Yushuang Cui, Lide Tian, Zhongyin Cai, Shangjie Wang
{"title":"中国降水δ18O对ENSO循环的空间非均匀响应","authors":"Yushuang Cui, Lide Tian, Zhongyin Cai, Shangjie Wang","doi":"10.1038/s41612-025-01057-1","DOIUrl":null,"url":null,"abstract":"<p>Water stable isotopes serve as essential natural tracers, offering broad applications in water cycle, atmosphere science and paleoclimate rebuilding. In this study, we created a precipitation stable isotope dataset for 1961–2022 by developing a fusion machine learning model, and mapped the time-series precipitation isoscape (δ<sup>18</sup>O) across the mainland of China over the past 62 years. This dataset allows for a further discussion on spatially different behavior of precipitation δ<sup>18</sup>O to the strong ENSO events, and we found that δ<sup>18</sup>O values are higher in El Niño years and lower in La Niña years in the southern of the line roughly from 30°N 80°E to 40°N 120°E, not fully consistent with the northern region. We also revealed an increasing trend in precipitation δ<sup>18</sup>O in the Western arid region and Eastern monsoon region in the past decades, while no significant trend on the Tibetan Plateau. These findings enhance our understanding of the climatic control mechanisms influencing precipitation isotopes and benefit paleoclimate rebuilding.</p>","PeriodicalId":19438,"journal":{"name":"npj Climate and Atmospheric Science","volume":"1 1","pages":""},"PeriodicalIF":8.5000,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spatially inhomogeneous response of precipitation δ18O in China to ENSO cycles\",\"authors\":\"Yushuang Cui, Lide Tian, Zhongyin Cai, Shangjie Wang\",\"doi\":\"10.1038/s41612-025-01057-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Water stable isotopes serve as essential natural tracers, offering broad applications in water cycle, atmosphere science and paleoclimate rebuilding. In this study, we created a precipitation stable isotope dataset for 1961–2022 by developing a fusion machine learning model, and mapped the time-series precipitation isoscape (δ<sup>18</sup>O) across the mainland of China over the past 62 years. This dataset allows for a further discussion on spatially different behavior of precipitation δ<sup>18</sup>O to the strong ENSO events, and we found that δ<sup>18</sup>O values are higher in El Niño years and lower in La Niña years in the southern of the line roughly from 30°N 80°E to 40°N 120°E, not fully consistent with the northern region. We also revealed an increasing trend in precipitation δ<sup>18</sup>O in the Western arid region and Eastern monsoon region in the past decades, while no significant trend on the Tibetan Plateau. These findings enhance our understanding of the climatic control mechanisms influencing precipitation isotopes and benefit paleoclimate rebuilding.</p>\",\"PeriodicalId\":19438,\"journal\":{\"name\":\"npj Climate and Atmospheric Science\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":8.5000,\"publicationDate\":\"2025-05-02\",\"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/s41612-025-01057-1\",\"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}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"npj Climate and Atmospheric Science","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1038/s41612-025-01057-1","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}
Spatially inhomogeneous response of precipitation δ18O in China to ENSO cycles
Water stable isotopes serve as essential natural tracers, offering broad applications in water cycle, atmosphere science and paleoclimate rebuilding. In this study, we created a precipitation stable isotope dataset for 1961–2022 by developing a fusion machine learning model, and mapped the time-series precipitation isoscape (δ18O) across the mainland of China over the past 62 years. This dataset allows for a further discussion on spatially different behavior of precipitation δ18O to the strong ENSO events, and we found that δ18O values are higher in El Niño years and lower in La Niña years in the southern of the line roughly from 30°N 80°E to 40°N 120°E, not fully consistent with the northern region. We also revealed an increasing trend in precipitation δ18O in the Western arid region and Eastern monsoon region in the past decades, while no significant trend on the Tibetan Plateau. These findings enhance our understanding of the climatic control mechanisms influencing precipitation isotopes and benefit paleoclimate rebuilding.
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.