Physical responses of Baiu extreme precipitation to future warming: Examples of the 2018 and 2020 western Japan events

Allan, 2013, Physically consistent responses of the global atmospheric hydrological cycle in models and observations, Surv. Geophys., 35, 533, 10.1007/s10712-012-9213-z Chen, 2022, Postprocessing ensemble weather forecasts for introducing multisite and multivariable correlations using rank shuffle and copula theory, Mon. Weather Rev., 150, 551, 10.1175/MWR-D-21-0100.1 Chen, 2021, Challenges and potential solutions in statistical downscaling of precipitation, Climatic Change, 165 Chen, 2021, Contributions of arctic sea‐ice loss and east siberian atmospheric blocking to 2020 record‐breaking meiyu‐baiu rainfall, Geophys. Res. Lett., 48, 10.1029/2021GL092748 Ding, 2020, Multiscale variability of Meiyu and its prediction: a new review, J. Geophys. Res. Atmos., 125, 10.1029/2019JD031496 Fischer, 2016, Observed heavy precipitation increase confirms theory and early models, Nat. Clim. Change, 6, 986, 10.1038/nclimate3110 Giorgi, 2019, The response of precipitation characteristics to global warming from climate projections, Earth System Dynamics, 10, 73, 10.5194/esd-10-73-2019 Guo, 2019, A new two-stage multivariate quantile mapping method for bias correcting climate model outputs, Clim. Dynam., 53, 3603, 10.1007/s00382-019-04729-w Guo, 2020, Impacts of using state‐of‐the‐art multivariate bias correction methods on hydrological modeling over north America, Water Resour. Res., 56, 10.1029/2019WR026659 Held, 2000, Water vapor feedback and global warming, Annu. Rev. Energy Environ., 25, 441, 10.1146/annurev.energy.25.1.441 Hibino, 2022 Hibino, 2018, Physical responses of convective heavy rainfall to future warming condition: case study of the Hiroshima event, Front. Earth Sci., 6, 10.3389/feart.2018.00035 Hirockawa, 2020, Characteristics of an extreme rainfall event in Kyushu district, southwestern Japan in early july 2020, Inside Solaris, 16, 265 Imada, 2020, Advanced risk-based event attribution for heavy regional rainfall events, npj Climate and Atmospheric Science, 3, 10.1038/s41612-020-00141-y 2021 Jiang, 2003, Moist dynamics and orographic precipitation, Tellus Dyn. Meteorol. Oceanogr., 55, 301, 10.3402/tellusa.v55i4.14577 Kanada, 2017, A multimodel intercomparison of an intense typhoon in future, warmer climates by four 5-km-Mesh models, J. Clim., 30, 6017, 10.1175/JCLI-D-16-0715.1 Kawase, 2020, The heavy rain event of july 2018 in Japan enhanced by historical warming, Bull. Am. Meteorol. Soc., 101, S109, 10.1175/BAMS-D-19-0173.1 Kimura, 2007, 4346 Kröner, 2016, Separating climate change signals into thermodynamic, lapse-rate and circulation effects: theory and application to the European summer climate, Clim. Dynam., 48, 3425 Li, 2019, How much information is required to well constrain local estimates of future precipitation extremes?, Earth's Future, 7, 11, 10.1029/2018EF001001 Liang, 2008, Review for climate change of Meiyu over the yangtze-huaihe basins, Plateau Meteorol., B12, 8 Makihara, 1996, Accuracy of radar-AMeDAS precipitation, IEICE Trans. Commun., E79b, 751 Matsumura, 2019, Jet–precipitation relation and future change of the mei-yu–baiu rainband and subtropical jet in CMIP5 coupled GCM simulations, J. Clim., 32, 2247, 10.1175/JCLI-D-18-0426.1 Mizuta, 2017, Over 5,000 Years of ensemble future climate simulations by 60-km global and 20-km regional atmospheric models, Bull. Am. Meteorol. Soc., 98, 1383, 10.1175/BAMS-D-16-0099.1 Myhre, 2019, Frequency of extreme precipitation increases extensively with event rareness under global warming, Sci. Rep., 9, 10.1038/s41598-019-52277-4 Nohara, 2020, Real-time flood management and preparedness: lessons from floods across the western Japan in 2018, 287 O'Gorman, 2015, Precipitation extremes under climate change, Curr. Clim. Change Rep., 1, 49, 10.1007/s40641-015-0009-3 Pall, 2017, Diagnosing conditional anthropogenic contributions to heavy Colorado rainfall in September 2013, Weather Clim. Extrem., 17, 1, 10.1016/j.wace.2017.03.004 Papalexiou, 2019, Global and regional increase of precipitation extremes under global warming, Water Resour. Res., 10.1029/2018WR024067 Patricola, 2018, Anthropogenic influences on major tropical cyclone events, Nature, 563, 339, 10.1038/s41586-018-0673-2 Sasaki, 2008, Preliminary experiments of reproducing the present climate using the non-hydrostatic regional climate model, Inside Solaris, 4, 25 Shimpo, 2019, Primary factors behind the heavy rain event of july 2018 and the subsequent heat wave in Japan, Inside Solaris, 15A, 13 Si, 2009, Decadal northward shift of the Meiyu belt and the possible cause, Sci. Bull., 54, 4742, 10.1007/s11434-009-0385-y Smith, 2004, A linear theory of orographic precipitation, J. Atmos. Sci., 61, 1377, 10.1175/1520-0469(2004)061<1377:ALTOOP>2.0.CO;2 Su, 2020, Multi-site bias correction of climate model outputs for hydro-meteorological impact studies: an application over a watershed in China, Hydrol. Process., 34, 2575, 10.1002/hyp.13750 Takahashi, 2021, Recent decadal enhancement of Meiyu-Baiu heavy rainfall over East Asia, Sci. Rep., 11, 10.1038/s41598-021-93006-0 Takayabu, 2015, Climate change effects on the worst-case storm surge: a case study of Typhoon Haiyan, Environ. Res. Lett., 10, 10.1088/1748-9326/10/6/064011 Takemura, 2019, Extreme moisture flux convergence over western Japan during the heavy rain event of july 2018, Inside Solaris, 15A, 49 Tett, 1996, Human influence on the atmospheric vertical temperature structure: detection and observations, Science, 274, 1170, 10.1126/science.274.5290.1170 Tsuguti, 2018, Meteorological overview and mesoscale characteristics of the heavy rain event of july 2018 in Japan, Landslides, 16, 363, 10.1007/s10346-018-1098-6 Utsumi, 2016, Which weather systems are projected to cause future changes in mean and extreme precipitation in CMIP5 simulations?, J. Geophys. Res. Atmos., 121, 10.1002/2016JD024939 Xie, 2010, Large-scale dynamics of the meiyu-baiu rainband: environmental forcing by the westerly jet, J. Clim., 23, 113, 10.1175/2009JCLI3128.1 Yin, 2022, A support vector machine-based method for improving real-time hourly precipitation forecast in Japan, J. Hydrol., 612, 10.1016/j.jhydrol.2022.128125 Yoshikane, 2022, A bias correction method for precipitation through recognizing mesoscale precipitation systems corresponding to weather conditions, PLOS Water, 1, 10.1371/journal.pwat.0000016 Zhang, 2020, Increasing impacts from extreme precipitation on population over China with global warming, Sci. Bull., 65, 243, 10.1016/j.scib.2019.12.002 Zhou, 2021, Historic Yangtze flooding of 2020 tied to extreme Indian Ocean conditions, Proc. Natl. Acad. Sci. U. S. A., 118, 10.1073/pnas.2022255118