer climate. Finally, Northwestern Europe, the British Isles, and the West Coast of North America are identified as hot spots with the greatest socio-economic impacts from increased cyclone-associated extreme winds.
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.
This study examines the potential impacts of large-scale atmospheric circulations that are forced by sea surface temperatures (SST) on global tropical cyclone (TC) formation. Using the Geophysical Fluid Dynamics Laboratory (GFDL) global atmosphere and land surface model, version 4 (AM4), under different SST distributions, it is found that the east–west clustering of global TC formation is mainly governed by large-scale circulations in response to given SSTs, instead of direct ocean surface fluxes associated with zonal SST anomalies. Our zonally homogeneous SST simulations in the presence of realistic surface coverage show that TC clusters still emerge as a result of the breakdown of zonal circulations related to land–sea distribution, which produce specific “hotspots” for global TC formation. Sensitivity experiments with different climate warming scenarios and model physics confirm the persistence of these TC clusters in the absence of all zonal SST variations. These robust results offer new insights into the effects of large-scale circulation and terrain forcing on TC clusters beyond the traditional view of direct SST impacts, which are based on the direct alignment of the warmest SST regions and TC clusters. In addition, our experiments also capture internal variability of the global TC frequency, with an average fluctuation of 6–8 TCs at several dominant frequencies of ∼3, 6, and 9 years, even in the absence of all SST interannual variability and ocean coupling. This finding reveals an intrinsic “noise” level of the global TC frequency that one has to take into account when examining the past and future trends in TC activity and their related significance or detectability.
Zhang, Bosong, Ming Zhao, and Zhihong Tan, February 2023: Using a Green’s Function approach to diagnose the pattern effect in GFDL AM4 and CM4. Journal of Climate, 36(4), DOI:10.1175/JCLI-D-22-0024.11105–1124. Abstract
Global radiative feedbacks exhibit large dependence on the spatial structure of sea surface temperature (SST) changes, which is referred to as the “pattern effect.” A Green’s function (GF) approach has been demonstrated to be useful in identifying and understanding contributions of regional SST changes to global radiative feedbacks. Here, we explore the ability of the GF approach in quantifying the pattern effect in an atmospheric model (AM4) and a coupled model (CM4) recently developed at NOAA’s Geophysical Fluid Dynamics Laboratory (GFDL), including the impact of SST changes on global-mean and local responses of key variables important to climate. Given historical SST patterns, the GF derived from idealized experiments with SST warming patches can largely reproduce AM4 simulated global-mean and regional responses. When AM4 is forced by SST patterns retrieved from the CM4 abrupt quadrupling of carbon dioxide experiment, the same GF captures interannual variations of AM4 simulated global-mean responses but falls short of reproducing the magnitude of the responses. A decomposition of such SST patterns into global-mean values plus remaining anomalies helps reduce biases. Additional idealized experiments are conducted to examine the sensitivity of the GF to the amplitude and sign of SST perturbations and to the integration time and the confidence level of the significance test. Impacts of these factors on the performance of the GF are discussed.
This study investigates how climate sensitivity depends upon the spatial pattern of radiative forcing. Sensitivity experiments using a coupled ocean-atmosphere model were conducted by adding anomalous incoming solar radiation over the entire globe, Northern Hemisphere mid-latitudes, Southern Ocean, and tropics. The varied forcing patterns led to highly divergent climate sensitivities. Specifically, the climate is nearly twice as sensitive to Southern Ocean forcing as tropical forcing. Strong coupling between the surface and free troposphere in the tropics increases the inversion strength, leading to smaller cloud feedback in the tropical forcing experiments. In contrast, the extratropics exhibit weaker coupling, a decrease or near-zero change in the inversion strength, and strong positive cloud feedback. These results contrast with the conventional SST-pattern effect in which tropical surface temperature changes regulate climate sensitivity. They also have important implications for other potentially asymmetric forcings, such as those from geoengineering, volcanic eruptions, and paleoclimatic changes.
Chu, Wenchao, Yanluan Lin, and Ming Zhao, January 2022: Implementation and evaluation of a double-plume convective parameterization in NCAR CAM5. Journal of Climate, 35(2), DOI:10.1175/JCLI-D-21-0267.1617-637. Abstract
Performance of global climate models (GCMs) is strongly affected by the cumulus parameterization (CP) used. Similar to the approach in GFDL AM4, a double-plume CP, which unifies the deep and shallow convection in one framework, is implemented and tested in the NCAR Community Atmospheric Model version 5 (CAM5). Based on the University of Washington (UW) shallow convection scheme, an additional plume was added to represent the deep convection. The shallow and deep plumes share the same cloud model, but use different triggers, fractional mixing rates, and closures. The scheme was tested in single-column, short-term hindcast, and AMIP simulations. Compared with the default combination of the Zhang–McFarlane scheme and UW scheme in CAM5, the new scheme tends to produce a top-heavy mass flux profile during the active monsoon period in the single-column simulations. The scheme increases the intensity of tropical precipitation, closer to TRMM observations. The new scheme increased subtropical marine boundary layer clouds and high clouds over the deep tropics, both in better agreement with observations. Sensitivity tests indicate that regime-dependent fractional entrainment rates of the deep plume are desired to improve tropical precipitation distribution and upper troposphere temperature. This study suggests that a double-plume approach is a promising way to combine shallow and deep convections in a unified framework.
An event-based assessment of the sea surface temperature (SST) threshold at the genesis of tropical mesoscale convective systems (MCSs) is performed in this study. We show that this threshold (SSTG) has undergone a significant warming trend at a rate of ∼0.2°C per decade. The SSTG shows a remarkable correspondence with the tropical mean SST and upper-tropospheric temperature on interannual and longer timescales. Using a high-resolution global climate model that permits realistic simulations of tropical MCSs, we find that the observed features of SSTG are well simulated. Both observation and model simulations demonstrate that the upward tendency in SSTG primarily results from the environmental SST warming over MCS genesis regions rather than the changes in MCS genesis location. A continuous increase in SSTG is projected in a warming simulation, but the relationship between SSTG and upper-tropospheric temperature remains unchanged, suggesting that the tropical tropospheric temperature generally follows a moist-adiabatic adjustment.
We describe the model performance of a new global coupled climate model configuration, CM4-MG2. Beginning with the Geophysical Fluid Dynamics Laboratory's fourth-generation physical climate model (CM4.0), we incorporate a two-moment Morrison-Gettelman bulk stratiform microphysics scheme with prognostic precipitation (MG2), and a mineral dust and temperature-dependent cloud ice nucleation scheme. We then conduct and analyze a set of fully coupled atmosphere-ocean-land-sea ice simulations, following Coupled Model Intercomparison Project Phase 6 protocols. CM4-MG2 generally captures CM4.0's baseline simulation characteristics, but with several improvements, including better marine stratocumulus clouds off the west coasts of Africa and North and South America, a reduced bias toward “double” Intertropical Convergence Zones south of the equator, and a stronger Madden-Julian Oscillation (MJO). Some degraded features are also identified, including excessive Arctic sea ice extent and a stronger-than-observed El Nino-Southern Oscillation. Compared to CM4.0, the climate sensitivity is reduced by about 10% in CM4-MG2.
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.
The frequency of atmospheric blocking has been largely underestimated by general circulation models (GCMs) participating in the Coupled Model Intercomparison Project (CMIP). Errors in the onset, persistence, barotropicity, geographical preference, seasonality, intensity, and moving speed of global blocking were diagnosed in 10 Geophysical Fluid Dynamics Laboratory (GFDL) GCMs for recent CMIP5 and CMIP6 using a detection approach that combines zonal eddies and the reversal of zonal winds. The blocking frequency, similar at 500 and 250 hPa, is underestimated by 50% in the Atlantic–Europe region during December–February but is overestimated by 60% in the Pacific–North America region during that season and by 70% in the southwest Pacific during July–August. These blocking biases at 500 hPa were investigated in the five CMIP6 models that showed improvements over the CMIP5 versions. The Atlantic–Europe underestimate corresponds to lower instantaneous blocking rates, lower persistent blocking rates, and higher persistent stationary ridge rates; the number of blocks with a duration of 4–5 days is only 40%–65% of that in observations. In contrast, the overestimate consists of excessive blocks with a duration longer than 12 days in the Pacific–North America and up to twice as many 4–6-day events in the southwest Pacific. Simulated December–February blocks up to 12 days in the Pacific–North America region tend to be stronger and to move more slowly than those in observations. Diagnostic sensitivity tests indicated that the zonal mean and zonal eddy components of the mean state play a key role, as replacing each with that of observations substantially reduced many of the outstanding biases in these GCMs.
Moon, Yumin, Daehyun Kim, Allison A Wing, Suzana J Camargo, and Ming Zhao, et al., November 2022: An evaluation of tropical cyclone rainfall structures in the HighResMIP simulations against satellite observations. Journal of Climate, 35(22), DOI:10.1175/JCLI-D-21-0564.13715-3738. Abstract
This study evaluates tropical cyclone (TC) rainfall structures in the CMIP6 HighResMIP global climate model (GCM) simulations against satellite rainfall retrievals. We specifically focus on TCs within the deep tropics (25°S–25°N). Analysis of TC rain rate composites indicates that in comparison to the satellite observations at the same intensity, many HighResMIP simulations tend to overproduce rain rates around TCs, in terms of both maximum rain rate magnitude and area-averaged rain rates. In addition, as model horizontal resolution increases, the magnitude of the peak rain rate appears to increase. However, the area-averaged rain rates decrease with increasing horizontal resolution, partly due to the TC eyewall being located closer to the TC center, thus occupying a smaller area and contributing less to the area-averaged rain rates. The effect of ocean coupling is to lower the TC rain rates, bringing them closer to the satellite observations, due to reduced horizontal moisture flux convergence and surface latent heat flux beneath TCs. Examination of horizontal rain rate distributions indicates that vertical wind shear–induced rainfall asymmetries in HighResMIP-simulated TCs are qualitatively consistent with the observations. In addition, a positive relationship is observed between the area-averaged inner-core rainfall and TC intensification likelihoods across the HighResMIP simulations, as GCM simulations producing stronger TCs more frequently have the greater rainfall close to the center, in agreement with previous theoretical and GCM simulation results.
A subseasonal-to-seasonal (S2S) prediction system was recently developed using the GFDL Seamless System for Prediction and Earth System Research (SPEAR) global coupled model. Based on 20-yr hindcast results (2000–19), the boreal wintertime (November–April) Madden–Julian oscillation (MJO) prediction skill is revealed to reach 30 days measured before the anomaly correlation coefficient of the real-time multivariate (RMM) index drops to 0.5. However, when the MJO is partitioned into four distinct propagation patterns, the prediction range extends to 38, 31, and 31 days for the fast-propagating, slow-propagating, and jumping MJO patterns, respectively, but falls to 23 days for the standing MJO. A further improvement of MJO prediction requires attention to the standing MJO given its large gap with its potential predictability (38 days). The slow-propagating MJO detours southward when traversing the Maritime Continent (MC), and confronts the MC prediction barrier in the model, while the fast-propagating MJO moves across the central MC without this prediction barrier. The MJO diversity is modulated by stratospheric quasi-biennial oscillation (QBO): the standing (slow-propagating) MJO coincides with significant westerly (easterly) phases of QBO, partially explaining the contrasting MJO prediction skill between these two QBO phases. The SPEAR model shows its capability, beyond the propagation, in predicting their initiation for different types of MJO along with discrete precursory convection anomalies. The SPEAR model skillfully predicts the observed distinct teleconnections over the North Pacific and North America related to the standing, jumping, and fast-propagating MJO, but not the slow-propagating MJO. These findings highlight the complexities and challenges of incorporating MJO prediction into the operational prediction of meteorological variables.
Zhao, Ming, January 2022: A study of AR-, TS-, and MCS-associated precipitation and extreme precipitation in present and warmer climates. Journal of Climate, 35(2), DOI:10.1175/JCLI-D-21-0145.1479-497. Abstract
Atmospheric rivers (ARs), tropical storms (TSs), and mesoscale convective systems (MCSs) are important weather phenomena that often threaten society through heavy precipitation and strong winds. Despite their potentially vital role in global and regional hydrological cycles, their contributions to long-term mean and extreme precipitation have not been systematically explored at the global scale. Using observational and reanalysis data, and NOAA’s Geophysical Fluid Dynamics Laboratory’s new high-resolution global climate model, we quantify that despite their occasional (13%) occurrence globally, AR, TS, and MCS days together account for ∼55% of global mean precipitation and ∼75% of extreme precipitation with daily rates exceeding its local 99th percentile. The model reproduces well the observed percentage of mean and extreme precipitation associated with AR, TS, and MCS days. In an idealized global warming simulation with a homogeneous SST increase of 4 K, the modeled changes in global mean and regional distribution of precipitation correspond well with changes in AR/TS/MCS precipitation. Globally, the frequency of AR days increases and migrates toward higher latitudes while the frequency of TS days increases over the central Pacific and part of the south Indian Ocean with a decrease elsewhere. The frequency of MCS days tends to increase over parts of the equatorial western and eastern Pacific warm pools and high latitudes and decreases over most part of the tropics and subtropics. The AR/TS/MCS mean precipitation intensity increases by ∼5% K−1 due primarily to precipitation increases in the top 25% of AR/TS/MCS days with the heaviest precipitation, which are dominated by the thermodynamic component with the dynamic and microphysical components playing a secondary role.
Zhao, Ming, September 2022: An investigation of the effective climate sensitivity in GFDL’s new climate models CM4.0 and SPEAR. Journal of Climate, 35(17), DOI:10.1175/JCLI-D-21-0327.15637-5660. Abstract
Despite a relatively low climate sensitivity indicated by atmospheric-only simulations with uniform sea surface temperature (SST) warming, GFDL’s new climate model CM4.0 participating in CMIP6 and the seasonal-to-decadal prediction system SPEAR, both of which use an identical atmospheric model AM4.0, produce relatively high effective climate sensitivity (EffCS). The substantial increase in CM4.0’s EffCS is found to be caused by additional positive forcing associated with the CO2 fertilization effect on vegetation, enhanced positive feedback due to stronger reduction in Southern Hemisphere (SH) sea ice concentration (SIC), and clouds whose feedback depends on SST warming patterns. Compared to a SPEAR run using a static vegetation model (SPEAR-SV), CM4.0 produces roughly 30% larger EffCS, among which roughly 1/3 of the increase is due to dynamical vegetation with the rest due primarily to changes in SIC. Although cloud feedback does not explain the key feedback differences among CM4.0, SPEAR, and SPEAR-SV, it is the primary cause of the models’ increase (less negative) in TOA net feedback during the later period of their quadrupling CO2 simulations due to changes in their SST warming patterns. Moreover, CM4.0’s SST warming pattern and its effects on cloud feedback appear to be the leading cause of CM4.0’s EffCS increase compared to the earlier generation GFDL model ESM2M, which produces one of the lowest EffCS values among CMIP5 models. In comparison, CM4.0’s enhanced reduction in SH SICs plays a slightly less important role in its increase in EffCS compared to ESM2M.
The characteristics of tropical mesoscale convective systems (MCSs) simulated with a finer-resolution (~50 km) version of the Geophysical Fluid Dynamics Laboratory (GFDL) AM4 model are evaluated by comparing with a comprehensive long-term observational dataset. It is shown that the model can capture the various aspects of MCSs reasonably well. The simulated spatial distribution of MCSs is broadly in agreement with the observations. This is also true for seasonality and interannual variability over different land and oceanic regions. The simulated MCSs are generally longer-lived, weaker, and larger than observed. Despite these biases, an event-scale analysis suggests that their duration, intensity, and size are strongly correlated. Specifically, longer-lived and stronger events tend to be bigger, which is consistent with the observations. The same model is used to investigate the response of tropical MCSs to global warming using time-slice simulations forced by prescribed sea surface temperatures and sea ice. There is an overall decrease in occurrence frequency, and the reduction over land is more prominent than over ocean.
A two-moment Morrison-Gettelman bulk cloud microphysics with prognostic precipitation (MG2), together with a mineral dust and temperature-dependent ice nucleation scheme, have been implemented into the Geophysical Fluid Dynamics Laboratory's Atmosphere Model version 4.0 (AM4.0). We refer to this configuration as AM4-MG2. This paper describes the configuration of AM4-MG2, evaluates its performance, and compares it with AM4.0. It is shown that the global simulations with AM4-MG2 compare favorably with observations and reanalyses. The model skill scores are close to AM4.0. Compared to AM4.0, improvements in AM4-MG2 include (a) better coastal marine stratocumulus and seasonal cycles, (b) more realistic ice fraction, and (c) dominant accretion over autoconversion. Sensitivity tests indicate that nucleation and sedimentation schemes have significant impacts on cloud liquid and ice water fields, but higher horizontal resolution (about 50 km instead of 100 km) does not.
Yin, Jianjun, and Ming Zhao, October 2021: Influence of the Atlantic meridional overturning circulation on the U.S. extreme cold weather. Communications Earth and Environment, 2, 218, DOI:10.1038/s43247-021-00290-9. Abstract
Due to its large northward heat transport, the Atlantic meridional overturning circulation influences both weather and climate at the mid-latitude Northern Hemisphere. Here we use a state-of-the-art global weather/climate modeling system with high resolution (GFDL CM4C192) to quantify this influence focusing on the U.S. extreme cold weather during winter. We perform a control simulation and the water-hosing experiment to obtain two climate states with and without a vigorous Atlantic meridional overturning circulation. We find that in the control simulation with an overturning circulation, the U.S. east of the Rockies is a region characterized by intense north-south heat exchange in the atmosphere during winter. Without the northward heat transport by the overturning circulation in the hosing experiment, this channel of atmospheric heat exchange becomes even more active through the Bjerknes compensation mechanism. Over the U.S., extreme cold weather intensifies disproportionately compared with the mean climate response after the shutdown of the overturning circulation. Our results suggest that an active overturning circulation in the present-day climate likely makes the U.S. winter less harsh and extreme.
Zhang, Gan, Levi G Silvers, Ming Zhao, and Thomas R Knutson, March 2021: Idealized aquaplanet simulations of tropical cyclone activity: Significance of temperature gradients, Hadley circulation, and zonal asymmetry. Journal of the Atmospheric Sciences, 78(3), DOI:10.1175/JAS-D-20-0079.1877-902. Abstract
Earlier studies have proposed many semiempirical relations between climate and tropical cyclone (TC) activity. To explore these relations, this study conducts idealized aquaplanet experiments using both symmetric and asymmetric sea surface temperature (SST) forcings. With zonally symmetric SST forcings that have a maximum at 10°N, reducing meridional SST gradients around an Earth-like reference state leads to a weakening and southward displacement of the intertropical convergence zone. With nearly flat meridional gradients, warm-hemisphere TC numbers increase by nearly 100 times due particularly to elevated high-latitude TC activity. Reduced meridional SST gradients contribute to a poleward expansion of the tropics, which is associated with a poleward migration of the latitudes where TCs form or reach their lifetime maximum intensity. However, these changes cannot be simply attributed to the poleward expansion of Hadley circulation. Introducing zonally asymmetric SST forcings tends to decrease the global TC number. Regional SST warming—prescribed with or without SST cooling at other longitudes—affects local TC activity but does not necessarily increase TC genesis. While regional warming generally suppresses TC activity in remote regions with relatively cold SSTs, one experiment shows a surprisingly large increase of TC genesis. This increase of TC genesis over relatively cold SSTs is related to local tropospheric cooling that reduces static stability near 15°N and vertical wind shear around 25°N. Modeling results are discussed with scaling analyses and have implications for the application of the “convective quasi-equilibrium and weak temperature gradient” framework.
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.
We document the development and simulation characteristics of the next generation modeling system for seasonal to decadal prediction and projection at the Geophysical Fluid Dynamics Laboratory (GFDL). SPEAR (Seamless System for Prediction and EArth System Research) is built from component models recently developed at GFDL ‐ the AM4 atmosphere model, MOM6 ocean code, LM4 land model and SIS2 sea ice model. The SPEAR models are specifically designed with attributes needed for a prediction model for seasonal to decadal time scales, including the ability to run large ensembles of simulations with available computational resources. For computational speed SPEAR uses a coarse ocean resolution of approximately 1.0o (with tropical refinement). SPEAR can use differing atmospheric horizontal resolutions ranging from 1o to 0.25o. The higher atmospheric resolution facilitates improved simulation of regional climate and extremes. SPEAR is built from the same components as the GFDL CM4 and ESM 4 models, but with design choices geared toward seasonal to multidecadal physical climate prediction and projection. We document simulation characteristics for the time‐mean climate, aspects of internal variability, and the response to both idealized and realistic radiative forcing change. We describe in greater detail one focus of the model development process that was motivated by the importance of the Southern Ocean to the global climate system. We present sensitivity tests that document the influence of the Antarctic surface heat budget on Southern Ocean ventilation and deep global ocean circulation. These findings were also useful in the development processes for the GFDL CM4 and ESM 4 models.
We describe the baseline coupled model configuration and simulation characteristics of GFDL's Earth System Model Version 4.1 (ESM4.1), which builds on component and coupled model developments at GFDL over 2013–2018 for coupled carbon‐chemistry‐climate simulation contributing to the sixth phase of the Coupled Model Intercomparison Project. In contrast with GFDL's CM4.0 development effort that focuses on ocean resolution for physical climate, ESM4.1 focuses on comprehensiveness of Earth system interactions. ESM4.1 features doubled horizontal resolution of both atmosphere (2° to 1°) and ocean (1° to 0.5°) relative to GFDL's previous‐generation coupled ESM2‐carbon and CM3‐chemistry models. ESM4.1 brings together key representational advances in CM4.0 dynamics and physics along with those in aerosols and their precursor emissions, land ecosystem vegetation and canopy competition, and multiday fire; ocean ecological and biogeochemical interactions, comprehensive land‐atmosphere‐ocean cycling of CO2, dust and iron, and interactive ocean‐atmosphere nitrogen cycling are described in detail across this volume of JAMES and presented here in terms of the overall coupling and resulting fidelity. ESM4.1 provides much improved fidelity in CO2 and chemistry over ESM2 and CM3, captures most of CM4.0's baseline simulations characteristics, and notably improves on CM4.0 in (1) Southern Ocean mode and intermediate water ventilation, (2) Southern Ocean aerosols, and (3) reduced spurious ocean heat uptake. ESM4.1 has reduced transient and equilibrium climate sensitivity compared to CM4.0. Fidelity concerns include (1) moderate degradation in sea surface temperature biases, (2) degradation in aerosols in some regions, and (3) strong centennial scale climate modulation by Southern Ocean convection.
We describe the baseline model configuration and simulation characteristics of the Geophysical Fluid Dynamics Laboratory (GFDL)'s Atmosphere Model version 4.1 (AM4.1), which builds on developments at GFDL over 2013–2018 for coupled carbon‐chemistry‐climate simulation as part of the sixth phase of the Coupled Model Intercomparison Project. In contrast with GFDL's AM4.0 development effort, which focused on physical and aerosol interactions and which is used as the atmospheric component of CM4.0, AM4.1 focuses on comprehensiveness of Earth system interactions. Key features of this model include doubled horizontal resolution of the atmosphere (~200 to ~100 km) with revised dynamics and physics from GFDL's previous‐generation AM3 atmospheric chemistry‐climate model. AM4.1 features improved representation of atmospheric chemical composition, including aerosol and aerosol precursor emissions, key land‐atmosphere interactions, comprehensive land‐atmosphere‐ocean cycling of dust and iron, and interactive ocean‐atmosphere cycling of reactive nitrogen. AM4.1 provides vast improvements in fidelity over AM3, captures most of AM4.0's baseline simulations characteristics, and notably improves on AM4.0 in the representation of aerosols over the Southern Ocean, India, and China—even with its interactive chemistry representation—and in its manifestation of sudden stratospheric warmings in the coldest months. Distributions of reactive nitrogen and sulfur species, carbon monoxide, and ozone are all substantially improved over AM3. Fidelity concerns include degradation of upper atmosphere equatorial winds and of aerosols in some regions.
Kuo, Yi-Hung, J David Neelin, C-C Chen, W-T Chen, Leo J Donner, Andrew Gettelman, Xianan Jiang, K-T Kuo, Eric Maloney, C R Mechoso, Yi Ming, K A Schiro, Charles J Seman, Chien-Ming Wu, and Ming Zhao, January 2020: Convective transition statistics over tropical oceans for climate model diagnostics: GCM evaluation. Journal of the Atmospheric Sciences, 77(1), DOI:10.1175/JAS-D-19-0132.1. Abstract
To assess deep-convective parameterizations in a variety of GCMs and examine the fast-timescale convective transition, a set of statistics characterizing the pickup of precipitation as a function of column water vapor (CWV), PDFs and joint-PDFs of CWV and precipitation, and the dependence of the moisture-precipitation relation on tropospheric temperature is evaluated using the hourly output of two versions of GFDL AM4, NCAR CAM5 and superparameterized CAM (SPCAM). The 6-hourly output from the MJOTF/GASS project is also analyzed. Contrasting statistics produced from individual models that primarily differ in representations of moist convection suggest that convective transition statistics can substantially distinguish differences in convective representation and its interaction with the large-scale flow, while models that differ only in spatial-temporal resolution, microphysics, or ocean-atmosphere coupling result in similar statistics. Most of the models simulate some version of the observed sharp increase in precipitation as CWV exceeds a critical value, as well as that convective onset occurs at higher CWV but at lower column RH as temperature increases. While some models quantitatively capture these observed features and associated probability distributions, considerable intermodel spread and departures from observations in various aspects of the precipitation-CWV relationship are noted. For instance, in many of the models, the transition from the low-CWV, non-precipitating regime to the moist regime for CWV around and above critical is less abrupt than in observations. Additionally, some models overproduce drizzle at low CWV, and some require CWV higher than observed for strong precipitation. For many of the models, it is particularly challenging to simulate the probability distributions of CWV at high temperature.
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.
Moon, Yumin, D Kim, Suzana J Camargo, Allison A Wing, Kevin A Reed, Michael F Wehner, and Ming Zhao, June 2020: A new method to construct a horizontal resolution‐dependent wind speed adjustment factor for tropical cyclones in global climate model simulations. Geophysical Research Letters, 47(11), DOI:10.1029/2020GL087528. Abstract
A new method to construct a horizontal resolution‐dependent wind speed adjustment factor for evaluating tropical cyclones (TCs) in global climate models (GCMs) is presented. In contrast to the previous studies that used idealized axisymmetric wind fields, this study analyzes 48 hours of 10‐second surface wind fields from 1‐km TC simulations. The adjustment factor is derived from filtering the simulated TC wind fields onto various horizontal grid spacings typical of those used in GCMs. The new adjustment factor leads to TCs with greater intensity than the existing adjustment factors for horizontal grid spacings smaller than 30 km. This difference is attributed to more realistic wind fields in the TC simulations that contain highly asymmetric, localized patches of higher wind speeds instead of axisymmetric wind fields. Applying the new adjustment factor to select GCM simulations suggests the common interpretation of low‐intensity bias in GCM‐simulated TCs might be slightly exaggerated.
Owing to the limited length of observed tropical cyclone data and the effects of multidecadal internal variability, it has been a challenge to detect trends in tropical cyclone activity on a global scale. However, there is a distinct spatial pattern of the trends in tropical cyclone frequency of occurrence on a global scale since 1980, with substantial decreases in the southern Indian Ocean and western North Pacific and increases in the North Atlantic and central Pacific. Here, using a suite of high-resolution dynamical model experiments, we show that the observed spatial pattern of trends is very unlikely to be explained entirely by underlying multidecadal internal variability; rather, external forcing such as greenhouse gases, aerosols, and volcanic eruptions likely played an important role. This study demonstrates that a climatic change in terms of the global spatial distribution of tropical cyclones has already emerged in observations and may in part be attributable to the increase in greenhouse gas emissions.
Naud, C M., J Jeyaratnam, James F Booth, Ming Zhao, and Andrew Gettelman, January 2020: Evaluation of modeled precipitation in oceanic extratropical cyclones using IMERG. Journal of Climate, 33(1), DOI:10.1175/JCLI-D-19-0369.1. Abstract
Using the high spatial and temporal resolution precipitation dataset Integrated Multi-satellitE Retrievals for GPM (IMERG), extratropical cyclone precipitation is evaluated in two reanalyses and two climate models. Based on cyclone-centered composites, all four models overestimate precipitation in the western subsiding and dry side of the cyclones, and underestimate the precipitation in the eastern ascending and moist side. By decomposing the composites into frequency of occurrence and intensity (mean precipitation rate when precipitating), the analysis reveals a tendency for all four models to overestimate frequency and underestimate intensity, with the former issue dominating in the western half and the latter in the eastern half of the cyclones. Differences in frequency are strongly dependent on cyclone environmental moisture, while the differences in intensity are strongly impacted by the strength of ascent within the cyclone. There are some uncertainties associated with the observations: IMERG might under-report frozen precipitation and possibly exaggerate rates in vigorously ascending regions. Nevertheless, the analysis suggests that all models produce extratropical cyclone precipitation too often and too lightly. These biases have consequences when evaluating the changes in precipitation characteristics with changes in cyclone properties: the models disagree on the magnitude of the change in precipitation intensity with a change in environmental moisture and in precipitation frequency with a change in cyclone strength. This complicates accurate predictions of precipitation changes in a changing climate.
Orbe, Clara, L Van Roekel, A F Adames, A Dezfuli, John Fasullo, Peter J Gleckler, Jiwoo Lee, Wei Li, Larissa Nazarenko, Gavin A Schmidt, Kenneth R Sperber, and Ming Zhao, September 2020: Representation of Modes of Variability in 6 U.S. Climate Models. Journal of Climate, 33(17), DOI:10.1175/JCLI-D-19-0956.1. Abstract
We compare the performance of several modes of variability across six U.S. climate modeling groups, with a focus on identifying robust improvements in recent models [including those participating in phase 6 of the Coupled Model Intercomparison Project (CMIP)] compared to previous versions. In particular, we examine the representation of the Madden–Julian oscillation (MJO), El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), the quasi-biennial oscillation (QBO) in the tropical stratosphere, and the dominant modes of extratropical variability, including the southern annular mode (SAM), the northern annular mode (NAM) [and the closely related North Atlantic Oscillation (NAO)], and the Pacific–North American pattern (PNA). Where feasible, we explore the processes driving these improvements through the use of “intermediary” experiments that utilize model versions between CMIP3/5 and CMIP6 as well as targeted sensitivity experiments in which individual modeling parameters are altered. We find clear and systematic improvements in the MJO and QBO and in the teleconnection patterns associated with the PDO and ENSO. Some gains arise from better process representation, while others (e.g., the QBO) from higher resolution that allows for a greater range of interactions. Our results demonstrate that the incremental development processes in multiple climate model groups lead to more realistic simulations over time.
Recent laboratory and field studies point to an increase of sea salt aerosol (SSA) emissions with temperature, suggesting that SSA may lower climate sensitivity. We assess the impact of a strong (4.2 % K‐1) and weak (0.7% K‐1) temperature response of SSA emissions on the climate sensitivity of the coupled climate model CM4. We find that the stronger temperature dependence improves the simulation of marine aerosol optical depth sensitivity to temperature and lowers CM4 Transient Climate Response (‐0.12K) and Equilibrium Climate Sensitivity (‐0.5K). At CO2 doubling, the higher SSA emission sensitivity causes a negative radiative feedback (‐0.125 W m‐2 K‐1), which can only be partly explained by changes in the radiative effect of SSA (‐0.08 W m‐2 K‐1). Stronger radiative feedbacks are dominated by more negative low‐level clouds feedbacks in the Northern Hemisphere, which are partly offset by more positive feedbacks in the Southern Hemisphere associated with a weaker Atlantic Meridional Overturning Circulation.
Dust emission is initiated when surface wind velocities exceed the threshold of wind erosion. Most dust models used constant threshold values globally. Here we use satellite products to characterize the frequency of dust events and surface properties. By matching this frequency derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue aerosol products with surface winds, we are able to retrieve a climatological monthly global distribution of wind erosion threshold (Vthreshold) over dry and sparsely-vegetated surface. This monthly two-dimensional threshold velocity is then implemented into the Geophysical Fluid Dynamics Laboratory coupled land-atmosphere model (AM4.0/LM4.0). It is found that the climatology of dust optical depth (DOD) and total aerosol optical depth, surface PM10 dust concentrations, and seasonal cycle of DOD are better captured over the dust belt (i.e. North Africa and the Middle East) by simulations with the new wind erosion threshold than those using the default globally constant threshold. The most significant improvement is the frequency distribution of dust events, which is generally ignored in model evaluation. By using monthly rather than annual mean Vthreshold, all comparisons with observations are further improved. The monthly global threshold of wind erosion can be retrieved under different spatial resolutions to match the resolution of dust models and thus can help improve the simulations of dust climatology and seasonal cycle as well as dust forecasting.
Wing, Allison A., Catherine L Stauffer, Tobias Becker, Kevin A Reed, Min-Seop Ahn, Nathan P Arnold, Sandrine Bony, Mark Branson, George H Bryan, Jean-Pierre Chaboureau, Stephan R de Roode, Kulkarni Gayatri, Cathy Hohenegger, I-Kuan Hu, Fredrik Jansson, Todd R Jones, Marat Khairoutdinov, Daehyun Kim, Zane K Martin, Shuhei Matsugishi, Brian Medeiros, Hiroaki Miura, Yumin Moon, Sebastian K Muller, Tomoki Ohno, Max Popp, Thara Prabhakaran, David A Randall, Rosimar Rios-Berrios, Nicolas Rochetin, Romain Roehrig, David M Romps, James H Ruppert Jr, Masaki Satoh, Levi G Silvers, Martin S Singh, Bjorn Stevens, Lorenzo Tomassini, Chiel C van Heerwaarden, Shuguang Wang, and Ming Zhao, September 2020: Clouds and Convective Self-Aggregation in a Multi-Model Ensemble of Radiative-Convective Equilibrium Simulations. Journal of Advances in Modeling Earth Systems, 12(9), DOI:10.1029/2020MS002138. Abstract
The Radiative‐Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative‐convective equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climate sensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique among intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud‐resolving models (CRMs), large eddy simulations (LES), and global cloud‐resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self‐aggregation in large domains and agree that self‐aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self‐aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than unaggregated simulations.
GFDL's new CM4.0 climate model has high transient and equilibrium climate sensitivities near the middle of the upper half of CMIP5 models. The CMIP5 models have been criticized for excessive sensitivity based on observations of present‐day warming and heat uptake and estimates of radiative forcing. An ensemble of historical simulations with CM4.0 produces warming and heat uptake that are consistent with these observations under forcing that is at the middle of the assessed distribution. Energy budget‐based methods for estimating sensitivities based on these quantities underestimate CM4.0's sensitivities when applied to its historical simulations. However, we argue using a simple attribution procedure that CM4.0's warming evolution indicates excessive transient sensitivity to greenhouse gases. This excessive sensitivity is offset prior to recent decades by excessive response to aerosol and land use changes.
Storm surge and coastal flooding caused by tropical cyclones (hurricanes) and extratropical cyclones (nor'easters) pose a threat to communities along the Atlantic coast of the United States. Climate change and sea level rise are altering the statistics of these extreme events in a rather complex fashion. Here we use a fully-coupled global weather/climate modeling system (GFDL CM4) to study characteristics of extreme daily sea level (ESL) along the US Atlantic coast and their response to global warming. We find that under natural weather processes, the Gulf of Mexico coast is most vulnerable to storm surge and related ESL. New Orleans is a striking hotspot with the highest surge efficiency in response to storm winds. Under a 1% per year atmospheric CO2 increase on centennial time scales, the anthropogenic signal in ESL is robust along the US East Coast. It can emerge from the background variability as soon as in twenty years, or even before global sea level rise is taken into account. The regional dynamic sea level rise induced by the weakening of the Atlantic meridional overturning circulation facilitates this early emergence, especially during wintertime coastal flooding associated with nor’easters. Along the Gulf Coast, ESL is sensitive to the modification of hurricane characteristics under the CO2 forcing.
Zhao, Ming, December 2020: Simulations of Atmospheric Rivers, Their Variability and Response to GlobalWarming Using GFDL’s New High Resolution General Circulation Model. Journal of Climate, 33(23), DOI:10.1175/JCLI-D-20-0241.1. Abstract
A 50-km-resolution GFDL AM4 well captures many aspects of observed atmospheric river (AR) characteristics including the probability density functions of AR length, width, length–width ratio, geographical location, and the magnitude and direction of AR mean vertically integrated vapor transport (IVT), with the model typically producing stronger and narrower ARs than the ERA-Interim results. Despite significant regional biases, the model well reproduces the observed spatial distribution of AR frequency and AR variability in response to large-scale circulation patterns such as El Niño–Southern Oscillation (ENSO), the Northern and Southern Hemisphere annular modes (NAM and SAM), and the Pacific–North American (PNA) teleconnection pattern. For global warming scenarios, in contrast to most previous studies that show a large increase in AR length and width and therefore the occurrence frequency of AR conditions at a given location, this study shows only a modest increase in these quantities. However, the model produces a large increase in strong ARs with the frequency of category 3–5 ARs rising by roughly 100%–300% K−1. The global mean AR intensity as well as AR intensity percentiles at most percent ranks increases by 5%–8% K−1, roughly consistent with the Clausius–Clapeyron scaling of water vapor. Finally, the results point out the importance of AR IVT thresholds in quantifying modeled AR response to global warming.
Mixed-phase clouds are frequently observed in the atmosphere. Here we present a parameterization for ice crystal concentration and ice nucleation rate based on parcel model simulations for mixed-phase stratocumulus clouds, in complement to a previous parameterization for stratus clouds. The parcel model uses a singular (time-independent) description for deposition nucleation and a time-dependent description for condensation nucleation and immersion freezing on mineral dust particles. The mineral dust and temperature-dependent parameterizations have been implemented in the Geophysical Fluid Dynamics Laboratory atmosphere model AM4.0 (new), while the standard AM4.0 (original) uses a temperature-dependent parameterization. Model simulations with the new and original AM4.0 show significant changes in cloud properties and radiative effects. In comparison to measurements, cloud-phase (i.e., liquid and ice partitioning) simulation appears to be improved in the new AM4.0 model. More supercooled liquid cloud is predicted in the new model, it is sustained even at temperatures lower than -25 °C unlike in the original model. A more accurate accounting of ice nucleating particles and ice crystals is essential for improved cloud phase simulation in the global atmosphere.
We describe GFDL's CM4.0 physical climate model, with emphasis on those aspects that may be of particular importance to users of this model and its simulations. The model is built with the AM4.0/LM4.0 atmosphere/land model and OM4.0 ocean model. Topics include the rationale for key choices made in the model formulation, the stability as well as drift of the pre‐industrial control simulation, and comparison of key aspects of the historical simulations with observations from recent decades. Notable achievements include the relatively small biases in seasonal spatial patterns of top‐of‐atmosphere fluxes, surface temperature, and precipitation; reduced double Intertropical Convergence Zone bias; dramatically improved representation of ocean boundary currents; a high quality simulation of climatological Arctic sea ice extent and its recent decline; and excellent simulation of the El Niño‐Southern Oscillation spectrum and structure. Areas of concern include inadequate deep convection in the Nordic Seas; an inaccurate Antarctic sea ice simulation; precipitation and wind composites still affected by the equatorial cold tongue bias; muted variability in the Atlantic Meridional Overturning Circulation; strong 100 year quasi‐periodicity in Southern Ocean ventilation; and a lack of historical warming before 1990 and too rapid warming thereafter due to high climate sensitivity and strong aerosol forcing, in contrast to the observational record. Overall, CM4.0 scores very well in its fidelity against observations compared to the Coupled Model Intercomparison Project Phase 5 generation in terms of both mean state and modes of variability and should prove a valuable new addition for analysis across a broad array of applications.
Maloney, Eric, Andrew Gettelman, Yi Ming, J David Neelin, D Barrie, Annarita Mariotti, C-C Chen, D B Coleman, Yi-Hung Kuo, B Singh, H Annamalai, Alexis Berg, James F Booth, Suzana J Camargo, A Dai, A Gonzalez, J Hafner, Xianan Jiang, X Jing, D Kim, Arun Kumar, Yumin Moon, C M Naud, Adam H Sobel, K Suzuki, F Wang, J Wang, Allison A Wing, X Xu, and Ming Zhao, September 2019: Process-Oriented Evaluation of Climate and Weather Forecasting Models. Bulletin of the American Meteorological Society, 100(9), DOI:10.1175/BAMS-D-18-0042.1. Abstract
Outcomes of NOAA MAPP Model Diagnostics Task Force activities to promote process-oriented diagnosis of models to accelerate development are described.
Realistic climate and weather prediction models are necessary to produce confidence in projections of future climate over many decades and predictions for days to seasons. These models must be physically justified and validated for multiple weather and climate processes. A key opportunity to accelerate model improvement is greater incorporation of process-oriented diagnostics (PODs) into standard packages that can be applied during the model development process, allowing the application of diagnostics to be repeatable across multiple model versions and used as a benchmark for model improvement. A POD characterizes a specific physical process or emergent behavior that is related to the ability to simulate an observed phenomenon. This paper describes the outcomes of activities by the Model Diagnostics Task Force (MDTF) under the NOAA Climate Program Office (CPO) Modeling, Analysis, Predictions and Projections (MAPP) program to promote development of PODs and their application to climate and weather prediction models. MDTF and modeling center perspectives on the need for expanded process-oriented diagnosis of models are presented. Multiple PODs developed by the MDTF are summarized, and an open-source software framework developed by the MDTF to aid application of PODs to centers’ model development is presented in the context of other relevant community activities. The paper closes by discussing paths forward for the MDTF effort and for community process-oriented diagnosis.
The clouds in southern hemisphere extratropical cyclones generated by the GFDL climate model are analyzed against MODIS, CloudSat and CALIPSO cloud and precipitation observations. Two model versions are used: one is a developmental version of AM4, a model GFDL will utilize for CMIP6, the other is the same model with a different parameterization of moist convection. Both model versions predict a realistic top-of-atmosphere cloud cover in the southern oceans, within 5% of the observations. However, an examination of cloud cover transects in extratropical cyclones reveals a tendency in the models to overestimate high-level clouds (by differing amounts) and underestimate cloud cover at low-levels (again by differing amounts), especially in the post-cold frontal (PCF) region, when compared to observations. Focusing on only the models, their differences in high and mid-level clouds are consistent with their differences in convective activity and relative humidity (RH), but the same is not true for the PCF region. In this region, RH is higher in the model with less cloud fraction. These seemingly contradictory cloud and RH differences can be explained by differences in the cloud parameterization tuning parameters that ensure radiative balance. In the PCF region, the model cloud differences are smaller than either of the model biases with respect to observations, suggesting other physics changes are needed to address the bias. The process-oriented analysis used to assess these model differences will soon be automated and shared.
A central strategy in achieving greenhouse gas mitigation targets is the transition of vehicles from internal combustion engines to electric power. However, due to complex emission sources and nonlinear chemistry, it is unclear how such a shift might impact air quality. Here we apply a prototype version of the new-generation NOAA GFDL global Atmospheric Model, version 4 (GFDL AM4) to investigate the impact on U.S. air quality from an aggressive conversion of internal combustion vehicles to battery-powered electric vehicles (EVs). We examine a suite of scenarios designed to quantify the effect of both the magnitude of EV market penetration and the source of electricity generation used to power them. We find that summer surface ozone (O3) decreases in most locations due to widespread reductions of traffic NOx emissions. Summer fine particulate matter (PM2.5) increases on average and largest in areas with increased coal-fired power generation demands. Winter O3 increases due to reduced loss via traffic NOx while PM2.5 decreases since larger ammonium nitrate reductions offset increases in ammonium sulfate. The largest magnitude changes are simulated at the extremes of the probability distribution. Increasing the fraction of vehicles converted to EVs further decreases summer O3, while increasing the fraction of electricity generated by “emission-free” sources largely eliminates the increases in summer PM2.5 at high EV adoption fractions. Ultimately, the number of conventional vehicles replaced by EVs has a larger effect on O3 than PM2.5, while the source of the electricity for those EVs exhibit greater control on PM2.5.
Surface layer (SL) variables [e.g., 2‐m temperature (T2) and 10‐m wind (U10)] are diagnosed by applying the flux‐profile relationships based on Monin‐Obukhov similarity theory to the lowest model height (LMH). This assumes that the LMH is in the SL, which is approximately the bottom 10% of the boundary layer, but atmospheric general circulation models rarely satisfy this in stable boundary layers (SBLs). To assess errors in the diagnostic variables due to the LMH solely linked to the diagnostic algorithm, offline tests of the flux‐profile relationships are performed with LMH from a few meters to 60 m for three SBL regimes: weakly stable, very stable, and transition stability regimes. The results show that T2 and U10 are underestimated by O(0.1–1 °C) and O(0.1–1 m s−1), respectively, if the LMH is higher than the SL height. The stronger the SL stability is, the larger the temperature biases are. The negative wind biases increase with the surface stress. Based on these findings, we analyze the impacts of the LMH on the climatologies of the diagnostic parameters in the GFDL AM4.0/LM4.0. The results show reduced negative biases in T2 and U10 by lowering the LMH. The decrease of the overall bias over land is mainly due to the sensitivity of the diagnostic method to the LMH in SBLs, as shown in the offline tests. The overall increase in T2 and U10 over the oceans results from the increase in the actual near‐surface temperature and wind rather than from the diagnostic method.
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.
With a GFDL coupled model, the subseasonal prediction of wintertime (December‐February) surface air temperature (SAT) is investigated through the analysis of 11‐year hindcasts. Significant subseasonal week 3‐5 correlation skill exists over a large portion of the global land domain, and the predictability originates primarily from the eight most predictable SAT modes. The first three modes, identified as the El Niño‐Southern Oscillation mode, the North Atlantic Oscillation (NAO) mode, and the Eurasia Meridional Dipole (EMD) mode, can be skillfully predicted more than 5 weeks in advance. The NAO and EMD modes are strongly correlated with the initial stratospheric polar vortex strength, highlighting the role of stratosphere in subseasonal prediction. Interestingly, the Madden‐Julian Oscillation is not essential for the subseasonal land SAT prediction in the Northern Hemisphere extratropics. The spatial correlation skill exhibits considerable intraseasonal and interannual fluctuations, indicative of the importance to identify the time window of opportunity for subseasonal prediction.
Zhou, W, Ming Zhao, and Da Yang, June 2019: Understand the direct effect of CO2 increase on tropical circulation and TC activity: land surface warming versus direct radiative forcing. Geophysical Research Letters, 46(12), DOI:10.1029/2019GL082865. Abstract
The direct effect of increased CO2 involves contributions from both land warming and direct radiative forcing. Here, their relative impacts on tropical circulation and tropical cyclones (TCs) are quantified by increasing CO2 over land and ocean separately in a high‐resolution atmosphere‐only model. It is found that land warming induces substantial vertical velocity changes over nearby oceans and such local changes are compensated by opposite motions within tropical ascending regions. The cloud‐mask effect leads to smaller CO2‐induced radiative heating over ascending regions. Such inhomogeneity in radiative forcing dominates compensated changes in surface fluxes and gross moist stability, leading to the slowdown of the tropical overturning circulation. TC activity is tightly linked with the large‐scale ascent because of the influence on the atmospheric humidity. Regional circulation changes caused by land warming strongly suppresses TC activity over the northwest Pacific while weakened ascent from direct radiative forcing causes an overall TC reduction.
Zhu, Y, Tim Li, Ming Zhao, and Tomoe Nasuno, July 2019: Interaction between MJO and High Frequency Waves over Maritime Continent in Boreal Winter. Journal of Climate, 32(13), DOI:10.1175/JCLI-D-18-0511.1. Abstract
The two-way interaction between Madden Julian Oscillation (MJO) and higher frequency waves (HFW) over the Maritime Continent (MC) during boreal winter of 1984-2005 is investigated. It is noted from observational analysis that strengthenedv (weakened) HFW activity appears to the west (east) of and under MJO convection during MJO active phase and the opposite is seen during MJO suppressed phase. Sensitivity model experiments indicate that the control of HFW activity by MJO is through change of the background vertical wind shear and specific humidity.
The upscale feedbacks from HFW to MJO through nonlinear rectification of condensational heating and eddy momentum transport are also investigated with observational data. It is found a significantly large amount (25%-40%) of positive heating anomaly at low level to the east of MJO convection is contributed by nonlinear rectification of HFW. This nonlinear rectification is primarily attributed to eddy meridional moisture advection.
A momentum budget diagnosis reveals that 60% of MJO zonal wind tendency at 850 hPa is attributed to the nonlinear interaction of HFW with other scale flows. Among them, the largest contribution arises from eddy zonal momentum flux divergence . Easterly (westerly) vertical shear to the west (east) of MJO convection during MJO active phase causes the strengthening (weakening) of HFW zonal wind anomaly. This leads to the increase (decrease) of eddy momentum flux activity at east (west) of MJO convection, which causes a positive (negative) eddy zonal momentum flux divergence in the zonal wind transitional region during MJO active (suppressed) phase, favoring the eastward propagation of MJO.
How the globally uniform component of sea surface temperature (SST) warming influences rainfall in the African Sahel remains under-studied, despite mean SST warming being among the most robustly simulated and theoretically grounded features of anthropogenic climate change. A prior study using the NOAA Geophysical Fluid Dynamics Laboratory (GFDL) AM2.1 atmospheric general circulation model (AGCM) demonstrated that uniform SST warming strengthens the prevailing northerly advection of dry Saharan air into the Sahel. The present study uses uniform SST warming simulations performed with seven GFDL and ten CMIP5 AGCMs to assess the robustness of this drying mechanism across models and uses observations to assess the physical credibility of the severe drying response in AM2.1.
In all seventeen AGCMs, mean SST warming enhances the free-tropospheric meridional moisture gradient spanning the Sahel and with it the Saharan dry air advection. Energetically, this is partially balanced by anomalous subsidence, yielding decreased precipitation in fourteen of the seventeen models. Anomalous subsidence and precipitation are tightly linked across the GFDL models but not the CMIP5 models, precluding the use of this relationship as the start of a causal chain ending in an emergent observational constraint. For AM2.1, cloud-rainfall covariances generate radiative feedbacks on drying through the subsidence mechanism and through surface hydrology that are excessive compared to observations at the interannual timescale. These feedbacks also act in the equilibrium response to uniform warming, calling into question the Sahel’s severe drying response to warming in all coupled models using AM2.1.
Jiang, Xianan, A F Adames, Ming Zhao, D E Waliser, and Eric Maloney, June 2018: A Unified Moisture Mode Framework for Seasonality of the Madden-Julian Oscillation. Journal of Climate, 31(11), DOI:10.1175/JCLI-D-17-0671.1. Abstract
The Madden-Julian Oscillation (MJO) exhibits pronounced seasonality. While it is largely characterized by equatorially eastward propagation during the boreal winter, MJO convection undergoes marked poleward movement over the Asian monsoon region during summer, producing a significant modulation of monsoon rainfall. In classical MJO theories that seek to interpret the distinct seasonality in MJO propagation features, the role of equatorial wave dynamics has been emphasized for its eastward propagation, whereas coupling between MJO convection and the mean monsoon flow is considered essential for its northward propagation. In this study, a unified physical framework based on the moisture mode theory, is offered to explain the seasonality in MJO propagation. Moistening and drying due to horizontal advection of the lower-tropospheric mean moisture by MJO winds, which was recently found to be critical for the eastward propagation of the winter MJO, is also shown to play a dominant role in operating the northward propagation of the summer MJO. The seasonal variations in the mean moisture pattern largely shapes the distinct MJO propagation in different seasons. The critical role of the seasonally-varying climatological distribution of moisture for the MJO propagation is further supported by the close association between model skill in representing the MJO propagation and skill at producing the lower-tropospheric mean moisture pattern. This study thus pinpoints an important direction for climate model development for improved MJO representation during all seasons.
Motivated by increasing demand in the community for intraseasonal predictions of weather extremes, predictive skill of tropical cyclogenesis is investigated in this study based on a global coupled model system. Limited intraseasonal cyclogenesis prediction skill with a high false alarm rate is found when averaged over about 600 tropical cyclones (TCs) over global oceans from 2003 to 2013, particularly over the North Atlantic (NA). Relatively skillful genesis predictions with more than one-week lead time are only evident for about 10 percent of the total TCs. Further analyses suggest that TCs with relatively higher genesis skill are closely associated with the Madden-Julian Oscillation (MJO) and tropical synoptic waves, with their geneses strongly phase-locked to the convectively active region of the MJO and low-level cyclonic vorticity associated with synoptic-scale waves. Moreover, higher cyclogenesis prediction skill is found for TCs that formed during the enhanced periods of strong MJO episodes than those during weak or suppressed MJO periods. All these results confirm the critical role of the MJO and tropical synoptic waves for intraseasonal prediction of TC activity.
Tropical cyclogenesis prediction skill in this coupled model is found to be closely associated with model predictability of several large-scale dynamical and thermo-dynamical fields. Particularly over the NA, higher predictability of low-level relative vorticity, mid-level humidity, and vertical zonal wind shear are evident along a tropical belt from the West Africa coast to Caribbean Seas, in accord with more predictable cyclogenesis over this region. Over the extratropical NA, large-scale variables exhibit less predictability due to influences of extratropical systems, leading to poor cyclogenesis predictive skill.
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.
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.
Li, Weiwei, Z Wang, Gan Zhang, M S Peng, S G Benjamin, and Ming Zhao, December 2018: Subseasonal Variability of Rossby Wave Breaking and Impacts on Tropical Cyclones during the North Atlantic Warm Season. Journal of Climate, 31(23), DOI:10.1175/JCLI-D-17-0880.1. Abstract
This study investigates the subseasonal variability of anticyclonic Rossby wave breaking (AWB) and its impacts on atmospheric circulations and tropical cyclones (TCs) over the North Atlantic in the warm season from 1985 to 2013. Significant anomalies in sea level pressure, tropospheric wind and humidity fields are found over the tropical-subtropical Atlantic within 8 days of an AWB activity peak. Such anomalies may lead to suppressed TC activity on the subseasonal timescale, but a significant negative correlation between the subseasonal variability of AWB and Atlantic basin-wide TC activity does not exist every year, likely due to the modulation of TCs by other factors. It is also found that AWB occurrence may be modulated by the Madden-Julian Oscillation (MJO). In particular, AWB occurrence over the tropical-subtropical West Atlantic is reduced in phases 2 and 3 and enhanced in phases 6 and 7 based on the Real-time Multivariate MJO Index (RMM).
The impacts of AWB on the predictive skill of Atlantic TCs are examined using the Global Ensemble Forecasting System (GEFS) reforecasts with the forecast lead time up to 2 weeks. The hit rate of tropical cyclogenesis during active AWB episodes is lower than the long-term mean hit rate, and the GEFS is less skillful in capturing the variations of weekly TC activity during the years of enhanced AWB activity. The lower predictability of TCs is consistent with the lower predictability of environmental variables (such as vertical wind shear, moisture, and low-level vorticity) under the extratropical influence.
Northern India (23° N–31° N, 68° E–90° E) is one of the most densely populated and polluted regions in world. Accurately modeling pollution in the region is difficult due to the extreme conditions with respect to emissions, meteorology, and topography, but it is paramount in order to understand how future changes in emissions and climate may alter the region's pollution regime. We evaluate the ability of a developmental version of the new-generation NOAA GFDL Atmospheric Model, version 4 (AM4) to simulate observed wintertime fine particulate matter (PM2.5) and its relationship to meteorology over Northern India. We compare two simulations of GFDL-AM4 nudged to observed meteorology for the period 1980–2016 driven by pollutant emissions from two global inventories developed in support of the Coupled Model Intercomparison Project Phases 5 (CMIP5) and 6 (CMIP6), and compare results with ground-based observations from India's Central Pollution Control Board (CPCB) for the period 1 October 2015–31 March 2016. Overall, our results indicate that the simulation with CMIP6 emissions, produces improved concentrations of pollutants over the region relative to the CMIP5-driven simulation.
While the particulate concentrations simulated by AM4 are biased low overall, the model generally simulates the magnitude and daily variability of observed total PM2.5. Nitrate and organic matter are the primary components of PM2.5 over Northern India in the model. On the basis of correlations of the individual model components with total observed PM2.5 and correlations between the two simulations, meteorology is the primary driver of daily variability. The model correctly reproduces the shape and magnitude of the seasonal cycle of PM2.5, but the simulated diurnal cycle misses the early evening rise and secondary maximum found in the observations. Observed PM2.5 abundances are by far the highest within the densely populated Indo-Gangetic Plain, where they are closely related to boundary layer meteorology, specifically relative humidity, wind speed, boundary layer height, and inversion strength. The GFDL AM4 model reproduces the overall observed pollution gradient over Northern India as well as the strength of the meteorology-PM2.5 relationship in most locations.
This study describes the performance of two Geophysical Fluid Dynamics Laboratory (GFDL) atmospheric general circulation models (AGCMs) in simulating the climatologies of planetary boundary layer (PBL) parameters, with a particular focus on the diurnal cycles. The two models differ solely in the PBL parameterization: one uses a prescribed K-profile PBL (KPP) scheme with an entrainment parameterization, and the other employs a turbulence kinetic energy (TKE) scheme. The models are evaluated through the comparison to the reanalysis ensemble, which is generated from ERA-20C, ERA-Interim, NCEP-CFSR and NASA-MERRA, and the following systematic biases are identified. The models exhibit wide-spread cold biases in the high latitudes, and the biases are smaller when the KPP scheme is used. The diurnal cycle amplitudes are underestimated in most dry regions, and the model with the TKE scheme simulates larger amplitudes. For the near-surface winds, the models underestimate both the daily means and the diurnal amplitudes. The differences between the models are relatively small compared to the biases.
The role of the PBL schemes in simulating the PBL parameters is investigated through the analysis of vertical profiles. The Sahara, which is suitable for focusing on the role of vertical mixing in dry PBLs, is selected for a detailed analysis. It reveals that compared to the KPP scheme, the heat transport is weaker with the TKE scheme in both convective and stable PBLs due to weaker vertical mixing, resulting in larger diurnal amplitudes. Lack of non-local momentum transport from the nocturnal low-level jets to the surfaces appears to explain the underestimation of the near-surface winds in the models.
Silvers, Levi G., David J Paynter, and Ming Zhao, January 2018: The Diversity of Cloud Responses to Twentieth Century Sea Surface Temperatures. Geophysical Research Letters, 45(1), DOI:10.1002/2017GL075583. Abstract
Low-level clouds are shown to be the conduit between the observed sea surface temperatures (SST) and large decadal fluctuations of the top of the atmosphere (TOA) radiative imbalance. The influence of low-level clouds on the climate feedback is shown for global mean time series as well as particular geographic regions. The changes of clouds are found to be important for a mid-century period of high sensitivity and a late century period of low sensitivity. These conclusions are drawn from analysis of amip-piForcing simulations using three atmospheric general circulation models (AM2.1, AM3, and AM4.0). All three models confirm the importance of the relationship between the global climate sensitivity and the eastern Pacific trends of SST and low-level clouds. However, this work argues that the variability of the climate feedback parameter is not driven by stratocumulus dominated regions in the eastern ocean basins, but rather by the cloudy response in the rest of the tropics.
Xiang, Baoqiang, Ming Zhao, and Yi Ming, et al., July 2018: Contrasting Impacts of radiative forcing in the Southern Ocean versus Southern Tropics on ITCZ position and energy transport in one GFDL climate model. Journal of Climate, 31(14), DOI:10.1175/JCLI-D-17-0566.1. Abstract
Most current climate models suffer from pronounced cloud and radiation biases in the Southern Ocean (SO) and in the tropics. Using one GFDL climate model, this study investigates the migration of the Inter-tropical Convergence Zone (ITCZ) with prescribed Top of Atmosphere (TOA) shortwave radiative heating in the SO (50°S-80°S) versus the Southern Tropics (ST, 0-20°S). Results demonstrate that the ITCZ position response to the ST forcing is twice as strong as the SO forcing, which is primarily driven by the contrasting sea surface temperature (SST) gradient over the tropics; however, the mechanism for the formation of the SST pattern remains elusive.
Energy budget analysis reveals that the conventional energetic constraint framework is inadequate in explaining the ITCZ shift in these two perturbed experiments. For both cases, the anomalous Hadley circulation does not contribute to transport the imposed energy from the Southern Hemisphere to the Northern Hemisphere, given a positive mean gross moist stability in the equatorial region. Changes in the cross-equatorial atmospheric energy are primarily transported by atmospheric transient eddies when the anomalous ITCZ shift is most pronounced during December-May.
The partitioning of energy transport between the atmosphere and ocean shows latitudinal dependence: the atmosphere and ocean play an overall equivalent role in transporting the imposed energy for the extratropical SO forcing, while for the ST forcing, the imposed energy is nearly completely transported by the atmosphere. This contrast originates from the different ocean heat uptake and also the different meridional scale of the anomalous ocean circulation.
In this two-part paper, a description is provided of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). This version, with roughly 100km horizontal resolution and 33 levels in the vertical, contains an aerosol model that generates aerosol fields from emissions and a “light” chemistry mechanism designed to support the aerosol model but with prescribed ozone. In Part I, the quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode – with prescribed sea surface temperatures (SSTs) and sea ice distribution – is described and compared with previous GFDL models and with the CMIP5 archive of AMIP simulations. The model's Cess sensitivity (response in the top-of-atmosphere radiative flux to uniform warming of SSTs) and effective radiative forcing are also presented. In Part II, the model formulation is described more fully and key sensitivities to aspects of the model formulation are discussed, along with the approach to model tuning.
In Part II of this two-part paper, documentation is provided of key aspects of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). The quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode has been provided in Part I. Part II provides documentation of key components and some sensitivities to choices of model formulation and values of parameters, highlighting the convection parameterization and orographic gravity wave drag. The approach taken to tune the model's clouds to observations is a particular focal point. Care is taken to describe the extent to which aerosol effective forcing and Cess sensitivity have been tuned through the model development process, both of which are relevant to the ability of the model to simulate the evolution of temperatures over the last century when coupled to an ocean model.
Dogar, Muhammad M., Georgiy Stenchikov, Sergey Osipov, Bruce Wyman, and Ming Zhao, August 2017: Sensitivity of the Regional Climate in the Middle East and North Africa to Volcanic perturbations. Journal of Geophysical Research: Atmospheres, 122(15), DOI:10.1002/2017JD026783. Abstract
The Middle East and North Africa (MENA) regional climate appears to be extremely sensitive to volcanic eruptions. Winter cooling after the 1991 Pinatubo eruption far exceeded the mean hemispheric temperature anomaly, even causing snowfall in Israel. To better understand MENA climate variability, the climate responses to the El Chichón and Pinatubo volcanic eruptions are analyzed using observations, NOAA/NCEP Climate Forecast System Reanalysis, and output from the Geophysical Fluid Dynamics Laboratory's High-Resolution Atmospheric Model (HiRAM). A multiple regression analysis both for the observations and the model output is performed on seasonal summer and winter composites to separate out the contributions from climate trends, El Niño Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Indian summer monsoon and volcanic aerosols. Strong regional temperature and precipitation responses over the MENA region are found in both winter and summer. The model and the observations both show that a positive NAO amplifies the MENA volcanic winter cooling. In boreal summer, the patterns of changing temperature and precipitation suggest a weakening and southward shift of the Intertropical Convergence Zone, caused by volcanic surface cooling and weakening of the Indian and West African monsoons. The model captures the main features of the climate response; however, it underestimates the total cooling, especially in winter, and exhibits a different spatial pattern of the NAO climate response in MENA compared to the observations. The conducted analysis sheds light on the internal mechanisms of MENA climate variability and helps to selectively diagnose the model deficiencies.
The Tropical Cyclones (TC) that form over the warm waters in the Gulf of Mexico region pose a major threat to the surrounding coastal communities. Skillful sub-seasonal prediction of TC activity is important for early preparedness and reducing the TC damage in this region. In this study, we evaluate the performance of a 25-km resolution Geophysical Fluid Dynamics Laboratory (GFDL) High Resolution Atmospheric Model (HiRAM) in simulating the modulation of the TC activity in the Gulf of Mexico and western Caribbean Sea by the Intraseasonal Oscillation (ISO) based on multi-year retrospective seasonal predictions. We demonstrate that the HiRAM faithfully captures the observed influence of ISO on TC activity over the region of interest, including the formation of tropical storms and (major) hurricanes, as well as the landfalling storms. This is likely because of the realistic representation of the large-scale anomalies associated with boreal summer ISO over Northeast Pacific in HiRAM, especially the enhanced (reduced) moisture throughout the troposphere during the convectively enhanced (suppressed) phase of ISO. The reasonable performance of HiRAM suggests its potential for the subseasonal prediction of regional TC risk.
Climate models generate a wide range of precipitation responses to global warming in the African Sahel, but all that use the NOAA Geophysical Fluid Dynamics Laboratory AM2.1 model as their atmospheric component dry the region sharply. This study compares the Sahel’s wet season response to uniform 2 K SST warming in AM2.1 using either its default convective parameterization, Relaxed Arakawa-Schubert (RAS), or an alternate, the University of Washington (UW) parameterization, using the moist static energy (MSE) budget to diagnose the relevant mechanisms.
UW generates a drier, cooler control Sahel climate than does RAS and a modest rainfall increase with SST warming rather than a sharp decrease. Horizontal advection of dry, low-MSE air from the Sahara Desert – a leading-order term in the control MSE budget with either parameterization – is enhanced with oceanic warming, driven by enhanced meridional MSE and moisture gradients spanning the Sahel. With RAS, this occurs throughout the free troposphere and is balanced by anomalous MSE import through anomalous subsidence, which must be especially large in the mid-troposphere where the moist static stability is small. With UW, the strengthening of the meridional MSE gradient is mostly confined to the lower troposphere, due in part to comparatively shallow prevailing convection. This necessitates less subsidence, enabling convective and total precipitation to increase with UW, although both large-scale precipitation and precipitation minus evaporation decrease. This broad set of hydrological and energetic responses persists in simulations with SSTs varied over a wide range.
Nakamura, J, Suzana J Camargo, Adam H Sobel, N Henderson, Kerry A Emanuel, Arun Kumar, T LaRow, Hiroyuki Murakami, Malcolm J Roberts, E Scoccimarro, Pier Luigi Vidale, H Wang, Michael F Wehner, and Ming Zhao, September 2017: Western North Pacific tropical cyclone model tracks in present and future climates. Journal of Geophysical Research: Atmospheres, 122(18), DOI:10.1002/2017JD027007. Abstract
Western North Pacific tropical cyclone (TC) model tracks are analyzed in two large multi-model ensembles, spanning a large variety of models and multiple future climate scenarios. Two methodologies are used to synthesize the properties of TC tracks in this large dataset: cluster analysis and mass moments ellipses. First, the models' TC tracks are compared to observed TC tracks' characteristics and a subset of the models is chosen for analysis, based on the tracks' similarity to observations and sample size. Potential changes in track types in a warming climate are identified by comparing the kernel smoothed probability distributions of various track variables in historical and future scenarios using a Kolmogorov-Smirnov significance test. Two track changes are identified. The first is a statistically significant increase in the North-South expansion, which can also be viewed as a poleward shift, as TC tracks are prevented from expanding equatorward due to the weak Coriolis force near the Equator. The second change is an eastward shift in the storm tracks that occur near the central Pacific in one of the multi-model ensembles, indicating a possible increase in the occurrence of storms near Hawaii in a warming climate. The dependence of the results on which model and future scenario are considered emphasizes the necessity of including multiple models and scenarios when considering future changes in TC characteristics.
The severity of the double Intertropical Convergence Zone (DI) problem in climate models can be measured by a tropical precipitation asymmetry index (PAI), indicating whether tropical precipitation favors the Northern Hemisphere or the Southern Hemisphere. Examination of 19 Coupled Model Intercomparison Project phase 5 models reveals that the PAI is tightly linked to the tropical sea surface temperature (SST) bias. As one of the factors determining the SST bias, the asymmetry of tropical net surface heat flux in Atmospheric Model Intercomparison Project (AMIP) simulations is identified as a skillful predictor of the PAI change from an AMIP to a coupled simulation, with an intermodel correlation of 0.90. Using tropical top-of-atmosphere (TOA) fluxes, the correlations are lower but still strong. However, the extratropical asymmetries of surface and TOA fluxes in AMIP simulations cannot serve as useful predictors of the PAI change. This study suggests that the largest source of the DI bias is from the tropics and from atmospheric models.
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.
Jiang, Xianan, and Ming Zhao, et al., October 2016: Convective Moisture Adjustment Time-scale as a Key Factor in Regulating Model Amplitude of the Madden-Julian Oscillation. Geophysical Research Letters, 43(19), DOI:10.1002/2016GL070898. Abstract
Despite its pronounced impacts on weather extremes worldwide, the Madden-Julian Oscillation (MJO) remains poorly represented in climate models. Here, we present findings that point to some necessary ingredients to produce a strong MJO amplitude in a large set of model simulations from a recent model inter-comparison project. While surface flux and radiative heating anomalies are considered important for amplifying the MJO, their strength per unit MJO precipitation anomaly is found to be negatively correlated to MJO amplitude across these multi-model simulations. However, model MJO amplitude is found to be closely tied to a model's convective moisture adjustment time-scale, a measure of how rapidly precipitation must increase to remove excess column water vapor, or alternately the efficiency of surface precipitation generation per unit column water vapor anomaly. These findings provide critical insights into key model processes for the MJO, and pinpoint a direction for improved model representation of the MJO.
Uncertainty in cumulus convection parameterization is one of the most important causes of model climate drift through interactions between large-scale background and local convection that has empirically-set parameters. Without addressing the large-scale feedback, the calibrated parameter values within a convection scheme are usually not optimal for a climate model. This study first designs a multiple-column atmospheric model which includes large-scale feedbacks for cumulus convection, and then explores the role of large-scale feedbacks in cumulus convection parameter estimation using an ensemble filter. The performance of convection parameter estimation with or without the presence of large-scale feedback is examined. It is found that including large-scale feedbacks in cumulus convection parameter estimation can significantly improve the estimation quality. This is because large-scale feedbacks help transform local convection uncertainties into global climate sensitivities, and including these feedbacks enhances the statistical representation of the relationship between parameters and state variables. The results of this study provide insights for further understanding of climate drift induced from imperfect cumulus convection parameterization, which may help improve climate modeling.
Tropical cyclone (TC)-permitting general circulation model simulations are performed with spherical geometry and uniform thermal forcing, including uniform sea surface temperature (SST) and insolation. The dependence of the TC number and TC intensity on SST is examined in a series of simulations with varied SST. The results are compared to corresponding simulations with doubly periodic f-plane geometry, rotating radiative convective equilibrium. The turbulent equilibria in simulations with spherical geometry have an inhomogenous distribution of TCs with the density of TCs increasing from low-to-high latitudes. The preferred region of TC genesis is the subtropics, but genesis shifts poleward and becomes less frequent with increasing SST. Both rotating radiative convective equilibrium and spherical geometry simulations have decreasing TC number and increasing TC intensity as SST is increased.
Strazzo, S E., J B Elsner, T LaRow, Hiroyuki Murakami, Michael F Wehner, and Ming Zhao, September 2016: The influence of model resolution on the simulated sensitivity of North Atlantic tropical cyclone maximum intensity to sea surface temperature. Journal of Advances in Modeling Earth Systems, 8(3), DOI:10.1002/2016MS000635. Abstract
Global climate models (GCMs) are routinely relied upon to study the possible impacts of climate change on a wide range of meteorological phenomena, including tropical cyclones (TCs). Previous studies addressed whether GCMs are capable of reproducing observed TC frequency and intensity distributions. This research builds upon earlier studies by examining how well GCMs capture the physically relevant relationship between TC intensity and SST. Specifically, the influence of model resolution on the ability of a GCM to reproduce the sensitivity of simulated TC intensity to SST is examined for the MRI-AGCM (20 km), the GFDL-HiRAM (50 km), the FSU-COAPS (0.94°) model, and two versions of the CAM5 (1° and 0.25°). Results indicate that while a 1° C increase in SST corresponds to a 5.5 – 7.0 m s– 1 increase in observed maximum intensity, the same 1° C increase in SST is not associated with a statistically significant increase in simulated TC maximum intensity for any of the models examined. However, it also is shown that the GCMs all capably reproduce the observed sensitivity of potential intensity to SST. The models generate the thermodynamic environment suitable for the development of strong TCs over the correct portions of the North Atlantic basin, but strong simulated TCs do not develop over these areas, even for models that permit Category 5 TCs. This result supports the notion that direct simulation of TC eyewall convection is necessary to accurately represent TC intensity and intensification processes in climate models, although additional explanations are also explored.
Uncertainty in equilibrium climate sensitivity impedes accurate climate projections. While the inter-model spread is known to arise primarily from differences in cloud feedback, the exact processes responsible for the spread remain unclear. To help identify some key sources of uncertainty, we use a developmental version of the next generation Geophysical Fluid Dynamics Laboratory global climate model (GCM) to construct a tightly controlled set of GCMs where only the formulation of convective precipitation is changed. The different models provide simulation of present-day climatology of comparable quality compared to the CMIP5 model ensemble. We demonstrate that model estimates of climate sensitivity can be strongly affected by the manner through which cumulus cloud condensate is converted into precipitation in a model’s convection parameterization, processes that are only crudely accounted for in GCMs. In particular, two commonly used methods for converting cumulus condensate into precipitation can lead to drastically different climate sensitivity, as estimated here with an atmosphere/land model by increasing sea surface temperatures uniformly and examining the response in the top-of-atmosphere energy balance. The effect can be quantified through a bulk convective detrainment efficiency, which measures the ability of cumulus convection to generate condensate per unit precipitation. The model differences, dominated by shortwave feedbacks, come from broad regimes ranging from large-scale ascent to subsidence regions. Given current uncertainties in representing convective precipitation microphysics and our current inability to find a clear observational constraint that favors one version of our model over the others, the implications of this ability to engineer climate sensitivity needs to be considered when estimating the uncertainty in climate projections.
The sensitivity of global tropical cyclone (TC) activity to changes in a zonally-symmetric sea surface temperature (SST) distribution and the associated large-scale atmospheric circulation are investigated. High-resolution (~50-km horizontal grid spacing) atmospheric general circulation model simulations with maximum SST away from the equator are presented. Simulations with both fixed SST and slab ocean lower boundary conditions are compared.
The simulated TCs that form on the poleward flank of the Intertropical Convergence Zone (ITCZ) are tracked and changes in the frequency and intensity of those storms are analyzed between the different experiments. The total accumulated cyclone energy (ACE) increases as the location of the maximum SST shifts further away from the equator. The location of the ITCZ also shifts in conjunction with changes to the SST profile, and this plays an important role in mediating the frequency and intensity of the TCs that form within this modeling framework.
Daloz, A S., Suzana J Camargo, James Kossin, Kerry A Emanuel, M Horn, J A Jonas, D Kim, T LaRow, Y-K Kim, Christina M Patricola, Malcolm J Roberts, E Scoccimarro, D Shaevitz, Pier Luigi Vidale, H Wang, Michael F Wehner, and Ming Zhao, February 2015: Cluster analysis of downscaled and explicitly simulated North Atlantic tropical cyclone tracks. Journal of Climate, 28(4), DOI:10.1175/JCLI-D-13-00646.1. Abstract
A realistic representation of the North Atlantic tropical cyclone tracks is crucial as it allows, for example, explaining potential changes in US landfalling systems. Here we present a tentative study, which examines the ability of recent climate models to represent North Atlantic tropical cyclone tracks. Tracks from two types of climate models are evaluated: explicit tracks are obtained from tropical cyclones simulated in regional or global climate models with moderate to high horizontal resolution (1° to 0.25°), and downscaled tracks are obtained using a downscaling technique with large-scale environmental fields from a subset of these models. For both configurations, tracks are objectively separated into four groups using a cluster technique, leading to a zonal and a meridional separation of the tracks. The meridional separation largely captures the separation between deep tropical and sub-tropical, hybrid or baroclinic cyclones, while the zonal separation segregates Gulf of Mexico and Cape Verde storms. The properties of the tracks’ seasonality, intensity and power dissipation index in each cluster are documented for both configurations. Our results show that except for the seasonality, the downscaled tracks better capture the observed characteristics of the clusters. We also use three different idealized scenarios to examine the possible future changes of tropical cyclone tracks under 1) warming sea surface temperature, 2) increasing carbon dioxide, and 3) a combination of the two. The response to each scenario is highly variable depending on the simulation considered. Finally, we examine the role of each cluster in these future changes and find no preponderant contribution of any single cluster over the others.
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.
CLUBB (Cloud Layers Unified by Binormals) is a higher-order closure (HOC) method with an assumed joint probability density function (PDF) for the subgrid variations in vertical velocity, temperature, and moisture. CLUBB has been implemented in the GFDL climate model AM3-CLUBB and successfully unifies the treatment of shallow convection, resolved clouds, and planetary boundary layer (PBL). In this study, we further explore the possibility for CLUBB to unify the deep convection in a new configuration referred as AM3-CLUBB+. AM3-CLUBB+ simulations with prescribed sea surface temperature are discussed. Cloud, radiation, and precipitation fields compare favorably with observations and reanalyses. AM3-CLUBB+ successfully captures the transition from stratocumulus to deep convection and the modulated response of liquid water path to aerosols. Simulations of tropical variability and the Madden-Julian oscillation (MJO) are also improved. Deficiencies include excessive tropical water vapor and insufficient ice clouds in the mid-latitudes.
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.
Lin, Yanluan, Ming Zhao, and M Zhang, March 2015: Tropical cyclone rainfall area controlled by relative sea surface temperature. Nature Communications, 6, 6591, DOI:10.1038/ncomms7591. Abstract
Tropical cyclone rainfall rates have been projected to increase in a warmer climate. The area
coverage of tropical cyclones influences their impact on human lives, yet little is known about
how tropical cyclone rainfall area will change in the future. Here, using satellite data and
global atmospheric model simulations, we show that tropical cyclone rainfall area is controlled
primarily by its environmental sea surface temperature (SST) relative to the tropical
mean SST (that is, the relative SST), while rainfall rate increases with increasing absolute SST.
Our result is consistent with previous numerical simulations that indicated tight relationships
between tropical cyclone size and mid-tropospheric relative humidity. Global statistics of
tropical cyclone rainfall area are not expected to change markedly under a warmer climate
provided that SST change is relatively uniform, implying that increases in total rainfall will be
confined to similar size domains with higher rainfall rates.
Mei, W, Shang-Ping Xie, Ming Zhao, and Yan Wang, January 2015: Forced and internal variability of tropical cyclone track density in the western North Pacific. Journal of Climate, 28(1), DOI:10.1175/JCLI-D-14-00164.1. Abstract
Forced interannual-to-decadal variability of annual tropical cyclone (TC) track density in the western North Pacific between 1979-2008 is studied using TC tracks from observations and simulations by a 25-km-resolution version of the GFDL High-Resolution Atmospheric Model (HiRAM) that is forced by observed sea surface temperatures (SSTs). Two modes dominate the decadal variability: a nearly-basin-wide mode, and a dipole mode between the subtropics and lower latitudes. The former mode links to variations in TC number and is forced by SST variations over the off-equatorial tropical central North Pacific, whereas the latter might be associated with the Atlantic Multidecadal Oscillation. The interannual variability is also controlled by two modes: a basin-wide mode driven by SST anomalies of opposite signs located respectively in the tropical central Pacific and eastern Indian Ocean, and a southeast-northwest dipole mode connected to the conventional eastern Pacific ENSO. The seasonal evolution of the ENSO effect on TC activity is further explored via a joint EOF analysis using TC track density of consecutive seasons, and the analysis reveals that two types of ENSO are at work.
Internal variability in TC track density is then examined using ensemble simulations from both HiRAM and a regional atmospheric model. It exhibits prominent spatial and seasonal patterns, and it is particularly strong in the South China Sea and along the coast of East Asia. This makes an accurate prediction and projection of TC landfall extremely challenging in these regions. In contrast, basin-integrated metrics (e.g., total TC counts and TC days) are more predictable.
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.
Webb, M J., A P Lock, Christopher S Bretherton, Sandrine Bony, Jason N S Cole, A Idelkadi, Sarah M Kang, T Koshiro, H Kawai, T Ogura, Romain Roehrig, Yechul Shin, T Mauritsen, S C Sherwood, J Vial, M Watanabe, M D Woelfle, and Ming Zhao, October 2015: The impact of parametrized convection on cloud feedback. Philosophical Transactions of the Royal Society of London, A, 373, DOI:10.1098/rsta.2014.0414. Abstract
We investigate the sensitivity of cloud feedbacks to the use of convective parametrizations by repeating the CMIP5/CFMIP-2 AMIP/AMIP + 4K uniform sea surface temperature perturbation experiments with 10 climate models which have had their convective parametrizations turned off. Previous studies have suggested that differences between parametrized convection schemes are a leading source of inter-model spread in cloud feedbacks. We find however that ‘ConvOff’ models with convection switched off have a similar overall range of cloud feedbacks compared with the standard configurations. Furthermore, applying a simple bias correction method to allow for differences in present-day global cloud radiative effects substantially reduces the differences between the cloud feedbacks with and without parametrized convection in the individual models. We conclude that, while parametrized convection influences the strength of the cloud feedbacks substantially in some models, other processes must also contribute substantially to the overall inter-model spread. The positive shortwave cloud feedbacks seen in the models in subtropical regimes associated with shallow clouds are still present in the ConvOff experiments. Inter-model spread in shortwave cloud feedback increases slightly in regimes associated with trade cumulus in the ConvOff experiments but is quite similar in the most stable subtropical regimes associated with stratocumulus clouds. Inter-model spread in longwave cloud feedbacks in strongly precipitating regions of the tropics is substantially reduced in the ConvOff experiments however, indicating a considerable local contribution from differences in the details of convective parametrizations. In both standard and ConvOff experiments, models with less mid-level cloud and less moist static energy near the top of the boundary layer tend to have more positive tropical cloud feedbacks. The role of non-convective processes in contributing to inter-model spread in cloud feedback is discussed.
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.
This study examines two sets of high-resolution coupled model forecasts starting from no-tropical cyclone (TC) and correct-TC-statistics initial conditions to understand the role of TC events on climate prediction. While the model with no-TC initial conditions can quickly spin up TCs within a week, the initial conditions with a corrected TC distribution can produce more accurate forecast of sea surface temperature up to one and half months and maintain larger ocean heat content up to 6 months due to enhanced mixing from continuous interactions between initialized and forecasted TCs and the evolving ocean states. The TC-enhanced tropical ocean mixing strengthens the meridional heat transport in the Southern Hemisphere driven primarily by Southern Ocean surface Ekman fluxes but weakens the Northern Hemisphere poleward transport in this model. This study suggests a future plausible initialization procedure for seamless weather-climate prediction when individual convection-permitting cyclone initialization is incorporated into this TC-statistics-permitting framework.
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.
Flannaghan, Thomas J., Stephan Fueglistaler, Isaac M Held, S Po-Chedley, Bruce Wyman, and Ming Zhao, December 2014: Tropical temperature trends in Atmospheric General Circulation Model simulations and the impact of uncertainties in observed SSTs. Journal of Geophysical Research: Atmospheres, 119(23), DOI:10.1002/2014JD022365. Abstract
The comparison of trends in various climate indices in observations and models is of fundamental importance for judging the credibility of climate projections. Tropical tropospheric temperature trends have attracted particular attention as this comparison may suggest a model deficiency [Santer et al., 2005; Christy et al., 2007, 2010; Fu et al., 2011; Thorne et al., 2011]. One can think of this problem as composed of two parts: one focused on tropical surface temperature trends and the associated issues related to forcing, feedbacks, and ocean heat uptake; and a second part focusing on connections between surface and tropospheric temperatures and the vertical profile of trends in temperature. Here, we focus on the atmospheric component of the problem. We show that two ensembles of GFDL HiRAM model runs (similar results are shown for NCAR's CAM4 model) with different commonly used prescribed sea surface temperatures (SSTs), namely the HadISST1 and ‘Hurrell’ data sets, have a difference in upper tropical tropospheric temperature trends (~0.1 K/decade at 300 hPa for the period 1984-2008) that is about a factor 3 larger than expected from moist adiabatic scaling of the tropical average SST trend difference. We show that this surprisingly large discrepancy in temperature trends is a consequence of SST trend differences being largest in regions of deep convection. Further, trends, and the degree of agreement with observations, not only depend on SST data set and the particular atmospheric temperature data set, but also on the period chosen for comparison. Due to the large impact on atmospheric temperatures, these systematic uncertainties in SSTs need to be resolved before the fidelity of climate models’ tropical temperature trend profiles can be assessed.
Horn, M, Kevin J E Walsh, Ming Zhao, Suzana J Camargo, E Scoccimarro, Hiroyuki Murakami, H Wang, and Andrew Ballinger, et al., December 2014: Tracking Scheme Dependence of Simulated Tropical Cyclone Response to Idealized Climate Simulations. Journal of Climate, 27(24), DOI:10.1175/JCLI-D-14-00200.1. Abstract
Future tropical cyclone activity is a topic of great scientific and societal interest. In the absence of a climate theory of tropical cyclogenesis, general circulation models are the primary tool available for investigating the issue. However, the identification of tropical cyclones in model data at moderate resolution is complex, and numerous schemes have been developed for their detection.
We here examine the influence of different tracking schemes on detected tropical cyclone activity and responses in the Hurricane Working Group experiments. These are idealized atmospheric general circulation model experiments aimed at determining and distinguishing the effects of increased sea-surface temperature and other increased CO2 effects on tropical cyclone activity. We apply two tracking schemes to these data and also analyze the tracks provided by each modelling group.
Our results indicate moderate agreement between the different tracking methods, with some models and experiments showing better agreement across schemes than others. When comparing responses between experiments, we find that much of the disagreement between schemes is due to differences in duration, wind speed, and formation-latitude thresholds. After homogenisation in these thresholds, agreement between different tracking methods is improved. However, much disagreement remains, accountable for by more fundamental differences between the tracking schemes. Our results indicate that sensitivity testing and selection of objective thresholds are the key factors in obtaining meaningful, reproducible results when tracking tropical cyclones in climate model data at these resolutions, but that more fundamental differences between tracking methods can also have a significant impact on the responses in activity detected.
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.
In this extended abstract, we report on progress in two areas of research at GFDL relating to Indian Ocean regional climate and climate change. The first topic is an assessment of regional surface temperature trends in the Indian Ocean and surrounding region. Here we illustrate the use of a multi-model approach (CMIP3 or CMIP5 model ensembles) to assess whether an anthropogenic warming signal has emerged in the historical data, including identification of where the observed trends are consistent or not with current climate models. Trends that are consistent with All Forcing runs but inconsistent with Natural Forcing Only runs are ones which we can attribute, at least in part, to anthropogenic forcing.
Maloney, Eric, Suzana J Camargo, E K M Chang, B A Colle, R Fu, K L Geil, Qi Hu, Xianan Jiang, Nathaniel C Johnson, K B Karnauskas, J L Kinter, Ben P Kirtman, Sanjiv Kumar, B Langenbrunner, K Lombardo, L Long, Annarita Mariotti, J E Meyerson, K Mo, J David Neelin, Zaitao Pan, Richard Seager, Yolande L Serra, A Seth, Justin Sheffield, Julienne Stroeve, J Thibeault, Shang-Ping Xie, Chunzai Wang, Bruce Wyman, and Ming Zhao, March 2014: North American Climate in CMIP5 Experiments: Part III: Assessment of 21st Century Projections. Journal of Climate, 27(6), DOI:10.1175/JCLI-D-13-00273.1. Abstract
In Part 3 of a three-part study on North American climate in Coupled Model Intercomparison project (CMIP5) models, we examine projections of 21st century climate in the RCP8.5 emission experiments. This paper summarizes and synthesizes results from several coordinated studies by the authors. Aspects of North American climate change that are examined include changes in continental-scale temperature and the hydrologic cycle, extremes events, and storm tracks, as well as regional manifestations of these climate variables. We also examine changes in eastern north Pacific and north Atlantic tropical cyclone activity and North American intraseasonal to decadal variability, including changes in teleconnections to other regions of the globe.
Projected changes are generally consistent with those previously published for CMIP3, although CMIP5 model projections differ importantly from those of CMIP3 in some aspects, including CMIP5 model agreement on increased central California precipitation. The paper also highlights uncertainties and limitations based on current results as priorities for further research. Although many projected changes in North American climate are consistent across CMIP5 models, substantial intermodel disagreement exists in other aspects. Areas of disagreement include projections of changes in snow water equivalent on a regional basis, summer Arctic sea ice extent, the magnitude and sign of regional precipitation changes, extreme heat events across the Northern U.S., and Atlantic and east Pacific tropical cyclone activity.
Mei, W, Shang-Ping Xie, and Ming Zhao, July 2014: Variability of Tropical Cyclone Track Density in the North Atlantic: Observations and High-Resolution Simulations. Journal of Climate, 27(13), DOI:10.1175/JCLI-D-13-00587.1. Abstract
nterannual-decadal variability of tropical cyclone (TC) track density over the North Atlantic (NA) between 1979 and 2008 is studied using observations and simulations with a 25-km-resolution version of the High Resolution Atmospheric Model (HiRAM) forced by observed sea surface temperatures (SSTs). The variability on decadal and interannual timescales is examined separately. On both timescales, a basin-wide mode dominates with the time series related to the seasonal TC counts. On decadal timescales, this mode relates to SST contrasts between the tropical NA and the tropical Northeast Pacific as well as the tropical South Atlantic, whereas on interannual timescales it is controlled by SSTs over the central-eastern equatorial Pacific and those over the tropical NA.
The temporal evolution of the spatial distribution of track density is further investigated by normalizing the track density with the seasonal TC counts. On decadal timescales, two modes emerge: One is an oscillation between the track density over the US East Coast and mid-latitude ocean and that over Gulf of Mexico and Caribbean Sea; the other oscillates between low and middle latitudes. They might be driven respectively by the preceding winter North Atlantic Oscillation and concurrent Atlantic Meridional Mode. On interannual timescales, two similar modes are presented in observations but are not well separated in HiRAM simulations.
Finally, the internal variability and predictability of the TC track density are explored and discussed using HiRAM ensemble simulations. The results suggest that the basin-wide total TC counts/days are much more predictable than the local TC occurrence, posing a serious challenge to the prediction and projection of regional TC threats, especially the U.S. landfall hurricanes.
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.
Shaevitz, D, Suzana J Camargo, Adam H Sobel, J A Jonas, D Kim, Arun Kumar, T LaRow, Y-K Lim, Hiroyuki Murakami, Kevin A Reed, Malcolm J Roberts, E Scoccimarro, Pier Luigi Vidale, H Wang, Michael F Wehner, Ming Zhao, and N Henderson, December 2014: Characteristics of tropical cyclones in high-resolution models in the present climate. Journal of Advances in Modeling Earth Systems, 6(4), DOI:10.1002/2014MS000372. Abstract
The global characteristics of tropical cyclones (TCs) simulated by several climate models are analyzed and compared with observations. The global climate models were forced by the same sea surface temperature (SST) fields in two types of experiments, using climatological SST and interannually varying SST. TC tracks and intensities are derived from each model's output fields by the group who ran that model, using their own preferred tracking scheme; the study considers the combination of model and tracking scheme as a single modeling system, and compares the properties derived from the different systems. Overall, the observed geographic distribution of global TC frequency was reasonably well reproduced. As expected, with the exception of one model, intensities of the simulated TC were lower than in observations, to a degree that varies considerably across models.
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.
Xiang, Baoqiang, Bin Wang, J Li, Ming Zhao, and June-Yi Lee, November 2014: Understanding the anthropogenically forced change of equatorial Pacific trade winds in coupled climate models. Journal of Climate, 27(22), DOI:10.1175/JCLI-D-14-00115.1. Abstract
Understanding the change of equatorial Pacific trade winds is pivotal for understanding the global mean temperature change and the El Nino/Southern Oscillation (ENSO) property change. The weakening of Walker circulation due to anthropogenic greenhouse gas (GHG) forcing was suggested as one of the most robust phenomena in current climate models by examining zonal sea level pressure gradient over the tropical Pacific. This study explores another component of the Walker circulation change focusing on equatorial Pacific trade wind change. Model sensitivity experiments demonstrate that the direct/fast response due to GHG forcing is to increase the trade winds especially over the equatorial central-western Pacific (ECWP, 5°S-5°N, 140°E-150°W), while the indirect/slow response associated with sea surface temperature (SST) warming weakens the trade winds.
Further, analysis of the results from 19 models in CMIP5 (Coupled Model Intercomparison Project Phase 5) and POP-OASIS-ECHAM model (POEM) shows that the projected weakening of trades is robust only in the equatorial eastern Pacific (EEP, 5°S-5°N, 150°W-80°W), but highly uncertain over the ECWP with 9 out of 19 CMIP5 models producing intensified trades. The prominent and robust weakening of EEP trades is suggested to be mainly driven a top-down mechanism: the mean vertical advection of more upper-tropospheric warming downward to generate a cyclonic circulation anomaly in the south-east tropical Pacific. In the ECWP, the large inter-model spread is primarily linked to the models’ diversity in simulating the relative warming of the equatorial Pacific versus the tropical mean sea surface temperature. The possible root causes of the uncertainty for the trade wind change are also discussed.
When observations are assimilated into a high-resolution coupled model, a traditional scheme that preferably projects observations to correct large scale background tends to filter out small scale cyclones. Here we separately process the large scale background and small scale perturbations with low-resolution observations for reconstructing historical cyclone statistics in a cyclone-permitting model. We show that by maintaining the interactions between small scale perturbations and successively-corrected large scale background, a model can successfully retrieve the observed cyclone statistics that in return improve estimated ocean states. The improved ocean initial conditions together with the continuous interactions of cyclones and background flows are expected to reduce model forecast errors. Combined with convection-permitting cyclone initialization, the new high-resolution model initialization along with the progressively-advanced coupled models should contribute significantly to the ongoing research on seamless weather-climate predictions.
Zhao, Ming, March 2014: An Investigation of the Connections among Convection, Clouds, and Climate Sensitivity in a Global Climate Model. Journal of Climate, 27(5), DOI:10.1175/JCLI-D-13-00145.1. Abstract
This study explores connections between process-level modeling of convection and GCM (global climate model) simulated clouds and cloud feedback to global warming through a set of perturbed-physics and perturbed-sea-surface-temperature experiments. A bulk diagnostic approach is constructed and a set of variables is derived and demonstrated to be useful in understanding the simulated relationship. In particular, a novel bulk quantity, the convective precipitation efficiency or equivalently the convective detrainment efficiency, is proposed as a simple measure of the aggregated properties of parameterized convection important to our GCM simulated clouds. As the convective precipitation efficiency increases in the perturbed-physics experiments, both liquid and ice water path decrease, with low and middle cloud fractions diminishing at a faster rate than high cloud fractions. This asymmetry results in a large sensitivity of top-of-atmosphere net cloud radiative forcing to changes in convective precipitation efficiency in this limited set of models.
For global warming experiments, intermodel variations in the response of cloud condensate, low cloud fraction, and total cloud radiative forcing are well explained by model variations in response of total precipitation (or detrainment) efficiency. Despite significant variability, all the perturbed-physics models produce a sizable increase in precipitation efficiency to warming. A substantial fraction of the increase is due to its convective component which depends on the parameterization of cumulus mixing and convective microphysics processes. The increase in convective precipitation efficiency and associated change in convective cloud height distribution to warming explains the increased cloud feedback and climate sensitivity in recently developed Geophysical Fluid Dynamics Laboratory GCMs. The results imply that a cumulus scheme using fractional removal of condensate for precipitation and inverse calculation of entrainment rate tends to produce a lower climate sensitivity than a scheme using threshold removal for precipitation and entrainment rate formulated inversely dependent on convective depth.
Blackburn, M, Ming Zhao, and Isaac M Held, et al., October 2013: The Aqua Planet Experiment (APE): CONTROL SST Simulation. Journal of the Meteorological Society of Japan, 91A, DOI:10.2151/jmsj.2013-A02. Abstract
Climate simulations by 16 atmospheric general circulation models (AGCMs) are compared on an aqua-planet, a water-covered Earth with prescribed sea surface temperature varying only in latitude. The idealised configuration is designed to expose differences in the circulation simulated by different models. Basic features of the aqua-planet climate are characterised by comparison with Earth.
The models display a wide range of behaviour. The balanced component of the tropospheric mean flow, and mid-latitude eddy covariances subject to budget constraints, vary relatively little among the models. In contrast, differences in damping in the dynamical core strongly influence transient eddy amplitudes. Historical uncertainty in modelled lower stratospheric temperatures persists in APE.
Aspects of the circulation generated more directly by interactions between the resolved fluid dynamics and parameterized moist processes vary greatly. The tropical Hadley circulation forms either a single or double inter-tropical convergence zone (ITCZ) at the equator, with large variations in mean precipitation. The equatorial wave spectrum shows a wide range of precipitation intensity and propagation characteristics. Kelvin mode-like eastward propagation with remarkably constant phase speed dominates in most models. Westward propagation, less dispersive than the equatorial Rossby modes, dominates in a few models or occurs within an eastward propagating envelope in others. The mean structure of the ITCZ is related to precipitation variability, consistent with previous studies.
The aqua-planet global energy balance is unknown but the models produce a surprisingly large range of top of atmosphere global net flux, dominated by differences in shortwave reflection by clouds. A number of newly developed models, not optimised for Earth climate, contribute to this. Possible reasons for differences in the optimised models are discussed.
The aqua-planet configuration is intended as one component of an experimental hierarchy used to evaluate AGCMs. This comparison does suggest that the range of model behaviour could be better understood and reduced in conjunction with Earth climate simulations. Controlled experimentation is required to explore individual model behaviour and investigate convergence of the aqua-planet climate with increasing resolution.
Elsner, J B., S E Strazzo, T H Jagger, T LaRow, and Ming Zhao, August 2013: Sensitivity of limiting hurricane intensity to SST in the Atlantic from observations and GCMs. Journal of Climate, 26(16), DOI:10.1175/JCLI-D-12-00433.1. Abstract
A statistical model for the intensity of the strongest hurricanes has been developed and a new methodology introduced for estimating the sensitivity of the strongest hurricanes to changes in sea-surface temperature. Here we use this methodology on observed hurricanes and hurricanes generated from two global climate models (GCMs). Hurricanes over the North Atlantic during the period 1981–2010 show a sensitivity of 7.9 ± 1.19 m s−1 K−1 (standard error) when over seas warmer than 25°C. In contrast, hurricanes over the same region and period generated from the GFDL HiRAM show a significantly lower sensitivity with the highest at 1.8 ± 0.42 m s−1 K−1 (s.e.). Similar weaker sensitivity is found using hurricanes generated from the FSU COAPS model with the highest at 2.9 ± 2.64 m s−1 K−1 (s.e.). A statistical refinement of HiRAM-generated hurricane intensities heightens the sensitivity to a maximum of 6.9 ± 3.33 m s−1 K−1 (s.e.), but the increase is offset by additional uncertainty associated with the refinement. Results suggest that the caution that should be exercised when interpreting GCM scenarios of future hurricane intensity stems from the low sensitivity of limiting GCM-generated hurricane intensity to ocean temperature.
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.
A set of GFDL AM2 sensitivity simulations by varying an entrainment threshold rate to control deep convection occurrence are used to investigate how cumulus parameterization impacts tropical cloud and precipitation characteristics. In the Tropics, model convective precipitation (CP) is frequent and light, while large-scale precipitation (LSP) is intermittent and strong. With deep convection inhibited, CP decreases significantly over land and LSP increases prominently over ocean. This results in an overall redistribution of precipitation from land to ocean. A composite analysis reveals that cloud fraction (low and middle) and cloud condensate associated with LSP is substantially larger than those associated with CP. With about the same total precipitation and precipitation frequency distribution over the Tropics, simulations having greater LSP fraction tend to have larger cloud condensate and low and middle cloud fraction.
Simulations having greater LSP fraction tend to be drier and colder in the upper-troposphere. The induced unstable stratification supports strong transient wind perturbations and LSP. Greater LSP also contributes to greater intraseasonal (20-100 day) precipitation variability. Model LSP has a close connection to the low level convergence via the resolved grid-scale dynamics and thus a close coupling with the surface heat flux. Such wind-evaporation feedback is essential to the development and maintenance of LSP and enhances model precipitation variability. LSP has stronger dependence and sensitivity on column moisture than CP. The moisture-convection feedback, critical to tropical intraseasonal variability, is enhanced in simulations with large LSP. Strong precipitation variability accompanied by the worse mean state implies that an optimal precipitation partitioning is critical to model tropical climate simulation.
The response of hurricane frequency to climate changes in an aquaplanet configuration of a 50-km resolution atmospheric general circulation model is examined. The lower boundary condition is an energetically consistent slab ocean with a prescribed cross-equatorial ocean heat flux, which breaks the hemispheric symmetry and moves the Intertropical Convergence Zone (ITCZ) off the equator. In this idealized configuration, hurricane frequency increases in response to radiatively forced warming. The ITCZ shifts poleward when the model is warmed with fixed cross-equatorial ocean heat flux, and it is argued that the increase in hurricane frequency results from this poleward shift. Varying the imposed cross-equatorial ocean heat flux amplitude with fixed radiative forcing can isolate the effect of ITCZ shifts. If an increase in radiative forcing is accompanied by a reduction in the ocean heat flux amplitude such that the position of the ITCZ is unchanged, the simulated hurricane frequency decreases under warmed conditions.
Sheffield, Justin, Suzana J Camargo, R Fu, Qi Hu, Xianan Jiang, Nathaniel C Johnson, K B Karnauskas, Seon Tae Kim, J L Kinter, Sanjiv Kumar, B Langenbrunner, Eric Maloney, Annarita Mariotti, J E Meyerson, J David Neelin, S Nigam, Zaitao Pan, A Ruiz-Barradas, Richard Seager, Yolande L Serra, D-Z Sun, Chunzai Wang, Shang-Ping Xie, J-Y Yu, Tao Zhang, and Ming Zhao, December 2013: North American Climate in CMIP5 Experiments. Part II: Evaluation of Historical Simulations of Intra-Seasonal to Decadal Variability. Journal of Climate, 26(23), DOI:10.1175/JCLI-D-12-00593.1. Abstract
This is the second part of a three-part paper on North American climate in CMIP5 that evaluates the 20th century simulations of intra-seasonal to multi-decadal variability and teleconnections with North American climate. Overall, the multi-model ensemble does reasonably well at reproducing observed variability in several aspects, but does less well at capturing observed teleconnections, with implications for future projections examined in part three of this paper. In terms of intra-seasonal variability, almost half of the models examined can reproduce observed variability in the eastern Pacific and most models capture the midsummer drought over Central America. The multi-model mean replicates the density of traveling tropical synoptic-scale disturbances but with large spread among the models. On the other hand, the coarse resolution of the models means that tropical cyclone frequencies are under predicted in the Atlantic and eastern North Pacific. The frequency and mean amplitude of ENSO are generally well reproduced, although teleconnections with North American climate are widely varying among models and only a few models can reproduce the east and central Pacific types of ENSO and connections with US winter temperatures. The models capture the spatial pattern of PDO variability and its influence on continental temperature and West coast precipitation, but less well for the wintertime precipitation. The spatial representation of the AMO is reasonable but the magnitude of SST anomalies and teleconnections are poorly reproduced. Multi-decadal trends such as the warming hole over the central-southeast US and precipitation increases are not replicated by the models, suggesting that observed changes are linked to natural variability.
Strazzo, S E., J B Elsner, T LaRow, D J Halperin, and Ming Zhao, November 2013: Observed versus GCM-generated local tropical cyclone frequency: Comparisons using a spatial lattice. Journal of Climate, 26(21), DOI:10.1175/JCLI-D-12-00808.1. Abstract
Of broad scientific and public interest is the reliability of global climate models (GCMs) to simulate future regional and local tropical cyclone (TC) occurrences. Atmospheric GCMs are now able to generate vortices resembling actual TCs, but questions remain about their fidelity to actual TCs. Here the authors demonstrate a spatial lattice approach for comparing actual with simulated TC occurrences regionally using actual TCs from the IBTrACS data set and GCM-generated TCs from the GFDL-HiRAM and FSU-COAPS models over the common period 1982–2008. Results show that the spatial distribution of TCs generated by the GFDL model compare well with observations globally, although there are areas of over and under prediction, particularly in parts of the Pacific. Difference maps using the spatial lattice highlight these discrepancies. Additionally, comparisons focusing on the North Atlantic basin are made. Results confirm a large area of over prediction by the FSU-COAPS model in the south-central portion of the basin. Relevant to projections of future U.S. hurricane activity is the fact that both models under predict TC activity in the Gulf of Mexico.
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.
Williamson, D L., Ming Zhao, and Isaac M Held, et al., October 2013: The Aqua Planet Experiment (APE): Response to Changed Meridional SST Profile. Journal of the Meteorological Society of Japan, 91A, DOI:10.2151/jmsj.2013-A03. Abstract
This paper explores the sensitivity of Atmospheric General Circulation Model (AGCM) simulations to changes in the meridional distribution of sea surface temperature (SST). The simulations are for an aqua-planet, a water covered Earth with no land, orography or sea-ice and with specified zonally symmetric SST. Simulations from 14 AGCMs developed for Numerical Weather Prediction and climate applications are compared. Four experiments are performed to study the sensitivity to the meridional SST profile. These profiles range from one in which the SST gradient continues to the equator to one which is flat approaching the equator, all with the same maximum SST at the equator.
The zonal mean circulation of all models shows strong sensitivity to latitudinal distribution of SST. The Hadley circulation weakens and shifts poleward as the SST profile flattens in the tropics. One question of interest is the formation of a double versus a single ITCZ. There is a large variation between models of the strength of the ITCZ and where in the SST experiment sequence they transition from a single to double ITCZ. The SST profiles are defined such that as the equatorial SST gradient flattens, the maximum gradient increases and moves poleward. This leads to a weakening of the mid-latitude jet accompanied by a poleward shift of the jet core. Also considered are tropical wave activity and tropical precipitation frequency distributions. The details of each vary greatly between models, both with a given SST and in the response to the change in SST.
One additional experiment is included to examine the sensitivity to an off-equatorial SST maximum. The upward branch of the Hadley circulation follows the SST maximum off the equator. The models that form a single precipitation maximum when the maximum SST is on the equator shift the precipitation maximum off equator and keep it centered over the SST maximum. Those that form a double with minimum on the equatorial maximum SST shift the double structure off the equator, keeping the minimum over the maximum SST. In both situations only modest changes appear in the shifted profile of zonal average precipitation. When the upward branch of the Hadley circulation moves into the hemisphere with SST maximum, the zonal average zonal, meridional and vertical winds all indicate that the Hadley cell in the other hemisphere dominates.
Zhang, M, Jean-Christophe Golaz, and Ming Zhao, et al., December 2013: CGILS: Results from the first phase of an international project to understand the physical mechanisms of low cloud feedbacks in single column models. Journal of Advances in Modeling Earth Systems, 5(4), DOI:10.1002/2013MS000246. Abstract
CGILS – the CFMIP-GASS Intercomparison of Large Eddy Models (LESs) and Single Column Models (SCMs) – investigates the mechanisms of cloud feedback in SCMs and LESs under idealized climate change perturbation. This paper describes the CGILS results from 15 SCMs and eight LES models. Three cloud regimes over the subtropical oceans are studied: shallow cumulus, stratocumulus, and well-mixed coastal stratus/stratocumulus. In the stratocumulus and coastal stratus regimes, SCMs without activated shallow convection generally simulated negative cloud feedbacks, while models with active shallow convection generally simulated positive cloud feedbacks. In the shallow cumulus regime, this relationship is less clear, likely due to the changes in cloud depth, lateral mixing, and precipitation or a combination of them. The majority of LES models simulated negative cloud feedback in the well-mixed coastal stratus/stratocumulus regime, and positive feedback in the shallow cumulus and stratocumulus regime. A general framework is provided to interpret SCM results: In a warmer climate, the moistening rate of the cloudy layer associated with the surface-based turbulence parameterization is enhanced; together with weaker large-scale subsidence, it causes negative cloud feedback. In contrast, in the warmer climate, the drying rate associated with the shallow convection scheme is enhanced. This causes positive cloud feedback. These mechanisms are summarized as “NESTS-SCOPE” (Negative feedback from Surface Turbulence under weaker Subsidence– Shallow Convection PositivE feedback) with the net cloud feedback depending on how the two opposing effects counteract each other. The LES results are consistent with these interpretations.
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.
Ginoux, Paul, J M Prospero, T E Gill, C Hsu, and Ming Zhao, August 2012: Global scale attribution of anthropogenic and natural dust sources and their emission rates based on MODIS Deep Blue aerosol products. Reviews of Geophysics, 50, RG3005, DOI:10.1029/2012RG000388. Abstract
Our understanding of the global dust cycle is limited by a dearth of information about dust sources, especially small-scale features which could account for a large fraction of global emissions. Here we present a global-scale high-resolution (0.1 deg) mapping of sources based on MODIS Deep Blue estimates of dust optical depth in conjunction with other data sets including land-use. We ascribe dust sources to natural and anthropogenic (primarily agricultural) origins, calculate their respective contribution to emissions, and extensively compare these products against literature. Natural dust sources globally account for 75% of emissions; anthropogenic, 25%. North Africa accounts for 55% of global dust emissions with only 8% being anthropogenic, mostly from the Sahel. Elsewhere, anthropogenic dust emissions can be much higher (75%, in Australia). Hydrologic dust sources (e.g., ephemeral water bodies) account for 31% worldwide; 15% of them are natural while 85% are anthropogenic. Globally, 20% of emissions are from vegetated surfaces, primarily desert shrub-lands and agricultural lands. Since anthropogenic dust sources are associated with land-use and ephemeral water bodies, both in turn linked to the hydrological cycle, their emissions are affected by climate variability. Such changes in dust emissions can impact climate, air quality, and human health. Improved dust emission estimates will require a better mapping of threshold wind velocities, vegetation dynamics, and surface conditions (soil moisture and land-use) especially in the sensitive regions identified here, as well as improved ability to address small-scale convective processes producing dust via cold pool (haboob) events frequent in monsoon regimes.
Hsu, P, Tim Li, J-J Luo, Hiroyuki Murakami, A Kitoh, and Ming Zhao, March 2012: Increase of global monsoon area and precipitation under global warming: A robust signal?Geophysical Research Letters, 39, L06701, DOI:10.1029/2012GL051037. Abstract
Monsoons, the most energetic tropical climate system, exert a great social and economic impact upon billions of people around the world. The global monsoon precipitation had an increasing trend over the past three decades. Whether or not this increase trend will continue in the 21st century is investigated, based on simulations of three high-resolution atmospheric general circulation models that were forced by different future sea surface temperature (SST) warming patterns. The results show that the global monsoon area, precipitation and intensity all increase consistently among the model projections. This indicates that the strengthened global monsoon is a robust signal across the models and SST patterns explored here. The increase of the global monsoon precipitation is attributed to the increases of moisture convergence and surface evaporation. The former is caused by the increase of atmospheric water vapor and the latter is due to the increase of SST. The effect of the moisture and evaporation increase is offset to a certain extent by the weakening of the monsoon circulation.
Jiang, Xianan, Ming Zhao, and D E Waliser, October 2012: Modulation of tropical cyclones over the Eastern Pacific by the intra-seasonal variability simulated in an AGCM. Journal of Climate, 25(19), DOI:10.1175/JCLI-D-11-00531.1. Abstract
This study illustrates that observed modulations of tropical cyclone (TC) genesis over the eastern Pacific (EPAC) by large-scale intraseasonal variability (ISV) are represented well in a recently developed high-resolution atmospheric model (HiRAM) at NOAA’s Geophysical Fluid Dynamics Laboratory (GFDL) with a horizontal resolution of about 50km. Considering the intrinsic predictability of the ISV of 2-4 weeks, this analysis thus has significant implications for dynamically based TC predictions on intraseasonal time scales. Analysis indicates that the genesis potential index (GPI) anomalies associated with the ISV can generally well depict ISV modulations of EPAC TC genesis in both observations and HiRAM simulations. Further investigation is conducted to explore the key factors associated with ISV modulation of TC activity based on an analysis of budget terms of the observed GPI during the ISV life cycle. It is found that, while relative roles of GPI factors are dependent on ISV phase and location, lower-level cyclonic vorticity, enhanced mid-level relative humidity, and reduced vertical wind shear can all contribute to the observed active TC genesis over the EPAC during particular ISV phases. In general, the observed anomalous ISV patterns of these large-scale GPI factors are well represented in HiRAM. Model deficiencies are also noted particularly in the anomalous mid-level relative humidity patterns and amplitude of vertical wind shear associated with the EPAC ISV.
Jiang, Xianan, D E Waliser, D Kim, Ming Zhao, Kenneth R Sperber, and William F Stern, et al., August 2012: Simulation of the intraseasonal variability over the Eastern Pacific ITCZ in climate models. Climate Dynamics, 39(3-4), DOI:10.1007/s00382-011-1098-x. Abstract
During boreal summer, convective activity over the eastern Pacific (EPAC) inter-tropical convergence zone (ITCZ) exhibits vigorous intraseasonal variability (ISV). Previous observational studies identified two dominant ISV modes over the EPAC, i.e., a 40-day mode and a quasi-biweekly mode (QBM). The 40-day ISV mode is generally considered a local expression of the Madden-Julian Oscillation. However, in addition to the eastward propagation, northward propagation of the 40-day mode is also evident. The QBM mode bears a smaller spatial scale than the 40-day mode, and is largely characterized by northward propagation. While the ISV over the EPAC exerts significant influences on regional climate/weather systems, investigation of contemporary model capabilities in representing these ISV modes over the EPAC is limited. In this study, the model fidelity in representing these two dominant ISV modes over the EPAC is assessed by analyzing six atmospheric and three coupled general circulation models (GCMs), including one super-parameterized GCM (SPCAM) and one recently developed high-resolution GCM (GFDL HIRAM) with horizontal resolution of about 50 km. While it remains challenging for GCMs to faithfully represent these two ISV modes including their amplitude, evolution patterns, and periodicities, encouraging simulations are also noted. In general, SPCAM and HIRAM exhibit relatively superior skill in representing the two ISV modes over the EPAC. While the advantage of SPCAM is achieved through explicit representation of the cumulus process by the embedded 2-D cloud resolving models, the improved representation in HIRAM could be ascribed to the employment of a strongly entraining plume cumulus scheme, which inhibits the deep convection, and thus effectively enhances the stratiform rainfall. The sensitivity tests based on HIRAM also suggest that fine horizontal resolution could also be conducive to realistically capture the ISV over the EPAC, particularly for the QBM mode. Further analysis illustrates that the observed 40-day ISV mode over the EPAC is closely linked to the eastward propagating ISV signals from the Indian Ocean/Western Pacific, which is in agreement with the general impression that the 40-day ISV mode over the EPAC could be a local expression of the global Madden-Julian Oscillation (MJO). In contrast, the convective signals associated with the 40-day mode over the EPAC in most of the GCM simulations tend to originate between 150°E and 150°W, suggesting the 40-day ISV mode over the EPAC might be sustained without the forcing by the eastward propagating MJO. Further investigation is warranted towards improved understanding of the origin of the ISV over the EPAC.
Lin, Yanluan, Leo J Donner, Stephen A Klein, and Ming Zhao, et al., May 2012: TWP-ICE global atmospheric model intercomparison: convection responsiveness and resolution impact. Journal of Geophysical Research: Atmospheres, 117, D09111, DOI:10.1029/2011JD017018. Abstract
Results are presented from an intercomparison of atmospheric general circulation model
(AGCM) simulations of tropical convection during the Tropical Warm Pool-International Cloud
Experiment (TWP-ICE). The distinct cloud properties, precipitation, radiation, and vertical diabatic
heating profiles associated with three different monsoon regimes (wet, dry, and break) from available
observations are used to evaluate 9 AGCM forecasts initialized daily from realistic global analyses. All
models captured well the evolution of large-scale circulation and thermodynamic fields, but cloud
properties differed substantially among models. Compared with the relatively well simulated top-heavy
heating structures during the wet and break period, most models had difficulty in depicting the bottomheavy
heating profiles associated with cumulus congestus during the dry period. The best performing
models during this period were the ones whose convection scheme was most responsive to the free
tropospheric humidity.
Compared with the large impact of cloud and convective parameterizations on model cloud and
precipitation characteristics, resolution has relatively minor impact on simulated cloud properties.
However, one feature that was influenced by resolution in several models was the diurnal cycle of
precipitation. Peaking at a different time from convective precipitation, large-scale precipitation
generally increases in high resolution forecasts and modulates the total precipitation diurnal cycle.
Overall, the study emphasizes the need for convection parameterizations that are more responsive to
environmental conditions as well as the substantial diversity among large-scale cloud and precipitation
schemes in current AGCMs. This experiment has demonstrated itself to be a very useful testbed for
those developing cloud and convection schemes for AGCMs.
Williamson, D L., M Blackburn, B J Hoskins, Ming Zhao, and Isaac M Held, et al., 2012: In The APE Atlas, NCAR Technical Note NCAR/TN-484+STR, Boulder, Colorado, National Center for Atmospheric Research, DOI:10.5065/D6FF3QBR.
Zhao, Ming, and Isaac M Held, April 2012: TC-permitting GCM simulations of hurricane frequency response to sea surface temperature anomalies projected for the late 21st century. Journal of Climate, 25(8), DOI:10.1175/JCLI-D-11-00313.1. Abstract
A tropical cyclone permitting global atmospheric model is used to explore hurricane frequency response to sea surface temperature (SST) anomalies generated by coupled models for the late 21st century. Results are presented for SST anomalies averaged over 18 models as well as from 8 individual models. For each basin, there exists large inter-model spread in the magnitude and even the sign of the frequency response among the different SST projections. These sizable variations in response are explored to understand features of SST distributions that are important for the basin-wide hurricane responses. In the N. Atlantic, the E. Pacific and the S. Indian basins, most (72-86%) of the inter-model variance in storm frequency response can be explained by a simple relative SST index defined as a basin's storm development region SST minus the tropical mean SST. The explained variance is significantly lower in the S. Pacific (48%) and much lower in the W. Pacific basin (27%).
Several atmospheric parameters are utilized to probe changes in tropical atmospheric circulation and thermodynamical properties relevant to storm genesis in the model. While all present strong correlation to storm response in some basins, a parameter measuring tropospheric convective mass-flux stands out as skillful in explaining the simulated differences for all basins. Globally, in addition to a modest reduction of total storm frequency, the simulations exhibit a small but robust eastward and poleward migration of genesis frequency in both the N. Pacific and the N. Atlantic oceans. This eastward migration of storms can also be explained by changes in convection.
High resolution global climate models (GCM) have been increasingly utilized for simulations of the global number and distribution of tropical cyclones (TCs), and how they might change with changing climate. In contrast, there is a lack of published studies on the sensitivity of TC genesis to parameterized processes in these GCMs.The uncertainties in these formulations might be an important source of uncertainty in the future projections of TC statistics.
In this study, we investigate the sensitivity of the global number of TCs in present-day simulations using the Geophysical Fluid Dynamics Laboratory HIgh Resolution Atmospheric Model (GFDL HIRAM) to alterations in physical parameterizations. Two parameters are identified to be important in TC genesis frequency in this model. They are the horizontal cumulus mixing rate which controls the entrainment into convective cores within the convection parameterization, and the strength of the damping of the divergent component of the horizontal flow. The simulated global number of TCs exhibits non-intuitive response to incremental changes of both parameters. As the cumulus mixing rate increases, the model produces non-monotonic response in global TC frequency with an initial sharp increase and then decrease. However, storm mean intensity rises montonically with the mixing rate. As the strength of the divergence damping increases, the model produces a continuous increase of global number of TCs and hurricanes with little change in storm mean intensity. Mechanisms for explaining these non-intuitive responses are discussed.
The Geophysical Fluid Dynamics Laboratory (GFDL) has developed a coupled general circulation model (CM3) for atmosphere, oceans, land, and sea ice. The goal of CM3 is to address emerging issues in climate change, including aerosol-cloud interactions, chemistry-climate interactions, and coupling between the troposphere and stratosphere. The model is also designed to serve as the physical-system component of earth-system models and models for decadal prediction in the near-term future, for example, through improved simulations in tropical land precipitation relative to earlier-generation GFDL models. This paper describes the dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component (AM3) of this model.
Relative to GFDL AM2, AM3 includes new treatments of deep and shallow cumulus convection, cloud-droplet activation by aerosols, sub-grid variability of stratiform vertical velocities for droplet activation, and atmospheric chemistry driven by emissions with advective, convective, and turbulent transport. AM3 employs a cubed-sphere implementation of a finite-volume dynamical core and is coupled to LM3, a new land model with eco-system dynamics and hydrology.
Most basic circulation features in AM3 are simulated as realistically, or more so, than in AM2. In particular, dry biases have been reduced over South America. In coupled mode, the simulation of Arctic sea ice concentration has improved. AM3 aerosol optical depths, scattering properties, and surface clear-sky downward shortwave radiation are more realistic than in AM2. The simulation of marine stratocumulus decks and the intensity distributions of precipitation remain problematic, as in AM2.
The last two decades of the 20th century warm in CM3 by .32°C relative to 1881-1920. The Climate Research Unit (CRU) and Goddard Institute for Space Studies analyses of observations show warming of .56°C and .52°C, respectively, over this period. CM3 includes anthropogenic cooling by aerosol cloud interactions, and its warming by late 20th century is somewhat less realistic than in CM2.1, which warmed .66°C but did not include aerosol cloud interactions. The improved simulation of the direct aerosol effect (apparent in surface clear-sky downward radiation) in CM3 evidently acts in concert with its simulation of cloud-aerosol interactions to limit greenhouse gas warming in a way that is consistent with observed global temperature changes.
The recently developed GFDL Atmospheric Model version 3 (AM3), an atmospheric general circulation model (GCM), incorporates a prognostic treatment of cloud drop number to simulate the aerosol indirect effect. Since cloud drop activation depends on cloud-scale vertical velocities, which are not reproduced in present-day GCMs, additional assumptions on the subgrid variability are required to implement a local activation parameterization into a GCM.
This paper describes the subgrid activation assumptions in AM3 and explores sensitivities by constructing alternate configurations. These alternate model configurations exhibit only small differences in their present-day climatology. However, the total anthropogenic radiative flux perturbation (RFP) between present-day and preindustrial conditions varies by ±50% from the reference, because of a large difference in the magnitude of the aerosol indirect effect. The spread in RFP does not originate directly from the subgrid assumptions but indirectly through the cloud retuning necessary to maintain a realistic radiation balance. In particular, the paper shows a linear correlation between the choice of autoconversion threshold radius and the RFP.
Climate sensitivity changes only minimally between the reference and alternate configurations. If implemented in a fully coupled model, these alternate configurations would therefore likely produce substantially different warming from preindustrial to present day.
The effects on tropical cyclone statistics of doubling CO2, with fixed sea surface
temperatures (SSTs), are compared to the effects of a 2K increase in SST, with fixed
CO2, using a 50km resolution global atmospheric model. Confirming earlier results of
Yoshimura and Sugi (2005), a significant fraction of the reduction in globally averaged
tropical storm frequency seen in simulations in which both SST and CO2 are increased can be
thought of as the effect of the CO2 increase with fixed SSTs. Globally, the model produces a
decrease in tropical cyclone frequency of about 10% due to doubling of CO2 and an additional
10% for a 2K increase in SST, resulting in roughly a 20% reduction when both effects are
present. The relative contribution of the CO2 effect to the total reduction is larger in the
Northern than in the Southern Hemisphere. The average intensity of storms increases in the
model with increasing SST, but intensity remains roughly unchanged, or decreases slightly,
with the increase in CO2 alone. As a result, when considering the frequency of more intense
cyclones, the intensity increase tends to compensate for the reduced total cyclone numbers for
the SST increase in isolation but not for the CO2 increase in isolation. Changes in genesis
in these experiments roughly follow changes in mean vertical motion, reflecting changes in
convective mass fluxes. Discussion is provided of one possible perspective on how changes in
the convective mass flux might alter genesis rates.
Kahn, B H., João Teixeira, E J Fetzer, Andrew Gettelman, S M Hristova-Veleva, X Huang, A K Kochanski, M Köhler, S K Krueger, R Wood, and Ming Zhao, September 2011: Temperature and water vapor variance scaling in global models: Comparisons to satellite and aircraft data. Journal of the Atmospheric Sciences, 68(9), DOI:10.1175/2011JAS3737.1. Abstract
Observations of the scale dependence of height-resolved temperature T and water vapor q variability are valuable for improved subgrid-scale climate model parameterizations and model evaluation. Variance spectral benchmarks for T and q obtained from the Atmospheric Infrared Sounder (AIRS) are compared to those generated by state-of-the-art numerical weather prediction “analyses” and “free-running” climate model simulations with spatial resolution comparable to AIRS. The T and q spectra from both types of models are generally too steep, with small-scale variance up to several factors smaller than AIRS. However, the two model analyses more closely resemble AIRS than the two free-running model simulations. Scaling exponents obtained for AIRS column water vapor (CWV) and height-resolved layers of q are also compared to the superparameterized Community Atmospheric Model (SP-CAM), highlighting large differences in the magnitude of CWV variance and the relative flatness of height-resolved q scaling in SP-CAM. Height-resolved q spectra obtained from aircraft observations during the Variability of the American Monsoon Systems Ocean–Cloud–Atmosphere–Land Study Regional Experiment (VOCALS-REx) demonstrate changes in scaling exponents that depend on the observations’ proximity to the base of the subsidence inversion with scale breaks that occur at approximately the dominant cloud scale (~10–30 km). This suggests that finer spatial resolution requirements must be considered for future satellite observations of T and q than those currently planned for infrared and microwave satellite sounders.
Teixeira, João, and Ming Zhao, et al., October 2011: Tropical and sub-tropical cloud transitions in weather and climate prediction models: the GCSS/WGNE Pacific Crosssection Intercomparison (GPCI). Journal of Climate, 24(20), DOI:10.1175/2011JCLI3672.1. Abstract
A model evaluation approach is proposed in which weather and climate prediction models are
analyzed along a Pacific Ocean cross-section, from the stratocumulus regions off the coast of California,
across the shallow convection dominated trade-winds, to the deep convection regions of the ITCZ: the
GEWEX Cloud System Study / Working Group on Numerical Experimentation (GCSS/WGNE) Pacific
Cross-section Intercomparison (GPCI). The main goal of GPCI is to evaluate, and help understand and
improve the representation of tropical and sub-tropical cloud processes in weather and climate prediction
models. In this paper, a detailed analysis of cloud regime transitions along the cross-section from the
sub-tropics to the tropics for the season June-July-August of 1998 is presented.
This GPCI study confirms many of the typical weather and climate prediction model problems in the
representation of clouds: underestimation of clouds in the stratocumulus regime by most models with the
corresponding consequences in terms of shortwave radiation biases; overestimation of clouds by the
ECMWF Re-Analysis (ERA40) in the deep tropics (in particular) with the corresponding impact in the
outgoing longwave radiation; large spread between the different models in terms of cloud cover, liquid
water path and shortwave radiation; significant differences between the models in terms of vertical crosssections
of cloud properties (in particular), vertical velocity and relative humidity.
An alternative analysis of cloud cover mean statistics is proposed where sharp gradients in cloud
cover along the GPCI transect are taken into account. This analysis shows that the negative cloud bias of
some models and ERA40 in the stratocumulus regions (as compared to ISCCP) is associated not only
with lower values of cloud cover in these regimes, but also with a stratocumulus-to-cumulus transition
that occurs too early along the trade-wind Lagrangian trajectory. Histograms of cloud cover along the
cross-section differ significantly between models. Some models exhibit a quasi-bimodal structure with
cloud cover being either very large (close to 100%) or very small, while other models show a more
continuous transition. The ISCCP observations suggest that reality is in-between these two extreme
examples. These different patterns reflect the diverse nature of the cloud, boundary layer, and convection
parameterizations in the participating weather and climate prediction 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.
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.
Li, Tim, Minho Kwon, and Ming Zhao, et al., November 2010: Global warming shifts Pacific tropical cyclone location. Geophysical Research Letters, 37, L21804, DOI:10.1029/2010GL045124. Abstract
A global high‐resolution (∼40 km) atmospheric general
circulation model (ECHAM5 T319) is used to investigate the
change of tropical cyclone frequency in the North Pacific
under global warming. A time slice method is used in which
sea surface temperature fields derived from a lower resolution
coupled model run under the 20C3M (in which
historical greenhouse gases in 20th century were prescribed
as a radiative forcing) and A1B (in which carbon dioxide
concentration was increased 1% each year from 2000 to
2070 and then was kept constant) scenarios are specified as
the lower boundary conditions to simulate the current and
the future warming climate, respectively. A significant shift
is found in the location of tropical cyclones from the western
to central Pacific. The shift to more tropical cyclones in the
central and less in the western Pacific is not attributable to a
change in atmospheric static stability, but to a change in the
variance of tropical synoptic‐scale perturbations associated
with a change in the background vertical wind shear and
boundary layer divergence.
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.
Zhao, Ming, and Isaac M Held, December 2010: An analysis of the effect of global warming on the intensity of Atlantic hurricanes using a GCM with statistical refinement. Journal of Climate, 23(23), DOI:10.1175/2010JCLI3837.1. Abstract
A statistical intensity adjustment is utilized to extract information from tropical cyclone
simulations in a 50km-resolution global model. A simple adjustment based on the modeled
and observed probability distribution of storm life-time maximum wind speed allows the
GCM to capture the differences between observed intensity distributions in active/inactive
year composites from the 1981-2008 period in the N. Atlantic. This intensity adjustment is
then used to examine the atmospheric model’s responses to different sea surface temperature
anomalies generated by coupled models for the late 21st century. In the North Atlantic all
simulations produce a reduction in the total number of cyclones, but with large inter-model
spread in the magnitude of the reduction. The intensity response is positively correlated with
changes in frequency across the ensemble. Yet there is, on average, an increase in intensity
in these simulations despite the mean reduction in frequency. We argue that it is useful to
decompose these intensity changes into two parts: an increase in intensity that is intrinsic to
the climate change experiments; and a change in intensity positively correlated with frequency,
just as in the active/inactive historical composites. Isolating the intrinsic component, which
is relatively independent of the details of the SST warming pattern, we find an increase in
storm-lifetime maximum winds of 5-10 ms−1 for storms with intensities of 30-60 ms−1, by
the end of the 21st century. The effects of change in frequency, which are dependent on the
details of the spatial structure of the warming, must then be superimposed on this intrinsic
change.
Mapes, B E., Julio T Bacmeister, Marat Khairoutdinov, Cecile Hannay, and Ming Zhao, January 2009: Virtual field campaigns on deep tropical convection in climate models. Journal of Climate, 22(2), DOI:10.1175/2008JCLI2203.1. Abstract
High-resolution time–height data
over warm tropical oceans are examined, from three global atmosphere models
[GFDL's Atmosphere Model 2 (AM2), NCAR's Community Atmosphere Model, version
3 (CAM3), and a NASA Global Modeling and Assimilation Office (GMAO) model],
field campaign observations, and observation-driven cloud model outputs. The
character of rain events is shown in data samples and summarized in lagged
regressions versus surface rain rate. The CAM3 humidity and cloud exhibit
little vertical coherence among three distinct layers, and its rain events
have a short characteristic time, reflecting the convection scheme's
penetrative nature and its closure's concentrated sensitivity to a thin
boundary layer source level. In contrast, AM2 rain variations have much
longer time scales as convection scheme plumes whose entrainment gives them
tops below 500 hPa interact with humidity variations in that layer. Plumes
detraining at model levels above 500 hPa are restricted by cloud work
function thresholds, and upper-tropospheric humidity and cloud layers fed by
these are detached from the lower levels and are somewhat sporadic. With
these discrete entrainment rates and instability thresholds, AM2 also
produces some synthetic-looking noise (sharp features in height and time) on
top of its slow rain variations. A distinctive feature of the NASA model is
a separate anvil scheme, distinct from the main large-scale cloud scheme,
fed by relaxed Arakawa–Schubert (RAS) plume ensemble convection (a different
implementation than in AM2). Its variability is rich and vertically
coherent, and involves a very strong vertical dipole component to its
tropospheric heating variations, of both signs (limited-depth convective
heating and top-heavy heating in strong deep events with significant
nonconvective rain). Grid-scale saturation events occur in all three models,
often without nonconvective surface rain, causing relatively rare episodes
of large negative top-of-atmosphere cloud forcing. Overall, cloud forcing
regressions show a mild net positive forcing by rain-correlated clouds in
CAM3 and mild net cooling in the other models, as the residual of large
canceling shortwave and longwave contributions.
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.
Rotating radiative–convective equilibrium, using the column physics and resolution of GCMs, is proposed as a useful framework for studying the tropical storm–like vortices produced by global models. These equilibria are illustrated using the column physics and dynamics of a version of the GFDL Atmospheric Model 2 (AM2) at resolutions of 220, 110, and 55 km in a large 2 × 104 km square horizontally homogeneous domain with fixed sea surface temperature and uniform Coriolis parameter. The large domain allows a number of tropical storms to exist simultaneously. Once equilibrium is attained, storms often persist for hundreds of days. The number of storms decreases as sea surface temperatures increase, while the average intensity increases. As the background rotation is decreased, the number of storms also decreases. At these resolutions and with this parameterization of convection, a dense collection of tropical storms is always the end state of moist convection in the cases examined.
Kang, Sarah M., Isaac M Held, D M W Frierson, and Ming Zhao, 2008: The response of the ITCZ to extratropical thermal forcing: Idealized slab-ocean experiments with a GCM. Journal of Climate, 21(14), DOI:10.1175/2007JCLI2146.1. Abstract
Using a comprehensive atmospheric GCM coupled to a slab mixed layer ocean, experiments are performed to study the mechanism by which displacements of the intertropical convergence zone (ITCZ) are forced from the extratropics. The northern extratropics are cooled and the southern extratropics are warmed by an imposed cross-equatorial flux beneath the mixed layer, forcing a southward shift in the ITCZ. The ITCZ displacement can be understood in terms of the degree of compensation between the imposed oceanic flux and the resulting response in the atmospheric energy transport in the tropics. The magnitude of the ITCZ displacement is very sensitive to a parameter in the convection scheme that limits the entrainment into convective plumes. The change in the convection scheme affects the extratropical–tropical interactions in the model primarily by modifying the cloud response. The results raise the possibility that the response of tropical precipitation to extratropical thermal forcing, important for a variety of problems in climate dynamics (such as the response of the tropics to the Northern Hemisphere ice sheets during glacial maxima or to variations in the Atlantic meridional overturning circulation), may be strongly dependent on cloud feedback. The model configuration described here is suggested as a useful benchmark helping to quantify extratropical–tropical interactions in atmospheric models.
Medeiros, Brian, Bjorn Stevens, Isaac M Held, Ming Zhao, D L Williamson, J Olson, and Christopher S Bretherton, October 2008: Aquaplanets, climate sensitivity, and low clouds. Journal of Climate, 21(19), DOI:10.1175/2008JCLI1995.1. Abstract
Cloud effects have repeatedly been pointed out as the leading source of uncertainty in projections of future climate, yet clouds remain poorly understood and simulated in climate models. Aquaplanets provide a simplified framework for comparing and understanding cloud effects, and how they are partitioned as a function of regime, in large-scale models. This work uses two climate models to demonstrate that aquaplanets can successfully predict a climate model's sensitivity to an idealized climate change. For both models, aquaplanet climate sensitivity is similar to that of the realistic configuration. Tropical low clouds appear to play a leading role in determining the sensitivity. Regions of large-scale subsidence, which cover much of the tropics, are most directly responsible for the differences between the models. Although cloud effects and climate sensitivity are similar for aquaplanets and realistic configurations, the aquaplanets lack persistent stratocumulus in the tropical atmosphere. This, and an additional analysis of the cloud response in the realistically configured simulations, suggests the representation of shallow (trade wind) cumulus convection, which is ubiquitous in the tropics, is largely responsible for differences in the simulated climate sensitivity of these two models.
Held, Isaac M., Ming Zhao, and Bruce Wyman, January 2007: Dynamic radiative-convective equilibria using GCM column physics. Journal of the Atmospheric Sciences, 64(1), 228-238. Abstract PDF
The behavior of a GCM column physics package in a nonrotating, doubly periodic, homogeneous setting with prescribed SSTs is examined. This radiative–convective framework is proposed as a useful tool for studying some of the interactions between convection and larger-scale dynamics and the effects of differing modeling assumptions on convective organization and cloud feedbacks.
For the column physics utilized here, from the Geophysical Fluid Dynamics Laboratory (GFDL) AM2 model, many of the properties of the homogeneous, nonrotating model are closely tied to the fraction of precipitation that is large-scale, rather than convective. Significant large-scale precipitation appears above a critical temperature and then increases with further increases in temperature. The amount of large-scale precipitation is a function of horizontal resolution and can also be controlled by modifying the convection scheme, as is illustrated here by modifying assumptions concerning entrainment into convective plumes. Significant similarities are found between the behavior of the homogeneous model and that of the Tropics of the parent GCM when ocean temperatures are increased and when the convection scheme is modified.
Wyant, M C., and Ming Zhao, et al., December 2007: A single-column model intercomparison of a heavily drizzling stratocumulus-topped boundary layer. Journal of Geophysical Research, D24204, DOI:10.1029/2007JD008536. Abstract
This study presents an intercomparison of single-column model simulations of a
nocturnal heavily drizzling marine stratocumulus-topped boundary layer. Initial conditions
and forcings are based on nocturnal flight observations off the coast of California during
the DYCOMS-II field experiment. Differences in turbulent and microphysical
parameterizations between models were isolated by slightly idealizing and standardizing
the specification of surface and radiative fluxes. For most participating models, the case
was run at both typical operational vertical resolution of about 100 m and also at high
vertical resolution of about 10 m. As in prior stratocumulus intercomparisons, the
simulations quickly develop considerable scatter in liquid water path (LWP) between
models. However, the simulated dependence of cloud base drizzle fluxes on LWP in most
models is broadly consistent with recent observations. Sensitivity tests with drizzle
turned off show that drizzle substantially decreases LWP for many models. The sensitivity
of entrainment rate to drizzle is more muted. Simulated LWP and entrainment are also
sensitive to the inclusion of cloud droplet sedimentation. Many models underestimate the
fraction of drizzle that evaporates below cloud base, which may distort the simulated
feedbacks of drizzle on turbulence, entrainment, and LWP.
Wyant, M C., Christopher S Bretherton, Julio T Bacmeister, J T Kiehl, Isaac M Held, Ming Zhao, Stephen A Klein, and Brian J Soden, 2006: A comparison of low-latitude cloud properties and their response to climate change in three AGCMs sorted into regimes using mid-tropospheric vertical velocity. Climate Dynamics, 27(2-3), DOI:10.1007/s00382-006-0138-4. Abstract
Low-latitude cloud distributions and cloud responses to climate perturbations are compared in near-current versions of three leading U.S. AGCMs, the NCAR CAM 3.0, the GFDL AM2.12b, and the NASA GMAO NSIPP-2 model. The analysis technique of Bony et al. (Clim Dyn 22:71–86, 2004) is used to sort cloud variables by dynamical regime using the monthly mean pressure velocity ω at 500 hPa from 30S to 30N. All models simulate the climatological monthly mean top-of-atmosphere longwave and shortwave cloud radiative forcing (CRF) adequately in all ω-regimes. However, they disagree with each other and with ISCCP satellite observations in regime-sorted cloud fraction, condensate amount, and cloud-top height. All models have too little cloud with tops in the middle troposphere and too much thin cirrus in ascent regimes. In subsidence regimes one model simulates cloud condensate to be too near the surface, while another generates condensate over an excessively deep layer of the lower troposphere. Standardized climate perturbation experiments of the three models are also compared, including uniform SST increase, patterned SST increase, and doubled CO2 over a mixed layer ocean. The regime-sorted cloud and CRF perturbations are very different between models, and show lesser, but still significant, differences between the same model simulating different types of imposed climate perturbation. There is a negative correlation across all general circulation models (GCMs) and climate perturbations between changes in tropical low cloud cover and changes in net CRF, suggesting a dominant role for boundary layer cloud in these changes. For some of the cases presented, upper-level clouds in deep convection regimes are also important, and changes in such regimes can either reinforce or partially cancel the net CRF response from the boundary layer cloud in subsidence regimes. This study highlights the continuing uncertainty in both low and high cloud feedbacks simulated by GCMs.
Zhao, Ming, and P H Austin, 2005: Life cycle of numerically simulated shallow cumulus clouds. Part I: Transport. Journal of the Atmospheric Sciences, 62(5), 1269-1290. Abstract
This paper is the first in a two-part series in which the life cycles of numerically simulated shallow cumulus clouds are systematically examined. The life cycle data for six clouds with a range of cloud-top heights are isolated from an equilibrium trade cumulus field generated by a large-eddy simulation (LES) with a uniform resolution of 25 m. A passive subcloud tracer is used to partition the cloud life cycle transport into saturated and unsaturated components: the tracer shows that on average cumulus convection occurs in a region with time-integrated volume roughly 2 to 3 times that of the liquid-water-containing volume. All six clouds exhibit qualitatively similar vertical mass flux profiles with net downward mass transport at upper levels and net upward mass flux at lower levels. This downward mass flux comes primarily from the unsaturated cloud-mixed convective region during the dissipation stage and is evaporatively driven. Unsaturated negatively buoyant cloud mixtures dominate the buoyancy and mass fluxes in the upper portion of all clouds while saturated positively buoyant cloud mixtures dominate the fluxes at lower levels. Small and large clouds have distinct vertical profiles of heating/cooling and drying/moistening, with small clouds cooling and moistening throughout their depth, while larger clouds cool and moisten at upper levels and heat and dry at lower levels. The simulation results are compared to the predictions of conceptual models commonly used in shallow cumulus parameterizations.
Zhao, Ming, and P H Austin, 2005: Life cycle of numerically simulated shallow cumulus clouds. Part II: Mixing dynamics. Journal of the Atmospheric Sciences, 62(5), 1291-1310. Abstract
This paper is the second in a two-part series in which life cycles of six numerically simulated shallow cumulus clouds are systematically examined. The six clouds, selected from a single realization of a large eddy simulation, grow as a series of pulses/therrnals detached from the subcloud layer. All six clouds exhibit a coherent vortical circulation and a low buoyancy, low velocity trailing wake. The ascending cloud top (ACT), which contains this vortical circulation, is associated with a dynamic perturbation pressure field with high pressure located at the ascending frontal cap and low pressure below and on the downshear side of the maximum updrafts. Examination of the thermodynamic and kinematic structure, together with passive tracer experiments, suggests that this vortical circulation is primarily responsible for mixing between cloud and environment. As the cloud ACTs rise through the sheared environment, the low pressure, vortical circulation, and mixing are all strongly enhanced on the downshear side and weakened on the upshear side. Collapse of the ACT also occurs on the downshear side, with subsequent thermals ascending on the upshear side of their predecessors. The coherent core structure is maintained throughout the ACT ascent: mixing begins to gradually dilute the ACT core only in the upper half of the cloud's depth. The characteristic kinematic and dynamic structure of these simulated ACTs, together with their mixing behavior, corresponds closely to that of shedding thermals. These shallow simulated clouds, however, reach a maximum height of only about four ACT diameters so that ACT mixing differs from predictions of self-similar laboratory thermals.
Episodic mixing and buoyancy-sorting (EMBS) models have been proposed as a physically more realistic alternative to entraining plume models of cumulus convection. Applying these models to shallow nonprecipitating clouds requires assumptions about the rate at which undilute subcloud air is eroded into the environment, an algorithm to calculate the eventual detrainment level of cloud–environment mixtures, and the probability distribution of mixing fraction. A diagnostic approach is used to examine the sensitivity of an EMBS model to these three closure assumptions, given equilibrium convection with known large-scale forcings taken from phase III of the Barbados Oceanographic Meteorological Experiment (BOMEX). The undilute eroding rate (UER) is retrieved and found to decrease exponentially with height above cloud base, suggesting a strong modulation by the cloud size distribution. The EMBS model is also used to calculate convective transport by individual clouds of varying thickness. No single cloud from this ensemble can balance the large-scale BOMEX forcing; the observed equilibrium requires a population of clouds with a cloud size distribution that is maximum for small clouds and decreases monotonically with cloud size.
The EMBS model depends sensitively on the assumptions governing the detrainment of positively buoyant mixtures. In particular, given the requirement that positively buoyant mixtures detrain at their neutral buoyancy level, there is no positive definite undilute eroding rate that is consistent with the BOMEX forcing. The model is less sensitive to the assumed distribution of cloud–environment mixtures, given a multiple mixing treatment of positively buoyant parcels and detrainment at the unsaturated neutral buoyancy level.
