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Combined assimilation of radar and lightning data for the short-term forecast of severe convection system.

Authors :
Zhang, Yuxin
Chen, Zhixiong
Xiao, Xian
Qie, Xiushu
Chen, Min
Lu, Jingyu
Wang, Dongfang
Yuan, Shanfeng
Lyu, Huimin
Feng, Jin
Fan, Shuiyong
Liu, Dongxia
Source :
Atmospheric Research. Mar2023, Vol. 283, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

In this study, a lightning data assimilation (LDA) method adjusting dynamical fields was examined in the rapid cycle with Weather Research and Forecasting (WRF) model and WRF Data Assimilation (WRFDA). This method retrieves pseudo vertical velocity profiles from total lightning observations and promotes wind convergence over lightning regions. This newly developed LDA scheme is compared with radar data assimilation (RDA) that has been routinely applied in severe storm nowcasting models. Depending on whether the radar or lightning data is assimilated, four experiments were designed to evaluate the positive impacts of dynamical adjustment from LDA. Using a typical severe mesoscale convection system occurred in Beijing, we found that the effect of RDA and LDA are different. The assimilation of radar radial velocity mainly improves the forecast in a longer time, while assimilation of pseudo-vertical-velocity from lightning data mainly corrects intensity and location of the forecasted precipitation. When both radar and lightning data are assimilated, the small-scale wind convergence are promoted and contributes to the intensified updrafts. Thermal and water vapor fields are also adjusted indirectly. Consequently, the convective precipitation is significantly improved and the positive impacts from the combined assimilation scheme persisted over a longer period (at least 3 h). It can be concluded that a combined assimilation of convective data from multiple sources such as radar and lightning data enhance prominently the accuracy of short-term convection forecasts. • A lightning data assimilation method adjusting dynamical fields is applied in nowcasting through rapid update cycling. • Radar data and lightning data assimilation are combined to improve the accuracy of short-term precipitation forecasts. • Radar radial velocity improves forecast in a longer time, while lightning data corrects its intensity and location. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01698095
Volume :
283
Database :
Academic Search Index
Journal :
Atmospheric Research
Publication Type :
Academic Journal
Accession number :
161277114
Full Text :
https://doi.org/10.1016/j.atmosres.2022.106562