Wang, Hai, Xiao-Tong Zheng, Wenju Cai, Zi-Wen Han, Shang-Ping Xie, Sarah M Kang, Yu-Fan Geng, Fukai Liu, Chuan-Yang Wang, Yue Wu, Baoqiang Xiang, and Lei Zhou, May 2024: Atmosphere teleconnections from abatement of China aerosol emissions exacerbate Northeast Pacific warm blob events. Proceedings of the National Academy of Sciences, 121(21), DOI:10.1073/pnas.2313797121. Abstract
During 2010 to 2020, Northeast Pacific (NEP) sea surface temperature (SST) experienced the warmest decade ever recorded, manifested in several extreme marine heatwaves, referred to as “warm blob” events, which severely affect marine ecosystems and extreme weather along the west coast of North America. While year-to-year internal climate variability has been suggested as a cause of individual events, the causes of the continuous dramatic NEP SST warming remain elusive. Here, we show that other than the greenhouse gas (GHG) forcing, rapid aerosol abatement in China over the period likely plays an important role. Anomalous tropospheric warming induced by declining aerosols in China generated atmospheric teleconnections from East Asia to the NEP, featuring an intensified and southward-shifted Aleutian Low. The associated atmospheric circulation anomaly weakens the climatological westerlies in the NEP and warms the SST there by suppressing the evaporative cooling. The aerosol-induced mean warming of the NEP SST, along with internal climate variability and the GHG-induced warming, made the warm blob events more frequent and intense during 2010 to 2020. As anthropogenic aerosol emissions continue to decrease, there is likely to be an increase in NEP warm blob events, disproportionately large beyond the direct radiative effects.
Boreal summer intraseasonal oscillation (BSISO) is a primary source of predictability for summertime weather and climate on the subseasonal-to-seasonal (S2S) time scale. Using the GFDL SPEAR S2S prediction system, we evaluate the BSISO prediction skills based on 20-yr (2000–19) hindcast experiments with initializations from May to October. It is revealed that the overall BSISO prediction skill using all hindcasts reaches out to 22 days as measured by BSISO indices before the bivariate anomalous correlation coefficient (ACC) drops below 0.5. Results also show that the northeastward-propagating canonical BSISO (CB) event has a higher prediction skill than the northward dipole BSISO (DB) event (28 vs 23 days). This is attributed to CB’s more periodic nature, resulting in its longer persistence, while DB events are more episodic accompanied by a rapid demise after reaching maximum enhanced convection over the equatorial Indian Ocean. From a forecaster’s perspective, a precursory strong Kelvin wave component in the equatorial western Pacific signifies the subsequent development of a CB event, which is likely more predictable. Investigation of individual CB events shows a large interevent spread in terms of their prediction skills. For CB, the events with weaker and fluctuating amplitude during their lifetime have relatively lower prediction skills likely linked to their weaker convection–circulation coupling. Interestingly, the prediction skills of individual CB events tend to be relatively higher and less scattered during late summer (August–October) than those in early summer (May–July), suggestive of the seasonal modulation on the evolution and predictability of BSISO.
Yang, Jing, Tao Zhu, Frederic Vitart, Bin Wang, Baoqiang Xiang, Qing Bao, and June-Yi Lee, July 2024: Synchronous Eurasian heat extremes tied to boreal summer combined extratropical intraseasonal waves. npj Climate and Atmospheric Science, 7, 169, DOI:10.1038/s41612-024-00714-1. Abstract
Heat extremes frequently hit different regions synchronously during boreal summer over the Eurasian continent. A remarkable coupling is first revealed between Eurasian heat extreme occurrence and individual extratropical intraseasonal oscillation (EISO). Further, the combined EISOs facilitate and largely increase the occurrence probabilities of synchronous Eurasian heat extremes. These dominant combined EISOs together contribute 20–45% to the total heat extreme days over the five Eurasian regions where the climatological heat extremes occur most frequently. A multi-model hindcast further shows that the subseasonal prediction exhibits higher skills for synchronous heat extremes over the combined-EISO hotspot regions when the associated combined EISOs are active, supporting the notion that the monitoring and prediction of EISOs are crucial for heat extremes’ early warning. Skillful prediction of EISOs opens a pathway for heat extremes’ prediction by extending it from the weather to the subseasonal timescales.
Atmospheric rivers (ARs) are characterized by intense lower tropospheric plumes of moisture transport that are frequently responsible for midlatitude wind and precipitation extremes. The prediction of ARs at subseasonal-to-seasonal (S2S) timescales is currently at a low level of skill, reflecting a need to improve our understanding of their underlying sources of predictability. Based on 20 year hindcast experiments from the Geophysical Fluid Dynamics Laboratory’s SPEAR S2S forecast system, we evaluate the S2S prediction skill of AR activities in the northern winter. Higher forecast skill is detected for high-frequency AR activities (3–7 days/week) compared to low-frequency AR activities (1–2 days/week), even though the occurrence rate of high-frequency ARs exceeds that of low-frequency ARs. For the first time, we have applied the Average Predictability Time technique to the SPEAR system to identify the three most predictable modes of AR in the North Pacific sector. These modes can be attributed to the influences of the El Niño–Southern Oscillation, the Pacific North American pattern, and the Arctic Oscillation. S2S AR forecast skill in western United States is modulated by various phases of large-scale variability. This study highlights potential windows of opportunity for operational S2S AR forecasting.
Zhou, Xuan, Lu Wang, Pang-Chi Hsu, Tim Li, and Baoqiang Xiang, October 2024: Understanding the factors controlling MJO prediction skill across events. Journal of Climate, 37(20), DOI:10.1175/JCLI-D-23-0635.15323-5336. Abstract
The prediction skill for individual Madden–Julian oscillation (MJO) events is highly variable, but the key factors behind this remain unclear. Using the latest hindcast results from the subseasonal-to-seasonal (S2S) phase II models, this study attempts to understand the diverse prediction skill for the MJO events with an enhanced convective anomaly over the eastern Indian Ocean (IO) at the forecast start date, by investigating the preference of the prediction skill to the MJO-associated convective anomalies and low-frequency background states (LFBS). Compared to the low-skill MJO events, the high-skill events are characterized by a stronger intraseasonal convection–circulation couplet over the IO before the forecast start date, which could result in a longer zonal propagation range during the forecast period, thereby leading to a higher score for assessing the prediction skill. The difference in intraseasonal fields can further be attributed to the LFBS of IO sea surface temperature (SST) and quasi-biannual oscillation (QBO), with the high-skill (low-skill) events corresponding to a warmer (colder) IO and easterly (westerly) QBO phase. The physical link is that a warm IO could increase the low-level convective instability and thus amplify MJO convection over the IO, whereas an easterly QBO phase could weaken the Maritime Continent barrier effect by weakening the static stability near the tropopause, thus favoring eastward propagation of the MJO. It is also found that the combined effects of IO SST and QBO phases are more effective in influencing MJO prediction skill than individual LFBS.
Cai, Wenju, Libao Gao, Yiyong Luo, Xichen Li, Xiao-Tong Zheng, Xuebin Zhang, Xuhua Cheng, Fan Jia, Ariaan Purich, Agus Santoso, Yan Du, David M Holland, Jia-Rui Shi, Baoqiang Xiang, and Shang-Ping Xie, May 2023: Southern Ocean warming and its climatic impacts. Science Bulletin, 68(9), DOI:10.1016/j.scib.2023.03.049946-960. Abstract
The Southern Ocean has warmed substantially, and up to early 21st century, Antarctic stratospheric ozone depletion and increasing atmospheric CO2 have conspired to intensify Southern Ocean warming. Despite a projected ozone recovery, fluxes to the Southern Ocean of radiative heat and freshwater from enhanced precipitation and melting sea ice, ice shelves, and ice sheets are expected to increase, as is a Southern Ocean westerly poleward intensification. The warming has far-reaching climatic implications for melt of Antarctic ice shelf and ice sheet, sea level rise, and remote circulations such as the intertropical convergence zone and tropical ocean-atmosphere circulations, which affect extreme weathers, agriculture, and ecosystems. The surface warm and freshwater anomalies are advected northward by the mean circulation and deposited into the ocean interior with a zonal-mean maximum at ∼45°S. The increased momentum and buoyancy fluxes enhance the Southern Ocean circulation and water mass transformation, further increasing the heat uptake. Complex processes that operate but poorly understood include interactive ice shelves and ice sheets, oceanic eddies, tropical-polar interactions, and impact of the Southern Ocean response on the climate change forcing itself; in particular, limited observations and low resolution of climate models hinder rapid progress. Thus, projection of Southern Ocean warming will likely remain uncertain, but recent community effort has laid a solid foundation for substantial progress.
Kim, Jiyeong, Sarah M Kang, Shang-Ping Xie, Baoqiang Xiang, Doyeon Kim, Xiao-Tong Zheng, and Hai Wang, June 2023: Large-scale climate response to regionally confined extratropical cooling: effect of ocean dynamics. Climate Dynamics, 60, DOI:10.1007/s00382-022-06500-03291-3306. Abstract
This study investigates the effect of ocean dynamics on the tropical climate response to localized radiative cooling over three northern extratropical land regions using hierarchical model simulations that vary in the degree of ocean coupling. Without ocean dynamics, the tropical climate response is independent of the extratropical forcing location, characterized by a southward tropical precipitation shift with a high degree of zonal symmetry, a reduced zonal sea surface temperature gradient along the equatorial Pacific, and the eastward-shifted Walker circulation. When ocean dynamical adjustments are allowed, the zonal-mean tropical precipitation shift is damped primarily via Eulerian-mean ocean heat transport. The oceanic damping effect is strongest (weakest) for North Asian (American) cooling, associated with the largest (smallest) Eulerian-mean ocean heat transport across the equatorial Pacific. The cross-equatorial ocean heat transport in the Pacific is anchored to the North Pacific subtropical high, the response of which can be inferred from the corresponding slab ocean simulations. Hence, the slab ocean simulations provide useful a priori prediction for oceanic damping efficiency. Ocean dynamics also modulates the spatial pattern of climate response in a distinct manner depending on the zonal distribution of imposed forcing. North Asian forcing induces a pronounced eastern equatorial Pacific cooling extending to the western basin, accompanying the westward shifted Walker circulation. European forcing causes cooling confined to the eastern equatorial Pacific and strengthens the Walker circulation. The tropical precipitation response in these two cases exhibits large zonal variations with a high degree of equatorial symmetry, being essentially uncorrelated with the corresponding slab ocean simulations. By contrast, North American forcing induces a sufficiently strong inter-hemispheric contrast in the tropical Pacific SST response, due to the relatively weak oceanic damping effect, producing a weaker but spatially similar tropical response to that in the slab ocean simulation. This study demonstrates that the effect of ocean dynamics in modulating the tropical climate response depends on the extratropical forcing location. The results are relevant for understanding the distinct climate response induced by aerosols from different continental sites.
Wang, Bin, Weiyi Sun, Chunhan Jin, Xiao Luo, Young-Min Yang, Tim Li, Baoqiang Xiang, Michael J McPhaden, Mark Cane, Fei-Fei Jin, Fei Liu, and Jian Liu, September 2023: Understanding the recent increase in multiyear La Niñas. Nature Climate Change, DOI:10.1038/s41558-023-01801-6. Abstract
Five out of six La Niña events since 1998 have lasted two to three years. Why so many long-lasting multiyear La Niña events have emerged recently and whether they will become more common remains unknown. Here we show that ten multiyear La Niña events over the past century had an accelerated trend, with eight of these occurring after 1970. The two types of multiyear La Niña events over this time period followed either a super El Niño or a central Pacific El Niño. We find that multiyear La Niña events differ from single-year La Niñas by a prominent onset rate, which is rooted in the western Pacific warming-enhanced zonal advective feedback for the central Pacific multiyear La Niña events type and thermocline feedback for the super El Niño multiyear La Niña events type. The results from large ensemble climate simulations support the observed multiyear La Niña events–western Pacific warming link. More multiyear La Niña events will exacerbate adverse socioeconomic impacts if the western Pacific continues to warm relative to the central Pacific.
Wei, Yuntao, Hong-Li Ren, Baoqiang Xiang, Yan Wang, Jie Wu, and Shuguang Wang, April 2023: Diverse MJO Genesis and Predictability. Bulletin of the American Meteorological Society, 104(1), DOI:10.1175/BAMS-D-22-0101.1E792-E809. Abstract
The Madden–Julian oscillation (MJO) is the dominant intraseasonal wave phenomenon influencing extreme weather and climate worldwide. Realistic simulations and accurate predictions of MJO genesis are the cornerstones for successfully monitoring, forecasting, and managing meteorological disasters 3–4 weeks in advance. Nevertheless, the genesis processes and emerging precursor signals of an eastward-propagating MJO event remain largely uncertain. Here, we find that the MJO genesis processes observed in the past four decades exhibit remarkable diversity with different seasonality and can be classified objectively into four types, namely, a novel downstream origin from the westward-propagating intraseasonal oscillation (WPISO; 20.4%), localized breeding from the Indian Ocean suppressed convection (IOSC; 15.4%), an upstream succession of the preceding weakly dispersive (WD; 25.9%), and strongly dispersive (SD; 38.3%) MJO. These four types are associated with different oceanic background states, characterized by central Pacific cooling, southern Maritime Continent warming, eastern Pacific cooling, and central Pacific warming for the WPISO, IOSC, WD, and SD types, respectively. The SD type is also favored during the easterly phase of the stratospheric quasi-biennial oscillation. Diverse convective initiations possibly imply various kinds of propagations of MJO. The subseasonal reforecasts indicate robustly distinct prediction skills for the diverse MJO genesis. A window of opportunity for skillful week 3–4 prediction probably opens with the aid of the WPISO-type MJO precursor, which has increased the predictability of primary MJO onset by 1 week. These findings suggest that the diversified MJO genesis can be skillfully foreseen by monitoring unique precursor signals and can also serve as benchmarks for evaluating contemporary models’ modeling and predicting capabilities.
Xiang, Baoqiang, Shang-Ping Xie, Sarah M Kang, and Ryan J Kramer, June 2023: An emerging Asian aerosol dipole pattern reshapes the Asian summer monsoon and exacerbates northern hemisphere warming. npj Climate and Atmospheric Science, 6, 77, DOI:10.1038/s41612-023-00400-8. Abstract
Since the early 2010s, anthropogenic aerosols have started decreasing in East Asia (EA) while have continued to increase in South Asia (SA). Yet the climate impacts of this Asian aerosol dipole (AAD) pattern remain largely unknown. Using a state-of-the-art climate model, we demonstrate that the climate response is distinctly different between the SA aerosol increases and EA aerosol decreases. The SA aerosol increases lead to ~2.7 times stronger land summer precipitation change within the forced regions than the EA aerosol decreases. Contrastingly, the SA aerosol increases, within the tropical monsoon regime, produce weak and tropically confined responses, while the EA aerosol decreases yield a pronounced northern hemisphere warming aided by extratropical mean westerly and positive air-sea feedbacks over the western North Pacific. By scaling the observed instantaneous shortwave radiative forcing, we reveal that the recent AAD induces a pronounced northern hemisphere extratropical (beyond 30°N) warming (0.024 ± 0.010 °C decade−1), particularly over Europe (0.049 ± 0.009 °C decade−1). These findings highlight the importance of the pattern effect of forcings in driving global climate and have important implications for decadal prediction.
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.
Hitchcock, Peter, Amy Butler, Andrew J Charlton-Perez, Chaim I Garfinkel, T N Stockdale, James Anstey, Dann Mitchell, Daniela I V Domeisen, Tongwen Wu, Yixiong Lu, Daniele Mastrangelo, Piero Malguzzi, Hai Lin, Ryan Muncaster, William J Merryfield, Michael Sigmond, Baoqiang Xiang, and Liwei Jia, et al., July 2022: Stratospheric Nudging And Predictable Surface Impacts (SNAPSI): a protocol for investigating the role of stratospheric polar vortex disturbances in subseasonal to seasonal forecasts. Geoscientific Model Development, 15(13), DOI:10.5194/gmd-15-5073-20225073-5092. Abstract
Major disruptions of the winter season, high-latitude stratospheric polar vortices can result in stratospheric anomalies that persist for months. These sudden stratospheric warming events are recognized as an important potential source of forecast skill for surface climate on subseasonal to seasonal timescales. Realizing this skill in operational subseasonal forecast models remains a challenge, as models must capture both the evolution of the stratospheric polar vortices in addition to their coupling to the troposphere. The processes involved in this coupling remain a topic of open research.
We present here the Stratospheric Nudging And Predictable Surface Impacts (SNAPSI) project. SNAPSI is a new model intercomparison protocol designed to study the role of the Arctic and Antarctic stratospheric polar vortex disturbances for surface predictability in subseasonal to seasonal forecast models. Based on a set of controlled, subseasonal ensemble forecasts of three recent events, the protocol aims to address four main scientific goals. First, to quantify the impact of improved stratospheric forecasts on near-surface forecast skill. Second, to attribute specific extreme events to stratospheric variability. Third, to assess the mechanisms by which the stratosphere influences the troposphere in the forecast models. Fourth, to investigate the wave processes that lead to the stratospheric anomalies themselves. Although not a primary focus, the experiments are furthermore expected to shed light on coupling between the tropical stratosphere and troposphere. The output requested will allow for a more detailed, process-based community analysis than has been possible with existing databases of subseasonal forecasts.
Lee, Jiheun, Sarah M Kang, Hanjun Kim, and Baoqiang Xiang, January 2022: Disentangling the effect of regional SST bias on the double-ITCZ problem. Climate Dynamics, 58, DOI:10.1007/s00382-021-06107-x3441-3453. Abstract
This study investigates the causes of the double intertropical convergence zone (ITCZ) bias, characterized by too northward northern Pacific ITCZ, too dry equatorial Pacific, and too zonally elongated southern Pacific rainband. While the biases within one fully coupled model GFDL CM2.1 are examined, the large-scale bias patterns are broadly common to CMIP5/6 models. We disentangle the individual contribution of regional sea surface temperature (SST) biases to the double-ITCZ bias pattern using a series of slab ocean model experiments. A previously suggested Southern Ocean warm bias effect in displacing the zonal-mean ITCZ southward is manifested in the northern Pacific ITCZ while having little contribution to the zonally elongated wet bias south of the equatorial Pacific. The excessive southern Pacific precipitation is instead induced by the warm bias along the west coast of South America. The Southern Ocean bias effect on the zonal-mean ITCZ position is diminished by the neighboring midlatitude bias of opposite sign in GFDL CM2.1. As a result, the northern extratropical cold bias turns out to be most responsible for a southward-displaced zonal-mean ITCZ. However, this southward ITCZ displacement results from the northern Pacific branch, so ironically fixing the extratropical biases only deteriorates the northern Pacific precipitation bias. Thus, we emphasize that the zonal-mean diagnostics poorly represent the spatial pattern of the tropical Pacific response. Examination of longitude-latitude structure indicates that the overall tropical precipitation bias is mostly locally driven from the tropical SST bias. While our model experiments are idealized with no ocean dynamics, the results shed light on where preferential foci should be applied in model development to improve particular features of tropical precipitation bias.
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.
Landfalling tropical cyclones (LTCs) are the most devastating disaster to affect the U.S., while the demonstration of skillful subseasonal (between 10 days and one season) prediction of LTCs is less promising. Understanding the mechanisms governing the subseasonal variation of TC activity is fundamental to improving its forecast, which is of critical interest to decision-makers and the insurance industry. This work reveals three localized atmospheric circulation modes with significant 10–30 days subseasonal variations: Piedmont Oscillation (PO), Great America Dipole (GAD), and the Subtropical High ridge (SHR) modes. These modes strongly modulate precipitation, TC genesis, intensity, track, and landfall near the U.S. coast. Compared to their strong negative phases, the U.S. East Coast has 19 times more LTCs during the strong positive phases of PO, and the Gulf Coast experiences 4–12 times more frequent LTCs during the positive phases of GAD and SHR. Results from the GFDL SPEAR model show a skillful prediction of 13, 9, and 22 days for these three modes, respectively. Our findings are expected to benefit the prediction of LTCs on weather timescale and also suggest opportunities exist for subseasonal predictions of LTCs and their associated heavy rainfalls.
Zhang, Wei, Ben P Kirtman, Baoqiang Xiang, Leo Siqueira, Johnna Infanti, and Natalie Perlin, January 2022: Decadal variability of Southeast US rainfall in an eddying global coupled model. Geophysical Research Letters, 49(1), DOI:10.1029/2021GL096709. Abstract
Ocean variability is a dominant source of remote rainfall predictability, but in many cases the physical mechanisms driving this predictability are not fully understood. This study examines how ocean mesoscales (i.e., the Gulf Stream SST front) affect decadal Southeast US (SEUS) rainfall, arguing that the local imprint of large-scale teleconnections is sensitive to resolved mesoscale features. Based on global coupled model experiments with eddying and eddy-parameterizing ocean, we find that a resolved Gulf Stream improves localized rainfall and remote circulation response in the SEUS. The eddying model generally improves the air-sea interactions in the Gulf Stream and the North Atlantic Subtropical High that modulate SEUS rainfall over decadal timescales. The eddy-parameterizing simulation fails to capture the sharp SST gradient associated with the Gulf Stream and overestimates the role of tropical Pacific SST anomalies in the SEUS rainfall.
We describe the third version of the Geophysical Fluid Dynamics Laboratory cloud microphysics scheme (GFDL MP v3) implemented in the System for High-resolution prediction on Earth-to-Local Domains (SHiELD). Compared to the GFDL MP v2, the GFDL MP v3 is entirely reorganized, optimized, and modularized into functions. The particle size distribution (PSD) of all hydrometeor categories is redefined to better mimic observations, and the cloud droplet number concentration (CDNC) is calculated from the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA2) aerosol data. In addition, the GFDL MP has been redesigned so all processes use the redefined PSD to ensure overall consistency and easily permit the introduction of new PSDs and microphysical processes. A year's worth of global 13-km, 10-day weather forecasts were performed with the new GFDL MP. Compared to the GFDL MP v2, the GFDL MP v3 significantly improves SHiELD's predictions of geopotential height, air temperature, and specific humidity in the Troposphere, as well as the high, middle and total cloud fractions and the liquid water path. The predictions are improved even further by the use of reanalysis aerosol data to calculate CDNC, and also by using the more realistic PSD available in GFDL MP v3. However, the upgrade of the GFDL MP shows little impact on the precipitation prediction. Degradations caused by the new scheme are discussed and provide a guide for future GFDL MP development.
Kang, Sarah M., Shang-Ping Xie, Clara Deser, and Baoqiang Xiang, December 2021: Zonal mean and shift modes of historical climate response to evolving aerosol distribution. Science Bulletin, 66(23), DOI:10.1016/j.scib.2021.07.0132405-2411. Abstract
Anthropogenic aerosols are effective radiative forcing agents that perturb the Earth’s climate. Major emission sources shifted from the western to eastern hemisphere around the 1980s. An ensemble of single-forcing simulations with an Earth System Model reveals two stages of aerosol-induced climate change in response to the global aerosol increase for 1940–1980 and the zonal shift of aerosol forcing for 1980–2020, respectively. Here, using idealized experiments with hierarchical models, we show that the aerosol increase and shift modes of aerosol-forced climate change are dynamically distinct, governed by the inter-hemispheric energy transport and basin-wide ocean–atmosphere interactions, respectively. The aerosol increase mode dominates in the motionless slab ocean model but is damped by ocean dynamics. Free of zonal-mean energy perturbation, characterized by an anomalous North Atlantic warming and North Pacific cooling, the zonal shift mode is amplified by interactive ocean dynamics through Bjerknes feedback. Both modes contribute to a La Niña-like pattern over the equatorial Pacific. We suggest that a global perspective that accommodates the evolving geographical distribution of aerosol emissions is vital for understanding the aerosol-forced historical climate change.
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 present the System for High‐resolution prediction on Earth‐to‐Local Domains (SHiELD), an atmosphere model developed by the Geophysical Fluid Dynamics Laboratory (GFDL) coupling the nonhydrostatic FV3 Dynamical Core to a physics suite originally taken from the Global Forecast System. SHiELD is designed to demonstrate new capabilities within its components, explore new model applications, and to answer scientific questions through these new functionalities. A variety of configurations are presented, including short‐to‐medium‐range and subseasonal‐to‐seasonal prediction, global‐to‐regional convective‐scale hurricane and contiguous U.S. precipitation forecasts, and global cloud‐resolving modeling. Advances within SHiELD can be seamlessly transitioned into other Unified Forecast System or FV3‐based models, including operational implementations of the Unified Forecast System. Continued development of SHiELD has shown improvement upon existing models. The flagship 13‐km SHiELD demonstrates steadily improved large‐scale prediction skill and precipitation prediction skill. SHiELD and the coarser‐resolution S‐SHiELD demonstrate a superior diurnal cycle compared to existing climate models; the latter also demonstrates 28 days of useful prediction skill for the Madden‐Julian Oscillation. The global‐to‐regional nested configurations T‐SHiELD (tropical Atlantic) and C‐SHiELD (contiguous United States) show significant improvement in hurricane structure from a new tracer advection scheme and promise for medium‐range prediction of convective storms.
Positive precipitation biases over western North America have remained a pervasive problem in the current generation of coupled global climate models. These biases are substantially reduced, however, in a version of the Geophysical Fluid Dynamics Laboratory Forecast-oriented Low Ocean Resolution (FLOR) coupled climate model with systematic sea surface temperature (SST) biases artificially corrected through flux adjustment. This study examines how the SST biases in the Atlantic and Pacific Oceans contribute to the North American precipitation biases. Experiments with the FLOR model in which SST biases are removed in the Atlantic and Pacific are carried out to determine the contribution of SST errors in each basin to precipitation statistics over North America. Tropical and North Pacific SST biases have a strong impact on northern North American precipitation, while tropical Atlantic SST biases have a dominant impact on precipitation biases in southern North America, including the western United States. Most notably, negative SST biases in the tropical Atlantic in boreal winter induce an anomalously strong Aleutian low and a southward bias in the North Pacific storm track. In boreal summer, the negative SST biases induce a strengthened North Atlantic Subtropical High and Great Plains low-level jet. Each of these impacts contributes to positive annual mean precipitation biases over western North America. Both North Pacific and North Atlantic SST biases induce SST biases in remote basins through dynamical pathways, so a complete attribution of the effects of SST biases on precipitation must account for both the local and remote impacts.
Kang, Sarah M., Shang-Ping Xie, Yechul Shin, Hanjun Kim, Yen-Ting Hwang, Malte F Stuecker, Baoqiang Xiang, and Matt Hawcroft, November 2020: Walker circulation response to extratropical radiative forcing. Science Advances, 6(47), DOI:10.1126/sciadv.abd3021. Abstract
Walker circulation variability and associated zonal shifts in the heating of the tropical atmosphere have far-reaching global impacts well into high latitudes. Yet the reversed high latitude–to–Walker circulation teleconnection is not fully understood. Here, we reveal the dynamical pathways of this teleconnection across different components of the climate system using a hierarchy of climate model simulations. In the fully coupled system with ocean circulation adjustments, the Walker circulation strengthens in response to extratropical radiative cooling of either hemisphere, associated with the upwelling of colder subsurface water in the eastern equatorial Pacific. By contrast, in the absence of ocean circulation adjustments, the Walker circulation response is sensitive to the forcing hemisphere, due to the blocking effect of the northward-displaced climatological intertropical convergence zone and shortwave cloud radiative effects. Our study implies that energy biases in the extratropics can cause pronounced changes of tropical climate patterns.
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.
Tropical cyclone (TC) genesis prediction at the extended-range to subseasonal timescale (a week to several weeks) is a gap between weather and climate predictions. The current dynamical prediction systems and statistical models show limited skills in TC genesis forecasting at the lead time of 1–3 weeks. A hybrid dynamical-statistical model is developed that reveals capability in predicting basin-wide TC frequency in every 10-day period over the western North Pacific at a 25-day forecast lead, which is superior to the statistical and dynamical model-based predictions examined in this study. In this hybrid model, the cyclogenesis counts for different TC clusters are predicted, respectively, using the statistical models in which the large-scale predictors associated with intraseasonal oscillation evolutions are provided by a dynamical model. A probabilistic map of TC tracks at the subseasonal timescale is further predicted by incorporating the climatological probability of track distributions of these TC clusters.
Subseasonal climate prediction has emerged as a top forecast priority but remains a great challenge. Subseasonal extreme prediction is even more difficult than predicting the time‐mean variability. Here we show that the wintertime cold extremes, measured by the frequency of extreme cold days (ECDs), are skillfully predicted by the European Centre for Medium‐Range Weather Forecasts (ECMWF) model 2‐4 weeks in advance over a large fraction of the Northern Hemisphere land region. The physical basis for such skill in predicting ECDs is primarily rooted in predicting a small subset of leading empirical orthogonal function (EOF) modes of ECDs identified from observations, including two modes in Eurasia (North Atlantic Oscillation and Eurasia Meridional Dipole mode), and three modes in North America (North Pacific Oscillation, Pacific‐North America teleconnection mode and the North America Zonal Dipole mode). It is of interest to note that these two modes in Eurasia are more predictable than the three leading modes in North America mainly due to their longer persistence.
The source of predictability for the leading EOF modes mainly originates from atmospheric internal modes and the land‐atmosphere coupling. All these modes are strongly coupled to dynamically coherent planetary‐scale atmospheric circulations, which not only amplify but also prolong the surface air temperature anomaly, serving as a source of predictability at subseasonal timescales. The Eurasian Meridional Dipole mode is also tied to the lower‐boundary snow anomaly, and the snow‐atmosphere coupling helps sustain this mode and provides a source of predictability.
We document the configuration and emergent simulation features from the Geophysical Fluid Dynamics Laboratory (GFDL) OM4.0 ocean/sea‐ice model. OM4 serves as the ocean/sea‐ice component for the GFDL climate and Earth system models. It is also used for climate science research and is contributing to the Coupled Model Intercomparison Project version 6 Ocean Model Intercomparison Project (CMIP6/OMIP). The ocean component of OM4 uses version 6 of the Modular Ocean Model (MOM6) and the sea‐ice component uses version 2 of the Sea Ice Simulator (SIS2), which have identical horizontal grid layouts (Arakawa C‐grid). We follow the Coordinated Ocean‐sea ice Reference Experiments (CORE) protocol to assess simulation quality across a broad suite of climate relevant features. We present results from two versions differing by horizontal grid spacing and physical parameterizations: OM4p5 has nominal 0.5° spacing and includes mesoscale eddy parameterizations and OM4p25 has nominal 0.25° spacing with no mesoscale eddy parameterization.
MOM6 makes use of a vertical Lagrangian‐remap algorithm that enables general vertical coordinates. We show that use of a hybrid depth‐isopycnal coordinate reduces the mid‐depth ocean warming drift commonly found in pure z* vertical coordinate ocean models. To test the need for the mesoscale eddy parameterization used in OM4p5, we examine the results from a simulation that removes the eddy parameterization. The water mass structure and model drift are physically degraded relative to OM4p5, thus supporting the key role for a mesoscale closure at this resolution.
We use the fvGFS model developed at the Geophysical Fluid Dynamics Laboratory (GFDL) to demonstrate the potential of the upcoming United States Next Generation Global Prediction System for hurricane prediction. The fvGFS retrospective forecasts initialized with the European Centre for Medium‐Range Weather Forecasts (ECMWF) data showed much‐improved track forecasts for the 2017 Atlantic hurricane season compared to the best performing ECMWF operational model. The fvGFS greatly improved the ECMWF's poor track forecast for Hurricane Maria (2017). For Hurricane Irma (2017), a well‐predicted case by the ECMWF model, the fvGFS produced even lower 5‐day track forecast errors. The fvGFS also showed better intensity prediction than both the United States and the ECMWF operational models, indicating the robustness of its numerical algorithms.
Ding, L, Tim Li, Baoqiang Xiang, and M S Peng, October 2019: On the Westward Turning of Hurricane Sandy (2012): Effect of Atmospheric Intraseasonal Oscillations. Journal of Climate, 32(20), DOI:10.1175/JCLI-D-18-0663.1. Abstract
Hurricane Sandy (2012) experienced an unusual westward turning and made landfall in New Jersey after its northward movement over the Atlantic. The landfall caused severe casualties and great economic losses. The westward turning took place in the mid-latitude Atlantic where the climatological mean wind is eastward. The cause of this unusual westward track is investigated through both observational analysis and model simulations.
The observational analysis indicates that the hurricane steering flow was primarily controlled by atmospheric intraseasonal oscillation (ISO), which was characterized by a pair of anticyclonic and cyclonic circulation systems. The anticyclone to the north was part of a global wave train forced by convection over the tropical Indian Ocean through Rossby wave energy dispersion, while the cyclone to the south originated from the tropical Atlantic through northward propagation. Hindcast experiments using a global coupled model show that the model is able to predict the observed circulation pattern as well as the westward steering flow six days prior to Sandy’s landfall. Sensitivity experiments with different initial dates confirm the important role of the ISO in establishing the westward steering flow in the mid-latitude Atlantic. Thus the successful numerical model experiments suggest a potential for extended-range dynamical tropical cyclone track predictions.
Ham, S, A-Young Lim, Suchul Kang, H Jeong, Y Jeong, Bin Wang, and Baoqiang Xiang, et al., September 2019: Correction to: A newly developed APCC SCoPS and its prediction of East Asia seasonal climate variability. Climate Dynamics, 53(5-6), DOI:10.1007/s00382-019-04894-y. Abstract
The original article can be found online at https://doi.org/10.1007/s00382-018-4516-5
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.
Kang, Sarah M., Matt Hawcroft, and Baoqiang Xiang, et al., December 2019: Extratropical–Tropical Interaction Model Intercomparison Project (Etin-Mip): Protocol and Initial Results. Bulletin of the American Meteorological Society, 100(12), DOI:10.1175/BAMS-D-18-0301.1. Abstract
This article introduces the Extratropical–Tropical Interaction Model Intercomparison Project (ETIN-MIP), where a set of fully coupled model experiments are designed to examine the sources of longstanding tropical precipitation biases in climate models. In particular, we reduce insolation over three targeted latitudinal bands of persistent model biases: the southern extratropics, the southern tropics, and the northern extratropics. To address the effect of regional energy bias corrections on the mean distribution of tropical precipitation, such as the double intertropical convergence zone problem, we evaluate the quasi-equilibrium response of the climate system corresponding to a 50-yr period after the 100 years of prescribed energy perturbation. Initial results show that, despite a large intermodel spread in each perturbation experiment due to differences in ocean heat uptake response and climate feedbacks across models, the southern tropics is most efficient at driving a meridional shift of tropical precipitation. In contrast, the extratropical energy perturbations are effectively damped by anomalous heat uptake over the subpolar oceans, thereby inducing a smaller meridional shift of tropical precipitation compared with the tropical energy perturbations. The ETIN-MIP experiments allow us to investigate the global implications of regional energy bias corrections, providing a route to guide the practice of model development, with implications for understanding dynamical responses to anthropogenic climate change and geoengineering.
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, Xiaoye, F Liu, Bin Wang, and Baoqiang Xiang, et al., August 2019: Different responses of East Asian summer rainfall to El Nino decays. Climate Dynamics, 53(3-4), DOI:10.1007/s00382-019-04684-6. Abstract
The East Asian summer monsoon (EASM) shows notable change during the summer after El Nino peak. This delayed response, however, is variable and difficult to predict. Here, we revisit this issue by separating El Nino decays into early transition and late transition. In the summer after an early transition, the central-to-eastern Pacific evolves into a La Nina condition, with positive rainfall anomaly occurring over most parts of eastern China. In contrast, in the summer after a late transition, the central-to-eastern Pacific sea surface temperature (SST)anomaly remains neutral or slightly above normal; correspondingly, the East Asian rainfall anomaly shows a tripolar structure with positive anomaly over the Yangtze-Huaihe River valley and negative anomalies over northern and southern China. These different rainfall responses are mainly related to different locations of the anomalous anticyclone (AAC) over the western North Pacific (WNP): it is centered at (165 degrees E, 25 degrees N) for late-transition El Ninos, but at (135 degrees E, 16 degrees N) for early-transition El Ninos. During the late transition, the AAC-SST feedback, identified by the dipole SST mode consisting of WNP cooling and northern Indian Ocean (NIO) warming, mainly works to support the WNP AAC. During the early transition, the AAC-SST feedback is weak and mainly attributed to NIO warming. The strong easterly anomaly over the western equatorial Pacific, which is tied to the central-to-eastern equatorial Pacific cooling and dipole precipitation pattern from western equatorial Pacific to the Maritime Continent, occurs to support the AAC and pulls it equatorward. These distinct responses exist in the last century, and the CMIP5 models can reproduce these distinct responses well except that the models underestimate the AAC-SST feedback for late-transition El Ninos. The findings in this study help predict the EASM rainfall in post-El Nino years, but the key is the accurate prediction of the timing of decay.
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 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.
Wang, Bin, Juan Li, Mark Cane, J Liu, P J Webster, and Baoqiang Xiang, et al., April 2018: Towards predicting changes in the land monsoon rainfall a decade in advance. Journal of Climate, 31(7), DOI:10.1175/JCLI-D-17-0521.1. Abstract
Predictions of changes of the land monsoon rainfall (LMR) in the coming decades are of vital importance for successful sustainable economic development. Current dynamic models, though, have shown little skill in the decadal prediction of the Northern Hemisphere (NH) LMR. The physical basis and predictability for such predictions remain largely unexplored. Decadal change of the NHLMR reflects changes in the total NH continental precipitation, tropical general circulation, and regional land monsoon rainfall over northern Africa, India, East Asia, and North America. Using observations from 1901 to 2014 and numerical experiments, we show that the decadal variability of the NHLMR is rooted primarily in (a) the north-south hemispheric thermal contrast in the Atlantic-Indian Ocean sector measured by the North Atlantic-southern Indian Ocean dipole (NAID) sea surface temperature (SST) index, and (b) an east-west thermal contrast in the Pacific measured by an Extended El Nino-Southern Oscillation (XEN) index. Results from a 500-year pre-industrial control experiment demonstrate that the leading mode of decadal NHLMR and the associated NAID and XEN SST anomalies may be largely an internal mode of the Earth’s climate system, although possibly modified by natural and anthropogenic external forcing. A 51-year, independent forward–rolling decadal hindcast was made with a hybrid dynamic-conceptual model and using the NAID index predicted by a multi-climate model ensemble. The results demonstrate that the decadal changes in the NHLMR can be predicted approximately a decade in advance with significant skills, opening a promising way forward for decadal predictions of regional land monsoon rainfall worldwide.
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.
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.
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.
Li, K, Z Li, Y Yang, and Baoqiang Xiang, et al., July 2016: Strong modulations on the Bay of Bengal monsoon onset vortex by the first northward-propagating intra-seasonal oscillation. Climate Dynamics, 47(1), DOI:10.1007/s00382-015-2826-4. Abstract
Monsoon onset vortex (OV) in the form of tropical cyclone is often observed in the pre-monsoon period and contributes to the subsequent abrupt establishment of summer monsoon over the Bay of Bengal (BoB). It is identified here that all historical OVs occurred during the convection-enhanced phase of the first northward-propagating intra-seasonal oscillation (FNISO). The individual contributions from the four large scale environmental fields associated with the intra-seasonal variations to the cyclone genesis are diagnosed with the aid of the genesis potential index. The significant moistening of mid-level atmosphere, which is embedded in the FNISO convection-enhanced phase, is shown to be the primary factor leading to the cyclone genesis. The water vapor budget analysis is further done to understand the governing process for the mid-level humidity increase. It is clearly seen that the vertical advection process, dominated by the anomalous vertical advection of the mean vertical water vapor gradient, plays the critical role. Hence the OVs are shown to be strongly modulated by FNISOs, both of which are important elements of the complex story of the BoB monsoon onset.
Cao, J, Bin Wang, and Baoqiang Xiang, et al., May 2015: Major Modes of Short-Term Climate Variability in the Newly Developed NUIST Earth System Model (NESM). Advances in Atmospheric Sciences, 32(5), DOI:10.1007/s00376-014-4200-6. Abstract
A coupled earth system model (ESM) has been developed at the Nanjing University of Information Science and Technology (NUIST) by using version 5.3 of the European Centre Hamburg Model (ECHAM), version 3.4 of the Nucleus for European Modelling of the Ocean (NEMO), and version 4.1 of the Los Alamos sea ice model (CICE). The model is referred to as NUIST ESM1 (NESM1). Comprehensive and quantitative metrics are used to assess the model’s major modes of climate variability most relevant to subseasonal-to-interannual climate prediction. The model’s assessment is placed in a multi-model framework. The model yields a realistic annual mean and annual cycle of equatorial SST, and a reasonably realistic precipitation climatology, but has difficulty in capturing the spring-fall asymmetry and monsoon precipitation domains. The ENSO mode is reproduced well with respect to its spatial structure, power spectrum, phase locking to the annual cycle, and spatial structures of the central Pacific (CP)-ENSO and eastern Pacific (EP)-ENSO; however, the equatorial SST variability, biennial component of ENSO, and the amplitude of CP-ENSO are overestimated. The model captures realistic intraseasonal variability patterns, the vertical-zonal structures of the first two leading predictable modes of Madden-Julian Oscillation (MJO), and its eastward propagation; but the simulated MJO speed is significantly slower than observed. Compared with the T42 version, the high resolution version (T159) demonstrates improved simulation with respect to the climatology, interannual variance, monsoon-ENSO lead-lag correlation, spatial structures of the leading mode of the Asian-Australian monsoon rainfall variability, and the eastward propagation of the MJO.
Wang, Bin, June-Yi Lee, and Baoqiang Xiang, January 2015: Asian summer monsoon rainfall predictability: a predictable mode analysis. Climate Dynamics, 44(1-2), DOI:10.1007/s00382-014-2218-1. Abstract
To what extent the Asian summer monsoon (ASM) rainfall is predictable has been an important but long-standing issue in climate science. Here we introduce a predictable mode analysis (PMA) method to estimate predictability of the ASM rainfall. The PMA is an integral approach combining empirical analysis, physical interpretation and retrospective prediction. The empirical analysis detects most important modes of variability; the interpretation establishes the physical basis of prediction of the modes; and the retrospective predictions with dynamical models and physics-based empirical (P–E) model are used to identify the “predictable” modes. Potential predictability can then be estimated by the fractional variance accounted for by the “predictable” modes. For the ASM rainfall during June–July–August, we identify four major modes of variability in the domain (20°S–40°N, 40°E–160°E) during 1979–2010: (1) El Niño-La Nina developing mode in central Pacific, (2) Indo-western Pacific monsoon-ocean coupled mode sustained by a positive thermodynamic feedback with the aid of background mean circulation, (3) Indian Ocean dipole mode, and (4) a warming trend mode. We show that these modes can be predicted reasonably well by a set of P–E prediction models as well as coupled models’ multi-model ensemble. The P–E and dynamical models have comparable skills and complementary strengths in predicting ASM rainfall. Thus, the four modes may be regarded as “predictable” modes, and about half of the ASM rainfall variability may be predictable. This work not only provides a useful approach for assessing seasonal predictability but also provides P–E prediction tools and a spatial-pattern-bias correction method to improve dynamical predictions. The proposed PMA method can be applied to a broad range of climate predictability and prediction problems.
Wang, Bin, and Baoqiang Xiang, et al., May 2015: Rethinking Indian monsoon rainfall prediction in the context of recent global warming. Nature Communications, 6, 7154, DOI:10.1038/ncomms8154. Abstract
Prediction of Indian summer monsoon rainfall (ISMR) is at the heart of tropical climate prediction. Despite enormous progress having been made in predicting ISMR since 1886, the operational forecasts during recent decades (1989–2012) have little skill. Here we show, with both dynamical and physical–empirical models, that this recent failure is largely due to the models’ inability to capture new predictability sources emerging during recent global warming, that is, the development of the central-Pacific El Nino-Southern Oscillation (CP–ENSO), the rapid deepening of the Asian Low and the strengthening of North and South Pacific Highs during boreal spring. A physical–empirical model that captures these new predictors can produce an independent forecast skill of 0.51 for 1989–2012 and a 92-year retrospective forecast skill of 0.64 for 1921–2012. The recent low skills of the dynamical models are attributed to deficiencies in capturing the developing CP–ENSO and anomalous Asian Low. The results reveal a considerable gap between ISMR prediction skill and predictability.
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.
Yun, K-S, K-J Ha, S-K Yeh, Bin Wang, and Baoqiang Xiang, March 2015: Critical role of boreal summer North Pacific subtropical highs in ENSO transition. Climate Dynamics, 44(7-8), DOI:10.1007/s00382-014-2193-6. Abstract
The quasi-biennial (QB)-type El Niño-Southern Oscillation (ENSO), showing a fast phase transition from El Niño to La Niña, is closely related to the variability of the North Pacific subtropical high (NPSH) and western North Pacific subtropical high (WNPSH) during summer. Here, we show that the NPSH plays a key role in the fast ENSO transition. The QB-type ENSO is associated with both strengthened WNPSH and NPSH during the boreal summer. By contrast, the low-frequency-type ENSO, which occurs in a typical period of 3–7 years, displays an enhanced WNPSH but weakened NPSH. The stronger El Niño tends to generate a more intensified WNPSH from spring to summer, leading to the initial decay of El Niño via the modulation of easterly wind in the western Pacific. On the contrary, the NPSH has greater linkage with the decaying El Niño process after the boreal summer. Therefore, the coupled pattern of WNPSH–NPSH is important in changing ENSO phase from El Niño to La Niña. The NPSH causes sea surface temperature cooling over the subtropical Northeastern Pacific. The resultant subtropical cooling induces anomalous anticyclone west of the reduced heating, which generates the strengthening of trade winds south of the anticyclone. Consequently, this process contributes to tropical central Pacific cooling and the rapid transition of El Niño to La Niña. This study hints that the QB-type ENSO could be significantly linked to a tropics-midlatitudes coupled system such as an in-phase pattern between WNPSH and NPSH. The results are useful for improvement of ENSO prediction.
Su, J, Baoqiang Xiang, Bin Wang, and Tim Li, December 2014: Abrupt termination of the 2012 Pacific warming and its implication on ENSO prediction. Geophysical Research Letters, 41(24), DOI:10.1002/2014GL062380. Abstract
In the summer of 2012, there was a clear signal of the developing El Niño over the equatorial Pacific and many climate models forecasted the occurrence of El Niño with a peak phase in the subsequent winter. However, the warming was aborted abruptly in late fall. Here we show that the abrupt termination of the 2012 Pacific warming was largely attributed to the anomalous sea surface temperature (SST) cooling in the northeastern and southeastern subtropical Pacific. The anomalous SST cooling induced strong easterly and low-level divergence anomalies, suppressing the development of westerly and convection anomalies over the equatorial central Pacific. Thus, the surface warming over the equatorial Pacific was decoupled from the surface wind forcing and subsurface thermocline variability, inhibiting its further development into a mature El Niño in the winter of 2012–2013. This study highlights the importance of the SST anomaly in the subtropical Pacific in El Niño prediction.
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.
