期刊
ADVANCES IN ATMOSPHERIC SCIENCES
卷 38, 期 12, 页码 2023-2039出版社
SCIENCE PRESS
DOI: 10.1007/s00376-021-1036-8
关键词
summer extreme floods; Middle; Lower Yangtze River; El Nino; Indian Ocean SST; decadal warming trend
资金
- National Natural Science Foundation of China [42030605, 42088101]
- National Key R&D Program of China [2020YFA0608004]
This study investigated the extreme floods in the Middle/Lower Yangtze River Valley during June-July 2020, finding a strong connection to an anomalous anticyclone over the western North Pacific and warm SST conditions in the tropical Indian Ocean. The multi-decadal warming trend and interannual variability of the Indian Ocean SSTs had positive impacts on the extreme floods.
The extreme floods in the Middle/Lower Yangtze River Valley (MLYRV) during June-July 2020 caused more than 170 billion Chinese Yuan direct economic losses. Here, we examine the key features related to this extreme event and explore relative contributions of SST anomalies in different tropical oceans. Our results reveal that the extreme floods over the MLYRV were tightly related to a strong anomalous anticyclone persisting over the western North Pacific, which brought tropical warm moisture northward that converged over the MLYRV. In addition, despite the absence of a strong El Nino in 2019/2020 winter, the mean SST anomaly in the tropical Indian Ocean during June-July 2020 reached its highest value over the last 40 years, and 43% (57%) of it is attributed to the multi-decadal warming trend (interannual variability). Based on the NUIST CFS1.0 model that successfully predicted the wet conditions over the MLYRV in summer 2020 initiated from 1 March 2020 (albeit the magnitude of the predicted precipitation was only about one-seventh of the observed), sensitivity experiment results suggest that the warm SST condition in the Indian Ocean played a dominant role in generating the extreme floods, compared to the contributions of SST anomalies in the Maritime Continent, central and eastern equatorial Pacific, and North Atlantic. Furthermore, both the multi-decadal warming trend and the interannual variability of the Indian Ocean SSTs had positive impacts on the extreme floods. Our results imply that the strong multi-decadal warming trend in the Indian Ocean needs to be taken into consideration for the prediction/projection of summer extreme floods over the MLYRV in the future.
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