气候变化领域集成服务门户(CCPortal): An improvement of convective precipitation nowcasting through lightning data dynamic nudging in a cloud-resolving scale forecasting system

CCPortal

DOI	10.1016/j.atmosres.2020.104994
	An improvement of convective precipitation nowcasting through lightning data dynamic nudging in a cloud-resolving scale forecasting system
	Wang H.; Chen D.; Yin J.; Xu D.; Dai G.; Chen L.
发表日期	2020
ISSN	0169-8095
卷号	242
英文摘要	A lightning data dynamic nudging (LDN) method was designed to adjust the dynamic field in convective clouds based on the physical relationship between lightning and vertical velocity. Under this framework, vertical velocity data retrieved from the Guangdong–Hongkong–Macau lightning location system were assimilated by a nudging approach using the Global/Regional Assimilation and Prediction System in mesoscale model (GRAPES-Meso). The effect of the assimilation on short-term (<6 h) precipitation forecast was evaluated by simulating the squall line event on 7 May and a continuous experiment from May to August 2018. Firstly, a series of sensitivity experiments was carried out to adjust the configuration of the assimilation system based on the squall line event. The results show that LDN expanded the spatial distribution of the positive vertical velocity (>1 m s−1) at 700 hPa by about 2%, and thus enlarged the spatial distribution of severe rainfall (>40 mm h−1). It should be noted that LDN did not significantly change the intensity of the updraft (i.e., the maximum vertical velocity) of the squall line relative to the simulation without assimilation. Overall, the equitable threat score (ETS) and fractions skill score (FSS) were increased by 0.04 and 0.13, respectively, and the positive effect lasted for 2–3 h after the data were assimilated. In view of the data assimilation frequency, using two successive nudging procedures with an interval of 12 min had the best effect on the forecast of severe precipitation. For the assimilation of both lightning and radar observations, the asynchronous assimilation of lightning and radar measurements performed slightly better than the synchronous assimilation. LDN improved the accuracy of severe precipitation forecast (>40 mm h−1 and > 20 mm h−1 for the squall line case and the continuous run, respectively), whereas assimilating radar data improved weak precipitation forecast (1–20 mm h−1 in the squall line case and 1–10 mm h−1 in the continuous run). © 2020 Elsevier B.V.
关键词	Lightning Radar Radar measurement Spatial distribution Storms Velocity Weather forecasting Assimilation system Convective precipitation Equitable threat score Forecasting system Lightning location systems Meso-scale modeling Precipitation forecast Radar observations Precipitation (meteorology)convective cloud data assimilation lightning nowcasting precipitation (climatology)squall line updraft China Guangdong Hong Kong Macau Vitaceae
语种	英语
来源机构	Atmospheric Research
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/132447
推荐引用方式 GB/T 7714	Wang H.,Chen D.,Yin J.,et al. An improvement of convective precipitation nowcasting through lightning data dynamic nudging in a cloud-resolving scale forecasting system[J]. Atmospheric Research,2020,242.
APA	Wang H.,Chen D.,Yin J.,Xu D.,Dai G.,&Chen L..(2020).An improvement of convective precipitation nowcasting through lightning data dynamic nudging in a cloud-resolving scale forecasting system.,242.
MLA	Wang H.,et al."An improvement of convective precipitation nowcasting through lightning data dynamic nudging in a cloud-resolving scale forecasting system".242(2020).