The Observed and Simulated Evolution of a Microburst Using X‐Band Phased‐Array Radar Data Assimilation With EnKF

Abstract A microburst is a severe small‐scale meteorological event that develops rapidly, producing intense downdrafts that result in catastrophic divergent winds near the ground. The fine‐scale structure and evolution of real‐case microbursts are rarely analyzed due to the limitation of regular observational platforms and the computational capacity for numerical simulations. On 12 September 2020, a microburst was effectively captured by China's S‐band operational weather radar network and an X‐band polarimetric phased‐array radar (XPAR). XPAR observations can identify precursor signatures of the rapidly evolving microburst before the occurrence of surface wind disasters, demonstrating superior spatiotemporal resolution in monitoring compared to the S‐band radars. To disclose the evolution of small‐scale structure and the underlying physical processes, this study utilizes the Weather Research and Forecasting (WRF) model and the ensemble Kalman filter (EnKF) system to assimilate XPAR data. The simulation successfully reproduces the fine‐scale structure and evolution of the microburst with a misocyclone. The analysis indicates that the microburst's downdraft is primarily triggered by the middle‐level hydrometeor loading. The misocyclone generates a downward‐directed perturbation pressure gradient then accelerates the microburst's downdraft toward the surface. This study is the first observation and simulation of a real‐case microburst using the WRF‐EnKF system assimilating XPAR data. The investigation of the impact of misocyclone on the microburst enhances our understanding of microbursts' forcing mechanism.

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Publication Details

Journal
Journal of Geophysical Research Atmospheres
Published
2024-12-29
DOI
https://doi.org/10.1029/2024jd042614
Citations
3
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
1.13

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article

The Observed and Simulated Evolution of a Microburst Using X‐Band Phased‐Array Radar Data Assimilation With EnKF

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3 citations
Journal of Geophysical Research Atmospheres
Meteorological Phenomena and Simulations
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article

The Observed and Simulated Evolution of a Microburst Using X‐Band Phased‐Array Radar Data Assimilation With EnKF

Yinghui Lu, Kun Zhao, Yiqing Zhu, Hao Huang, Ang Zhou
article en
3 citations

Abstract

Abstract A microburst is a severe small‐scale meteorological event that develops rapidly, producing intense downdrafts that result in catastrophic divergent winds near the ground. The fine‐scale structure and evolution of real‐case microbursts are rarely analyzed due to the limitation of regular observational platforms and the computational capacity for numerical simulations. On 12 September 2020, a microburst was effectively captured by China's S‐band operational weather radar network and an X‐band polarimetric phased‐array radar (XPAR). XPAR observations can identify precursor signatures of the rapidly evolving microburst before the occurrence of surface wind disasters, demonstrating superior spatiotemporal resolution in monitoring compared to the S‐band radars. To disclose the evolution of small‐scale structure and the underlying physical processes, this study utilizes the Weather Research and Forecasting (WRF) model and the ensemble Kalman filter (EnKF) system to assimilate XPAR data. The simulation successfully reproduces the fine‐scale structure and evolution of the microburst with a misocyclone. The analysis indicates that the microburst's downdraft is primarily triggered by the middle‐level hydrometeor loading. The misocyclone generates a downward‐directed perturbation pressure gradient then accelerates the microburst's downdraft toward the surface. This study is the first observation and simulation of a real‐case microburst using the WRF‐EnKF system assimilating XPAR data. The investigation of the impact of misocyclone on the microburst enhances our understanding of microbursts' forcing mechanism.

Journal of Geophysical Research AtmospheresVol. 130(1)
China Meteorological Administration (CN), Nanjing University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Jiangsu Province
Climate action
Openalex Percentile: Top 23%
Meteorological Phenomena and Simulations
1.13
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