DOI: 10.1016/j.atmosres.2018.12.017
Scopus记录号: 2-s2.0-85059132152
论文题名: The evaluation of EnVar method including hydrometeors analysis variables for assimilating cloud liquid/ice water path on prediction of rainfall events
作者: Meng D. ; Chen Y. ; Wang H. ; Gao Y. ; Potthast R. ; Wang Y.
刊名: Atmospheric Research
ISSN: 1698095
出版年: 2019
卷: 219 起始页码: 1
结束页码: 12
语种: 英语
英文关键词: Data assimilation
; EnVar method
; Hydrometeors
; Precipitation forecast
Scopus关键词: Clouds
; Liquids
; Mean square error
; NASA
; Potential energy
; Rain
; Background-error covariances
; Convective available potential energies
; Data assimilation
; EnVar method
; Hydrometeors
; Precipitation forecast
; Variational data assimilation
; Weather research and forecasting models
; Weather forecasting
; cloud water
; data assimilation
; ensemble forecasting
; hydrometeorology
; precipitation intensity
; spatial distribution
英文摘要: The Weather Research and Forecasting (WRF) model's data assimilation (WRFDA) hybrid ensemble-variational data assimilation (EnVar) system is used to examine the performance of the EnVar method for assimilating cloud liquid/ice water path products. To add flow-dependent features to background error covariance (BEC) of hydrometeors, hydrometeors mixing ratios (Q c , Q i , Q r , Q s ) are extended into analysis state vector for the “alpha” control variable. Then the BEC in the updated WRFDA-EnVar system combines the static hydrometeors BEC and flow-dependent hydrometeors BEC derived from ensemble forecasts. The updated system is evaluated by performing a series of single observation tests and two-weeks cycling assimilation and forecasting experiments by assimilating Cloud Liquid/Ice Water Path from NASA. The single observation tests show that the flow-dependent and multivariate BEC is introduced into the updated WRFDA-EnVar system by including extended hydrometeors analysis variables. The cycling assimilation and forecasting experiments demonstrate that by using the updated system included hydrometeors analysis variables, the root mean square errors (RMSEs) of analysis and forecasts are reduced and the Fractions Skill Scores (FSSs) of the precipitation forecasts are increased when compared with 3DVar method and the EnVar method without hydrometeors analysis variables. The diagnostics for a local severe rainfall case in the two-weeks cycling assimilation and forecasting experiments further show that through the application of the EnVar method included hydrometeors analysis variables, the convective available potential energy (CAPE) and humidity are increased effectively, and then better forecasts in terms of spatial distribution and intensity in accumulated precipitation are obtained, as well as cloud component. © 2018 Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/122328
Appears in Collections: 气候变化事实与影响
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作者单位: Key Laboratory of Meteorological Disaster of Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing, 210044, China; Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, NOAA/OAR/Earth System Research Laboratory/Global Systems Division, Boulder, CO, United States; Department of Mathematics and Statistics, University of Reading, Reading, United Kingdom; Division for Data Assimilation (FE12, Deutscher Wetterdienst, Offenbach, Germany
Recommended Citation:
Meng D.,Chen Y.,Wang H.,et al. The evaluation of EnVar method including hydrometeors analysis variables for assimilating cloud liquid/ice water path on prediction of rainfall events[J]. Atmospheric Research,2019-01-01,219