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contributor authorSun, Juanzhen
contributor authorChen, Mingxuan
contributor authorWang, Yingchun
date accessioned2017-06-09T16:38:35Z
date available2017-06-09T16:38:35Z
date copyright2010/12/01
date issued2010
identifier issn0882-8156
identifier otherams-71458.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4213352
description abstractThe Variational Doppler Radar Analysis System (VDRAS) was implemented in Beijing, China, and contributed to the Beijing 2008 Forecast Demonstration Project (B08FDP) in support of the Beijing Summer Olympics. VDRAS is a four-dimensional variational data assimilation system that produces frequently updated analyses using Doppler radar radial velocities and reflectivities, surface observations, and mesoscale model data. The system was tested in real time during the B08FDP pretrials in the summers of 2006 and 2007 and run during the Olympics to assist the 0?6-h convective weather nowcasting. This paper provides a description of the upgraded system and its Beijing implementation, an evaluation of the system performance using data collected during the pretrials, and its utility on convective weather nowcasting through two case studies. Verification of VDRAS wind against a wind profiler shows that the analyzed wind is reasonably accurate with a smaller RMS difference for 2006 than for 2007 due to better radar data coverage in 2006. The analyzed cold pools in three convective episodes are compared with surface observations at selected stations. The result shows good agreement between the analysis and the observations. The two case studies demonstrate the role that VDRAS could play in nowcasting convective initiation.
publisherAmerican Meteorological Society
titleA Frequent-Updating Analysis System Based on Radar, Surface, and Mesoscale Model Data for the Beijing 2008 Forecast Demonstration Project
typeJournal Paper
journal volume25
journal issue6
journal titleWeather and Forecasting
identifier doi10.1175/2010WAF2222336.1
journal fristpage1715
journal lastpage1735
treeWeather and Forecasting:;2010:;volume( 025 ):;issue: 006
contenttypeFulltext


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