The Heavy Rain Event of July 2018 in Japan Enhanced by Historical Warming

Atmospheric Rivers Bring More Frequent and Intense Extreme Rainfall Events Over East Asia Under Global Warming

“…Model outputs at every one hour with 20‐km horizontal resolution are more instrumental in examining extreme rainfall than the 6‐hr outputs from the d4PDF AGCM simulations with a 60‐km horizontal resolution. The combination of the d4PDF AGCM and RCM simulations greatly facilitates the evaluation of the changes in extreme rainfall associated with ARs under climate change (Fujita et al., 2019; Imada et al., 2020; Kawase et al., 2019, 2020; Miyasaka et al., 2020). In this study, we defined extreme rainfall events in the PAST simulations as upper 0.1% cases of wet hours (rainfall >0.1 mm hr −1 ) using 1‐hr outputs of the RCM simulations.…”

“…In July 2018 and July 2020, ARs passing through East Asia brought extreme rainfall and large social damages to the region (Araki et al., 2021; Hirockawa et al., 2020; Takemura et al., 2019; Tsuguti et al., 2019; Zhao et al., 2021). The higher frequency of AR‐induced natural disasters in recent years suggest a possible influence of ongoing global warming on the occurrence of extreme events (e.g., Imada et al., 2020; Kamae, Shiogama, et al., 2017; Kawase et al., 2020, 2019).…”

Higher Probability of Occurrence of Hotter and Shorter Heat Waves Followed by Heavy Rainfall

“…The compound occurrence of heat waves and heavy rainfall poses a critical challenge for the society responding to and preparing for extreme heat and flash flooding, which can cause even more damages than heat waves and heavy rainfall events individually (Kawase et al, 2020;Mukherjee & Mishra, 2021;Ruiter et al, 2020;Zscheischler et al, 2020). There is growing evidence that the sequential occurrence of heavy rainfall after the end of heat waves is likely to cause flash flooding, which can cause extensive damage to water quality, fundamental infrastructures, crop yields, and human livelihood.…”

Convection‐permitting modeling with regional climate models: Latest developments and next steps

“…In addition, uncertainties in related driving factors may usually be retrieved from robust ensembles of coarser models (GCMs). Therefore, this approach has a relatively low computational cost compared to ensembles, partly explaining its rapid gain of interest in the CPRCM community (Hegdahl et al, 2020; Kawase, Imada, et al, 2020; Schaller et al, 2020; Takayabu, Hibino, et al, 2015). Another reason for this gain in interest is the great potential of this approach to raise climate change risk awareness, particularly when addressing decision‐makers, as understanding a story is sometimes easier than juggling with complex probabilistic uncertainties.…”