The Extreme Mei-yu Season in 2020: Role of the Madden-Julian Oscillation and the Cooperative Influence of the Pacific and Indian Oceans
The middle and lower reaches of the Yangtze River in eastern China during summer 2020 suffered the strongest mei-yu since 1961. In this work, we comprehensively analyzed the mechanism of the extreme mei-yu season in 2020, with focuses on the combined effects of the Madden-Julian Oscillation (MJO) an...
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Veröffentlicht in: | Advances in atmospheric sciences 2021-12, Vol.38 (12), p.2040-2054 |
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Zusammenfassung: | The middle and lower reaches of the Yangtze River in eastern China during summer 2020 suffered the strongest mei-yu since 1961. In this work, we comprehensively analyzed the mechanism of the extreme mei-yu season in 2020, with focuses on the combined effects of the Madden-Julian Oscillation (MJO) and the cooperative influence of the Pacific and Indian Oceans in 2020 and from a historical perspective. The prediction and predictability of the extreme mei-yu are further investigated by assessing the performances of the climate model operational predictions and simulations.
It is noted that persistent MJO phases 1−2 during June−July 2020 played a crucial role for the extreme mei-yu by strengthening the western Pacific subtropical high. Both the development of La Niña conditions and sea surface temperature (SST) warming in the tropical Indian Ocean exerted important influences on the long-lived MJO phases 1−2 by slowing down the eastward propagation of the MJO and activating convection related to the MJO over the tropical Indian Ocean. The spatial distribution of the 2020 mei-yu can be qualitatively captured in model real-time forecasts with a one-month lead. This can be attributed to the contributions of both the tropical Indian Ocean warming and La Niña development. Nevertheless, the mei-yu rainfall amounts are seriously underestimated. Model simulations forced with observed SST suggest that internal processes of the atmosphere play a more important role than boundary forcing (e.g., SST) in the variability of mei-yu anomaly, implying a challenge in quantitatively predicting an extreme mei-yu season, like the one in 2020. |
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ISSN: | 0256-1530 1861-9533 |
DOI: | 10.1007/s00376-021-1078-y |