DOI: 10.1029/2018JD028494
Scopus记录号: 2-s2.0-85053431560
论文题名: Continuous Assimilation of Lightning Data Using Time-Lagged Ensembles for a Convection-Allowing Numerical Weather Prediction Model
作者: Wang H. ; Liu Y. ; Zhao T. ; Liu Y. ; Xu M. ; Shen S. ; Jiang Y. ; Yang H. ; Feng S.
刊名: Journal of Geophysical Research: Atmospheres
ISSN: 2169897X
出版年: 2018
卷: 123, 期: 17 起始页码: 9652
结束页码: 9673
语种: 英语
英文关键词: Convection-allowing scales
; Data assimilation
; EnKF
; Lightning data
; Time-lagged ensembles
英文摘要: In this study, a lightning data assimilation method based on the time-lagged ensembles for predicting severe convection is presented. With the lightning data assimilation scheme, the background error covariances are computed using time-lagged ensembles, which consist of deterministic forecasts from eight forecast cycles initialized every 3 hr. Pseudo-observations of graupel mixing ratio (qg) are retrieved from total lightning rates by utilizing empirical vertical profiles obtained from the simulation results of the previous forecast cycles, and the corresponding observation errors are estimated according to the uncertainties in the lightning observations and the empirical vertical profiles of qg. The increments of the model state variables are computed with the Kalman gain matrices and are continuously ingested into the Weather Research and Forecasting model via nudging terms acting on the prognostic equations over each time step during model integration. The effect of the lightning data assimilation scheme on convection analysis and forecast was assessed through a case study of a severe convective event, which took place in the Guangdong of China. Assimilating lightning data recovered many of the observed convective cells, suppressed the spurious convection, and corrected the displacement errors of the convective systems. Quantitative verifications indicate that forecast skills were improved mainly in the convective regions with the impact of assimilating lightning data on stratiform regions being overall less effective. ©2018. American Geophysical Union. All Rights Reserved. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/113187
Appears in Collections: 气候减缓与适应
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作者单位: Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China; National Center for Atmospheric Research, Boulder, CO, United States; China Electric Power Research Institute, Beijing, China; Meteorology Bureau of Shenzhen Municipality, Shenzhen, China
Recommended Citation:
Wang H.,Liu Y.,Zhao T.,et al. Continuous Assimilation of Lightning Data Using Time-Lagged Ensembles for a Convection-Allowing Numerical Weather Prediction Model[J]. Journal of Geophysical Research: Atmospheres,2018-01-01,123(17)