Performance Evaluation of the MPAS Model in Simulating Southeast Asian Rainfall Characteristics

Abstract

Southeast Asia's (SEA) complex monsoon climate is highly vulnerable to extreme weather, necessitating robust atmospheric models for improved forecasting. This study evaluates the performance of the next‐generation Model for Prediction Across Scales–Atmosphere (MPAS) in simulating seasonal rainfall and atmospheric dynamics over SEA. We conducted a continuous MPAS simulation with uniform 10 km horizontal cell spacing from 2000 to 2020, forced by ERA5 reanalysis and validated outputs against multi‐source weighted‐ensemble precipitation (MSWEP) observed precipitation (10 km) and ERA5 reanalyses. The model captures the north–south rainfall gradients and the spatial–temporal characteristics of seasonal rainfall, transitions, wind reversals and moisture transport with high fidelity over northern continental regions. It also captures the timing and intensity of peak rainfall. An Empirical Orthogonal Function analysis further shows that MPAS effectively represents the dominant rainfall variability modes associated with ENSO and IOD, though with slightly weaker amplitudes. However, a persistent wet bias is evident across the Maritime Continent, marked by the overestimation of high‐intensity rainfall events. Despite these specific biases, MPAS effectively captures the core features of the SEA monsoons, highlighting its potential as a powerful tool for regional climate simulation. Continued refinement of convection and microphysics schemes, together with increased model resolution, could further enhance its performance for both research and operational applications over SEA.

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