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Atmospheric and oceanic signals for the interannual variability of warm-season flood-inducing rainfall frequency over the middle and lower reaches of the Yangtze River basin

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Abstract

In China, the middle and lower reaches of the Yangtze River basin (MLRYRB) is a core region suffering frequent devastating floods triggered by heavy precipitation during warm seasons, exerting serious impacts on society. However, the physical mechanisms responsible for the increasing flood-inducing rainfall (FIR) frequency over MLRYRB during warm seasons remain unclear. Based on objective definition procedures, the present study investigates the salient atmospheric and oceanic signals tied to the interannual fluctuations of warm-season FIR frequency over MLRYRB. The results show that the suppressed convection from the remote western Pacific to the east of the Philippines could serve as a salient synchronous atmospheric signal for the increased FIR frequency. Moreover, the sea surface temperature (SST) warming over the tropical Indian Ocean (TIO) and the preceding wintertime El Niño-related SST anomaly pattern are deemed as salient contemporaneous and precursory oceanic signals linking the enhancement of the warm-season FIR frequency over MLRYRB on the interannual timescale, respectively. Further observational evidence and tropical Pacific pacemaker experiment results based on the Community Earth System Model Version 2 (CESM2) suggest that the mature El Niño in the prior winter can exert a delayed impact on the enhanced FIR frequency over MLRYRB during the subsequent warm season by exerting vital contributions to the FIR-favorable systems (i.e., southwestward-shifted western North Pacific anomalous anticyclone and the southward-displaced East Asian subtropical westerly jet). The basin-wide positive TIO SST anomalies act as El Niño’s capacitor to relay its impact. These signals have important implications for seasonal prediction of FIR frequency over MLRYRB, and it is essential to place a high requirement on consideration of the better-known El Niño’s cross-season atmospheric teleconnection.

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Data availability

The global GloFAS river discharge reanalysis data are openly available at https://cds.climate.copernicus.eu/cdsapp#!/dataset/cems-glofas-historical?tab=overview. Gauged precipitation data were obtained from the China Meteorological Administration’s National Meteorological Information Centre (http://data.cma.cn). Monthly mean NCEP-2 data are openly available at https://psl.noaa.gov/data/gridded/data.ncep.reanalysis2.html. Monthly mean CMAP data are openly available at https://psl.noaa.gov/data/gridded/data.cmap.html. Monthly mean OLR data are openly available at https://psl.noaa.gov/data/gridded/data.olrcdr.interp.html. Monthly mean ERSST5 data are openly available at https://psl.noaa.gov/data/gridded/data.noaa.ersst.v5.html. The monthly ONI index is downloaded from https://www.cpc.ncep.noaa.gov/data/indices/oni.ascii.txt. Monthly CESM2 Pacific pacemaker ensemble is from https://www.earthsystemgrid.org/dataset/ucar.cgd.cesm2.pacific.pacemaker.html.

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Acknowledgements

This work was jointly supported by the National Natural Science Foundation of China (Grant No. 42175056; Grant No. U2342208), the Natural Science Foundation of Shanghai (Grant No. 21ZR1457600), the China Meteorological Administration Innovation and Development Project (Grant No. CXFZ2022J009), the Shanghai Sailing Program (Grant No. 23YF1437300; Grant No. 23YF1440100), and the China Meteorological Administration Joint Research Project for Meteorological Capacity Improvement (Grant No. 23NLTSQ006). Jing Wang acknowledges the Open Fund of the Key Laboratory of Cities’ Mitigation and Adaptation to Climate Change in Shanghai (2023), China. Ping Liang acknowledges the Key Innovation Team of Climate Prediction of the China Meteorological Administration (Grant No. CMA2023ZD03).

Funding

This work was supported by the National Natural Science Foundation of China (Grant No. 42175056; Grant No. U2342208), the Natural Science Foundation of Shanghai (Grant No. 21ZR1457600), the China Meteorological Administration Innovation and Development Project (Grant No. CXFZ2022J009), the Shanghai Sailing Program (Grant No. 23YF1437300; Grant No. 23YF1440100), the China Meteorological Administration Joint Research Project for Meteorological Capacity Improvement (Grant No. 23NLTSQ006), the Open Fund of the Key Laboratory of Cities’ Mitigation and Adaptation to Climate Change in Shanghai (2023), China, and the Key Innovation Team of Climate Prediction of the China Meteorological Administration (Grant No. CMA2023ZD03).

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Authors and Affiliations

  1. Key Laboratory of Cities’ Mitigation and Adaptation to Climate Change in Shanghai, Shanghai Regional Climate Center, Shanghai, 200030, China

    Jing Wang, Yue Ma, Ping Liang & Zhiqi Zhang

  2. Tianjin Key Laboratory for Oceanic Meteorology, Tianjin Institute of Meteorological Science, Tianjin, 300074, China

    Jing Wang

  3. Shanghai Jiading District Meteorological Bureau, Shanghai, 201800, China

    Yue Ma

  4. Shanghai Typhoon Institute of China Meteorological Administration, Shanghai, 200030, China

    Ping Liang

  5. School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, 610225, China

    Xinpei Cao

  6. Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, 210044, China

    Jinhai He

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  1. Jing Wang
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Contributions

PL, JW, and YM contributed to the conception and design. Material preparation, data collection, and observational analysis were performed by JW, YM, XC, and ZZ. The numerical experiments were performed by JW. The first draft of the manuscript was written by JW and PL. JH provided intellectual contributions to the improvement of this manuscript. All authors read and approved the final manuscript.

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Correspondence to Ping Liang.

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The authors have no relevant financial or non-financial interests to disclose.

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Wang, J., Ma, Y., Liang, P. et al. Atmospheric and oceanic signals for the interannual variability of warm-season flood-inducing rainfall frequency over the middle and lower reaches of the Yangtze River basin. Clim Dyn (2024). https://doi.org/10.1007/s00382-024-07171-9

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