Skill improvement of the yearly updated reforecasts in ECMWF S2S prediction from 2016 to 2022

被引：0

作者：

Yihao Peng ^{[1
]}

Xiaolei Liu ^{[1
]}

Jingzhi Su ^{[2
,1
]}

Xinli Liu ^{[1
]}

Yixu Zhang ^{[3
]}

机构：

[1] State Key Laboratory of Severe Weather,Chinese Academy of Meteorological Sciences

[2] Center for Earth System Modeling and Prediction of CMA(CEMC)

[3] Chengdu University of Information Technology

来源：

AtmosphericandOceanicScienceLetters | 2023年 / 16卷 / 05期

关键词：

回报; 次季节预测; 预测技巧; ECMWF;

D O I：

暂无

中图分类号：

P456 [预报方法];

学科分类号：

0706 ; 070601 ;

摘要：

在2016年至2022年间,ECMWF次季节预测系统不断升级并逐年完成新的回报试验.本文考察该预测系统逐年升级带来的预测技巧提升潜力.从2米气温和降水来看,在起报之后的前两周内天气尺度上预测技巧表现出逐年稳定提升的趋势;在从第三周开始的次季节时间尺度上,预测技巧的提升仅限于热带部分区域.MJO预测技巧并不随着模式升级而逐年单调提升.尽管目前S2S预测技巧存在局限性,但目前已有的进展增强了在未来深入合作以提高S2S预测技术的信心.

引用

页码：3 / 9

页数：7

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