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<p>Precipitation and its extremes have profound impacts on human lives and economies, particularly in the Southeast Asia (SEA) region. This study evaluated the performance of 19 CMIP6 models in simulating precipitation and its extremes using three indices: total wet-day precipitation (PRCPTOT), simple daily intensity index (SDII), and consecutive dry days (CDD). Through a rigorous quantitative assessment, the models were categorized into two distinct groups: a high-performing ensemble (Better_group, 8 models) consisting of EC-Earth3, EC-Earth3-Veg, GFDL-CM4, GFDL-ESM4, INM-CM4-8, KIOST-ESM, MPI-ESM1-2-HR, and MPI-ESM1-2-LR, and a low-performing ensemble (Lower_group, 7 models) comprising ACCESS-CM2, ACCESS-ESM1-5, BCC-CSM2-MR, MIROC6, MRI-ESM2-0, NESM3, and NorESM2-LM. The Lower_group exhibited higher mean absolute errors, for all indices (PRCPTOT, CDD and SDII) with median errors of approximately 44%, 44 and 41%, respectively. In contrast, the Better_group demonstrated superior performance for all indices PRCPTOT, CDD and SDII, reducing median relative biases by 16%, 22% and 19% respectively compared to the Lower_group. Despite advancements in CMIP6 models, including higher resolutions and improved parameterizations, persistent challenges remain in accurately capturing the extreme precipitation dynamics of SEA. This study not only identifies the most reliable models for regional climate projections but also highlights specific areas requiring model improvement, providing crucial guidance for model selection and a scientific basis for enhancing climate adaptation strategies in SEA.</p>

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CMIP6 model performance in simulating precipitation and its extreme characteristics across Southeast Asia

  • 期刊论文

  • 发表日期：

    2025年11月10日

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  • Thet Mar Soe,
  • Fangmin Zhang,
  • Okrah Abraham,
  • Kyaw Than Oo,
  • He Ma,
  • Kazora Jonah,
  • Ebaju Gerverse Kamukama

摘要

Precipitation and its extremes have profound impacts on human lives and economies, particularly in the Southeast Asia (SEA) region. This study evaluated the performance of 19 CMIP6 models in simulating precipitation and its extremes using three indices: total wet-day precipitation (PRCPTOT), simple daily intensity index (SDII), and consecutive dry days (CDD). Through a rigorous quantitative assessment, the models were categorized into two distinct groups: a high-performing ensemble (Better_group, 8 models) consisting of EC-Earth3, EC-Earth3-Veg, GFDL-CM4, GFDL-ESM4, INM-CM4-8, KIOST-ESM, MPI-ESM1-2-HR, and MPI-ESM1-2-LR, and a low-performing ensemble (Lower_group, 7 models) comprising ACCESS-CM2, ACCESS-ESM1-5, BCC-CSM2-MR, MIROC6, MRI-ESM2-0, NESM3, and NorESM2-LM. The Lower_group exhibited higher mean absolute errors, for all indices (PRCPTOT, CDD and SDII) with median errors of approximately 44%, 44 and 41%, respectively. In contrast, the Better_group demonstrated superior performance for all indices PRCPTOT, CDD and SDII, reducing median relative biases by 16%, 22% and 19% respectively compared to the Lower_group. Despite advancements in CMIP6 models, including higher resolutions and improved parameterizations, persistent challenges remain in accurately capturing the extreme precipitation dynamics of SEA. This study not only identifies the most reliable models for regional climate projections but also highlights specific areas requiring model improvement, providing crucial guidance for model selection and a scientific basis for enhancing climate adaptation strategies in SEA.