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High-skill members in the subseasonal forecast ensemble of extreme cold events in East Asia

Xinli Liu Jingzhi Su Yihao Peng Xiaolei Liu

大气和海洋科学快报（英文版）2025，Vol.18Issue(6)：22-28,7.

大气和海洋科学快报（英文版）2025，Vol.18Issue(6)：22-28,7.DOI:10.1016/j.aosl.2025.100610

High-skill members in the subseasonal forecast ensemble of extreme cold events in East Asia

Xinli Liu ¹Jingzhi Su ²Yihao Peng ¹Xiaolei Liu¹

作者信息

1. State Key Laboratory of Disaster Weather Science and Technology,Chinese Academy of Meteorological Sciences,Beijing,China
2. State Key Laboratory of Disaster Weather Science and Technology,Chinese Academy of Meteorological Sciences,Beijing,China||Center for Earth System Modeling and Prediction of CMA(CEMC),Beijing,China||Key Laboratory of Earth System Modeling and Prediction China Meteorological Administration,Beijing,China
折叠

摘要

Abstract

极端事件次季节预报对防灾减灾保障社会经济安全具有重要意义.本研究针对东亚地区极端低温事件的次季节预报难题,通过分析1998-2020年34起东亚地区极端低温事件,并重点关注2018年1月中国东北地区极端低温事件,系统评估不同版本ECMWF模式集合成员之间的预报性能.提前3周的模式集合平均预报性能存在局限,但不同集合成员的预报技巧存在差异.部分成员具有高预报技巧,约10％的高技巧成员能提前14天捕捉气温快速转折的过程.研究指出集合成员是否具有高预报技巧依赖于对大气环流演变特征的合理预报.该发现为极端冷事件次季节预报评估和后期订正提供了新视角,凸显挖掘集合成员预报潜力的重要性,并为提升次季节时间尺度预警能力提供了理论支撑.

关键词

次季节预报/预报技巧/集合成员/极端低温事件

Key words

Subseasonal forecast/Forecast skill/Ensemble members/Extreme cold event

引用本文复制引用

Xinli Liu,Jingzhi Su,Yihao Peng,Xiaolei Liu..High-skill members in the subseasonal forecast ensemble of extreme cold events in East Asia[J].大气和海洋科学快报（英文版）,2025,18(6):22-28,7.

基金项目

This work was supported by the National Key Research and Devel-opment Program[grant number 2022YFC3004203]and the S&T Devel-opment Fund of CAMS(Chinese Academy of Meteorological Sciences)[grant numbers 2023KJ040 and 2024KJ013]. （Chinese Academy of Meteorological Sciences）

大气和海洋科学快报（英文版）

ISSN：1674-2834

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