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Comprehensive Appraisal and Bias Diagnostics of CMIP6 HighResMIP Model Simulations on South Asian Summer Monsoon Precipitation  ( SCI-EXPANDED收录 EI收录)  

文献类型:期刊文献

英文题名:Comprehensive Appraisal and Bias Diagnostics of CMIP6 HighResMIP Model Simulations on South Asian Summer Monsoon Precipitation

作者:Li, Jiahao[1];Xu, Jianjun[2];Lin, Chunqiao[1];Song, Luchi[1];Fan, Lingli[1]

机构:[1]Guangdong Ocean Univ, Coll Ocean & Meteorol, Zhanjiang, Peoples R China;[2]Guangdong Ocean Univ, Shenzhen Inst, Shenzhen, Peoples R China

年份:2025

卷号:38

期号:20

起止页码:5775

外文期刊名:JOURNAL OF CLIMATE

收录:SCI-EXPANDED(收录号:WOS:001596249900002)、、EI(收录号:20254319379512)、Scopus(收录号:2-s2.0-105019380438)、WOS

基金:Acknowledgments. We are deeply grateful for the invalu-able open data provided by the various institutions men-tioned in this study, which significantly contributed to the success of this research. We also extend our sincere thanks to the researchers and staff who curated and maintained these datasets, enabling in-depth analyses of monsoon dy-namics over South Asia. This work was supported by the Major Program of the National Natural Science Foundation of China (Grant 72293604) and the Innovation Team Project of General University in Guangdong Province of China (2024KCXTD042) . The authors declare no conflicts of interest.

语种:英文

外文关键词:South Asia; Dynamics; Precipitation; Tropical cyclones; Climate change; Model evaluation/performance

外文摘要:The South Asian summer monsoon (SASM) system, coupled with its intricate topography, presents formidable challenges to the accuracy of global climate models in realistically replicating the regional precipitation distribution. Employing atmospheric-only simulations from the High-Resolution Model Intercomparison Project (HighResMIP), this study rigorously assesses the capability of models with varying horizontal resolutions in simulating SASM precipitation, utilizing metrics such as horizontal configuration, intensity distribution, interannual variability, and long-term trends. The findings suggest that, despite intermodel discrepancies, high-resolution (HR) models exhibit substantial advantages over low-resolution (LR) models in simulating precipitation over complex orography, particularly in key regions such as the Himalayan foothills, the windward slopes of the Western Ghats, and the central-northern Indian plains. Nonetheless, limitations persist in accurately capturing the long-term trends of precipitation. A comprehensive appraisal reveals that the HR models CMCC-CM2-VHR4, EC-Earth3P-HR, ECMWF-IFS-HR, and HadGEM3-GC31-HM demonstrate superior aptitude in simulating the spatiotemporal distribution of precipitation. Analysis of the moisture budget equation reveals that atmospheric moisture variability in South Asia's principal monsoon regions is primarily governed by the dynamical term dDY, which elucidates the origin of discrepancies in precipitation simulations between HR and LR models. Specifi-cally, the HR model more precisely characterizes atmospheric circulation features and local dynamical processes and more realistically reproduces the activity characteristics of tropical cyclones over the Bay of Bengal. These improvements yield a more realistic dynamical environment for the SASM, thereby enhancing the accuracy and reliability of simulated precipitation distributions. SIGNIFICANCE STATEMENT: Our findings reveal that high-resolution (HR) models significantly enhance monsoonal precipitation simulation over the complex terrain of South Asia, effectively reducing wet biases over the Tibetan Plateau and Pakistan regions. We find that CMCC-CM2-VHR4, EC-Earth3P-HR, ECMWF-IFS-HR, and HadGEM3-GC31-HM exhibit superior ability in resolving spatial patterns and interannual variability, resulting from their capacity to better capture atmospheric circulation, orographically driven vertical motions, and synoptic systems like tropical cyclones. These findings underscore the importance of increased model resolution for more reliable representations of monsoon dynamics and precipitation and highlight the need to prioritize HR models in future research.

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