Camargo, Suzana J., Hiroyuki Murakami, Nadia Bloemendaal, Savin S Chand, Medha S Deshpande, Christian Dominguez-Sarmiento, Juan Jesús González-Alemán, and Thomas R Knutson, et al., September 2023: An update on the influence of natural climate variability and anthropogenic climate change on tropical cyclones. Tropical Cyclone Research and Review, 12(3), DOI:10.1016/j.tcrr.2023.10.001216-239. Abstract
A substantial number of studies have been published since the Ninth International Workshop on Tropical Cyclones (IWTC-9) in 2018, improving our understanding of the effect of climate change on tropical cyclones (TCs) and associated hazards and risks. These studies have reinforced the robustness of increases in TC intensity and associated TC hazards and risks due to anthropogenic climate change. New modeling and observational studies suggested the potential influence of anthropogenic climate forcings, including greenhouse gases and aerosols, on global and regional TC activity at the decadal and century time scales. However, there are still substantial uncertainties owing to model uncertainty in simulating historical TC decadal variability in the Atlantic, and the limitations of observed TC records. The projected future change in the global number of TCs has become more uncertain since IWTC-9 due to projected increases in TC frequency by a few climate models. A new paradigm, TC seeds, has been proposed, and there is currently a debate on whether seeds can help explain the physical mechanism behind the projected changes in global TC frequency. New studies also highlighted the importance of large-scale environmental fields on TC activity, such as snow cover and air-sea interactions. Future projections on TC translation speed and medicanes are new additional focus topics in our report. Recommendations and future research are proposed relevant to the remaining scientific questions and assisting policymakers.
Extreme precipitation is among the most destructive natural disasters. Simulating changes in regional extreme precipitation remains challenging, partially limited by climate models’ horizontal resolution. Here, we use an ensemble of high-resolution global climate model simulations to study September–November extreme precipitation over the Northeastern United States, where extremes have increased rapidly since the mid-1990s. We show that a model with 25 km horizontal resolution simulates much more realistic extreme precipitation than comparable models with 50 or 100 km resolution, including frequency, amplitude, and temporal variability. The 25 km model simulated trends are quantitatively consistent with observed trends over recent decades. We use the same model for future projections. By the mid-21st century, the model projects unprecedented rainfall events over the region, driven by increasing anthropogenic radiative forcing and distinguishable from natural variability. Very extreme events (>150 mm/day) may be six times more likely by 2100 than in the early 21st century.
Lee, Chia-Ying, Adam H Sobel, Michael K Tippett, Suzana J Camargo, Marc Wüest, Michael F Wehner, and Hiroyuki Murakami, November 2023: Climate change signal in Atlantic tropical cyclones today and near future. Earth's Future, 11(11), DOI:10.1029/2023EF003539. Abstract
This manuscript discusses the challenges in detecting and attributing recently observed trends in the Atlantic tropical cyclone (TC) and the epistemic uncertainty we face in assessing future risk. We use synthetic storms downscaled from five CMIP5 models by the Columbia HAZard model (CHAZ), and directly simulated storms from high-resolution climate models. We examine three aspects of recent TC activity: the upward trend and multi-decadal oscillation of the annual frequency, the increase in storm wind intensity, and the decrease in forward speed. Some data sets suggest that these trends and oscillation are forced while others suggest that they can be explained by natural variability. Projections under warming climate scenarios also show a wide range of possibilities, especially for the annual frequencies, which increase or decrease depending on the choice of moisture variable used in the CHAZ model and on the choice of climate model. The uncertainties in the annual frequency lead to epistemic uncertainties in TC risk assessment. Here, we investigate the potential for reduction of these epistemic uncertainties through a statistical practice, namely likelihood analysis. We find that historical observations are more consistent with the simulations with increasing frequency than those with decreasing frequency, but we are not able to rule out the latter. We argue that the most rational way to treat epistemic uncertainty is to consider all outcomes contained in the results. In the context of risk assessment, since the results contain possible outcomes in which TC risk is increasing, this view implies that the risk is increasing.
Qian, Yitian, Pang-Chi Hsu, Hiroyuki Murakami, Gan Zhang, Huijun Wang, and Mingkeng Duan, December 2023: Intraseasonal variability of anticyclonic Rossby wave breaking and its impact on tropical cyclone activity over the western North Pacific. Journal of Climate, 37(1), DOI:10.1175/JCLI-D-23-0091.1179-197. Abstract
The intraseasonal variations in anticyclonic Rossby wave breaking (AWB) events, which are characterized by synoptic-scale irreversible meridional overturning of potential vorticity over the North Pacific, and their modulations on tropical cyclone (TC) activity over the western North Pacific (WNP), were investigated in this study. Spectral analysis of the AWB frequency shows significant variability within a period of 7–40 days, closely linked to the subseasonal variability of the jet stream intensity. When the jet stream weakens at its exit region over the North Pacific, the AWB occurs along with an equatorward Rossby wave flux. This AWB is preceded by an intensified Rossby wave train across Eurasia 12 days earlier. Simultaneously, a high potential vorticity intrusion is advected in the upper troposphere from the North Pacific toward the WNP, and suppressed TC activities are observed over the WNP open ocean where decreased moisture and temperature, subsidence, and increased vertical wind shear prevail. In contrast, anomalously enhanced convection, positive relative vorticity, and ascending motion are found in the southwestern quadrant of the AWB, facilitating enhanced TC activities over the South China Sea (SCS). Further analysis indicates that the impact of the AWB on TC activities over the WNP is robust and independent of the tropical intraseasonal convection over the tropical Indian Ocean and SCS, even though it accompanies the increased AWB frequency.
Qian, Yitian, Pang-Chi Hsu, Hiroyuki Murakami, Jianyun Gao, Huijing Wang, and Mingkeng Duan, November 2023: Influences of ENSO and intraseasonal oscillations on distinct tropical cyclone clusters over the western North Pacific. Climate Dynamics, DOI:10.1007/s00382-023-07000-5. Abstract
Although the influences of El Niño–Southern Oscillation (ENSO) and boreal summer intraseasonal oscillation (ISO) on basin-wide tropical cyclone (TC) activity over the western North Pacific (WNP) have been widely recognized, how the seasonal and subseasonal anomalies of sea surface temperature and atmospheric ISO variations modulate different types of WNP TCs needed further examination, as addressed in this study. Using a fuzzy c-means clustering method, we objectively classified the WNP TCs into seven distinct clusters with different genesis locations and trajectories. The genesis numbers of all seven TC clusters revealed significant spectral variance at the intraseasonal timescale in the bands of 10–30 and 30–90 days. Based on the diagnosis of scale-decomposed genesis potential index, we found that the increase in ISO-related mid-tropospheric moistening plays the most important role in TC genesis for all seven clusters, while anomalous circulations (low-level vorticity and mid-level vertical motion) are secondary. The trajectories associated with straight-moving and recurving TC clusters are modulated by ISO-related steering flows. These modulations of TC activities by ISO vary with the phase of ENSO. The modulations of ISO are significantly greater for TCs generated in the southeast quadrant of the WNP in El Niño years than in La Niña years, while ISO imposes a larger impact on landfalling TCs occurring in La Niña years, which are changed by the low-level winds associated with ENSO conditions. The compound effects of ENSO and ISO on TC clusters provide useful sources of subseasonal TC predictability. Our statistical model using the information of ENSO and ISO shows skillful predictions of WNP TC genesis numbers and track distributions at the lead time up to 30 days.
Takaya, Yuhei, Louis-Philippe Caron, Eric Blake, François Bonnardot, Nicolas Bruneau, Joanne Camp, Johnny C L Chan, Paul Gregory, Jhordanne J Jones, Namyoung Kang, Philip J Klotzbach, Yuriy Kuleshov, Marie-Dominique Leroux, Julia F Lockwood, and Hiroyuki Murakami, et al., September 2023: Recent advances in seasonal and multi-annual tropical cyclone forecasting. Tropical Cyclone Research and Review, 12(3), DOI:10.1016/j.tcrr.2023.09.003182-199. Abstract
Seasonal tropical cyclone (TC) forecasting has evolved substantially since its commencement in the early 1980s. However, present operational seasonal TC forecasting services still do not meet the requirements of society and stakeholders: current operational products are mainly basin-scale information, while more detailed sub-basin scale information such as potential risks of TC landfall is anticipated for decision making. To fill this gap and make the TC science and services move forward, this paper reviews recent research and development in seasonal tropical cyclone (TC) forecasting. In particular, this paper features new research topics on seasonal TC predictability in neutral conditions of El Niño–Southern Oscillation (ENSO), emerging forecasting techniques of seasonal TC activity including Machine Learning/Artificial Intelligence, and multi-annual TC predictions. We also review the skill of forecast systems at predicting landfalling statistics for certain regions of the North Atlantic, Western North Pacific and South Indian oceans and discuss the gap that remains between current products and potential user's expectations. New knowledge and advanced forecasting techniques are expected to further enhance the capability of seasonal TC forecasting and lead to more actionable and fit-for-purpose products.
It remains a mystery if and how anthropogenic climate change has altered the global tropical cyclone (TC) activities, mainly due to short reliable TC observations and climate internal variabilities. Here we show with large-ensemble TC-permitting simulations that the observed increases in TC frequency since 1980 near the US Atlantic coast and Hawaii are likely related to the aerosol and greenhouse gases (GHG) effects, respectively. The observed decrease in the South China Sea after 1980 could be associated with GHG emissions alone, whereas the observed increase near Japan and Korea during this period would be related to the aerosol and GHG combined effects. These changes in coastal TC frequency are explained by the responses of large-scale environmental conditions to anthropogenic forcing.
Zhao, Jiuwei, Ruifen Zhan, Hiroyuki Murakami, Yuqing Wang, Shang-Ping Xie, Leying Zhang, and Yipeng Guo, December 2023: Atmospheric modes fiddling the simulated ENSO impact on tropical cyclone genesis over the Northwest Pacific. npj Climate and Atmospheric Science, 6, 213, DOI:10.1038/s41612-023-00537-6. Abstract
The El Niño-Southern Oscillation (ENSO) is crucial to the interannual variability of tropical cyclone (TC) genesis over the western North Pacific (WNP). However, most state-of-the-art climate models exhibit a consistent pattern of uncertainty in the simulated TC genesis frequency (TCGF) over the WNP in ENSO phases. Here, we analyze large ensemble simulations of TC-resolved climate models to identify the source of this uncertainty. Results show that large uncertainty appears in the South China Sea and east of the Philippines, primarily arising from two distinct atmospheric modes: the Matsuno-Gill-mode (MG-mode) and the Pacific-Japan-like pattern (PJ-mode). These two modes are closely associated with anomalous diabatic heating linked to tropical precipitation bias in model simulations. By conditionally constraining either of the modes, we can significantly reduce model uncertainty in simulating the dipole structure of the TCGF anomalies, confirming that it is the atmospheric circulation bias in response to tropical precipitation bias that causes uncertainty in the simulated WNP TCGF.
Tropical cyclone rapid intensification events often cause destructive hurricane landfalls because they are associated with the strongest storms and forecasts with the highest errors. Multi-decade observational datasets of tropical cyclone behavior have recently enabled documentation of upward trends in tropical cyclone rapid intensification in several basins. However, a robust anthropogenic signal in global intensification trends and the physical drivers of intensification trends have yet to be identified. To address these knowledge gaps, here we compare the observed trends in intensification and tropical cyclone environmental parameters to simulated natural variability in a high-resolution global climate model. In multiple basins and the global dataset, we detect a significant increase in intensification rates with a positive contribution from anthropogenic forcing. Furthermore, thermodynamic environments around tropical cyclones have become more favorable for intensification, and climate models show anthropogenic warming has significantly increased the probability of these changes.
Research over the past decade has demonstrated that dynamical forecast systems can skillfully predict pan-Arctic sea ice extent (SIE) on the seasonal time scale; however, there have been fewer assessments of prediction skill on user-relevant spatial scales. In this work, we evaluate regional Arctic SIE predictions made with the Forecast-Oriented Low Ocean Resolution (FLOR) and Seamless System for Prediction and Earth System Research (SPEAR_MED) dynamical seasonal forecast systems developed at the NOAA/Geophysical Fluid Dynamics Laboratory. Compared to FLOR, we find that the recently developed SPEAR_MED system displays improved skill in predicting regional detrended SIE anomalies, partially owing to improvements in sea ice concentration (SIC) and thickness (SIT) initial conditions. In both systems, winter SIE is skillfully predicted up to 11 months in advance, whereas summer minimum SIE predictions are limited by the Arctic spring predictability barrier, with typical skill horizons of roughly 4 months. We construct a parsimonious set of simple statistical prediction models to investigate the mechanisms of sea ice predictability in these systems. Three distinct predictability regimes are identified: a summer regime dominated by SIE and SIT anomaly persistence; a winter regime dominated by SIE and upper-ocean heat content (uOHC) anomaly persistence; and a combined regime in the Chukchi Sea, characterized by a trade-off between uOHC-based and SIT-based predictability that occurs as the sea ice edge position evolves seasonally. The combination of regional SIE, SIT, and uOHC predictors is able to reproduce the SIE skill of the dynamical models in nearly all regions, suggesting that these statistical predictors provide a stringent skill benchmark for assessing seasonal sea ice prediction systems.
Chand, Savin S., Kevin J E Walsh, Suzana J Camargo, James Kossin, Kevin J Tory, Michael F Wehner, Johnny C L Chan, Philip J Klotzbach, Andrew J Dowdy, Samuel S Bell, Hamish A Ramsay, and Hiroyuki Murakami, June 2022: Declining tropical cyclone frequency under global warming. Nature Climate Change, 12, DOI:10.1038/s41558-022-01388-4655-661. Abstract
Assessing the role of anthropogenic warming from temporally inhomogeneous historical data in the presence of large natural variability is difficult and has caused conflicting conclusions on detection and attribution of tropical cyclone (TC) trends. Here, using a reconstructed long-term proxy of annual TC numbers together with high-resolution climate model experiments, we show robust declining trends in the annual number of TCs at global and regional scales during the twentieth century. The Twentieth Century Reanalysis (20CR) dataset is used for reconstruction because, compared with other reanalyses, it assimilates only sea-level pressure fields rather than utilize all available observations in the troposphere, making it less sensitive to temporal inhomogeneities in the observations. It can also capture TC signatures from the pre-satellite era reasonably well. The declining trends found are consistent with the twentieth century weakening of the Hadley and Walker circulations, which make conditions for TC formation less favourable.
Chu, Pao-Shin, and Hiroyuki Murakami, 2022: Climate Variability and Tropical Cyclone Activity In , Cambridge, Cambridge University Press, DOI:10.1017/9781108586467.
Huang, Mingfeng, Qing Wang, Maofeng Liu, Ning Lin, Yifan Wang, Renzhi Jing, Zoe S Aarons, Jianping Sun, Hiroyuki Murakami, and Wenjuan Lou, September 2022: Increasing typhoon impact and economic losses due to anthropogenic warming in Southeast China. Scientific Reports, 12, 14048, DOI:10.1038/s41598-022-17323-8. Abstract
Despite a variety of studies on the tropical cyclone (TC) response to climate change, few of them have examined the projected damages of future TCs. Here we quantify the impact of anthropogenic warming on TC-induced damages in the late twenty-first century along the coasts of Southeast China based on convection-permitting TC simulations and machine-learning-based damage models. We found that if the area’s 10 super typhoons between 2013 and 2019 were to occur at the end of the century under the high emissions RCP8.5 scenario, they would have on average a 12% ± 4% increase in landfall intensity, 25% ± 23% increase in precipitation, and 128% ± 70% increase in economic losses, compared to historical simulations. We also found a significant increase in the full risk profile. The estimated typhoon loss with a 50-year return period for Zhejiang, Fujian, Guangdong, and Hainan (four most typhoon-prone provinces among the seven provinces in the region) would increase by 71%, 170%, 20%, and 85%, respectively, towards the end of the century even under the lower emissions RCP4.5 pathway. Our findings imply the need to design effective local hazard mitigation measures to reduce future typhoon risks.
This study shows that the frequency of North American summertime (June–August) heat extremes is skillfully predicted several months in advance in the newly developed Geophysical Fluid Dynamics Laboratory (GFDL) Seamless System for Prediction and Earth System Research (SPEAR) seasonal forecast system. Using a statistical optimization method, the average predictability time, we identify three large-scale components of the frequency of North American summer heat extremes that are predictable with significant correlation skill. One component, which is related to a secular warming trend, shows a continent-wide increase in the frequency of summer heat extremes and is highly predictable at least 9 months in advance. This trend component is likely a response to external radiative forcing. The second component is largely driven by the sea surface temperatures in the North Pacific and North Atlantic and is significantly correlated with the central U.S. soil moisture. The second component shows largest loadings over the central United States and is significantly predictable 9 months in advance. The third component, which is related to the central Pacific El Niño, displays a dipole structure over North America and is predictable up to 4 months in advance. Potential implications for advancing seasonal predictions of North American summertime heat extremes are discussed.
Murakami, Hiroyuki, January 2022: Tropical Cyclones in a Changing Climate In Handbook of Air Quality and Climate Change [Akimoto, H. and H. Tanimoto (eds.)], Springer, Singapore, DOI:10.1007/978-981-15-2527-8_34-1.
The frequency of large-scale anomalous precipitation events associated with heavy precipitation has been increasing in Japan. However, it is unclear if the increase is due to anthropogenic warming or internal variability. Also, it is challenging to develop an objective methodology to identify anomalous events because of the large variety of anomalous precipitation cases. In this study, we applied a deep learning technique to objectively detect anomalous precipitation events in Japan for both observations and simulations using high-resolution climate models. The results show that the observed increases in anomalous heavy precipitation events in Western Japan during 1977–2015 were not made only by internal variability but the increases in anthropogenic forcing played an important role. Such events will continue to increase in frequency this century. The increases are attributable to the increasing frequency of tropical cyclones and enhanced frontal rainbands near Japan. These results highlight the mitigation challenge posed by the increasing occurrence of unprecedented precipitation events in the future.
Murakami, Hiroyuki, and Bin Wang, April 2022: Patterns and frequency of projected future tropical cyclone genesis are governed by dynamic effects. Communications Earth and Environment, 3, 77, DOI:10.1038/s43247-022-00410-z. Abstract
Potential future changes in the genesis frequency and distribution of tropical cyclones are important for society, yet uncertain. Confidence in the model projections largely relies on whether we can physically explain why the models projected such changes. Here we analyze multi-model climate simulations, and find that future changes in the patterns and frequency of tropical cyclone genesis are largely governed by dynamic effects—that is, by human-induced changes in the atmospheric circulation. These large-scale circulation changes include decreases in the mid-level upward motion and lower-to-mid level cyclonic vorticity, and increases in vertical wind shear. Conversely, the thermodynamic effect—a result of increased maximum potential intensity in a warmer climate—would yield tropical cyclone genesis patterns that are opposite to the model projections. We conclude that dynamic changes in response to anthropogenic greenhouse gas emissions are an important factor in determining the response of tropical cyclones to global warming.
Over the past 40 years, anthropogenic aerosols have been substantially decreasing over Europe and the United States owing to pollution control measures, whereas they have increased in South and East Asia because of the economic and industrial growth in these regions. However, it is not yet clear how the changes in anthropogenic aerosols have altered global tropical cyclone (TC) activity. In this study, we reveal that the decreases in aerosols over Europe and the United States have contributed to significant decreases in TCs over the Southern Hemisphere as well as increases in TCs over the North Atlantic, whereas the increases in aerosols in South and East Asia have exerted substantial decreases in TCs over the western North Pacific. These results suggest that how society controls future emissions of anthropogenic aerosols will exert a substantial impact on the world’s TC activity.
Nasuno, Tomoe, Masuo Nakano, Hiroyuki Murakami, Kazuyoshi Kikuchi, and Yohei Yamada, May 2022: Impacts of midlatitude western North Pacific sea surface temperature anomaly on the subseasonal to seasonal tropical cyclone activity: Case study of the 2018 boreal summer. SOLA, 18, DOI:10.2151/sola.2022-01588-95. Abstract
In this study, we explored the impacts of midlatitude western North Pacific (WNP) sea surface temperature (SST) on tropical cyclone (TC) activity at intraseasonal to seasonal time scales during the 2018 boreal summer. During this period, a positive SST anomaly occurred in the midlatitude WNP and subtropical central Pacific; TC activity was abnormally high under the influence of the strong Asian summer monsoon. We performed sensitivity experiments using a global cloud system-resolving model for global SST (control, CTL) and SST that were regionally restored according to midlatitude WNP climatology (MWNPCLM). TC track density in the eastern WNP was higher in CTL than in MWNPCLM, in association with large-scale atmospheric responses; enhanced monsoon westerlies in the subtropical WNP, moist rising (dry subsiding) tendencies, and reduced (enhanced) vertical wind shear in the eastern (western) WNP. Enhanced TC activity in the eastern WNP was more distinct for intense TCs and during the active phase of intraseasonal oscillation (ISO). These results suggest that the impacts of midlatitude SST anomalies can reach lower latitudes to affect TC activity via large-scale atmospheric responses and ISO, which are usually overwhelmed by the impacts of SST anomalies in the tropics and subtropics.
Quantifying the response of atmospheric rivers (ARs) to radiative forcing is challenging due to uncertainties caused by internal climate variability, differences in shared socioeconomic pathways (SSPs), and methods used in AR detection algorithms. In addition, the requirement of medium-to-high model resolution and ensemble sizes to explicitly simulate ARs and their statistics can be computationally expensive. In this study, we leverage the unique 50-km large ensembles generated by a Geophysical Fluid Dynamics Laboratory next-generation global climate model, Seamless system for Prediction and EArth system Research, to explore the warming response in ARs. Under both moderate and high emissions scenarios, increases in AR-day frequency emerge from the noise of internal variability by 2060. This signal is robust across different SSPs and time-independent detection criteria. We further examine an alternative approach proposed by Thompson et al. (2015), showing that unforced AR variability can be approximated by a first-order autoregressive process. The confidence intervals of the projected response can be analytically derived with a single ensemble member.
One of the most puzzling observed features of recent climate has been a multidecadal surface cooling trend over the subpolar Southern Ocean (SO). In this study we use large ensembles of simulations with multiple climate models to study the role of the SO meridional overturning circulation (MOC) in these sea surface temperature (SST) trends. We find that multiple competing processes play prominent roles, consistent with multiple mechanisms proposed in the literature for the observed cooling. Early in the simulations (twentieth century and early twenty-first century) internal variability of the MOC can have a large impact, in part due to substantial simulated multidecadal variability of the MOC. Ensemble members with initially strong convection (and related surface warming due to convective mixing of subsurface warmth to the surface) tend to subsequently cool at the surface as convection associated with internal variability weakens. A second process occurs in the late-twentieth and twenty-first centuries, as weakening of oceanic convection associated with global warming and high-latitude freshening can contribute to the surface cooling trend by suppressing convection and associated vertical mixing of subsurface heat. As the simulations progress, the multidecadal SO variability is suppressed due to forced changes in the mean state and increased oceanic stratification. As a third process, the shallower mixed layers can then rapidly warm due to increasing forcing from greenhouse gas warming. Also, during this period the ensemble spread of SO SST trend partly arises from the spread of the wind-driven Deacon cell strength. Thus, different processes could conceivably have led to the observed cooling trend, consistent with the range of possibilities presented in the literature. To better understand the causes of the observed trend, it is important to better understand the characteristics of internal low-frequency variability in the SO and the response of that variability to global warming.
Aarons, Zoe S., Suzana J Camargo, Jeffrey D Strong, and Hiroyuki Murakami, March 2021: Tropical cyclone characteristics in the MERRA-2 reanalysis and AMIP simulations. Earth and Space Science, 8(3), DOI:10.1029/2020EA001415. Abstract
This study evaluates the tropical cyclone (TC) activity in two high-resolution data sets—MERRA-2 Reanalysis (Modern-Era Retrospective Analysis for Research and Applications, Version 2) and MERRA-2 AMIP (Atmospheric Model Intercomparison Project). These data sets use the same atmospheric model, the Goddard Earth Observing System Model, Version 5 (GEOS-5) during the same period. However, while MERRA-2 AMIP is a free-running atmospheric simulation forced only with sea surface temperature (SST), MERRA-2 Reanalysis uses an advanced data assimilation system to include a large variety of data sets. Thus, we analyze (1) the sensitivity of TC activity to the model forcing, (2) how well the TCs in both data sets replicate observed TC characteristics, (3) the sensitivity of these results to tracking schemes and thresholds. Standard diagnostics such as the number of tropical cyclones and their intensity distribution are very similar in the AMIP model and the reanalysis. TCs in both data sets are weaker than observed, as is typical for the spatial resolution of these global models. Overall, the use of data assimilation in the MERRA-2 Reanalysis does not lead to a significantly better TC climatology than in AMIP. Furthermore, comparison of the MERRA-2 Reanalysis to two other reanalysis data sets shows that MERRA-2 generates fewer, but more intense TCs, than those reanalysis products.
Compared to the Arctic, seasonal predictions of Antarctic sea ice have received relatively little attention. In this work, we utilize three coupled dynamical prediction systems developed at the Geophysical Fluid Dynamics Laboratory to assess the seasonal prediction skill and predictability of Antarctic sea ice. These systems, based on the FLOR, SPEAR_LO, and SPEAR_MED dynamical models, differ in their coupled model components, initialization techniques, atmospheric resolution, and model biases. Using suites of retrospective initialized seasonal predictions spanning 1992–2018, we investigate the role of these factors in determining Antarctic sea ice prediction skill and examine the mechanisms of regional sea ice predictability. We find that each system is capable of skillfully predicting regional Antarctic sea ice extent (SIE) with skill that exceeds a persistence forecast. Winter SIE is skillfully predicted 11 months in advance in the Weddell, Amundsen/Bellingshausen, Indian, and west Pacific sectors, whereas winter skill is notably lower in the Ross sector. Zonally advected upper-ocean heat content anomalies are found to provide the crucial source of prediction skill for the winter sea ice edge position. The recently developed SPEAR systems are more skillful than FLOR for summer sea ice predictions, owing to improvements in sea ice concentration and sea ice thickness initialization. Summer Weddell SIE is skillfully predicted up to 9 months in advance in SPEAR_MED, due to the persistence and drift of initialized sea ice thickness anomalies from the previous winter. Overall, these results suggest a promising potential for providing operational Antarctic sea ice predictions on seasonal time scales.
Chen, Jilong, Chi-Yung Tam, Kevin Cheung, Ziqian Wang, Hiroyuki Murakami, Ngar-Cheung Lau, Stephen T Garner, Ziniu Xiao, Chun-Wing Choy, and Peng Wang, November 2021: Changing impacts of tropical cyclones on east and southeast Asian inland regions in the past and a globally warmed future climate. Frontiers in Earth Science, 9:769005, DOI:10.3389/feart.2021.769005. Abstract
The impacts of the western North Pacific (WNP) tropical cyclone (TC) on East and Southeast Asian inland regions are analyzed. Here, based on a stringent TC selecting criterion, robust increase of TC-related inland impacts between 1979 and 2016 over East and Southeast Asian regions have been detected. The storms sustained for 2–9 h longer and penetrated 30–190 km further inland, as revealed from different best track datasets. The most significant increase of the TC inland impacts occurred over Hanoi and South China. The physical mechanism that affects TC-related inland impacts is shortly discussed. First, the increasing TC inland impacts just occur in the WNP region, but it is not a global effect. Second, besides the significant WNP warming effects on the enhanced TC landfall intensity and TC inland impacts, it is suggested that the weakening of the upper-level Asian Pacific teleconnection pattern since 1970s may also play an important role, which may reduce the climatic 200 hPa anti-cyclonic wind flows over the Asian region, weakening the wind shear near the Philippine Sea, and may eventually intensify the TC intensity when the TCs across the basin. Moreover, the TC inland impacts in the warming future are projected based on a high-resolution (20 km) global model according to the Representative Concentration Pathway 8.5 scenario. By the end of the 21st century, TC mean landfall intensity will increase by 2 m/s (6%). The stronger storms will sustain 4.9 h (56%) longer and penetrate 92.4 km (50%) farther inland, thereby almost doubling the destructive power delivered to Asian inland regions. More inland locations will therefore be exposed to severe storm–related hazards in the future due to warmer climate. Long-term planning to enhance disaster preparedness and resilience in these regions is called for.
Hsu, Pang-Chi, Zhen Fu, Hiroyuki Murakami, June-Yi Lee, Changhyun Yoo, Nathaniel C Johnson, Chueh-Hsin Chang, and Yu Liu, June 2021: East Antarctic cooling induced by decadal changes in Madden-Julian oscillation during austral summer. Science Advances, 7(26), DOI:10.1126/sciadv.abf9903. Abstract
While West Antarctica has experienced the most significant warming in the world, a profound cooling trend in austral summer was observed over East Antarctica (30°W to 150°E, 70° to 90°S) from 1979 to 2014. Previous studies attributed these changes to high-latitude atmospheric dynamics, stratospheric ozone change, and tropical sea surface temperature anomalies. We show that up to 20 to 40% of the observed summer cooling trend in East Antarctica was forced by decadal changes of the Madden-Julian oscillation (MJO). Both observational analysis and climate model experiments indicate that the decadal changes in the MJO, characterized by less (more) atmospheric deep convection in the Indian Ocean (western Pacific) during the recent two decades, led to the net cooling trend over East Antarctica through modifying atmospheric circulations linked to poleward-propagating Rossby wave trains. This study highlights that changes in intraseasonal tropical climate patterns may result in important climate change over Antarctica.
Kim, Dasol, Chang-Hoi Ho, Hiroyuki Murakami, and Doo-Sun R Park, March 2021: Assessing the influence of large-scale environmental conditions on the rainfall structure of Atlantic tropical cyclones: An observational study. Journal of Climate, 34(6), DOI:10.1175/JCLI-D-20-0376.1. Abstract
Understanding the mechanisms related to the variations in the rainfall structure of tropical cyclones (TCs) is crucial in improving forecasting systems of TC rainfall and its impact. Using satellite precipitation and reanalysis data, we examined the influence of along-track large-scale environmental conditions on inner-core rainfall strength (RS) and total rainfall area (RA) for Atlantic TCs during the TC season (July–November) from 1998 to 2019. Factor analysis revealed three major factors associated with variations in RS and RA: large-scale low and high pressure systems [factor 1 (F1)]; environmental flows, sea surface temperature, and humidity [factor 2 (F2)]; and maximum wind speed of TCs [factor 3 (F3)]. Results from our study indicate that RS increases with an increase in the inherent primary circulation of TCs (i.e., F3) but is less affected by large-scale environmental conditions (i.e., F1 and F2), whereas RA is primarily influenced by large-scale low and high pressure systems (i.e., F1) over the entire North Atlantic and partially influenced by environmental flows, sea surface temperature, humidity, and maximum wind speed (i.e., F2 and F3). A multivariable regression model based on the three factors accounted for the variations of RS and RA across the entire basin. In addition, regional distributions of mean RS and RA from the model significantly resembled those from observations. Therefore, our study suggests that large-scale environmental conditions over the North Atlantic Ocean are important predictors for TC rainfall forecasts, particularly with regard to RA.
Ma, Hsi-Yen, A Cheska Siongco, Stephen A Klein, Shaocheng Xie, Alicia R Karspeck, Kevin Raeder, Jeffrey L Anderson, Jiwoo Lee, Ben P Kirtman, William J Merryfield, Hiroyuki Murakami, and Joseph J Tribbia, January 2021: On the correspondence between seasonal forecast biases and long-term climate biases in sea surface temperature. Journal of Climate, 34(1), DOI:10.1175/JCLI-D-20-0338.1. Abstract
The correspondence between mean sea surface temperature (SST) biases in retrospective seasonal forecasts (hindcasts) and long-term climate simulations from five global climate models is examined to diagnose the degree to which systematic SST biases develop on seasonal time scales. The hindcasts are from the North American Multimodel Ensemble, and the climate simulations are from the Coupled Model Intercomparison Project. The analysis suggests that most robust climatological SST biases begin to form within 6 months of a realistically initialized integration, although the growth rate varies with location, time, and model. In regions with large biases, interannual variability and ensemble spread is much smaller than the climatological bias. Additional ensemble hindcasts of the Community Earth System Model with a different initialization method suggest that initial conditions do matter for the initial bias growth, but the overall global bias patterns are similar after 6 months. A hindcast approach is more suitable to study biases over the tropics and subtropics than over the extratropics because of smaller initial biases and faster bias growth. The rapid emergence of SST biases makes it likely that fast processes with time scales shorter than the seasonal time scales in the atmosphere and upper ocean are responsible for a substantial part of the climatological SST biases. Studying the growth of biases may provide important clues to the causes and ultimately the amelioration of these biases. Further, initialized seasonal hindcasts can profitably be used in the development of high-resolution coupled ocean–atmosphere models.
Atmospheric rivers (ARs) exert significant socioeconomic impacts in western North America, where 30% of the annual precipitation is determined by ARs that occur in less than 15% of wintertime. ARs are thus beneficial to water supply but can produce extreme precipitation hazards when making landfall. While most prevailing research has focused on the subseasonal (<5 weeks) prediction of ARs, only limited efforts have been made for AR forecasts on multiseasonal timescales (>3 months) that are crucial for water resource management and disaster preparedness. Through the analysis of reanalysis data and retrospective predictions from a new seasonal-to-decadal forecast system, this research shows the existing potential of multiseasonal AR frequency forecasts with predictive skills 9 months in advance. Additional analysis explores the dominant predictability sources and challenges for multiseasonal AR prediction.
Climate models often show errors in simulating and predicting tropical cyclone (TC) activity, but the sources of these errors are not well understood. This study proposes an evaluation framework and analyzes three sets of experiments conducted using a seasonal prediction model developed at the Geophysical Fluid Dynamics Laboratory (GFDL). These experiments apply the nudging technique to the model integration and/or initialization to estimate possible improvements from nearly perfect model conditions. The results suggest that reducing sea surface temperature (SST) errors remains important for better predicting TC activity at long forecast leads—even in a flux-adjusted model with reduced climatological biases. Other error sources also contribute to biases in simulated TC activity, with notable manifestations on regional scales. A novel finding is that the coupling and initialization of the land and atmosphere components can affect seasonal TC prediction skill. Simulated year-to-year variations in June land conditions over North America show a significant lead correlation with the North Atlantic large-scale environment and TC activity. Improved land–atmosphere initialization appears to improve the Atlantic TC predictions initialized in some summer months. For short-lead predictions initialized in June, the potential skill improvements attributable to land–atmosphere initialization might be comparable to those achievable with perfect SST predictions. Overall, this study delineates the SST and non-oceanic error sources in predicting TC activity and highlights avenues for improving predictions. The nudging-based evaluation framework can be applied to other models and help improve predictions of other weather extremes.
Midlatitude baroclinic waves drive extratropical weather and climate variations, but their predictability beyond 2 weeks has been deemed low. Here we analyze a large ensemble of climate simulations forced by observed sea surface temperatures (SSTs) and demonstrate that seasonal variations of baroclinic wave activity (BWA) are potentially predictable. This potential seasonal predictability is denoted by robust BWA responses to SST forcings. To probe regional sources of the potential predictability, a regression analysis is applied to the SST-forced large ensemble simulations. By filtering out variability internal to the atmosphere and land, this analysis identifies both well-known and unfamiliar BWA responses to SST forcings across latitudes. Finally, we confirm the model-indicated predictability by showing that an operational seasonal prediction system can leverage some of the identified SST-BWA relationships to achieve skillful predictions of BWA. Our findings help to extend long-range predictions of the statistics of extratropical weather events and their impacts.
Bieli, M, Adam H Sobel, Suzana J Camargo, Hiroyuki Murakami, and Gabriel A Vecchi, April 2020: Application of the Cyclone Phase Space to Extratropical Transition in a Global Climate Model. Journal of Advances in Modeling Earth Systems, 12(4), DOI:10.1029/2019MS001878. Abstract
The authors analyze the global statistics of tropical cyclones (TCs) undergoing extratropical transition (ET) in the Forecast‐oriented Low Ocean Resolution version of CM2.5 with Flux Adjustment (FLOR‐FA). The Cyclone Phase Space (CPS) is used to diagnose ET. A simulation of the recent historical climate is analyzed and compared with data from the Japanese 55‐year Reanalysis (JRA‐55), and then a simulation of late 21st century climate under Representative Concentration Pathway 4.5 is compared to the historical simulation.
When CPS is applied to the FLOR‐FA output in the historical simulation, the results diverge from those obtained from JRA‐55 by having an unrealistic number of ET cases at low latitudes, due to the presence of strong local maxima in the upper‐level geopotential. These features mislead CPS into detecting a cold core where one is not present. The misdiagnosis is largely corrected by either replacing the maxima required by CPS with the 95th percentile values, smoothing the CPS trajectories in time, or both. Other climate models may contain grid‐scale structures akin to those in FLOR‐FA, and, when used for CPS analysis, require solutions such as those discussed here.
Comparisons of ET in the projected future climate with the historical climate show a number of changes that are robust to the details of the ET diagnosis, though few are statistically significant according to standard tests. Among them are an increase in the ET fraction and a reduction in the mean latitude at which ET occurs in the western North Pacific.
Camargo, Suzana J., C F Giulivi, Adam H Sobel, Allison A Wing, D Kim, Yumin Moon, Jeffrey D Strong, A Del Genio, M Kelley, Hiroyuki Murakami, Kevin A Reed, E Scoccimarro, Gabriel A Vecchi, Michael F Wehner, Colin M Zarzycki, and Ming Zhao, June 2020: Characteristics of model tropical cyclone climatology and the large-scale environment. Journal of Climate, 33(11), DOI:10.1175/JCLI-D-19-0500.1. Abstract
Here we explore the relationship between the global climatological characteristics of tropical cyclones (TCs) in climate models and the modeled large-scale environment across a large number of models. We consider the climatology of TCs in 30 climate models with a wide range of horizontal resolutions. We examine if there is a systematic relationship between the climatological diagnostics for the TC activity (number of tropical cyclones (NTC) and accumulated cyclone energy (ACE)) by hemisphere in the models and the environmental fields usually associated with TC activity, when examined across a large number of models. For low-resolution models, there is no association between a conducive environment and TC activity, when integrated over space (tropical hemisphere) and time (all years of the simulation). As the model resolution increases, for a couple of variables, in particular vertical wind shear there is a statistically significant relationship in between the models’ TC characteristics and the environmental characteristics, but in most cases the relationship is either non-existent or the opposite of what is expected based on observations. It is important to stress that these results do not imply that there is no relationship between individual models’ environmental fields and their TC activity by basin with respect to intraseasonal or interannual variability or due to climate change. However, it is clear that when examined across many models, the models’ mean state does not have a consistent relationship with the models’ mean TC activity. Therefore, other processes associated with model physics, dynamical core, and resolution determine the climatological TC activity in climate models.
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.
Hsu, Pang-Chi, Yitian Qian, Y Liu, and Hiroyuki Murakami, et al., April 2020: Role of Abnormally Enhanced MJO over the Western Pacific in the Formation and Subseasonal Predictability of the Record-breaking Northeast Asian Heatwave in the Summer of 2018. Journal of Climate, 33(8), DOI:10.1175/JCLI-D-19-0337.1. Abstract
In the summer of 2018, Northeast Asia experienced a heatwave event that broke the existing high-temperature records in several locations in Japan, the Korean Peninsula and northeastern China. At the same time, an unusually strong Madden–Julian Oscillation (MJO) was observed to stay over the western Pacific warm pool. Based on reanalysis diagnosis, numerical experiments and assessments of real-time forecast data from two subseasonal-to-seasonal (S2S) models, we discovered the importance of the western Pacific MJO in the generation of this heatwave event, as well as its predictability at the subseasonal timescale.
During the prolonged heat extreme period (11 July to 14 August), a high pressure anomaly with variability at the intraseasonal (30–90 days) timescale appeared over Northeast Asia, causing persistent adiabatic heating and clear skies in this region. As shown in the composites of MJO-related convection and circulation anomalies, the occurrence of this 30–90-day high anomaly over Northeast Asia was linked with an anomalous wave train induced by tropical heating associated with the western tropical Pacific MJO. The impact of the MJO on the heatwave was further confirmed by sensitivity experiments with a coupled GCM. As the western Pacific MJO-related components were removed by nudging prognostic variables over the tropics towards their annual cycle and longer timescales (>90 days) in the coupled GCM, the anomalous wave train along the East Asian coast disappeared and the surface air temperature in Northeast Asia reduced. The MJO over the western Pacific warm pool also influenced the predictability of the extratropical heatwave. Our assessments of two S2S models’ real-time forecasts suggest that the extremity of this Northeast Asian heatwave can be better predicted 1–4 weeks in advance if the enhancement of MJO convections over the western Pacific warm pool is predicted well.
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.
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.
Wang, Bin, and Hiroyuki Murakami, October 2020: Dynamic genesis potential index for diagnosing present-day and future global tropical cyclone genesis. Environmental Research Letters, 15, DOI:10.1088/1748-9326/abbb01. Abstract
Tropical cyclone (TC) genesis potential index (GPI) has been extensively used to understand the processes governing climate variability and future change of TC genesis (TCG). However, the relative roles of the thermodynamic versus dynamic environmental factors in TC genesis remain elusive, especially under a warming world. Here we show that four leading dynamic factors, the 850 hPa absolute vorticity, 500 hPa vertical motion, tropospheric vertical wind shear, and 500 hPa shear vorticity of zonal winds, are objectively identified by the logarithmic stepwise regression analysis from 11 dynamic and thermodynamic candidate factors. We further demonstrate that the model results from a TC-permitting global model ascertain the four leading dynamical factors as the most influential in both the present-day simulation and future projection under global warming. A dynamic GPI, consisting of the four dynamic parameters, provides a diagnostic tool for understanding future change of TC genesis. Meanwhile, it improves skills in representing interannual variations of TCG frequency in the western Pacific and Southern Hemisphere oceans.
The locally accumulated damage by tropical cyclones (TCs) can intensify substantially when these cyclones move more slowly. While some observational evidence suggests that TC motion might have slowed significantly since the mid-20th century (1), the robustness of the observed trend and its relation to anthropogenic warming have not been firmly established (2–4). Using large-ensemble simulations that directly simulate TC activity, we show that future anthropogenic warming can lead to a robust slowing of TC motion, particularly in the midlatitudes. The slowdown there is related to a poleward shift of the midlatitude westerlies, which has been projected by various climate models. Although the model’s simulation of historical TC motion trends suggests that the attribution of the observed trends of TC motion to anthropogenic forcings remains uncertain, our findings suggest that 21st-century anthropogenic warming could decelerate TC motion near populated midlatitude regions in Asia and North America, potentially compounding future TC-related damages.
Tropical cyclones that rapidly intensify are typically associated with the highest forecast errors and cause a disproportionate amount of human and financial losses. Therefore, it is crucial to understand if, and why, there are observed upward trends in tropical cyclone intensification rates. Here, we utilize two observational datasets to calculate 24-hour wind speed changes over the period 1982–2009. We compare the observed trends to natural variability in bias-corrected, high-resolution, global coupled model experiments that accurately simulate the climatological distribution of tropical cyclone intensification. Both observed datasets show significant increases in tropical cyclone intensification rates in the Atlantic basin that are highly unusual compared to model-based estimates of internal climate variations. Our results suggest a detectable increase of Atlantic intensification rates with a positive contribution from anthropogenic forcing and reveal a need for more reliable data before detecting a robust trend at the global scale.
Mediterranean hurricanes (Medicanes) are intense cyclones that acquire tropical characteristics, associated with extreme winds and rainfall, thus posing a serious natural hazard to populated areas along Mediterranean coasts. Understanding how Medicanes will change with global warming remains, however, a challenge, because coarse resolution and/or the lack of atmosphere‐ocean coupling limit the reliability of numerical simulations. Here we investigate the Medicanes' response to global warming using a recently developed 25‐km global coupled climate model, which features a realistic representation of Medicanes in present climate conditions. It is found that despite a decrease in frequency, Medicanes potentially become more hazardous in the late century, lasting longer and producing stronger winds and rainfall. These changes are associated with a more robust hurricane‐like structure and are mainly confined to autumn. Thus, continued anthropogenic warming will increase the risks associated with Medicanes even in an intermediate scenario (Representative Concentration Pathway, RCP4.5), with potential natural and socioeconomic consequences.
Klotzbach, Philip J., Eric Blake, Joanne Camp, Louis-Philippe Caron, Johnny C L Chan, N-Y Kang, Yuriy Kuleshov, Sai-Ming Lee, and Hiroyuki Murakami, et al., September 2019: Seasonal Tropical Cyclone Forecasting. Tropical Cyclone Research and Review, 8(3), DOI:10.1016/j.tcrr.2019.10.003. Abstract
This paper summarizes the forecast methods, outputs and skill offered by twelve agencies for seasonal tropical cyclone (TC) activity around the world. These agencies use a variety of techniques ranging from statistical models to dynamical models to predict basinwide activity and regional activity. In addition, several dynamical and hybrid statistical/dynamical models now predict TC track density as well as landfall likelihood. Realtime Atlantic seasonal hurricane forecasts have shown low skill in April, modest skill in June and good skill in August at predicting basinwide TC activity when evaluated over 2003-2018. Real-time western North Pacific seasonal TC forecasts have shown good skill by July for basinwide intense typhoon numbers and the ACE index when evaluated for 2003-2018. Both hindcasts and real-time forecasts have shown skill for other TC basins. A summary of recent research into forecasting TC activity beyond seasonal (e.g., multi-year) timescales is included. Recommendations for future areas of research are also discussed.
Levin, Emma L., and Hiroyuki Murakami, May 2019: Impact of Anthropogenic Climate Change on United States Major Hurricane Landfall Frequency. Journal of Marine Science and Engineering, 7(5), DOI:10.3390/jmse7050135. Abstract
Although anthropogenic climate change has contributed to warmer ocean temperatures that are seemingly more favorable for Atlantic hurricane development, no major hurricanes made landfall in the United States between 2006 and 2016. The U.S., therefore, experienced a major hurricane landfall drought during those years. Using the high-resolution Geophysical Fluid Dynamics Laboratory 25 km grid High-Resolution Forecast-Oriented Low Ocean Resolution (HiFLOR) global climate model, the present study shows that increases in anthropogenic forcing, due to increases in greenhouse gasses, are associated with fewer long-duration major hurricane landfall droughts in the U.S., which implies an increase in major hurricane landfall frequency. We create six different fixed-distance ‘buffers’ that artificially circle the United States coastline in 100 km radial increments and can compensate for the bias in hurricane landfall calculations with six-hourly datasets. Major hurricane landfall frequencies are computed by applying the buffer zones to the six-hourly observed and simulated storm track datasets, which are then compared with the observed recorded major hurricane frequencies. We found that the major hurricane landfall frequencies generated with the 200 km buffer using the six-hourly observed best-track dataset are most correlated with the observed recorded major hurricane landfall frequencies. Using HiFLOR with an implemented buffer system, we found less frequent projections of long-duration major hurricane landfall drought events in controlled scenarios with greater anthropogenic global warming, which is independent on the radius of the coastal buffer. These results indicate an increase in U.S. major hurricane landfall frequencies with an increase in anthropogenic warming, which could pose a substantial threat to coastal communities in the U.S.
This study explores the impact of El Niño and La Niña events on precipitation and circulation in East Asia. The results are based on statistical analysis of various observational datasets and Geophysical Fluid Dynamics Laboratory’s (GFDL’s) global climate model experiments. Multiple observational datasets and certain models show that in the southeastern coast of China, precipitation exhibits a nonlinear response to Central Pacific sea surface temperature anomalies during boreal deep fall/early winter. Higher mean rainfall is observed during both El Niño and La Niña events compared to the ENSO-Neutral phase, by an amount of approximately 0.4–0.5 mm/day on average per oC change. We argue that, in October to December, while the precipitation increases during El Niño are the result of anomalous onshore moisture fluxes, those during La Niña are driven by the persistence of terrestrial moisture anomalies resulting from earlier excess rainfall in this region. This is consistent with the nonlinear extreme rainfall behavior in coastal southeastern China, which increases during both ENSO phases and becomes more severe during El Niño than La Niña events.
The 2018 tropical cyclone (TC) season in the North Pacific was very active, with 39 tropical storms including 8 typhoons/hurricanes. This activity was successfully predicted up to 5 months in advance by the Geophysical Fluid Dynamics Laboratory Forecast‐oriented Low Ocean Resolution (FLOR) global coupled model. In this work, a suite of idealized experiments with three dynamical global models (FLOR, NICAM and MRI‐AGCM) was used to show that the active 2018 TC season was primarily caused by warming in the subtropical Pacific, and secondarily by warming in the tropical Pacific. Furthermore, the potential effect of anthropogenic forcing on the active 2018 TC season was investigated using two of the global models (FLOR and MRI‐AGCM). The models projected opposite signs for the changes in TC frequency in the North Pacific by an increase in anthropogenic forcing, thereby highlighting the substantial uncertainty and model dependence in the possible impact of anthropogenic forcing on Pacific TC activity.
Responses of tropical cyclones (TCs) to CO2 doubling are explored using coupled global climate models (GCMs) with increasingly refined atmospheric/land horizontal grids (~ 200 km, ~ 50 km and ~ 25 km). The three models exhibit similar changes in background climate fields thought to regulate TC activity, such as relative sea surface temperature (SST), potential intensity, and wind shear. However, global TC frequency decreases substantially in the 50 km model, while the 25 km model shows no significant change. The ~ 25 km model also has a substantial and spatially-ubiquitous increase of Category 3–4–5 hurricanes. Idealized perturbation experiments are performed to understand the TC response. Each model’s transient fully-coupled 2 × CO2 TC activity response is largely recovered by “time-slice” experiments using time-invariant SST perturbations added to each model’s own SST climatology. The TC response to SST forcing depends on each model’s background climatological SST biases: removing these biases leads to a global TC intensity increase in the ~ 50 km model, and a global TC frequency increase in the ~ 25 km model, in response to CO2-induced warming patterns and CO2 doubling. Isolated CO2 doubling leads to a significant TC frequency decrease, while isolated uniform SST warming leads to a significant global TC frequency increase; the ~ 25 km model has a greater tendency for frequency increase. Global TC frequency responds to both (1) changes in TC “seeds”, which increase due to warming (more so in the ~ 25 km model) and decrease due to higher CO2 concentrations, and (2) less efficient development of these“seeds” into TCs, largely due to the nonlinear relation between temperature and saturation specific humidity.
Since the Eighth International Workshop on Tropical Cyclones (IWTC-8), held in December 2014, progress has been made in our understanding of the relationship between tropical cyclone (TC) characteristics, climate and climate change. New analysis of observations has revealed trends in the latitude of maximum TC intensity and in TC translation speed. Climate models are demonstrating an increasing ability to simulate the observed TC climatology and its regional variations. The limited representation of air-sea interaction processes in most climate simulations of TCs remains an issue. Consensus projections of future TC behavior continue to indicate decreases in TC numbers, increases in their maximum intensities and increases in TC-related rainfall. Future sea level rise will exacerbate the impact of storm surge on coastal regions, assuming all other factors equal. Studies have also begun to estimate the effect on TCs of the climate change that has occurred to date. Recommendations are made regarding future research directions.
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.
This study examines the performance of the Geophysical Fluid Dynamics Laboratory Forecast-Oriented Low Ocean Resolution version of CM2.5 (FLOR; ~ 50-km mesh) and high-resolution FLOR (HiFLOR; ~ 25-km mesh) in reproducing the climatology and interannual variability in rainfall associated with tropical cyclones (TCs) in both sea surface temperature (SST)-nudging and seasonal-forecast experiments. Overall, HiFLOR outperforms FLOR in capturing the observed climatology of TC rainfall, particularly in East Asia, North America and Australia. In general, both FLOR and HiFLOR underestimate the observed TC rainfall in the coastal regions along the Bay of Bengal, connected to their failure to accurately simulate the bimodal structure of the TC genesis seasonality. A crucial factor in capturing the climatology of TC rainfall by the models is the simulation of the climatology of spatial TC density. Overall, while HiFLOR leads to a better characterization of the areas affected by TC rainfall, the SST-nudging and seasonal-forecast experiments with both models show limited skill in reproducing the year-to-year variation in TC rainfall. Ensemble-based estimates from these models indicate low potential skill for year-to-year variations in TC rainfall, yet the models show lower skill than this. Therefore, the low skill for interannual TC rainfall in these models reflects both a fundamental limit on predictability/reproducibility of seasonal TC rainfall as well as shortcomings in the models.
Improving the seasonal prediction of tropical cyclone (TC) activity demands a robust analysis of the prediction skill and the inherent predictability of TC activity. Using the resampling technique, this study analyzes a state‐of‐the‐art prediction system and offers a robust assessment of when and where the seasonal prediction of TC activity is skillful. We found that uncertainties of initial conditions affect the predictions and the skill evaluation significantly. The sensitivity of predictions to initial conditions also suggests that landfall and high‐latitude activity are inherently harder to predict. The lower predictability is consistent with the relatively low prediction skill in these regions. Additionally, the lower predictability is largely related to the atmospheric environment rather than the sea surface temperature, at least for the predictions initialized shortly before the hurricane season. These findings suggest the potential for improving the seasonal TC prediction and will help the development of the next‐generation prediction systems.
As one of the first global coupled climate models to simulate and predict category 4 and 5 (Saffir–Simpson scale) tropical cyclones (TCs) and their interannual variations, the High-Resolution Forecast-Oriented Low Ocean Resolution (HiFLOR) model at the Geophysical Fluid Dynamics Laboratory (GFDL) represents a novel source of insight on how the entire TC intensification distribution could be transformed due to climate change. In this study, three 70-year HiFLOR experiments are performed to identify the effects of climate change on TC intensity and intensification. For each of the experiments, sea surface temperature (SST) is nudged to different climatological targets and atmospheric radiative forcing is specified, allowing us to explore the sensitivity of TCs to these conditions.
First, a control experiment, which uses prescribed climatological ocean and radiative forcing based on observations during the years 1986-2005, is compared to two observational records and evaluated for its ability to capture the mean TC behavior during these years. The simulated intensification distributions as well as the percentage of TCs that become major hurricanes show similarities with observations. The control experiment is then compared to two 21st century experiments, in which the climatological SSTs from the control experiment are perturbed by multimodel projected SST anomalies and atmospheric radiative forcing from either 2016-2035 or 2081-2100 (RCP4.5 scenario). The frequency, intensity, and intensification distribution of TCs all shift to higher values as the 21st century progresses. HiFLOR’s unique response to climate change and fidelity in simulating the present climate lays the groundwork for future studies involving models of this type.
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.
Landfalling tropical cyclone (TC) rainfall is an important element of inland flood hazards in the eastern United States. The projection of landfalling TC rainfall under anthropogenic warming provides insight to future flood risks. This study examines the frequency of landfalling TCs and associated rainfall using the GFDL Forecast-oriented Low Ocean Resolution (FLOR) climate model through comparisons with observed TC track and rainfall over the July–November 1979–2005 seasons. The projection of landfalling TC frequency and rainfall under the representative concentration pathway (RCP) 4.5 scenario for the late twenty-first century is explored, including an assessment of the impacts of extratropical transition (ET). In most regions of the southeastern United States, competition between increased storm rain rate and decreased storm frequency dominates the change of annual TC rainfall, and rainfall from ET and non-ET storms. In the northeastern United States, a prominent feature is the striking increase of ET storm frequency but with tropical characteristics (i.e., prior to the ET phase), a key element of increased rainfall. The storm-centered rainfall composite analyses show the greatest increase at radius a few hundred kilometers from the storm centers. Over both ocean and land, the increase of rainfall within 500 km from the storm center exceeds the Clausius-Clapeyron scaling for TC-phase storms. Similar results are found in the front-left quadrant of ET-phase storms. Future work involving explorations of multiple models (e.g., higher atmospheric resolution version of FLOR) for TC rainfall projection is expected to add more robustness to projection results.
Extratropical transition can extend the threat of tropical cyclones into the mid‐latitudes, and modify it through expansion of rainfall and wind fields. Despite the scientific and socioeconomic interest, the seasonal forecast of extratropical transition has received little attention. The GFDL High‐Resolution Forecast‐Oriented Low Ocean Resolution (FLOR) model (HiFLOR) shows skill in seasonal forecasts of tropical cyclone frequency as well as major hurricanes. A July‐initialized twelve‐member ensemble retrospective seasonal forecast experiment with HiFLOR in the North Atlantic is conducted, representing one of the very first attempts to predict the extratropical transition activity months in advance. HiFLOR exhibits retrospective skill in seasonal forecasts of basin‐wide and regional ET activity relative to best track and reanalysis data. In contrast, the skill of HiFLOR in predictions of non‐ET activity is limited. Future work targeted at improved predictions of non‐ET storms provides a path for enhanced TC activity forecasting.
We explore factors potentially linked to the enhanced major hurricane activity in the Atlantic during 2017. Using a suite of high-resolution model experiments, we show that the increase in 2017 major hurricanes was not primarily caused by La Niña conditions in the Pacific Ocean, but mainly by pronounced warm sea surface conditions in the tropical North Atlantic. It is further shown that, in the future, a similar pattern of North Atlantic surface warming, superimposed upon long-term increasing sea surface temperature from increases in greenhouse gas concentrations and decreases in aerosols, will likely lead to even higher numbers of major hurricanes. The key factor controlling Atlantic major hurricane activity appears to be how much the tropical Atlantic warms relative to the rest of the global ocean.
This study examines the impacts of the Pacific Meridional Mode (PMM) on North Atlantic tropical cyclones (TCs) making landfall along the coastal US, Caribbean Islands and Mexico, and provides insights on the underlying physical mechanisms using observations and model simulations. There is a statistically significant time-lagged association between spring PMM and the August–October US and Caribbean landfalling TCs. Specifically, the positive (negative) spring PMM events tend to be followed by fewer (more) TCs affecting the coastal US (especially over the Gulf of Mexico and Florida) and the Caribbean Islands. This lagged association is mainly caused by the lagged impacts of PMM on the El Niño Southern Oscillation (ENSO), and the subsequent impacts of ENSO on TC frequency and landfalls. Positive (negative) PMM events are largely followed by El Niño (La Niña) events, which lead to less (more) TC geneses close to the US coast (i.e., the Gulf of Mexico and the Caribbean Sea); this also leads to easterly (westerly) steering flow in the vicinity of the US and Caribbean coast, which is unfavorable (favorable) to TC landfall across the Gulf of Mexico, Florida and Caribbean Islands. Perturbation simulations with the state-of-the-art Geophysical Fluid Dynamics Laboratory Forecast-oriented Low Ocean Resolution Version of CM2.5 (FLOR) support the linkage between PMM and TC landfall activity. The time-lagged impacts of spring PMM on TC landfalling activity results in a new predictor to forecast seasonal TC landfall activity along the US (especially over the Gulf of Mexico and Florida) and Caribbean coastal regions.
Over the 1997-2014 period, the mean frequency of western North Pacific (WNP) tropical cyclones (TCs) was markedly lower (~18%) than the period 1980-1996. Here we show that these changes were driven by an intensification of the vertical wind shear in the southeastern/eastern WNP tied to the changes in the Walker circulation, which arose primarily in response to the enhanced sea surface temperature (SST) warming in the North Atlantic, while the SST anomalies associated with the negative phase of the Pacific Decadal Oscillation (PDO) in the tropical Pacific and the anthropogenic forcing play only secondary roles. These results are based on observations and experiments using the Geophysical Fluid Dynamics Laboratory (GFDL) Forecast-oriented Low-ocean Resolution Coupled Climate Model (FLOR) coupled climate model. The present study suggests a crucial role of the North Atlantic SST in causing decadal changes to WNP TC frequency.
Liu, Maofeng, Gabriel A Vecchi, James A Smith, and Hiroyuki Murakami, April 2017: The Present-Day Simulation and Twenty-First-Century Projection of the Climatology of Extratropical Transition in the North Atlantic. Journal of Climate, 30(8), DOI:10.1175/JCLI-D-16-0352.1. Abstract
This study explores the simulations and 21st century projections of extratropical transition (ET) of tropical cyclones (TCs) in the North Atlantic, with a newly developed global climate model: the Forecast-oriented Low Ocean Resolution (FLOR) version of the Geophysical Fluid Dynamics Laboratory (GFDL) Coupled Model version 2.5 (CM2.5). FLOR exhibits good skill in simulating present-day ET properties (e.g., Cyclone Phase Space parameters). A version of FLOR in which sea surface temperature (SST) biases are artificially corrected through flux-adjustment (FLOR-FA) shows much improved simulation of ET activity (e.g., annual ET number). This result is largely attributable to better simulation of basinwide TC activity which is strongly dependent on larger-scale climate simulation. FLOR-FA is also used to explore changes of ET activity in the 21st century under the representative concentration pathway (RCP) 4.5 scenario. We find a contrasting pattern in which regional TC density increases in the eastern North Atlantic and decreases in the western North Atlantic, probably due to changes in the TC genesis location. The increasing TC frequency in the eastern Atlantic is dominated by increased ET cases. The increased density of TCs undergoing ET in the eastern subtropics of the Atlantic shows two propagation paths: one moves northwest towards the northeast coast of the United States and the other moves northeast toward Western Europe, implying increased TC-related risks in these regions. A more TC-favorable future climate, evident in the projected changes of SST and vertical wind shear, is hypothesized to favor the increased ET occurrence in the eastern North Atlantic.
The 2015 hurricane season in the Eastern and Central Pacific Oceans (EPO and CPO), particularly around Hawaii, was extremely active – including a record number of tropical cyclones (TCs) and the first instance of three simultaneous Category 4 hurricanes in the EPO and CPO. A strong El Niño developed during the 2015 boreal summer season, and was attributed by some to be the cause of the extreme number of TCs. However, according to a suite of targeted high-resolution model experiments, the extreme 2015 EPO and CPO hurricane season was not primarily induced by the 2015 El Niño’s tropical Pacific warming, but by warming in the subtropical Pacific Ocean. This warming is not typical of El Niño, but rather the “Pacific Meridional Mode (PMM)” superimposed on long-term anthropogenic warming. Although the likelihood of such an extreme year depends on the phase of natural variability, the coupled GCM projects an increase in the frequency of such extremely active TC years over the next few decades for the EPO, CPO, and Hawaii due enhanced subtropical Pacific warming from anthropogenic greenhouse forcing.
In 2014 and 2015, post-monsoon extremely severe cyclonic storms (ESCS)—defined by the WMO as tropical storms with lifetime maximum winds greater than 46 m s−1—were first observed over the Arabian Sea (ARB), causing widespread damage. However, it is unknown to what extent this abrupt increase in post-monsoon ESCSs can be linked to anthropogenic warming, natural variability, or stochastic behaviour. Here, using a suite of high-resolution global coupled model experiments that accurately simulate the climatological distribution of ESCSs, we show that anthropogenic forcing has likely increased the probability of late-season ECSCs occurring in the ARB since the preindustrial era. However, the specific timing of observed late-season ESCSs in 2014 and 2015 was likely due to stochastic processes. It is further shown that natural variability played a minimal role in the observed increase of ESCSs. Thus, continued anthropogenic forcing will further amplify the risk of cyclones in the ARB, with corresponding socio-economic implications.
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.
Future changes in the North American monsoon, a circulation system that brings abundant summer rains to vast areas of the North American Southwest1, 2, could have significant consequences for regional water resources3. How this monsoon will change with increasing greenhouse gases, however, remains unclear4, 5, 6, not least because coarse horizontal resolution and systematic sea-surface temperature biases limit the reliability of its numerical model simulations5, 7. Here we investigate the monsoon response to increased atmospheric carbon dioxide (CO2) concentrations using a 50-km-resolution global climate model which features a realistic representation of the monsoon climatology and its synoptic-scale variability8. It is found that the monsoon response to CO2 doubling is sensitive to sea-surface temperature biases. When minimizing these biases, the model projects a robust reduction in monsoonal precipitation over the southwestern United States, contrasting with previous multi-model assessments4, 9. Most of this precipitation decline can be attributed to increased atmospheric stability, and hence weakened convection, caused by uniform sea-surface warming. These results suggest improved adaptation measures, particularly water resource planning, will be required to cope with projected reductions in monsoon rainfall in the American Southwest.
Recent modeling studies have consistently shown that the global frequency of tropical cyclones will decrease but that of very intense tropical cyclones may increase in the future warmer climate. It has been noted, however, that the uncertainty in the projected changes in the frequency of very intense tropical cyclones, particularly the changes in the regional frequency, is very large. Here we present a projection of the changes in the frequency of intense tropical cyclones estimated by a statistical downscaling of ensemble of many high-resolution global model experiments. The results indicate that the changes in the frequency of very intense (category 4 and 5) tropical cyclones are not uniform on the globe. The frequency will increase in most regions but decrease in the south western part of Northwest Pacific, the South Pacific, and eastern part of the South Indian Ocean.
Yoshida, K, M Sugi, Ryo Mizuta, Hiroyuki Murakami, and Masao Ishii, October 2017: Future changes in tropical cyclone activity in high-resolution large-ensemble simulations. Geophysical Research Letters, 44(19), DOI:10.1002/2017GL075058. Abstract
Projected future changes in global tropical cyclone (TC) activity are assessed using 5,000-year-scale ensemble simulations for both current and 4K-surface-warming climates with a 60-km global atmospheric model. The global number of TCs decreases by 33% in the future projection. Although geographical TC occurrences decrease generally, they increase in the central and eastern parts of the extratropical North Pacific. Meanwhile, very intense (category 4 and 5) TC occurrences increase over a broader area including the south of Japan and south of Madagascar. The global number of category 4 and 5 TCs significantly decreases, contrary to the increase seen in several previous studies. Lifetime maximum surface wind speeds and precipitation rate are amplified globally. Regional TC activity changes have large uncertainty corresponding to sea surface temperature warming patterns. TC-resolving large-ensemble simulations provide useful information, especially for policy-making related to future climate change.
This study examines the year-to-year modulation of the western North Pacific (WNP) tropical cyclones (TC) activity by the Atlantic Meridional Mode (AMM) using both observations and the Geophysical Fluid Dynamics Laboratory Forecast-oriented Low Ocean Resolution Version of CM2.5 (FLOR) global coupled model. 1. The positive (negative) AMM phase suppresses (enhances) WNP TC activity in observations. The anomalous occurrence of WNP TCs results mainly from changes in TC genesis in the southeastern part of the WNP. 2. The observed responses of WNP TC activity to the AMM are connected to the anomalous zonal vertical wind shear (ZVWS) caused by AMM-induced changes to the Walker circulation. During the positive AMM phase, the warming in the North Atlantic induces strong descending flow in the tropical eastern and central Pacific, which intensifies the Walker cell in the WNP. The intensified Walker cell is responsible for the suppressed (enhanced) TC genesis in the eastern (western) part of the WNP by strengthening (weakening) ZVWS. 3. The observed WNPTC–AMM linkage is examined by the long-term control and idealized perturbations experiment with FLOR-FA. A suite of sensitivity experiments strongly corroborate the observed WNPTC–AMM linkage and underlying physical mechanisms.
This study attempts to improve the prediction of western North Pacific (WNP) and East Asia (EA) landfalling tropical cyclones (TCs) using modes of large-scale climate variability [e.g., the Pacific meridional mode (PMM), the Atlantic meridional mode (AMM), and North Atlantic sea surface temperature anomalies (NASST)] as predictors in a hybrid statistical–dynamical scheme, based on dynamical model forecasts with the GFDL Forecast-Oriented Low Ocean Resolution version of CM2.5 with flux adjustments (FLOR-FA). Overall, the predictive skill of the hybrid model for the WNP TC frequency increases from lead month 5 (initialized in January) to lead month 0 (initialized in June) in terms of correlation coefficient and root-mean-square error (RMSE). The hybrid model outperforms FLOR-FA in predicting WNP TC frequency for all lead months. The predictive skill of the hybrid model improves as the forecast lead time decreases, with values of the correlation coefficient increasing from 0.56 for forecasts initialized in January to 0.69 in June. The hybrid models for landfalling TCs over the entire East Asian (EEA) coast and its three subregions [i.e., southern EA (SEA), middle EA (MEA), and northern EA (NEA)] dramatically outperform FLOR-FA. The correlation coefficient between predicted and observed TC landfall over SEA increases from 0.52 for forecasts initialized in January to 0.64 in June. The hybrid models substantially reduce the RMSE of landfalling TCs over SEA and EEA compared with FLOR-FA. This study suggests that the PMM and NASST/AMM can be used to improve statistical/hybrid forecast models for the frequencies of WNP or East Asia landfalling TCs.
Tropical cyclone (TC) activity in the North Pacific and North Atlantic Oceans is known to be affected by the El Niño Southern Oscillation (ENSO). This study uses GFDL FLOR model, which has relatively high-resolution in the atmosphere, as a tool to investigate the sensitivity of TC activity to the strength of ENSO events. We show that TCs exhibit a non-linear response to the strength of ENSO in the tropical eastern North Pacific (ENP) but a quasi-linear response in the tropical western North Pacific (WNP) and tropical North Atlantic. Specifically, stronger El Niño results in disproportionate inhibition of TCs in the ENP and North Atlantic, and leads to an eastward shift in the location of TCs in the southeast of the WNP. However, the character of the response of TCs in the Pacific is insensitive to the amplitude of La Niña events. The eastward shift of TCs in the southeast of the WNP in response to a strong El Niño is due to an eastward shift of the convection and of the associated environmental conditions favorable for TCs. The inhibition of TC activity in the ENP and Atlantic during El Niño is attributed to the increase in the number of days with strong vertical wind shear during stronger El Niño events. These results are further substantiated with coupled model experiments. Understanding of the impact of strong ENSO on TC activity is important for present and future climate as the frequency of occurrence of extreme ENSO events is projected to increase in future.
Retrospective seasonal forecasts of North Atlantic tropical cyclone (TC) activity over the period 1980–2014 are conducted using a GFDL high-resolution coupled climate model [Forecast-Oriented Low Ocean Resolution (FLOR)]. The focus is on basin-total TC and U.S. landfall frequency. The correlations between observed and model predicted basin-total TC counts range from 0.4 to 0.6 depending on the month of the initial forecast. The correlation values for U.S. landfalling activity based on individual TCs tracked from the model are smaller and between 0.1 and 0.4. Given the limited skill from the model, statistical methods are used to complement the dynamical seasonal TC prediction from the FLOR model. Observed and predicted TC tracks were classified into four groups using fuzzy c-mean clustering to evaluate the model’s predictability in observed classification of TC tracks. Analyses revealed that the FLOR model has the highest skill in predicting TC frequency for the cluster of TCs that tracks through the Caribbean and the Gulf of Mexico.
New hybrid models are developed to improve the prediction of observed basin-total TC and landfall TC frequencies. These models use large-scale climate predictors from the FLOR model as predictors for generalized linear models. The hybrid models show considerable improvements in the skill in predicting the basin-total TC frequencies relative to the dynamical model. The new hybrid model shows correlation coefficients as high as 0.75 for basinwide TC counts from the first two lead months and retains values around 0.50 even at the 6-month lead forecast. The hybrid model also shows comparable or higher skill in forecasting U.S. landfalling TCs relative to the dynamical predictions. The correlation coefficient is about 0.5 for the 2–5-month lead times.
Skillful seasonal forecasting of tropical cyclone (TC; wind speed ≥17.5 m s−1) activity is challenging, even more so when the focus is on major hurricanes (wind speed ≥49.4 m s−1), the most intense hurricanes (Category 4–5; wind speed ≥58.1 m s−1), and landfalling TCs. Here we show that a 25-km resolution global coupled model (HiFLOR) developed at the Geophysical Fluid Dynamics Laboratory (GFDL) has improved skill in predicting the frequencies of major hurricanes and Category 4–5 hurricanes in the North Atlantic, and landfalling TCs over the United States and Caribbean Islands a few months in advance, relative to its 50-km resolution predecessor climate model (FLOR). HiFLOR also shows significant skill in predicting Category 4–5 hurricanes in the western North Pacific and eastern North Pacific, while both models show comparable skills in predicting basin-total and landfalling TC frequency in the basins. The improved skillful forecasts of basin-total TCs, major hurricanes, and Category 4–5 hurricane activity in the North Atlantic by HiFLOR are obtained mainly by improved representation of the TCs and their response to climate from the increased horizontal resolution, rather than improvements in large-scale parameters.
Ogata, Tomomichi, Ryo Mizuta, Yukimasa Adachi, Hiroyuki Murakami, and Tomoaki Ose, July 2016: Atmosphere-Ocean Coupling Effect on Intense Tropical Cyclone Distribution and its Future Change with 60 km-AOGCM. Scientific Reports, 6, 29800, DOI:10.1038/srep29800. Abstract
Atmosphere-ocean coupling effect on the frequency distribution of tropical cyclones (TCs) and its future change is studied using an atmosphere and ocean coupled general circulation model (AOGCM). In the present climate simulation, the atmosphere-ocean coupling in the AOGCM improves biases in the AGCM such as the poleward shift of the maximum of intense TC distribution in the Northern Hemisphere and too many intense TCs in the Southern Hemisphere. Particularly, subsurface cold water plays a key role to reduce these AGCM biases of intense TC distribution. Besides, the future change of intense TC distribution is significantly different between AOGCM and AGCM despite the same monthly SST. In the north Atlantic, subsurface warming causes larger increase in frequency of intense TCs in AOGCM than that in AGCM. Such subsurface warming in AOGCM also acts to alter large decrease of intense TC in AGCM to no significant change in AOGCM over the southwestern Indian Ocean. These results suggest that atmosphere-ocean coupling characterized by subsurface oceanic structure is responsible for more realistic intense TC distribution in the current climate simulation and gives significant impacts on its future projection.
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.
Precipitation extremes have a widespread impact on societies and ecosystems; it is therefore important to understand current and future patterns of extreme precipitation. Here, a set of new global coupled climate models with varying atmospheric resolution has been used to investigate the ability of these models to reproduce observed patterns of precipitation extremes and to investigate changes in these extremes in response to increased atmospheric CO2 concentrations. The atmospheric resolution was increased from 2°×2° grid cells (typical resolution in the CMIP5 archive) to 0.25°×.25° (tropical cyclone-permitting). Analysis has been confined to the contiguous United States (CONUS). It is shown that, for these models, integrating at higher atmospheric resolution improves all aspects of simulated extreme precipitation: spatial patterns, intensities and seasonal timing. In response to 2×CO2 concentrations, all models show a mean intensification of precipitation rates during extreme events of approximately 3-4% K−1. However, projected regional patterns of changes in extremes are dependent on model resolution. For example, the highest-resolution models show increased precipitation rates during extreme events in the hurricane season in the CONUS southeast, this increase is not found in the low-resolution model. These results emphasize that, for the study of extreme precipitation there is a minimum model resolution that is needed to capture the weather phenomena generating the extremes. Finally, the observed record and historical model experiments were used to investigate changes in the recent past. In part because of large intrinsic variability, no evidence was found for changes in extreme precipitation attributable to climate change in the available observed record.
This study investigates the association between the Pacific Meridional Mode (PMM) and tropical cyclone (TC) activity in the western North Pacific (WNP). It is found that the positive PMM phase favors the occurrence of TCs in the WNP while the negative PMM phase inhibits the occurrence of TCs there. Observed relationships are consistent with those from a long-term pre-industrial control experiment (1000 years) of a high-resolution TC-resolving Geophysical Fluid Dynamics Laboratory (GFDL) Forecast-oriented Low Ocean Resolution (FLOR) coupled climate model. The diagnostic relationship between the PMM and TCs in observations and the model is further supported by sensitivity experiments with FLOR. The modulation of TC genesis by the PMM is primarily through the anomalous zonal vertical wind shear (ZVWS) changes in the WNP, especially in the southeastern WNP. The anomalous ZVWS can be attributed to the responses of the atmosphere to the anomalous warming in the northwestern part of the PMM pattern during the positive PMM phase, which resembles a classic Matsuno-Gill pattern. Such influences on TC genesis are strengthened by a cyclonic flow over the WNP. The significant relationship between TCs and the PMM identified here may provide a useful reference for seasonal forecasting of TCs and interpreting changes in TC activity in the WNP.
This study aims to assess whether, and the extent to which, an increase in atmospheric resolution in versions of the Geophysical Fluid Dynamics Laboratory (GFDL) High-Resolution Forecast-oriented Low Ocean Resolution Version of CM2.5 (FLOR) with 50 km and HiFLOR with 25 km improves the simulation of the El Niño Southern Oscillation-tropical cyclone (ENSO-TC) connections in the western North Pacific (WNP). HiFLOR simulates better ENSO-TC connections in the WNP including TC track density, genesis and landfall than FLOR in both long-term control experiments and sea surface temperature (SST)- and sea surface salinity (SSS)-restoring historical runs (1971-2012). Restoring experiments are performed with SSS and SST restored to observational estimates of climatological SSS and interannually-varying monthly SST. In the control experiments of HiFLOR, an improved simulation of the Walker circulation arising from more realistic SST and precipitation is largely responsible for its better performance in simulating ENSO-TC connections in the WNP. In the SST-restoring experiments of HiFLOR, more realistic Walker circulation and steering flow during El Niño/La Niña are responsible for the improved simulation of ENSO-TC connections in the WNP. The improved simulation of ENSO-TC connections with HiFLOR arises from a better representation of SST and better responses of environmental large-scale circulation to SST anomalies associated with El Niño/La Niña. A better representation of ENSO-TC connections in HiFLOR can benefit the seasonal forecasting of TC genesis, track and landfall, improve our understanding of the interannual variation of TC activity, and provide better projection of TC activity under climate change.
Zhang, Wei, Gabriele Villarini, Gabriel A Vecchi, Hiroyuki Murakami, and Richard G Gudgel, June 2016: Statistical-dynamical seasonal forecast of western North Pacific and East Asia landfalling tropical cyclones using the high-resolution GFDL FLOR coupled model. Journal of Advances in Modeling Earth Systems, 8(2), DOI:10.1002/2015MS000607. Abstract
This study examines the seasonal prediction of western North Pacific [WNP) and East Asia landfalling tropical cyclones (TCs) using the Geophysical Fluid Dynamics Laboratory(GFDL) Forecast-oriented Low Ocean Resolution version of CM2.5 with Flux Adjustment (FLOR-FA) and finite-mixture-model (FMM)-based statistical cluster analysis. Using the FMM-based cluster analysis, seven clusters are identified from the historical and FLOR-FA-predicted TC tracks for the period 1980–2013. FLOR-FA has significant skill in predicting year-to-year variations in the frequency of TCs within clusters 1 (recurving TCs) and 5 (straight-moving TCs). By building Poisson regression models for each cluster using key predictors (i.e., sea surface temperature, 500 hPa geopotential height, and zonal vertical wind shear), the predictive skill for almost all the clusters at all initialization months improves with respect to the dynamic prediction. The prediction of total WNP TC frequency made by combining hybrid predictions for each of the seven clusters in the hybrid model shows skill higher than what achieved using the TC frequency directly from FLOR-FA initialized from March to July. However, the hybrid predictions for total WNP TC frequency initialized from January to February exhibit lower skill than FLOR-FA. The prediction of TC landfall over East Asia made by combining the hybrid models of TC frequency in each cluster and its landfall rate over East Asia also outperforms FLOR-FA for all initialization months January through July.
This study aims to assess the connections between the El Niño Southern Oscillation (ENSO) and tropical cyclones near Guam (GuamTC) using the state-of-the-art Geophysical Fluid Dynamics Laboratory (GFDL) Forecast-oriented Low Ocean Resolution Version of CM2.5 (FLOR). In observations, more (less) GuamTCs occur in El Niño (La Niña) years and the ENSO-GuamTC connections arise from TC genesis locations in ENSO phases. The observed ENSO-GuamTC connections are realistically simulated in the two control experiments that use two versions of FLOR, the standard version and another with flux adjustments (FLOR-FA). The ENSO-GuamTC connections in FLOR-FA are closer to observations than those in FLOR because of a better representation of TC genesis during ENSO phases. The physical mechanisms underlying the observed ENSO-GuamTC connections are further supported in the long-term control experiments with FLOR/FLOR-FA. The ENSO-GuamTC connections in sea surface temperature (SST)- and sea surface salinity (SSS)-restoring experiments with FLOR 1990 strongly resemble the observations, suggesting the ENSO-GuamTC connections arise substantially from the forcing of SST. The prediction skill of FLOR-FA for GuamTC frequency is quite promising in terms of correlation and root mean square error and is higher than that of FLOR for the period 1980-2014. This study shows the capability of global climate models (FLOR/FLOR-FA) in simulating the linkage between ENSO and TC activity near a highly localized region (i.e., Guam) and in predicting the frequency of TCs at the sub-basin scale.
A new high-resolution Geophysical Fluid Dynamics Laboratory (GFDL) coupled model (HiFLOR) has been developed and used to investigate potential skill in simulation and prediction of tropical cyclone (TC) activity. HiFLOR comprises of high-resolution (~25-km mesh) atmosphere and land components and a more moderate-resolution (~100-km mesh) sea ice and ocean components. HiFLOR was developed from the Forecast Oriented Low Resolution Ocean model (FLOR) by decreasing the horizontal grid spacing of the atmospheric component from 50-km to 25-km, while leaving most of the sub-gridscale physical parameterizations unchanged. Compared with FLOR, HiFLOR yields a more realistic simulation of the structure, global distribution, and seasonal and interannual variations of TCs, and a comparable simulation of storm-induced cold wakes and TC-genesis modulation induced by the Madden Julian Oscillation (MJO). Moreover, HiFLOR is able to simulate and predict extremely intense TCs (categories 4 and 5) and their interannual variations, which represents the first time a global coupled model has been able to simulate such extremely intense TCs in a multi-century simulation, sea surface temperature restoring simulations, and retrospective seasonal predictions.
Ogata, Tomomichi, Ryo Mizuta, Yukimasa Adachi, Hiroyuki Murakami, and Tomoaki Ose, December 2015: Effect of air-sea coupling on the frequency distribution of intense tropical cyclones over the northwestern Pacific. Geophysical Research Letters, 42(23), DOI:10.1002/2015GL066774. Abstract
Effect of air-sea coupling on the frequency distribution of intense tropical cyclones (TCs) over the northwestern Pacific (NWP) region is investigated using an atmosphere and ocean coupled general circulation model (AOGCM). Monthly varying flux adjustment enables AOGCM to simulate both subseasonal air-sea interaction and realistic seasonal to interannual sea surface temperature (SST) variability. The maximum of intense TC distribution around 20–30°N in the AGCM shifts equatorward in the AOGCM due to the air-sea coupling. Hence, AOGCM reduces northward intense TC distribution bias seen in AGCM. Over the NWP, AOGCM-simulated SST variability is large around 20–30°N where the warm mixed layer becomes shallower rapidly. Active entrainment from subsurface water over this region causes stronger SST cooling, and hence, TC intensity decreases. These results suggest that air-sea coupling characterized by subsurface oceanic condition causes more realistic distribution of intense TCs over the NWP.
Recent review papers reported that many high-resolution global climate models consistently projected a reduction of global tropical cyclone (TC) frequency in a future warmer climate, although the mechanism of the reduction is not yet fully understood. Here we present a result of 4K-cooler climate experiment. The global TC frequency significantly increases in the 4K-cooler climate compared to the present climate. This is consistent with a significant decrease in TC frequency in the 4K-warmer climate. For the mechanism of TC frequency reduction in a warmer climate, upward mass flux hypothesis and saturation deficit hypothesis have been proposed. The result of the 4K-cooler climate experiment is consistent with these two hypotheses. One very interesting point is that the experiment has clearly shown that TC genesis is possible at sea surface temperature (SST) well below 26°C which has been considered as the lowest SST limit for TC genesis.
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.
Yoshimura, H, Ryo Mizuta, and Hiroyuki Murakami, February 2015: A Spectral Cumulus Parameterization Scheme Interpolating Between Two Convective Updrafts with Semi-Lagrangian Calculation of Transport by Compensatory Subsidence. Monthly Weather Review, 143(2), DOI:10.1175/MWR-D-14-00068.1. Abstract
We have developed a new spectral cumulus parameterization scheme that explicitly considers an ensemble of multiple convective updrafts by interpolating in-cloud variables between two convective updrafts with large and small entrainment rates. This cumulus scheme has the advantages that the variables in entraining and detraining convective updrafts are calculated in detail layer-by-layer as in the Tiedtke scheme, and that a spectrum of convective updrafts with different heights due to difference in entrainment rates is explicitly represented, as in the Arakawa–Schubert scheme. A conservative and monotonic semi-Lagrangian scheme is used for calculation of transport by convection-induced compensatory subsidence. Use of the semi-Lagrangian scheme relaxes the mass flux limit due to the Courant–Friedrichs–Lewy (CFL) condition, and moreover ensures non-negative natural material transport. A global atmospheric model using this cumulus scheme gives an atmospheric simulation that agrees well with the observational climatology.
Christensen, J H., K K Kanikicharla, Thomas R Knutson, Hiroyuki Murakami, Mary Jo Nath, and Andrew T Wittenberg, et al., March 2014: Climate Phenomena and their Relevance for Future Regional Climate Change In Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, DOI:10.1017/CBO9781107415324.0281217-1308.
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.
Hsu, P, Tim Li, and Hiroyuki Murakami, December 2014: Moisture Asymmetry and MJO Eastward Propagation in an Aquaplanet General Circulation Model. Journal of Climate, 27(13), DOI:10.1175/JCLI-D-14-00148.1. Abstract
The role of zonal moisture asymmetry in the eastward propagation of the Madden–Julian oscillation (MJO) is investigated through a set of aquaplanet atmospheric general circulation model (AGCM) experiments with a zonally symmetric sea surface temperature distribution. In the control experiment, the model produces eastward-propagating MJO-like perturbations with a dominant period of 30–90 days. The model MJO exhibits a clear zonal asymmetry in the lower-tropospheric specific humidity field, with a positive (negative) anomaly appearing to the east (west) of the MJO convection. A diagnosis of the lower-tropospheric moisture budget indicates that the asymmetry primarily arises from vertical moisture advection associated with boundary layer convergence, while horizontal moisture advection has the opposite effect.
In a sensitivity experiment, the lower-tropospheric specific humidity field is relaxed toward a zonal-mean basic state derived from the control simulation. In this case, the model’s mean state remains the same, but its intraseasonal mode becomes quasi-stationary. The numerical model experiments clearly demonstrate the importance of the zonal moisture asymmetry in MJO eastward propagation.
Murakami, Hiroyuki, M Sugi, and A Kitoh, January 2014: Future Changes in Tropical Cyclone Activity in the North Indian Ocean Projected by the New High-Resolution MRI-AGCM In Monitoring and Prediction of Tropical Cyclones in the Indian Ocean and Climate Change, New Delhi, India, Springer, DOI:10.1007/978-94-007-7720-0_6.
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.
Sugi, M, Hiroyuki Murakami, and J Yoshimura, January 2014: Mechanism of the Indian Ocean Tropical Cyclone Frequency Changes due to Global Warming In Monitoring and Prediction of Tropical Cyclones in the Indian Ocean and Climate Change, New Delhi, India, Springer, DOI:10.1007/978-94-007-7720-0_4.
Zhao, H, Pao-Shin Chu, Pang-Chi Hsu, and Hiroyuki Murakami, December 2014: Exploratory analysis of extremely low tropical cyclone activity during the late-season of 2010 and 1998 over the western North Pacific and the South China Sea. Journal of Advances in Modeling Earth Systems, 6(4), DOI:10.1002/2014MS000381. Abstract
This study attempts to understand why the tropical cyclone (TC) frequency over the western North Pacific and the South China Sea was so low in 2010 and 1998 even though a strong La Niña signal occurred in both years. We found that the TC frequency during the late-season (October to December), not in the peak season (July to September), makes 2010 a record low year; the next lowest year is 1998. Specifically, four TCs were observed over the South China Sea (SCS) in the late-season of 1998, but no TCs occurred over the SCS in the same season during 2010. The genesis potential index is used to help diagnose changes in environmental conditions for TC genesis frequency. Results indicate that the decreased low-level vorticity makes the largest contribution to the decreased TC formation over the SCS. The second largest contribution comes from the enhanced vertical wind shear, with relatively small contributions from the negative anomaly in potential intensity and reduction in midlevel relative humidity. These observational results are consistent with numerical simulations using a state of the art model from the Meteorological Research Institute (MRI-AGCM 3.2 Model). Numerical experiments show that the unfavorable conditions for sharply decreased TC formation during the late-season over the SCS in 2010 mainly results from the sea surface temperature anomaly over the western North Pacific basin. This effect is partly offset by the sea surface temperature anomaly in the South Indian Ocean and Northern Indian Ocean basins.
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.
