Quantifying the practical local predictability of the January 2021 sudden stratospheric warming using a novel nonlinear method
编号:448 访问权限:仅限参会人 更新:2025-03-29 09:50:40 浏览:42次 口头报告

报告开始:2025年04月19日 17:40(Asia/Shanghai)

报告时间:10min

所在会场:[S1-11] 专题1.11 极端气候事件的形成机理与预测技术 [S1-11] 专题1.11 极端气候事件的形成机理与预测技术

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摘要
A major sudden stratospheric warming (SSW) occurred in the Northern Hemisphere in early 2021, which caused extreme cold events across East Asia and North America, with record-breaking cold temperatures, notably 151 deaths in Texas. A better understanding of the SSW predictability for an improved surface seasonal to subseasonal (S2S) forecast is a pressing issue. Here we quantify the practical local predictability limit and find sensitive areas of forecast errors of 2021 SSW event within ERA5 reanalysis data and subseasonal to seasonal (S2S) reforecasts. A novel nonlinear method, Backward Searching for the Initial Condition (BaSIC), is used to estimate the local predictability of the SSW. This method is advanced because the nature of SSW is chaotic system with intrinsic properties, making it difficult to measure its predictability with traditional linear methods. The local predictability limit of this 2021 SSW event is estimated to be 17 days using BaSIC method.
We also trace the sensitive areas of forecast errors of this SSW. At the beginning, the overall forecast errors are relatively small, but with increase of time, errors increased more in the high altitude over central Eurasia (30°E-60°E). This indicates that this area is sensitive to forecast error growth, which limits the forecast skills of the 2021 SSW event. And it suggests that the central Eurasia is a key area for the improvements of the SSW forecast.
关键词
Sudden stratospheric warming; practical local predictability limit; the BaSIC method; forecast errors
报告人
张桂萍
研究生 成都信息工程大学大气科学学院

稿件作者
李旋 西北工业大学海洋研究院
张桂萍 成都信息工程大学大气科学学院
李扬 成都信息工程大学,大气科学学院
陈权亮 成都信息工程大学,大气科学学院
周欣 成都信息工程大学
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重要日期
  • 会议日期

    04月17日

    2025

    04月21日

    2025

  • 04月10日 2025

    初稿截稿日期

  • 04月20日 2025

    注册截止日期

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中国科学院大气物理研究所
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中国科学院大气物理研究所
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