Subseasonal to Seasonal (S2S) Predictability of Continental Cold and Snowstorms Following the Sudden Stratospheric Warming in the 2022/23 Winter
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更新:2024-04-11 20:51:35 浏览:882次
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摘要
Using the ERA5 reanalysis and subseasonal to seasonal (S2S) real-time forecasts, this study explores the predictability of stratospheric disturbances in the 2022/23 winter, with a particular focus on the February 2023 major sudden stratospheric warming (SSW). Diagnostics of the northern annular mode (NAM) index and the circulation anomalies show that stratosphere-troposphere coupling is enhanced in three periods and drives surface climate extremes. The February 2023 SSW is primarily driven by enhanced wave activities originating in the lower stratosphere. In the enhanced stratosphere-troposphere coupling periods, compound dry-cold anomalies prevail over Asian or/and North American midlatitudes, and compound wet-cold anomalies are evident in Northeastern Asia or/and North Atlantic. Snowstorm frequency increases along the midlatitude edge of the stratospheric and especially tropospheric polar vortices. Forecasts initialized around two lead time groups capture the SSW, one within the medium range time limit (1–2 weeks), and the other (4–6 weeks) far beyond the typical predictability of SSWs. Both groups have a hit ratio > 50% in a few models. During periods with strong stratosphere-troposphere coupling, the predictability of precipitation and snowstorms is higher with a more realistic spatial pattern than the weak coupling period. Consistent with the reanalysis, the snowstorms are more active where the tropospheric polar vortex extended equatorward in models. However, models also tend to exaggerate the downward impact of the SSW and forecast more snowstorms along the midlatitude edge of the stratospheric polar vortex. Forecasts with a better SSW representation usually capture the cold over the North American continent in the SSW occurrence and post-SSW periods.
关键词
Sudden stratospheric warming (SSW); Subseasonal to seasonal (S2S); Snowstorms; Forecasts
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