Spatially inhomogeneous response of precipitation δ18O in China to ENSO cycles
Abstract 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...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
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| Series: | npj Climate and Atmospheric Science |
| Online Access: | https://doi.org/10.1038/s41612-025-01057-1 |
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| Summary: | Abstract 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. |
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| ISSN: | 2397-3722 |