Frontiers of Earth Science

, Volume 12, Issue 3, pp 457–467 | Cite as

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

  • Yan-An Liu
  • Zhibin SunEmail author
  • Maosi Chen
  • Hung-Lung Allen Huang
  • Wei GaoEmail author
Research Article


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.


AIRS WRF/GSI model radiance assimilation typhoon forecast 


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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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Copyright information

© Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Key Laboratory of Geographic Information Science (Ministry of Education)East China Normal UniversityShanghaiChina
  2. 2.School of Geographic SciencesEast China Normal UniversityShanghaiChina
  3. 3.ECNU-CSU Joint Research Institute for New Energy and the EnvironmentEast China Normal UniversityShanghaiChina
  4. 4.Joint Laboratory for Environmental Remote Sensing and Data AssimilationEast China Normal UniversityShanghaiChina
  5. 5.Natural Resource Ecology LaboratoryColorado State UniversityFort CollinsUSA
  6. 6.Cooperative Institute for Meteorological Satellite StudiesUniversity of Wisconsin-MadisonMadisonUSA

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