• Adler, R. F., and Coauthors, 2003: The version-2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979–present). J. Hydrometeor., 4, 11471167, https://doi.org/10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ashrit, R. G., A. Kitoh, and S. Yukimoto, 2005: Transient response of ENSO–monsoon teleconnection in MRI-CGCM2.2 climate change simulations. J. Meteor. Soc. Japan, 83, 273291, https://doi.org/10.2151/JMSJ.83.273.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Biasutti, M., 2013: Forced Sahel rainfall trends in the CMIP5 archive. J. Geophys. Res. Atmos., 118, 16131623, https://doi.org/10.1002/JGRD.50206.

  • Bony, S., G. Bellon, D. Klocke, S. Sherwood, S. Fermepin, and S. Denvil, 2013: Robust direct effect of carbon dioxide on tropical circulation and regional precipitation. Nat. Geosci., 6, 447451, https://doi.org/10.1038/ngeo1799.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bukovsky, M. S., C. M. Carrillo, D. J. Gochis, D. M. Hammerling, R. R. McCrary, and L. O. Mearns, 2015: Toward assessing NARCCAP regional climate model credibility for the North American monsoon: Future climate simulations. J. Climate, 28, 67076728, https://doi.org/10.1175/JCLI-D-14-00695.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cai, W., and Coauthors, 2014: Increasing frequency of extreme El Niño events due to greenhouse warming. Nat. Climate Change, 4, 111116, https://doi.org/10.1038/nclimate2100.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chadwick, R., P. Good, and K. Willett, 2016: A simple moisture advection model of specific humidity change over land in response to SST warming. J. Climate, 29, 76137632, https://doi.org/10.1175/JCLI-D-16-0241.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, X., and T. Zhou, 2015: Distinct effects of global mean warming and regional sea surface warming pattern on projected uncertainty in the South Asian summer monsoon. Geophys. Res. Lett., 42, 94339439, https://doi.org/10.1002/2015GL066384.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Colorado-Ruiz, G., T. Cavazos, J. A. Salinas, P. De Grau, and R. Ayala, 2018: Climate change projections from Coupled Model Intercomparison Project phase 5 multi-model weighted ensembles for Mexico, the North American monsoon, and the mid-summer drought region. Int. J. Climatol., 38, 56995716, https://doi.org/10.1002/joc.5773.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cook, B. I., and R. Seager, 2013: The response of the North American monsoon to increased greenhouse gas forcing. J. Geophys. Res. Atmos., 118, 16901699, https://doi.org/10.1002/JGRD.50111.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597, https://doi.org/10.1002/qj.828.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Duffy, P. B., P. Brando, G. P. Asner, and C. B. Field, 2015: Projections of future meteorological drought and wet periods in the Amazon. Proc. Natl. Acad. Sci. USA, 112, 13 17213 177, https://doi.org/10.1073/pnas.1421010112.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Endo, H., and A. Kitoh, 2014: Thermodynamic and dynamic effects on regional monsoon rainfall changes in a warmer climate. Geophys. Res. Lett., 41, 17041711, https://doi.org/10.1002/2013GL059158.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Endo, H., A. Kitoh, and H. Ueda, 2018: A unique feature of the Asian summer monsoon response to global warming: The role of different land–sea thermal contrast change between the lower and upper troposphere. SOLA, 14, 5763, https://doi.org/10.2151/SOLA.2018-010.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Eyring, V., S. Bony, G. A. Meehl, C. A. Senior, B. Stevens, R. J. Stouffer, and K. E. Taylor, 2016: Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geosci. Model Dev., 9, 19371958, https://doi.org/10.5194/gmd-9-1937-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fasullo, J., 2012: A mechanism for land–ocean contrasts in global monsoon trends in a warming climate. Climate Dyn., 39, 11371147, https://doi.org/10.1007/s00382-011-1270-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Geil, K. L., Y. L. Serra, and X. Zeng, 2013: Assessment of CMIP5 model simulations of the North American monsoon system. J. Climate, 26, 87878801, https://doi.org/10.1175/JCLI-D-13-00044.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Guo, Q.-Y., 1983: The summer monsoon intensity index in East Asia and its variation. Acta Geogr. Sin., 38, 207217.

  • Held, I. M., and B. J. Soden, 2006: Robust responses of the hydrological cycle to global warming. J. Climate, 19, 56865699, https://doi.org/10.1175/JCLI3990.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hsu, P., T. Li, H. Murakami, and A. Kitoh, 2013: Future change of the global monsoon revealed from 19 CMIP5 models. J. Geophys. Res. Atmos., 118, 12471260, https://doi.org/10.1002/JGRD.50145.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huang, B., and Coauthors, 2017: Extended Reconstructed Sea Surface Temperature, version 5 (ERSSTv5): Upgrades, validations, and intercomparisons. J. Climate, 30, 81798205, https://doi.org/10.1175/JCLI-D-16-0836.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jones, C., and L. M. V. Carvalho, 2013: Climate change in the South American monsoon system: Present climate and CMIP5 projections. J. Climate, 26, 66606678, https://doi.org/10.1175/JCLI-D-12-00412.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jourdain, N. C., A. Sen Gupta, A. S. Taschetto, C. C. Ummenhofer, A. F. Moise, and K. Ashok, 2013: The Indo-Australian monsoon and its relationship to ENSO and IOD in reanalysis data and the CMIP3/CMIP5 simulations. Climate Dyn., 41, 30733102, https://doi.org/10.1007/s00382-013-1676-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kitoh, A., H. Endo, K. Krishna Kumar, I. F. A. Cavalcanti, P. Goswami, and T. Zhou, 2013: Monsoons in a changing world: A regional perspective in a global context. J. Geophys. Res. Atmos., 118, 30533065, https://doi.org/10.1002/JGRD.50258.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lee, J.-Y., and B. Wang, 2014: Future change of global monsoon in the CMIP5. Climate Dyn., 42, 101119, https://doi.org/10.1007/s00382-012-1564-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Magaña, V. O., J. L. Vázquez, J. L. Pérez, and J. B. Pérez, 2003: Impact of El Niño on precipitation in Mexico. Geofis. Int., 42, 313330.

    • Search Google Scholar
    • Export Citation
  • Malhi, Y., J. T. Roberts, R. A. Betts, T. J. Killeen, W. Li, and C. A. Nobre, 2008: Climate change, deforestation, and the fate of the Amazon. Science, 319, 169172, https://doi.org/10.1126/science.1146961.

    • Search Google Scholar
    • Export Citation
  • Mastrandrea, M. D., and Coauthors, 2010: Guidance note for lead authors of the IPCC Fifth Assessment Report on consistent treatment of uncertainties. IPCC, 7 pp., https://www.ipcc.ch/site/assets/uploads/2018/05/uncertainty-guidance-note.pdf.

  • Meehl, G. A., and Coauthors, 2007: Global climate projections. Climate Change 2007: The Physical Science Basis, S. Solomon et al., Eds., Cambridge University Press, 747–846.

  • Menon, A., A. Levermann, J. Schewe, J. Lehmann, and K. Frieler, 2013: Consistent increase in Indian monsoon rainfall and its variability across CMIP-5 models. Earth Syst. Dyn., 4, 287300, https://doi.org/10.5194/esd-4-287-2013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Meyer, J. D. D., and J. Jin, 2017: The response of future projections of the North American monsoon when combining dynamical downscaling and bias correction of CCSM4 output. Climate Dyn., 49, 433447, https://doi.org/10.1007/s00382-016-3352-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Moon, S., and K.-J. Ha, 2017: Temperature and precipitation in the context of the annual cycle over Asia: Model evaluation and future change. Asia-Pac. J. Atmos. Sci., 53, 229242, https://doi.org/10.1007/s13143-017-0024-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nam, C., S. Bony, J. Dufresne, and H. Chepfer, 2012: The ‘too few, too bright’ tropical low-cloud problem in CMIP5 models. Geophys. Res. Lett., 39, L21801, https://doi.org/10.1029/2012gl053421.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • North, G. R., T. L. Bell, R. F. Cahalan, and F. J. Moeng, 1982: Sampling errors in the estimation of empirical orthogonal functions. Mon. Wea. Rev., 110, 699706, https://doi.org/10.1175/1520-0493(1982)110<0699:SEITEO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • O’Neill, B. C., and Coauthors, 2016: The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6. Geosci. Model Dev., 9, 34613482, https://doi.org/10.5194/gmd-9-3461-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pachauri, R. K., and Coauthors, 2014: Climate Change 2014: Synthesis Report. IPCC, 151 pp.,https://www.ipcc.ch/site/assets/uploads/2018/05/SYR_AR5_FINAL_full_wcover.pdf.

  • Pascale, S., W. R. Boos, S. Bordoni, T. L. Delworth, S. B. Kapnick, H. Murakami, G. A. Vecchi, and W. Zhang, 2017: Weakening of the North American monsoon with global warming. Nat. Climate Change, 7, 806812, https://doi.org/10.1038/nclimate3412.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ramage, C. S., 1971: Monsoon Meteorology. Academic Press, 296 pp.

  • Rayner, N. A., D. E. Parker, E. B. Horton, C. K. Folland, L. V. Alexander, D. P. Rowell, E. C. Kent, and A. Kaplan, 2003: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res., 108, 4407, https://doi.org/10.1029/2002JD002670.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roehrig, R., D. Bouniol, F. Guichard, F. Hourdin, and J.-L. Redelsperger, 2013: The present and future of the West African monsoon: A process-oriented assessment of CMIP5 simulations along the AMMA transect. J. Climate, 26, 64716505, https://doi.org/10.1175/JCLI-D-12-00505.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sabeerali, C. T., and R. S. Ajayamohan, 2018: On the shortening of Indian summer monsoon season in a warming scenario. Climate Dyn., 50, 16091624, https://doi.org/10.1007/s00382-017-3709-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seager, R., N. Naik, and G. A. Vecchi, 2010: Thermodynamic and dynamic mechanisms for large-scale changes in the hydrological cycle in response to global warming. J. Climate, 23, 46514668, https://doi.org/10.1175/2010JCLI3655.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seager, R., M. Cane, N. Henderson, D.-E. Lee, R. Abernathey, and H. Zhang, 2019: Strengthening tropical Pacific zonal sea surface temperature gradient consistent with rising greenhouse gases. Nat. Climate Change, 9, 517522, https://doi.org/10.1038/s41558-019-0505-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seth, A., M. Rojas, and S. A. Rauscher, 2010: CMIP3 projected changes in the annual cycle of the South American monsoon. Climatic Change, 98, 331357, https://doi.org/10.1007/s10584-009-9736-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seth, A., S. A. Rauscher, M. Biasutti, A. Giannini, S. J. Camargo, and M. Rojas, 2013: CMIP5 projected changes in the annual cycle of precipitation in monsoon regions. J. Climate, 26, 73287351, https://doi.org/10.1175/JCLI-D-12-00726.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sharmila, S., S. Joseph, A. K. Sahai, S. Abhilash, and R. Chattopadhyay, 2015: Future projection of Indian summer monsoon variability under climate change scenario: An assessment from CMIP5 climate models. Global Planet. Change, 124, 6278, https://doi.org/10.1016/j.gloplacha.2014.11.004.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Song, F., T. Zhou, and Y. Qian, 2014: Responses of East Asian summer monsoon to natural and anthropogenic forcings in the 17 latest CMIP5 models. Geophys. Res. Lett., 41, 596603, https://doi.org/10.1002/2013GL058705.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sperber, K. R., H. Annamalai, I.-S. Kang, A. Kitoh, A. Moise, A. Turner, B. Wang, and T. Zhou, 2013: The Asian summer monsoon: An intercomparison of CMIP5 vs. CMIP3 simulations of the late 20th century. Climate Dyn., 41, 27112744, https://doi.org/10.1007/s00382-012-1607-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vecchi, G. A., and B. J. Soden, 2007: Global warming and the weakening of the tropical circulation. J. Climate, 20, 43164340, https://doi.org/10.1175/JCLI4258.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, B., 1994: Climatic regimes of tropical convection and rainfall. J. Climate, 7, 11091118, https://doi.org/10.1175/1520-0442(1994)007<1109:CROTCA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, B., and Q. Ding, 2008: Global monsoon: Dominant mode of annual variation in the tropics. Dyn. Atmos. Oceans, 44, 165183, https://doi.org/10.1016/j.dynatmoce.2007.05.002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, B., S. C. Clemens, and P. Liu, 2003: Contrasting the Indian and East Asian monsoons: Implications on geologic timescales. Mar. Geol., 201, 521, https://doi.org/10.1016/S0025-3227(03)00196-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, B., J. Liu, H.-J. Kim, P. J. Webster, and S.-Y. Yim, 2012: Recent change of the global monsoon precipitation (1979–2008). Climate Dyn., 39, 11231135, https://doi.org/10.1007/s00382-011-1266-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, B., S.-Y. Yim, J.-Y. Lee, J. Liu, and K.-J. Ha, 2014: Future change of Asian-Australian monsoon under RCP 4.5 anthropogenic warming scenario. Climate Dyn., 42, 83100, https://doi.org/10.1007/s00382-013-1769-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, B., X. Luo, Y.-M. Yang, W. Sun, M. A. Cane, W. Cai, S.-W. Yeh, and J. Liu, 2019: Historical change of El Niño properties sheds light on future changes of extreme El Niño. Proc. Natl. Acad. Sci. USA, 116, 22 51222 517, https://doi.org/10.1073/pnas.1911130116.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, B., and Coauthors, 2020a: Monsoons climate change assessment. Bull. Amer. Meteor. Soc., https://doi.org/10.1175/BAMS-D-19-0335.1, in press.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, B., C. Jin, and J. Liu, 2020b: Understanding future change of global monsoons projected by CMIP6 models. J. Climate, 33, 64716489, https://doi.org/10.1175/JCLI-D-19-0993.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Webster, P. J., A. M. Moore, J. P. Loschnigg, and R. R. Leben, 1999: Coupled ocean–atmosphere dynamics in the Indian Ocean during 1997–98. Nature, 401, 356360, https://doi.org/10.1038/43848.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yasunari, T., 1991: The monsoon year—A new concept of the climatic year in the tropics. Bull. Amer. Meteor. Soc., 72, 13311338, https://doi.org/10.1175/1520-0477(1991)072<1331:TMYNCO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yim, S.-Y., B. Wang, J. Liu, and Z. Wu, 2014: A comparison of regional monsoon variability using monsoon indices. Climate Dyn., 43, 14231437, https://doi.org/10.1007/s00382-013-1956-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yin, L., R. Fu, E. Shevliakova, and R. E. Dickinson, 2013: How well can CMIP5 simulate precipitation and its controlling processes over tropical South America? Climate Dyn., 41, 31273143, https://doi.org/10.1007/s00382-012-1582-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ying, J., P. Huang, T. Lian, and H. Tan, 2019: Understanding the effect of an excessive cold tongue bias on projecting the tropical Pacific SST warming pattern in CMIP5 models. Climate Dyn., 52, 18051818, https://doi.org/10.1007/s00382-018-4219-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
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Future Changes and Controlling Factors of the Eight Regional Monsoons Projected by CMIP6 Models

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  • 1 Key Laboratory for Virtual Geographic Environment, Ministry of Education, State Key Laboratory Cultivation Base of Geographical Environment Evolution of Jiangsu Province, Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, School of Geography Science, Nanjing Normal University, Nanjing, China
  • 2 Department of Atmospheric Sciences, University of Hawai‘i at Mānoa, Honolulu, Hawaii, and Earth System Modeling Center, Nanjing University of Information Science and Technology, Nanjing, China
  • 3 Key Laboratory for Virtual Geographic Environment, Ministry of Education, State Key Laboratory Cultivation Base of Geographical Environment Evolution of Jiangsu Province, Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, School of Geography Science, and Jiangsu Provincial Key Laboratory for Numerical Simulation of Large Scale Complex Systems, School of Mathematical Science, Nanjing Normal University, Nanjing, China
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Abstract

An accurate prediction of land monsoon precipitation (LMP) is critical for the sustainable future of the planet as it provides water resources for more than two-thirds of the global population. Here, we show that the ensemble mean of 24 CMIP6 (phase 6 of the Coupled Model Intercomparison Project) models projects that, under the Shared Socioeconomic Pathway 2–4.5 (SSP2–4.5) scenario, summer LMP will very likely increase in South Asia (~4.1% °C−1), likely increase in East Asia (~4.6% °C−1) and northern Africa (~2.9% °C−1), and likely decrease in North America (~−2.3% °C−1). The annual mean LMP in three Southern Hemisphere monsoon regions will likely remain unchanged due to significantly decreased winter precipitation. Regional mean LMP changes are dominated by the change in upward moisture transport with moderate contribution from evaporation and can be approximated by the changes of the product of the midtropospheric ascent and 850-hPa specific humidity. Greenhouse gas (GHG)-induced thermodynamic effects increase moisture content and stabilize the atmosphere, tending to offset each other. The spatially uniform increase of humidity cannot explain markedly different regional LMP changes. Intermodel spread analysis demonstrates that the GHG-induced circulation changes (dynamic effects) are primarily responsible for the regional differences. The GHGs induce a warm land–cool ocean pattern that strengthens the Asian monsoon, and a warm North Atlantic and Sahara that enhances the northern African monsoon, as well as an equatorial central Pacific warming that weakens the North American monsoon. CMIP6 models generally capture realistic monsoon rainfall climatology, but commonly overproduce summer rainfall variability. The models’ biases in projected regional SST and land–sea thermal contrast likely contribute to the models’ uncertainties in the projected monsoon rainfall changes.

Denotes content that is immediately available upon publication as open access.

Corresponding author: Jian Liu, jliu@njnu.edu.cn

Abstract

An accurate prediction of land monsoon precipitation (LMP) is critical for the sustainable future of the planet as it provides water resources for more than two-thirds of the global population. Here, we show that the ensemble mean of 24 CMIP6 (phase 6 of the Coupled Model Intercomparison Project) models projects that, under the Shared Socioeconomic Pathway 2–4.5 (SSP2–4.5) scenario, summer LMP will very likely increase in South Asia (~4.1% °C−1), likely increase in East Asia (~4.6% °C−1) and northern Africa (~2.9% °C−1), and likely decrease in North America (~−2.3% °C−1). The annual mean LMP in three Southern Hemisphere monsoon regions will likely remain unchanged due to significantly decreased winter precipitation. Regional mean LMP changes are dominated by the change in upward moisture transport with moderate contribution from evaporation and can be approximated by the changes of the product of the midtropospheric ascent and 850-hPa specific humidity. Greenhouse gas (GHG)-induced thermodynamic effects increase moisture content and stabilize the atmosphere, tending to offset each other. The spatially uniform increase of humidity cannot explain markedly different regional LMP changes. Intermodel spread analysis demonstrates that the GHG-induced circulation changes (dynamic effects) are primarily responsible for the regional differences. The GHGs induce a warm land–cool ocean pattern that strengthens the Asian monsoon, and a warm North Atlantic and Sahara that enhances the northern African monsoon, as well as an equatorial central Pacific warming that weakens the North American monsoon. CMIP6 models generally capture realistic monsoon rainfall climatology, but commonly overproduce summer rainfall variability. The models’ biases in projected regional SST and land–sea thermal contrast likely contribute to the models’ uncertainties in the projected monsoon rainfall changes.

Denotes content that is immediately available upon publication as open access.

Corresponding author: Jian Liu, jliu@njnu.edu.cn
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