The influence of latent heating on the sub-seasonal prediction of winter blocking over Northern Hemisphere

被引:0
|
作者
Huang, Bo [1 ]
He, Yongli [1 ,2 ]
Li, Dongdong [3 ,4 ]
Zhang, Boyuan [1 ]
Jia, Jingjing [1 ]
机构
[1] Lanzhou Univ, Coll Atmospher Sci, Key Lab Semiarid Climate Change, Minist Educ, Lanzhou, Gansu, Peoples R China
[2] Collaborat Innovat Ctr Western Ecol Safety, Lanzhou, Peoples R China
[3] Fudan Univ, Dept Atmospher, Shanghai, Peoples R China
[4] Fudan Univ, Inst Atmospher Sci, Shanghai, Peoples R China
基金
美国国家科学基金会;
关键词
Atmospheric blocking; Latent heating; Prediction skill; Sub-seasonal forecast; ATMOSPHERIC BLOCKING; ARCTIC AMPLIFICATION; PERSISTENT ANOMALIES; EXTREME COLD; CLIMATOLOGY; CIRCULATION; FREQUENCIES; DYNAMICS; IMPACT; MODEL;
D O I
10.1007/s00382-024-07442-5
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The critical role of latent heating (LH) in atmospheric blocking events is well-recognized, yet its influence on the predictability of such events remains underexplored. This study examines the prediction accuracy of winter atmospheric blocking days over the Northern Hemisphere, utilizing 20 years of retrospective forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF). Atmospheric blocking events are categorized into three sectors: Atlantic, Continent, and Pacific. Results indicate substantial variations in the LH contribution among different blocking events. During the first 21 days, the Pacific blockings exhibit the most significant impact on prediction skill under strong LH conditions, followed by the Continent blockings, with the Atlantic blockings being least affected. Interestingly, a consistent pattern emerged across sectors: blocking prediction skill is lower under strong LH than under weak LH. During the first 12 days, the Pacific sector typically exhibit lower prediction skill for blocking onset under strong LH, compared to weak LH. For blocking decay, a consistent pattern is observed: lower prediction skill under strong LH than weak LH. Regarding blocking intensity, the forecasting bias escalates with increasing lead time, particularly for strong LH. This study highlights the need to improve moist process simulations in models, aiming to improve atmospheric blocking forecasting accuracy.
引用
收藏
页码:10167 / 10184
页数:18
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