17:15 〜 19:15
[MIS04-P03] Impacts of Climate Change on the Localized Heavy Rainfall Event in Northern Japan in 2022: Uncertainties in the Pseudo-Global Warming Approach
★Invited Papers
キーワード：線状降水帯、擬似温暖化、WRF
This study used the pseudo-global warming (PGW) method within the Weather Research and Forecasting (WRF) model to assess the impact of climate change on localized heavy rainfall events in the Tohoku and Hokuriku regions of Japan, which occurred in August 2022. This specific heavy rainfall event was heavily influenced by water vapor transport from the Sea of Japan, which is considered a representative case for the region. Our modeling results suggest that both the frequency and intensity of such events are expected to increase as a result of climate change. Through our modeling approach, we found that the simulated 48-hour accumulated precipitation under the projected warming conditions for the 2090s was 34.6% higher compared to simulations that did not consider the effects of future warming. In general, warming resulted in an increase in atmospheric water vapor and convection instability over the ocean. While the increase in water vapor generally consists with the Clausius-Clapeyron relationship (7% per degree Celsius of surface temperature rise), the simulated 48-hour precipitation exceeded this rate of increase, even surpassing triple the Clausius-Clapeyron scaling. This disproportionate increase in precipitation was driven by a combination of thermodynamic and dynamic effects. Thermodynamically, rising temperatures led to a higher concentration of water vapor, while dynamically, strengthened updrafts contributed to enhanced precipitation. Additionally, our study revealed the significant impact of model domain placement on the simulated precipitation and its projected changes in the PGW simulations. For example, a change in the position of the innermost domain resulted in a 29.2% variation in the 48-hour precipitation values. This highlights the critical importance of domain positioning within the PGW method, as it can introduce considerable uncertainty in the results.