The Extreme Mei-yu Season in 2020: Role of the Madden-Julian Oscillation and the Cooperative Influence of the Pacific and Indian Oceans

• Published in: Advances in atmospheric sciences 2021-12, Vol.38 (12), p.2040-2054
• Main Authors: Liang, Ping, Hu, Zeng-Zhen, Ding, Yihui, Qian, Qiwen
• Format: Article
• Language: English
• Subjects: Atmospheric Sciences; Climate models; Climate prediction; Convection; Earth and Environmental Science; Earth Sciences; El Nino phenomena; Geophysics/Geodesy; La Nina; Madden-Julian oscillation; Mei-yu rainfall; Meteorology; Ocean temperature; Ocean warming; Oceans; Original Paper; Predictability and Impacts; Rain; Rainfall; Sea surface; Sea surface temperature; Seasons; Spatial distribution; Summer 2020: Record Rainfall in Asia — Mechanisms; Surface temperature; Tropical climate
• ISSN: 0256-1530; 1861-9533
• DOI: 10.1007/s00376-021-1078-y

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.