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Influence of ENSO on the ECMWF subseasonal prediction of summer rainfall over the Yangtze River

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Abstract

In this study, based on the ECMWF 20-year (1997 ~ 2016) hindcasts, the subseasonal prediction of the weekly summer rainfall anomaly over the middle and lower reaches of the Yangtze River (YR) were studied. The skill at 2-week lead time exhibits prominent interannual variation, which is significantly correlated with the preceding winter ENSO. That is, rainfall anomaly can be better predicted in El Niño decaying summer than in La Niña decaying summer. Observation analyses show that in El Niño decaying summer the intraseasonal variation of YR summer rainfall is featured by strong low-frequency (> 30 days) intraseasonal oscillation (ISO) partly associated with the first boreal summer ISO mode (BSISO1) activity, in comparison with La Niña decaying summer. This is possibly because El Niño-induced mean state western North Pacific (WNP) anti-cyclone blocks the northward propagation of convection over the WNP, resulting in BSISO1 stagnation in phases 3–4. The phase stagnation could force stable atmospheric teleconnection, which is favorable to sufficient moisture transportation to the YR and persistent rainfall formation. Finally, prediction verification showed that more accurate prediction for the middle-low-level circulation contribute to the better prediction of rainfall anomaly in El Niño decaying summer than in La Niña decaying summer.

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Data Availability

We greatly appreciate the reforecast data provided by the S2S project, which can be archived at http://apps.ecmwf.int/datasets/data/s2s/. The monthly Niño 3.4/Niño 3/Niño 4 indices used in this study were obtained from the NOAA/NCEP CPC(Climate Prediction Center) (https://psl.noaa.gov/enso/dashboard.html). And the real-time BSISO index proposed by Lee et al. (2013) is openly available from http://iprc.soest.hawaii.edu/users/jylee/bsiso.

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Funding

This work was supported by National Natural Science Foundation of China, with Project Number 41975078. The authors thank the Super Computing Center of Beijing Normal University for providing computing resources.

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  1. Key Laboratory of Environmental Change and Natural Disasters of Chinese Ministry of Education, Beijing Normal University, Beijing, 100875, China

    Muqiu Yan & Yan Guo

  2. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China

    Muqiu Yan & Yan Guo

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  1. Muqiu Yan
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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Muqiu Yan. All authors read and approved the final manuscript.

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Correspondence to Yan Guo.

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Yan, M., Guo, Y. Influence of ENSO on the ECMWF subseasonal prediction of summer rainfall over the Yangtze River. Clim Dyn 61, 3955–3969 (2023). https://doi.org/10.1007/s00382-023-06784-w

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