Greenhouse Gas Forcing and the Changing Persistence of Extreme Rainfall Episodes in East Asia
Keywords:
Extreme rainfall, persistence, CMIP6, Bayesian modeling, East Asia×Abstract
This study investigates how greenhouse gas forcing alters the persistence structure of extreme rainfall events in East Asia by combining CMIP6 multi-model ensembles (23 models, daily resolution, 1950–2100, ~2.1 million grid–time samples) with observational datasets (ERA5 and APHRODITE, 1979–2022). Extreme rainfall events are identified using a peaks-over-threshold approach (95th and 99th percentiles), and persistence is quantified through a run-length encoding framework coupled with a generalized extreme value (GEV) distribution for duration modeling. A hierarchical Bayesian model is further introduced to separate thermodynamic and dynamic contributions to persistence changes. Results show that under SSP5-8.5, the frequency of multi-day extreme rainfall events (>3 consecutive days) increases by 26–38%, while mean event duration increases from 2.3 days to 3.1–3.8 days by the end of the century. The tail index of duration distributions shifts significantly (Δξ ≈ +0.12), indicating heavier persistence tails. Moisture budget diagnostics reveal that column-integrated water vapor increases by 6.8% per °C warming, contributing 57% of the persistence extension, while circulation changes account for the remaining 43%. Model validation against observations yields a correlation of 0.84 for persistence metrics. These results demonstrate that greenhouse gas forcing systematically reorganizes rainfall duration structure rather than merely increasing intensity.
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