Review on identification and forecasting of dusty weather

doi:10.7522/j.issn.1000-694X.2023.00054

Journal of Desert Research ›› 2024, Vol. 44 ›› Issue (1): 11-21.DOI: 10.7522/j.issn.1000-694X.2023.00054

Review on identification and forecasting of dusty weather

Siyu Chen¹^,²^,³(), Shikang Du³^,¹^,², Hongru Bi¹^,², Dan Zhao¹^,², Yue Zhang¹^,², Yu Chen¹^,², Gaotong Lou¹^,², Junyan Chen¹^,²

^1.College of Atmospheric Science /, Lanzhou University，Lanzhou 730000，China
^2.Ministry of Education Key Laboratory for Semi-Arid Climate Change /, Lanzhou University，Lanzhou 730000，China
^3.College of Earth and Environmental Sciences, Lanzhou University，Lanzhou 730000，China

Received:2023-03-15 Revised:2023-04-19 Online:2024-01-20 Published:2023-12-26

Abstract

Abstract:

Dusty weather is an extreme weather phenomenon that occurs frequently in the northern China. It leads to a turbidity of the air and a sharp decline in visibility， causing adverse effects on various aspects of human society. Dust aerosols transported into the atmosphere by strong winds also have a significant impact on weather and climate by modulating atmospheric radiation budget and cloud microphysics. Accurate identification and forecasting of dusty weather are of great significance in ecological protection and climate change mitigation. This paper provides a comprehensive review of recent research on methods for identifying and forecasting dust events. Important methods are described in detail， and their advantages and disadvantages are analyzed and compared. Finally， this paper summarizes the research achievements related to the identification and forecasting of dusty weather and proposes valuable future research directions.

Key words: dusty weather, identification of dusty weather, forecasting of dusty weather, numerical simulation, machine learning

CLC Number:

P427.2

Siyu Chen, Shikang Du, Hongru Bi, Dan Zhao, Yue Zhang, Yu Chen, Gaotong Lou, Junyan Chen. Review on identification and forecasting of dusty weather[J]. Journal of Desert Research, 2024, 44(1): 11-21.

Figures/Tables 3

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