Journal
ADVANCES IN ATMOSPHERIC SCIENCES
Volume 39, Issue 4, Pages 658-672Publisher
SCIENCE PRESS
DOI: 10.1007/s00376-021-1130-y
Keywords
extreme cold event; predictability; La Nina; Arctic sea ice loss
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Funding
- Key Research Program of Frontier Sciences, CAS [ZDBS-LY-DQC010]
- National Natural Science Foundation of China [41876012, 41861144015, 42175045]
- Strategic Priority Research Program of the Chinese Academy of Sciences [XDB42000000]
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This study explores the physical factors that can improve the accuracy of seasonal climate predictions and identifies the key factors for predicting the 2020/21 La Nina phenomenon and Arctic sea ice loss.
Several consecutive extreme cold events impacted China during the first half of winter 2020/21, breaking the low-temperature records in many cities. How to make accurate climate predictions of extreme cold events is still an urgent issue. The synergistic effect of the warm Arctic and cold tropical Pacific has been demonstrated to intensify the intrusions of cold air from polar regions into middle-high latitudes, further influencing the cold conditions in China. However, climate models failed to predict these two ocean environments at expected lead times. Most seasonal climate forecasts only predicted the 2020/21 La Nina after the signal had already become apparent and significantly underestimated the observed Arctic sea ice loss in autumn 2020 with a 1-2 month advancement. In this work, the corresponding physical factors that may help improve the accuracy of seasonal climate predictions are further explored. For the 2020/21 La Nina prediction, through sensitivity experiments involving different atmospheric-oceanic initial conditions, the predominant southeasterly wind anomalies over the equatorial Pacific in spring of 2020 are diagnosed to play an irreplaceable role in triggering this cold event. A reasonable inclusion of atmospheric surface winds into the initialization will help the model predict La Nina development from the early spring of 2020. For predicting the Arctic sea ice loss in autumn 2020, an anomalously cyclonic circulation from the central Arctic Ocean predicted by the model, which swept abnormally hot air over Siberia into the Arctic Ocean, is recognized as an important contributor to successfully predicting the minimum Arctic sea ice extent.
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