Assimilation of atmospheric infrared sounder radiances with WRF-GSI for improving typhoon forecast

Abstract

The Atmospheric Infrared Sounder (AIRS) can provide the profile information on atmospheric temperature and humidity in high vertical resolution. The assimilation of its radiances has been proven to improve the Numerical Weather Prediction (NWP) in global models. In this study, regional assimilation of AIRS radiances was carried out in a community assimilation system, using Gridpoint Statistical Interpolation (GSI) coupled with the Weather Research and Forecasting (WRF) model. The AIRS channel selection, quality control, and radiances bias correction were examined and illustrated for optimized assimilation. The bias correction scheme in the regional model showed that corrections on most of the channels produce satisfactory results except for several land surface channels. The assimilation and forecast experiments were carried out for three typhoon cases (Saola, Damrey, and Haikui in 2012) with and without including AIRS radiances. Results show that the assimilation of AIRS radiances into the WRF/GSI model improves both the typhoon track and intensity in a 72-hour forecast.

Keywords

AIRS / WRF/GSI model / radiance assimilation / typhoon forecast

References

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Acknowledgement

This work was supported by the National Natural Science Foundation of China (Grant No. 41601469) and Fundamental Research Funds for the Central Universities in China (East China Normal University). The experiments were run on the Supercomputer located at the Computing Center of East China Normal University.

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