Predictors and prediction skill for marine cold-air outbreaks over the Barents Sea

被引：8

作者：

Polkova, Iuliia ^{[1
]}

Afargan-Gerstman, Hilla ^{[2
]}

Domeisen, Daniela I. V. ^{[2
]}

King, Martin P. ^{[3
,4
]}

Ruggieri, Paolo ^{[5
,6
]}

Athanasiadis, Panos ^{[5
]}

Dobrynin, Mikhail ^{[1
,7
]}

Aarnes, Oivin ^{[8
]}

Kretschmer, Marlene ^{[9
]}

Baehr, Johanna ^{[1
]}

机构：

[1] Univ Hamburg, Ctr Earth Syst Res & Sustainabil CEN, Inst Oceanog, Bundesstr 53, D-20146 Hamburg, Germany

[2] Swiss Fed Inst Technol, Inst Atmospher & Climate Sci, Zurich, Switzerland

[3] NORCE Climate, Bergen, Norway

[4] Bjerknes Ctr Climate Res, Bergen, Norway

[5] Euro Mediterranean Ctr Climate Change CMCC, Bologna, Italy

[6] Univ Bologna, Dept Phys & Astron, Bologna, Italy

[7] Deutsch Wetterdienst, Hamburg, Germany

[8] DNV GL, Bergen, Norway

[9] Univ Reading, Reading, Berks, England

来源：

QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY | 2021年 / 147卷 / 738期

基金：

欧盟地平线“2020”;

关键词：

Arctic climate; causal drivers; marine cold air outbreak; polar low; seasonal prediction; CIRCULATION PATTERNS; POLAR LOWS; CLIMATOLOGY; ICE; INITIALIZATION; FORECASTS; EUROPE; MODEL;

D O I：

10.1002/qj.4038

中图分类号：

P4 [大气科学（气象学）];

学科分类号：

0706 ; 070601 ;

摘要：

Marine cold-air outbreaks (MCAOs) create conditions for hazardous maritime mesocyclones (polar lows) posing risks to marine infrastructure. For marine management, skilful predictions of MCAOs would be highly beneficial. For this reason, we investigate (a) the ability of a seasonal prediction system to predict MCAOs and (b) the possibilities to improve predictions through large-scale causal drivers. Our results show that the seasonal ensemble predictions have high prediction skill for MCAOs over the Nordic Seas for about 20 days starting from November initial conditions. To study causal drivers of MCAOs, we utilize a causal effect network approach applied to the atmospheric reanalysis ERA-Interim and identify local sea surface temperature and atmospheric circulation patterns over Scandinavia as valuable predictors. Prediction skill for MCAOs is further improved up to 40 days by including MCAO predictors in the analysis.

引用

页码：2638 / 2656

页数：19

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