气候变化领域集成服务门户(CCPortal): A Method to Update Model Kinematic States by Assimilating Satellite-Observed Total Lightning Data to Improve Convective Analysis and Forecasting

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DOI	10.1029/2020JD033330
	A Method to Update Model Kinematic States by Assimilating Satellite-Observed Total Lightning Data to Improve Convective Analysis and Forecasting
	Chen Z.; Sun J.; Qie X.; Zhang Y.; Ying Z.; Xiao X.; Cao D.
发表日期	2020
ISSN	2169897X
卷号	125 期号:22
英文摘要	This study assesses the benefit of convective-scale data assimilation (DA) for model initialization using well-known functional relationships between lightning flash rate and vertical velocity. Based on the relationships, a lightning DA scheme to update model kinematic states was implemented in the Weather Research and Forecasting Data Assimilation (WRFDA) three-dimensional variational (3DVar) system. This scheme combines total lightning observations with model-based prescribed vertical velocity profiles to retrieve kinematic information through a DA scheme. With the availability of space-borne lightning imagers in recent years, total lightning observations from the Lightning Mapping Imager (LMI) on board the FY-4A geostationary satellite were assimilated in combination with radar DA. A detailed analysis of the impact of the lightning DA scheme on convective precipitation forecasting was conducted using a squall line case over Beijing on 13 July 2017. The assimilation of LMI data provides added benefits to the assimilation of radar radial winds by reducing wind errors and strengthening convergence along the squall line in the analysis. Although the microphysical states are identical due to the assimilation of reflectivity, the lightning DA scheme helps in promoting updraft developments at lightning observation locations, which improves the representation of mixed-phase convection. The quantitative verification of short-term convective forecasts indicated that the lightning DA adds value to the radar DA by improving the precipitation forecast skill. The lightning DA scheme was evaluated further for a heavy rainfall case in 2018 over the Beijing metropolitan area and revealed overall similar forecast improvements for composite reflectivity and accumulated rainfall. ©2020. American Geophysical Union. All Rights Reserved.
英文关键词	Lightning Data Assimilation; Lightning Mapping Imager; nowcasting; radar data assimilation; WRFDA
语种	英语
来源期刊	Journal of Geophysical Research: Atmospheres
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/185640
作者单位	Key Laboratory of Middle Atmosphere and Global Environment Observation (LAGEO), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China; Key Laboratory for Subtropical Mountain Ecology, School of Geographical Sciences, Fujian Normal University, Fuzhou, China; College of Earth and Planetary Science, University of Chinese Academy of Sciences, Beijing, China; National Center for Atmospheric Research, Boulder, CO, United States; Beijing Urban Meteorological Engineering Research Center, Beijing, China; National Satellite Meteorological Center, Beijing, China
推荐引用方式 GB/T 7714	Chen Z.,Sun J.,Qie X.,et al. A Method to Update Model Kinematic States by Assimilating Satellite-Observed Total Lightning Data to Improve Convective Analysis and Forecasting[J],2020,125(22).
APA	Chen Z..,Sun J..,Qie X..,Zhang Y..,Ying Z..,...&Cao D..(2020).A Method to Update Model Kinematic States by Assimilating Satellite-Observed Total Lightning Data to Improve Convective Analysis and Forecasting.Journal of Geophysical Research: Atmospheres,125(22).
MLA	Chen Z.,et al."A Method to Update Model Kinematic States by Assimilating Satellite-Observed Total Lightning Data to Improve Convective Analysis and Forecasting".Journal of Geophysical Research: Atmospheres 125.22(2020).