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Causes of positive precipitation anomalies in South China during La Niña winters

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Abstract

The effects of El Niño-Southern Oscillation (ENSO) on winter precipitation in South China are considerably asymmetric. A positive correlation is significant between the sea surface temperature anomalies (SSTA) in the equatorial middle-eastern Pacific and the precipitation in South China during El Niño winters, whereas no significant relationship instead of a negative correlation between them during La Niña winters. The possible causes of abnormally positive precipitation in South China during La Niña winters remain a puzzle. The analysis indicates that positive precipitation anomalies in South China during La Niña winters are closely related to the strengthening of southerly winds over the South China Sea and convective activities over South China. Moreover, during La Niña winters, the low-level southerly wind anomalies over the South China Sea are modulated by an anomalous positive local zonal sea surface temperature gradient (SSTG) between the South China Sea and the tropical western Pacific, which strengthens in late autumn and maintains through the following winter. This positive local zonal SSTG is independent of La Niña and leads to the weakening of Walker circulation. The strengthened downward motion over the tropical western Pacific further promotes the weakening of local Hadley circulation. Weakened local Hadley circulation, with strengthened southerlies over the South China Sea in the lower troposphere, is conducive to the enhancement of water vapor transport from the South China Sea to South China. Besides, the weakened local Hadley circulation also shows strengthened upward motion over South China, which provides more advantageous dynamic conditions for precipitation. Therefore, the positive local zonal SSTG simultaneously promotes the two most important conditions affecting precipitation, resulting in positive precipitation anomalies over South China during La Niña winters. These results advance the understanding of prediction of winter precipitation in south China.

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Availability of data and materials

The data that support the finding of this study are available from the following resources: https://cmdp.ncc-cma.net/cn/index.htm. https://psl.noaa.gov/thredds/catalog/Datasets/ncep.reanalysis/Monthlies/pressure/catalog.html. https://psl.noaa.gov/thredds/catalog/Datasets/noaa.ersst.v5/catalog.html. https://origin.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ONI_v5.php.

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Acknowledgements

This work was jointly funded by the Key Program of the National Natural Science Foundation of China (42130610, U2142207), and the General Program of the National Natural Science Foundation of China (41975088, 42175028). We express sincere gratitude to the reviewers for their constructive comments and suggestions. Their advice will benefit the improvement of the paper and our future research.

Funding

This work was jointly funded by the Key Program of the National Natural Science Foundation of China (42130610, U2142207), and the General Program of the National Natural Science Foundation of China (41975088, 42175028).

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RZ and GF bring forward the main idea of this article. RZ, ZZ and SQ designed the study and analyzed the data. RZ wrote the main manuscript text and prepared all the figures. All authors reviewed the manuscript.

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Correspondence to Zhihai Zheng or Shaobo Qiao.

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I declare that the authors have no competing interests as defined by Springer, or other interests that might be perceived to influence the results and/or discussion reported in this paper. The results in this manuscript have not been published elsewhere, nor are they under consideration (from me or one of my Contributing Authors) by another publisher. I have read the Springer journal policies on author responsibilities and submit this manuscript in accordance with those policies. All of the material is owned by the authors and/or no permissions are required.

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Zhi, R., Zheng, Z., Qiao, S. et al. Causes of positive precipitation anomalies in South China during La Niña winters. Clim Dyn 61, 3343–3352 (2023). https://doi.org/10.1007/s00382-023-06738-2

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  • DOI: https://doi.org/10.1007/s00382-023-06738-2

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