DOI: 10.1016/j.atmosres.2018.03.002
Scopus记录号: 2-s2.0-85044456571
论文题名: Incorporating geostationary lightning data into a radar reflectivity based hydrometeor retrieval method: An observing system simulation experiment
作者: Wang H. ; Liu Y. ; Zhao T. ; Xu M. ; Liu Y. ; Guo F. ; Cheng W.Y.Y. ; Feng S. ; Mansell E.R. ; Fierro A.O.
刊名: Atmospheric Research
ISSN: 1698095
出版年: 2018
卷: 209 起始页码: 1
结束页码: 13
语种: 英语
英文关键词: Data assimilation
; Hydrometeor retrieval
; Lightning
; Numerical weather prediction
; Observing system simulation experiment
Scopus关键词: Clouds
; Geostationary satellites
; Information retrieval
; Input output programs
; Lightning
; Mixing
; Radar
; Reflection
; Storms
; Weather forecasting
; Convective precipitation
; Data assimilation
; Four-dimensional data assimilation
; Hydrometeor retrieval
; Mesoscale Convective System
; Numerical weather prediction
; Observing system simulation experiments
; Weather research and forecasting models
; Search engines
; data assimilation
; experiment
; geostationary satellite
; hydrometeorology
; lightning
; mixing ratio
; numerical model
; reflectivity
; weather forecasting
英文摘要: A retrieval method for deriving the hydrometeor mixing ratio within mesoscale convective system (MCS) is presented in this study. The hydrometeor retrieval method was designed to incorporate the flash extent densities (FED) data from the Feng-Yun-4 geostationary satellite into the S-band radar reflectivity (Zh) and ambient temperature (T) data-based hydrometeor retrieval method. Total lightning data are utilized to better discern regions containing graupel in clouds. In the quantitative estimation of rain mixing ratio, different intercept parameters are used for different ranges of Zh and different estimated precursors of raindrop in cold-cloud microphysical processes (i.e., graupel and snow aggregate). The hydrometeor retrieval method was evaluated through an observing system simulation experiment (OSSE) in which the pseudo-input-data for the hydrometeor retrieval (i.e., the FED, Zh and T data) were obtained from the cloud-scale (1-km) simulation of an MCS using explicit electrification implemented within the Weather Research and Forecasting model. By incorporating the FED data as an additional input data source into the Zh and T-based hydrometeor retrieval method, the hydrometeor retrieval accuracy was improved. The hydrometeor retrievals were then assimilated into the model using the Real-Time Four-Dimensional Data Assimilation (RTFDDA) system. Assimilating more accurate hydrometeor fields slightly improved the analyses and forecasts of convective precipitation in the test MCS case. The improvement could be due to the more accurate hydrometeor analysis, which further affected the strength of the cold pool and gust front. © 2018 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/108865
Appears in Collections: 影响、适应和脆弱性 气候变化事实与影响
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作者单位: Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing, 210044, China; National Center for Atmospheric Research, Boulder, CO 80301, United States; China Electric Power Research Institute, Beijing, 100192, China; NOAA/OAR/National Severe Storms Laboratory, Norman, OK 73072, United States; Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, NOAA/OAR/National Severe Storms Laboratory, Norman, OK 73072, United States
Recommended Citation:
Wang H.,Liu Y.,Zhao T.,et al. Incorporating geostationary lightning data into a radar reflectivity based hydrometeor retrieval method: An observing system simulation experiment[J]. Atmospheric Research,2018-01-01,209