气候变化领域集成服务门户(CCPortal): The evaluation of EnVar method including hydrometeors analysis variables for assimilating cloud liquid/ice water path on prediction of rainfall events

CCPortal

DOI	10.1016/j.atmosres.2018.12.017
	The evaluation of EnVar method including hydrometeors analysis variables for assimilating cloud liquid/ice water path on prediction of rainfall events
	Meng D.; Chen Y.; Wang H.; Gao Y.; Potthast R.; Wang Y.
发表日期	2019
ISSN	0169-8095
起始页码	1
结束页码	12
卷号	219
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 (Qc, Qi, Qr, Qs) 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
英文关键词	Data assimilation; EnVar method; Hydrometeors; Precipitation forecast
语种	英语
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
来源期刊	Atmospheric Research
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/162167
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
推荐引用方式 GB/T 7714	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],2019,219.
APA	Meng D.,Chen Y.,Wang H.,Gao Y.,Potthast R.,&Wang Y..(2019).The evaluation of EnVar method including hydrometeors analysis variables for assimilating cloud liquid/ice water path on prediction of rainfall events.Atmospheric Research,219.
MLA	Meng D.,et al."The evaluation of EnVar method including hydrometeors analysis variables for assimilating cloud liquid/ice water path on prediction of rainfall events".Atmospheric Research 219(2019).