Gudongze Li, Chun Zhao, Jun Gu, Jiawang Feng, Mingyue Xu, Xiaoyu Hao, Junshi Chen, Hong An, Wenju Cai, Tao Geng
{"title":"Excessive equatorial light rain causes modeling dry bias of Indian summer monsoon rainfall","authors":"Gudongze Li, Chun Zhao, Jun Gu, Jiawang Feng, Mingyue Xu, Xiaoyu Hao, Junshi Chen, Hong An, Wenju Cai, Tao Geng","doi":"10.1038/s41612-025-00916-1","DOIUrl":null,"url":null,"abstract":"<p>Simulating accurately the South Asian summer monsoon is crucial for food security of several South Asian countries yet challenging for global climate models (GCMs). The GCMs suffer from some systematic biases including dry bias in mean monsoon rainfall over the India subcontinent and excessive equatorial light rain between which the relationship was rarely discussed. Numerical experiments are conducted for one month during active monsoon with global quasi-uniform resolution of 60 km (U60 km) and 3 km (U3 km) separately. Evaluation with observations shows that U3 km reduces the dry bias over northern India and excessive light rain over the equatorial Indian Ocean (EIO) that are both prominent in U60 km. Excessive light rain in U60 km contributes critically to stronger rainfall and latent heating over the EIO. A Hadley-type anomalous circulation is thus induced, whose subsidence branch suppresses updrafts and reduces moisture transport into northern India, contributing to the dry bias. The findings highlight the importance of constraining excessive light rain for regional climate projection in GCMs.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"20 1","pages":""},"PeriodicalIF":8.5000,"publicationDate":"2025-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"npj Climate and Atmospheric Science","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1038/s41612-025-00916-1","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Simulating accurately the South Asian summer monsoon is crucial for food security of several South Asian countries yet challenging for global climate models (GCMs). The GCMs suffer from some systematic biases including dry bias in mean monsoon rainfall over the India subcontinent and excessive equatorial light rain between which the relationship was rarely discussed. Numerical experiments are conducted for one month during active monsoon with global quasi-uniform resolution of 60 km (U60 km) and 3 km (U3 km) separately. Evaluation with observations shows that U3 km reduces the dry bias over northern India and excessive light rain over the equatorial Indian Ocean (EIO) that are both prominent in U60 km. Excessive light rain in U60 km contributes critically to stronger rainfall and latent heating over the EIO. A Hadley-type anomalous circulation is thus induced, whose subsidence branch suppresses updrafts and reduces moisture transport into northern India, contributing to the dry bias. The findings highlight the importance of constraining excessive light rain for regional climate projection in GCMs.
期刊介绍:
npj Climate and Atmospheric Science is an open-access journal encompassing the relevant physical, chemical, and biological aspects of atmospheric and climate science. The journal places particular emphasis on regional studies that unveil new insights into specific localities, including examinations of local atmospheric composition, such as aerosols.
The range of topics covered by the journal includes climate dynamics, climate variability, weather and climate prediction, climate change, ocean dynamics, weather extremes, air pollution, atmospheric chemistry (including aerosols), the hydrological cycle, and atmosphere–ocean and atmosphere–land interactions. The journal welcomes studies employing a diverse array of methods, including numerical and statistical modeling, the development and application of in situ observational techniques, remote sensing, and the development or evaluation of new reanalyses.