Assimilation and simulation of typhoon Bilis(2006) using GRAPES(global and regional assimilation prediction system)

Yan Liu; Jishan Xue; Dehui Chen

doi:10.1117/12.733376

27 October 2007 Assimilation and simulation of typhoon Bilis(2006) using GRAPES(global and regional assimilation prediction system)

Yan Liu, Jishan Xue, Dehui Chen

Author Affiliations +

Proceedings Volume 6685, Assimilation of Remote Sensing and In Situ Data in Modern Numerical Weather and Environmental Prediction Models; 66850M (2007) https://doi.org/10.1117/12.733376
Event: Optical Engineering + Applications, 2007, San Diego, California, United States

Abstract

GRAPES (Global and Regional Assimilation Prediction System) is the Chinese new generation numerical weather prediction (NWP) system which has been operational run in the national operational NWP centers. However, sparseness of conventional data is the biggest challenge in upgrading NWP in China. Application of satellite observations is the most effective way to solve the problem of data sparseness, therefore the assimilation of satellite data into GRAPES analysis system is the first priority in the development of GRAPES model. In this paper we show the effects of assimilating satellite remote sensing data into GRAPES-3DVar (three-dimensional variational assimilation system) for a landing typhoon precipitation process in the east of China in 2006. The typhoon case is named Bilis, which landed in Fujian province on July 14 2006 and caused a prolonged and intense precipitation. Typhoon Bilis affected China for 120 hours since it landed, which is unusual in the history of China. In the end, the simulation of precipitation process associated with typhoon Bilis using GRAPES-Meso is also showed, and the performance of GRAPES is evaluated.

Citation Download Citation

Yan Liu, Jishan Xue, and Dehui Chen "Assimilation and simulation of typhoon Bilis(2006) using GRAPES(global and regional assimilation prediction system)", Proc. SPIE 6685, Assimilation of Remote Sensing and In Situ Data in Modern Numerical Weather and Environmental Prediction Models, 66850M (27 October 2007); https://doi.org/10.1117/12.733376

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