Impacts of February climate conditions in the Gobi Desert on March dust activities in the northern East Asia.

Atmospheric teleconnection Dust activities Precipitation Prediction factors Sea surface temperature Surface air temperature

Journal

The Science of the total environment
ISSN: 1879-1026
Titre abrégé: Sci Total Environ
Pays: Netherlands
ID NLM: 0330500

Informations de publication

Date de publication:
05 Sep 2024
Historique:
received: 18 07 2024
revised: 26 08 2024
accepted: 04 09 2024
medline: 8 9 2024
pubmed: 8 9 2024
entrez: 7 9 2024
Statut: aheadofprint

Résumé

Amid ongoing global warming, intense dust storms continue to plague regions despite efforts to understand and mitigate their impacts. This study explores the connection between surface temperature (ST) and precipitation (PRE) in the Gobi Desert (GD) during February and their subsequent effects on March dust concentrations across northern East Asia. Our analysis reveals a clear pattern: higher February ST combined with lower PRE in GD correlates with increased dust levels in March, with ST effects predominantly in northern areas of dust sources compared to PRE. The warming of the ST in February facilitates surface thawing, and the concurrently reduced PRE decreases soil moisture in GD. These conditions both contribute to the loosening of the soil, thereby creating favorable lower boundary conditions for the onset of dust activities in the subsequent March. Atmospheric dynamics play a pivotal role in the changes of ST and PRE. The preceding ST warming is closely tied to the weakening of the East Asian winter monsoon. Furthermore, the Eurasia teleconnection (EU) pattern is identified as a key circulation factor driving the changes of February PRE in GD. Additionally, sea surface temperature anomalies in the Barents Sea and the North Atlantic appear to influence these atmospheric circulation changes, altering ST and PRE in GD, and consequently, impacting March dust dynamics in northern East Asia. This study provides crucial insights into the climatic precursors that drive dust storm activities, which are essential for improving the accuracy of dust storm forecasting.

Identifiants

pubmed: 39244054
pii: S0048-9697(24)06249-1
doi: 10.1016/j.scitotenv.2024.176093
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

176093

Informations de copyright

Copyright © 2024. Published by Elsevier B.V.

Auteurs

Lin Liu (L)

State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China.

Dongping Bai (D)

Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China.

Zhili Wang (Z)

State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China. Electronic address: wangzl@cma.gov.cn.

Deying Wang (D)

State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China. Electronic address: wangdeying@cma.gov.cn.

Huizheng Che (H)

State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China.

Yadong Lei (Y)

State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China.

Ke Gui (K)

State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China.

Junting Zhong (J)

State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China.

Xiaoye Zhang (X)

State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China.

Classifications MeSH