{"title":"高分辨率模式集合中南亚季风低压系统的历史和未来趋势","authors":"S. Vishnu, William R. Boos, William D. Collins","doi":"10.1038/s41612-023-00502-3","DOIUrl":null,"url":null,"abstract":"Historical trends in monsoon low pressure systems (LPS), the dominant rain-bearing weather system of South Asia, have been difficult to assess due to changes in the observing network. Future projections have also remained uncertain because prior studies concluded that many coarse-resolution climate models do not accurately simulate LPS. Here, we examine changes in South Asian monsoon LPS simulated by an ensemble of global models, including some with high spatial resolution, that we show skillfully represent LPS. In the ensemble mean, the number of strong LPS (monsoon depressions) decreased over the last 65 years (1950–2014) by about 15% while no trend was detected for weaker LPS (monsoon lows). The reduction in depression counts then moderated, yielding no trend in the periods 1980–2050 or 2015–2050. The ensemble mean projects a shift in genesis from ocean to land and an increase in LPS precipitation of at least 7% K−1, which together contribute to a projected increase in seasonal mean and extreme precipitation over central India.","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":" ","pages":"1-11"},"PeriodicalIF":8.5000,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41612-023-00502-3.pdf","citationCount":"0","resultStr":"{\"title\":\"Historical and future trends in South Asian monsoon low pressure systems in a high-resolution model ensemble\",\"authors\":\"S. Vishnu, William R. Boos, William D. Collins\",\"doi\":\"10.1038/s41612-023-00502-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Historical trends in monsoon low pressure systems (LPS), the dominant rain-bearing weather system of South Asia, have been difficult to assess due to changes in the observing network. Future projections have also remained uncertain because prior studies concluded that many coarse-resolution climate models do not accurately simulate LPS. Here, we examine changes in South Asian monsoon LPS simulated by an ensemble of global models, including some with high spatial resolution, that we show skillfully represent LPS. In the ensemble mean, the number of strong LPS (monsoon depressions) decreased over the last 65 years (1950–2014) by about 15% while no trend was detected for weaker LPS (monsoon lows). The reduction in depression counts then moderated, yielding no trend in the periods 1980–2050 or 2015–2050. The ensemble mean projects a shift in genesis from ocean to land and an increase in LPS precipitation of at least 7% K−1, which together contribute to a projected increase in seasonal mean and extreme precipitation over central India.\",\"PeriodicalId\":19438,\"journal\":{\"name\":\"npj Climate and Atmospheric Science\",\"volume\":\" \",\"pages\":\"1-11\"},\"PeriodicalIF\":8.5000,\"publicationDate\":\"2023-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.nature.com/articles/s41612-023-00502-3.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"npj Climate and Atmospheric Science\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.nature.com/articles/s41612-023-00502-3\",\"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}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"npj Climate and Atmospheric Science","FirstCategoryId":"89","ListUrlMain":"https://www.nature.com/articles/s41612-023-00502-3","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}
Historical and future trends in South Asian monsoon low pressure systems in a high-resolution model ensemble
Historical trends in monsoon low pressure systems (LPS), the dominant rain-bearing weather system of South Asia, have been difficult to assess due to changes in the observing network. Future projections have also remained uncertain because prior studies concluded that many coarse-resolution climate models do not accurately simulate LPS. Here, we examine changes in South Asian monsoon LPS simulated by an ensemble of global models, including some with high spatial resolution, that we show skillfully represent LPS. In the ensemble mean, the number of strong LPS (monsoon depressions) decreased over the last 65 years (1950–2014) by about 15% while no trend was detected for weaker LPS (monsoon lows). The reduction in depression counts then moderated, yielding no trend in the periods 1980–2050 or 2015–2050. The ensemble mean projects a shift in genesis from ocean to land and an increase in LPS precipitation of at least 7% K−1, which together contribute to a projected increase in seasonal mean and extreme precipitation over central India.
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.