A frequent-updating analysis system based on radar, surface, and mesoscale model data for the Beijing 2008 Forecast Demonstration Project

The 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.

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Author Sun, Juanzhen
Chen, Mingxuan
Wang, Yingchun
Publisher UCAR/NCAR - Library
Publication Date 2010-12-01T00:00:00
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Topic Category geoscientificInformation
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Metadata Date 2023-08-18T19:03:08.128977
Metadata Record Identifier edu.ucar.opensky::articles:17049
Metadata Language eng; USA
Suggested Citation Sun, Juanzhen, Chen, Mingxuan, Wang, Yingchun. (2010). A frequent-updating analysis system based on radar, surface, and mesoscale model data for the Beijing 2008 Forecast Demonstration Project. UCAR/NCAR - Library. http://n2t.net/ark:/85065/d7m32x14. Accessed 28 June 2025.

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