Seasonal advance of intense tropical cyclones in a warming climate.
Journal
Nature
ISSN: 1476-4687
Titre abrégé: Nature
Pays: England
ID NLM: 0410462
Informations de publication
Date de publication:
Nov 2023
Nov 2023
Historique:
received:
25
01
2023
accepted:
15
08
2023
medline:
3
11
2023
pubmed:
28
9
2023
entrez:
27
9
2023
Statut:
ppublish
Résumé
Intense tropical cyclones (TCs), which often peak in autumn
Identifiants
pubmed: 37758952
doi: 10.1038/s41586-023-06544-0
pii: 10.1038/s41586-023-06544-0
pmc: PMC10620083
doi:
Substances chimiques
Greenhouse Gases
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
83-89Informations de copyright
© 2023. The Author(s).
Références
Mei, W. et al. Northwestern Pacific typhoon intensity controlled by changes in ocean temperatures. Sci. Adv. 1, e1500014 (2015).
pubmed: 26601179
pmcid: 4640637
doi: 10.1126/sciadv.1500014
Shan, K. & Yu, X. Interdecadal variability of tropical cyclone genesis frequency in western North Pacific and South Pacific Ocean basins. Environ. Res. Lett. 15, 064030 (2020).
doi: 10.1088/1748-9326/ab8093
Klotzbach, P. et al. Surface pressure a more skillful predictor of normalized hurricane damage than maximum sustained wind. Bull. Am. Meteorological Soc. 101, E830–E846 (2020).
doi: 10.1175/BAMS-D-19-0062.1
Patricola, C., Cassidy, D. & Klotzbach, P. Tropical oceanic influences on observed global tropical cyclone frequency. Geophys. Res. Lett. 49, e2022GL099354 (2022).
doi: 10.1029/2022GL099354
Zhu, Y., Collins, J., Klotzbach, P. & Schreck, C. III Hurricane Ida (2021): rapid intensification followed by slow inland decay. Bull. Am. Meteorological Soc. 103, E2354–E2369 (2022).
doi: 10.1175/BAMS-D-21-0240.1
Song, F., Leung, R., Lu, J. & Dong, L. Seasonally dependent responses of subtropical highs and tropical rainfall to anthropogenic warming. Nat. Clim. Change 8, 787–792 (2018).
doi: 10.1038/s41558-018-0244-4
Song, F. et al. Emergence of seasonal delay of tropical rainfall during 1979–2019. Nat. Clim. Change 11, 605–612 (2021).
doi: 10.1038/s41558-021-01066-x
Mei, W. & Xie, S. Intensification of landfalling typhoons over the northwest Pacific since the late 1970s. Nat. Geosci. 9, 753–757 (2016).
doi: 10.1038/ngeo2792
Wang, S. & Toumi, R. Recent migration of tropical cyclones toward coasts. Science 371, 514–517 (2021).
pubmed: 33510027
doi: 10.1126/science.abb9038
IPCC Special Report on Global Warming of 1.5 °C (eds Masson-Delmotte, V. et al) (Cambridge Univ. Press, 2018).
Emanuel, K. Response of global tropical cyclone activity to increasing CO
doi: 10.1175/JCLI-D-20-0367.1
Kossin, J., Knapp, K., Olander, T. & Velden, C. Global increase in major tropical cyclone exceedance probability over the past four decades. Proc. Natl Acad. Sci. USA 117, 11975–11980 (2020).
pubmed: 32424081
pmcid: 7275711
doi: 10.1073/pnas.1920849117
Chand, S. et al. Declining tropical cyclone frequency under global warming. Nat. Clim. Change 12, 655–661 (2022).
doi: 10.1038/s41558-022-01388-4
Emanuel, K. Atlantic tropical cyclones downscaled from climate reanalyses show increasing activity over past 150 years. Nat. Commun. 12, 7027 (2021).
pubmed: 34857770
pmcid: 8639808
doi: 10.1038/s41467-021-27364-8
Vecchi, G. & Knutson, T. On estimates of historical North Atlantic tropical cyclone activity. J. Clim. 21, 3580–3600 (2008).
doi: 10.1175/2008JCLI2178.1
Emanuel, K. Downscaling CMIP5 climate models shows increased tropical cyclone activity over the 21st century. Proc. Natl Acad. Sci. USA 110, 12219–12224 (2013).
pubmed: 23836646
pmcid: 3725040
doi: 10.1073/pnas.1301293110
Kossin, J., Emanuel, K. & Vecchi, G. The poleward migration of the location of tropical cyclone maximum intensity. Nature 509, 349–352 (2014).
pubmed: 24828193
doi: 10.1038/nature13278
Sharmila, S. & Walsh, K. Recent poleward shift of tropical cyclone formation linked to Hadley cell expansion. Nat. Clim. Change 8, 730–736 (2018).
doi: 10.1038/s41558-018-0227-5
Shan, K. & Yu, X. Enhanced understanding to poleward migration of tropical cyclone genesis. Environ. Res. Lett. 15, 104062 (2020).
doi: 10.1088/1748-9326/abaf85
Feng, X., Klingaman, N. & Hodges, K. Poleward migration of western North Pacific tropical cyclones related to changes in cyclone seasonality. Nat. Commun. 12, 6210 (2021).
pubmed: 34707112
pmcid: 8551271
doi: 10.1038/s41467-021-26369-7
Truchelut, R. et al. Earlier onset of North Atlantic hurricane season with warming oceans. Nat. Commun. 13, 4646 (2022).
pubmed: 35973988
pmcid: 9381499
doi: 10.1038/s41467-022-31821-3
Knutson, T. et al. Tropical cyclones and climate change assessment. Part 1: detection and attribution. Bull. Am. Meteorological Soc. 100, 1987–2007 (2019).
doi: 10.1175/BAMS-D-18-0189.1
Sobel, A. et al. Human influence on tropical cyclone intensity. Science 353, 242–246 (2016).
pubmed: 27418502
doi: 10.1126/science.aaf6574
Murakami, H. et al. Dominant effect of relative tropical Atlantic warming on major hurricane occurrence. Science 117, 10706–10714 (2018).
Pielke, R. Jr et al. Normalized hurricane amage in the United States: 1900–2005. Nat. Hazards Rev. 9, 29–42 (2008).
doi: 10.1061/(ASCE)1527-6988(2008)9:1(29)
Mendelsohn, R., Emanuel, K., Chonabayashi, S. & Bakkensen, L. The impact of climate change on global tropical cyclone damage. Nat. Clim. Change 2, 205–209 (2012).
doi: 10.1038/nclimate1357
Klotzbach, P., Bowen, S., Pielke, R. Jr & Bell, M. Continental U.S. hurricane landfall frequency and associated damage: observations and future risks. Bull. Am. Meteorological Soc. 99, 1359–1376 (2018).
doi: 10.1175/BAMS-D-17-0184.1
Elsner, J., Kossin, J. & Jagger, T. The increasing intensity of the strongest tropical cyclones. Nature 455, 92–95 (2008).
pubmed: 18769438
doi: 10.1038/nature07234
Patricola, C. & Wehner, M. Anthropogenic influences on major tropical cyclone events. Nature 563, 339–346 (2018).
pubmed: 30429550
doi: 10.1038/s41586-018-0673-2
Dwyer, J. et al. Projected twenty-first-century changes in the length of the tropical cyclone season. J. Clim. 28, 6181–6192 (2015).
doi: 10.1175/JCLI-D-14-00686.1
Bloemendaal, N. et al. A globally consistent local-scale assessment of future tropical cyclone risk. Sci. Adv. 8, eabm8438 (2022).
pubmed: 35476436
pmcid: 9045717
doi: 10.1126/sciadv.abm8438
Chu, P. & Murakami, H. Climate Variability and Tropical Cyclone Activity (Cambridge Univ. Press, 2022).
Zscheischler, J. et al. Future climate risk from compound events. Nat. Clim. Change 8, 469–477 (2018).
doi: 10.1038/s41558-018-0156-3
Matthews, T., Wilby, R. & Murphy, C. An emerging tropical cyclone–deadly heat compound hazard. Nat. Clim. Change 9, 602–606 (2019).
doi: 10.1038/s41558-019-0525-6
Klotzbach, P. et al. Trends in global tropical cyclone activity: 1990–2021. Geophys. Res. Lett. 49, e2021GL095774 (2022).
doi: 10.1029/2021GL095774
Lee, C. et al. Rapid intensification and the bimodal distribution of tropical cyclone intensity. Nat. Commun. 7, 10625 (2016).
pubmed: 26838056
pmcid: 4742962
doi: 10.1038/ncomms10625
Klotzbach, P. El Niño–Southern Oscillation, the Madden–Julian Oscillation and Atlantic basin tropical cyclone rapid intensification. J. Geophys. Res. 117, D1410 (2012).
Kaplan, J. et al. Evaluating environmental impacts on tropical cyclone rapid intensification predictability utilizing statistical models. Weather Forecast. 30, 1374–1396 (2015).
doi: 10.1175/WAF-D-15-0032.1
Ge, X., Shi, D. & Guan, L. Monthly variations of tropical cyclone rapid intensification ratio in the western North Pacific. Atmos. Sci. Lett. 19, e814 (2018).
doi: 10.1002/asl.814
Klotzbach, P. et al. Seasonal tropical cyclone forecasting. Trop. Cyclone Res. Rev. 10, 134–149 (2019).
doi: 10.1016/j.tcrr.2019.10.003
Bister, M. & Emanuel, K. Low frequency variability of tropical cyclone potential intensity. 1. Interannual to interdecadel variability. J. Geophys. Res. 107, 4801 (2002).
Vecchi, G. & Soden, B. Effect of remote sea surface temperature change on tropical cyclone potential intensity. Nature 450, 1066–1070 (2007).
pubmed: 18075590
doi: 10.1038/nature06423
Bhatia, K. et al. A potential explanation for the global increase in tropical cyclone rapid intensification. Nat. Commun. 13, 6626 (2022).
pubmed: 36333371
pmcid: 9636401
doi: 10.1038/s41467-022-34321-6
Sobel, A. & Camargo, S. Projected future changes in tropical summer climate. J. Clim. 24, 473–487 (2011).
doi: 10.1175/2010JCLI3748.1
Zhao, H., Duan, X., Raga, G. & Klotzbach, P. Changes in characteristics of rapidly intensifying western North Pacific tropical cyclones related to climate regime shifts. J. Clim. 31, 8163–8179 (2018).
doi: 10.1175/JCLI-D-18-0029.1
Song, F., Lu, J., Leung, R. & Liu, F. Contrasting phase changes of precipitation annual cycle between land and ocean under global warming. Geophys. Res. Lett. 47, e2020GL090327 (2020).
doi: 10.1029/2020GL090327
Gao, H., Jiang, W. & Li, W. Transition of the annual cycle of precipitation from double-peak mode to single-peak mode in South China. Chin. Sci. Bull. 58, 3994–3999 (2013).
doi: 10.1007/s11434-013-5905-0
Luo, Y. et al. Synoptic situations of extreme hourly precipitation over China. J. Clim. 26, 110–132 (2016).
doi: 10.1175/JCLI-D-12-00100.1
Marsooli, R., Lin, N., Emanuel, K. & Feng, K. Climate change exacerbates hurricane flood hazards along US Atlantic and Gulf coasts in spatially varying patterns. Nat. Commun. 10, 3785 (2019).
pubmed: 31439853
pmcid: 6706450
doi: 10.1038/s41467-019-11755-z
Easterling, D. et al. Climate extremes: observations, modeling, and impacts. Science 289, 2068–2074 (2000).
pubmed: 11000103
doi: 10.1126/science.289.5487.2068
Knapp, K. et al. The international best track archive for climate stewardship (IBTrACS) unifying tropical cyclone data. Bull. Am. Meteorological Soc. 91, 363–376 (2010).
doi: 10.1175/2009BAMS2755.1
Knapp, K. Calibration of long-term geostationary infrared observations using HIRS. J. Atmos. Ocean. Technol. 25, 183–195 (2008).
doi: 10.1175/2007JTECHA910.1
Bhatia, T. et al. Recent increases in tropical cyclone intensification rates. Nat. Commun. 10, 635 (2019).
pubmed: 30733439
pmcid: 6367364
doi: 10.1038/s41467-019-08471-z
Wilks, D. Statistical Methods in Atmospheric Sciences (Elsevier, 2019).
Leipper, D. & Volgenau, D. Hurricane heat potential of the Gulf of Mexico. J. Phys. Oceanogr. 2, 218–224 (1972).
doi: 10.1175/1520-0485(1972)002<0218:HHPOTG>2.0.CO;2
Zuo, H., Balmaseda, M., Mogensen, K. & Tietsche, S. OCEAN5: The ECMWF Ocean Reanalysis System and its Real-Time Analysis Component 2018 ECMWF Technical Memorandum (ECMWF, 2018).
Behringer, D. W. & Xue, Y. Evaluation of the global ocean data assimilation system at NCEP: the Pacific Ocean. In Proc. Eighth Symposium on Integrated Observing and Assimilation Systems for Atmosphere, Oceans, and Land Surface, AMS 84th Annual Meeting11–15 (AMS, 2004).
Hersbach, H. et al. The ERA5 global reanalysis. Quart. J. R. Met. Soc. 146, 1999–2049 (2020).
doi: 10.1002/qj.3803
Kobayashi, S. et al. The JRA-55 reanalysis: general specifications and basic characteristics. J. Meteorol. Soc. Jpn. 93, 5–48 (2015).
doi: 10.2151/jmsj.2015-001
Gelaro, R. et al. The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). J. Clim. 30, 5419–5454 (2017).
doi: 10.1175/JCLI-D-16-0758.1
Keller, J. & Wahl, S. Representation of climate in reanalyses: an intercomparison for Europe and North America. J. Clim. 34, 1667–1684 (2021).
doi: 10.1175/JCLI-D-20-0609.1
Eyring, V. et al. Overview of the Coupled Model Intercomparison Project phase 6 (CMIP6) experimental design and organization. Geosci. Model Dev. 9, 1937–1958 (2016).
doi: 10.5194/gmd-9-1937-2016
Rodgers, K. et al. Ubiquity of human-induced changes in climate variability. Earth Syst. Dyn. 12, 1393–1411 (2021).
doi: 10.5194/esd-12-1393-2021
Hsu, W., Patricola, C. & Chang, P. The impact of climate model sea surface temperature biases on tropical cyclone simulations. Clim. Dyn. 53, 173–192 (2019).
doi: 10.1007/s00382-018-4577-5
Huang, H., Patricola, C. & Collins, W. The influence of ocean coupling on simulated and projected tropical cyclone precipitation in the HighResMIP-PRIMAVERA simulations. Geophys. Res. Lett. 48, e2021GL094801 (2021).
doi: 10.1029/2021GL094801
Gillett, N. et al. The detection and attribution model intercomparison project (DAMIP v1.0) contribution to CMIP6. Geosci. Model Dev. 9, 3685–3697 (2016).
doi: 10.5194/gmd-9-3685-2016
Chen, M. et al. Assessing objective techniques for gauge-based analyses of global daily precipitation. J. Geophys. Res. 113, D04110 (2008).
Dare, R., Davidson, N. & McBride, J. Tropical cyclone contribution to rainfall over Australia. Mon. Weather Rev. 140, 3606–3619 (2012).
doi: 10.1175/MWR-D-11-00340.1
Zhang, W., Villarini, G., Vecchi, G. & Murakami, H. 2019: rainfall from tropical cyclones: high-resolution simulations and seasonal forecasts. Clim. Dyn. 52, 5269–5289 (2019).
doi: 10.1007/s00382-018-4446-2
Chen, Y. & Zhai, P. Persistent extreme precipitation events in China during 1951–2010. Clim. Res. 57, 143–155 (2013).
doi: 10.3354/cr01171
Chu, P., Chen, Y. & Schroeder, T. Changes in precipitation extremes in the Hawaiian Islands in a warming climate. J. Clim. 23, 4881–4900 (2010).
doi: 10.1175/2010JCLI3484.1
Murakami, H. et al. Detected climatic change in global distribution of tropical cyclones. Proc. Natl Acad. Sci. USA 117, 10706–10714 (2020).
pubmed: 32366651
pmcid: 7245084
doi: 10.1073/pnas.1922500117
Mondal, A., Kundu, S. & Mukhopadhyay, A. Rainfall trend analysis by Mann–Kendall test: a case study of north-eastern part of Cuttack district, Orissa. Int. J. Geol. Earth. Environ. Sci. 2, 70–78 (2012).
Jiang, J. & Zhou, T. Human‐induced rainfall reduction in drought‐prone northern central Asia. Geophys. Res. Lett. 48, e2020GL092156 (2021).
doi: 10.1029/2020GL092156
Weissgerber, T., Milic, N., Winham, S. & Garovic, V. Beyond bar and line graphs: time for a new data presentation paradigm. PLoS Biol. 13, e1002128 (2015).
pubmed: 25901488
pmcid: 4406565
doi: 10.1371/journal.pbio.1002128
Hunter, J. Matplotlib: a 2D graphics environment. Comput. Sci. Eng. 9, 90–95 (2007).
doi: 10.1109/MCSE.2007.55
Bi, D. et al. Configuration and spin-up of ACCESS-CM2, the new generation Australian Community Climate and Earth System Simulator Coupled Model. J. South. Hemisph. Earth Syst. Sci. https://doi.org/10.1071/ES19040 (2020).
doi: 10.1071/ES19040
Wu, T. et al. Beijing Climate Center Earth System Model version 1 (BCC-ESM1): model description and evaluation of aerosol simulations. Geosci. Model Dev. 13, 977–1005 (2020).
doi: 10.5194/gmd-13-977-2020
Rong, X.-Y. et al. Introduction of CAMS-CSM model and its participation in CMIP6. Clim. Change Res. 15, 540–544 (2019).
Swart, N. C. et al. The Canadian Earth System Model version 5 (CanESM5.0.3). Geosci. Model Dev. 12, 4823–4873 (2019).
doi: 10.5194/gmd-12-4823-2019
Jin, J. B. et al. CAS-ESM2.0 model datasets for the CMIP6 Flux-Anomaly-Forced Model Intercomparison Project (FAFMIP). Adv. Atmos. Sci. 38, 296–306 (2021).
doi: 10.1007/s00376-020-0188-2
Danabasoglu, G. et al. The Community Earth System Model Version 2 (CESM2). J. Adv. Model. Earth Syst. 12, e2019MS001916 (2020).
doi: 10.1029/2019MS001916
Lin, Y. et al. Community Integrated Earth System Model (CIESM): description and evaluation. J. Adv. Model. Earth Syst. 12, e2019MS002036 (2020).
doi: 10.1029/2019MS002036
Lovato, T. et al. CMIP6 simulations with the CMCC Earth System Model (CMCC-ESM2). J. Adv. Model. Earth Syst. 14, e2021MS002814 (2022).
doi: 10.1029/2021MS002814
Zheng, X. et al. Description of historical and future projection simulations by the global coupled E3SMv1.0 model as used in CMIP6. Geosci. Model Dev. 15, 3941–3967 (2022).
doi: 10.5194/gmd-15-3941-2022
Li, L. et al. The flexible global ocean-atmosphere-land system model grid-point version 3 (fgoals-g3): description and evaluation. J. Adv. Model. Earth Syst. 12, e2019MS002012 (2020).
doi: 10.1029/2019MS002012
Bao, Y., Song, Z. & Qiao, F. FIO-ESM version 2.0: model description and evaluation. J. Geophys. Res. Oceans 125, e2019JC016036 (2020).
doi: 10.1029/2019JC016036
Dunne, J. P. et al. The GFDL Earth System Model Version 4.1 (GFDL-ESM 4.1): overall coupled model description and simulation characteristics. J. Adv. Model. Earth Syst. 12, e2019MS002015 (2020).
doi: 10.1029/2019MS002015
Kelley, M. et al. GISS-E2.1: configurations and climatology. J. Adv. Model. Earth Syst. 12, e2019MS002025 (2020).
pubmed: 32999704
pmcid: 7507764
doi: 10.1029/2019MS002025
Volodin, E. & Gritsun, A. Simulation of observed climate changes in 1850–2014 with climate model INM-CM5. Earth Syst. Dyn. 9, 1235–1242 (2018).
doi: 10.5194/esd-9-1235-2018
Boucher, O. et al. Presentation and evaluation of the IPSL-CM6A-LR climate model. J. Adv. Model. Earth Syst. 12, e2019MS002010 (2020).
doi: 10.1029/2019MS002010
Stouffer, R. U of Arizona MCM-UA-1-0 Model Output Prepared for CMIP6 CMIP v.20230314 (Earth System Grid Federation, 2019); https://doi.org/10.22033/ESGF/CMIP6.2421 .
Mauritsen, T. et al. Developments in the MPI-M Earth System Model version 1.2 (MPI-ESM1.2) and its response to increasing CO
pubmed: 32742553
pmcid: 7386935
doi: 10.1029/2018MS001400
Yukimoto, S. et al. The Meteorological Research Institute Earth System Model version 2.0, MRI-ESM2.0: description and basic evaluation of the physical component. J. Meteor. Soc. Japan 97, 931–965 (2019).
doi: 10.2151/jmsj.2019-051
Cao, J. et al. The NUIST Earth System Model (NESM) version 3: description and preliminary evaluation. Geosci. Model Dev. 11, 2975–2993 (2018).
doi: 10.5194/gmd-11-2975-2018
Seland, Ø. et al. Overview of the Norwegian Earth System Model (NorESM2) and key climate response of CMIP6 DECK, historical, and scenario simulations. Geosci. Model Dev. 13, 6165–6200 (2020).
doi: 10.5194/gmd-13-6165-2020