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• W4308587462 abstract "In the first half of winter 2020/2021, several unprecedented cold events occurred in most parts of China and caused record-breaking low temperatures in many cities. However, seasonal predictions related to the onset and evolution of extreme cold events are still challenging. In this study, we first evaluated the short-term climate prediction skills in winter of the CAS-ESM-c global coupled model and revealed the key dynamic processes of the onset and development of 2020/2021 extreme cold events based on the ensemble forecasts starting on October 1st, 2020. Under the background provided by the synergistic effect of the warm Arctic and the cold tropical Pacific (La Niña), the model captured the abnormal meridional atmospheric pattern well, including the intensification of the Ural Blocking High and the negative phase of the Arctic Oscillation, forecasted the negative geopotential height anomalies over the Eastern Asian region, and finally, successfully predicted the outbreak of cold waves in December 2020 two months in advance. Moreover, the dominant differences in the initial ocean fields between the best and the worst forecast members were further compared to isolate the triggering factor for predicting cold events by CAS-ESM-c. The initial warm sea surface temperature over the Barents Sea can gradually form a meridional pattern between the warm Arctic and the cold Asian continent, which could lead to a reduction in the large-scale meridional temperature gradient at mid-high latitudes and weaken the atmospheric baroclinicity with more conducive to the southward outbreak of cold waves, highlighting that realistic Arctic ocean conditions in autumn can be reasonably assimilated into coupled models to stimulate the successful prediction of extreme cold events in the 2020/2021 winter." @default.
• W4308587462 created "2022-11-12" @default.
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• W4308587462 date "2022-11-08" @default.
• W4308587462 modified "2023-10-10" @default.
• W4308587462 title "Realistic ocean initial condition for stimulating the successful prediction of extreme cold events in the 2020/2021 winter" @default.
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• W4308587462 doi "https://doi.org/10.1007/s00382-022-06557-x" @default.
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