摘要
The impacts of AMSU-A and IASI（Infrared Atmospheric Sounding Interferometer） radiances assimilation on the prediction of typhoons Vicente and Saola（2012） are studied by using the ensemble transform Kalman filter/three-dimensional variational（ETKF/3DVAR） Hybrid system for the Weather Research and Forecasting（WRF） model. The experiment without assimilating radiance data in 3DVAR is compared with two experiments using the 3DVAR and ETKF/3DVAR hybrid systems to assimilate AMSU-A radiance,respectively. The results show that AMSU-A radiance data have slight positive impacts on track forecasts of the 3DVAR system. When the ETKF/3DVAR hybrid system is employed, typhoon track forecast skills are greatly improved. For 36-h forecasts, the hybrid system has a lower root-mean-square error for wind and temperature at most levels, and specific humidity at low levels, compared to 3DVAR. It is also found that, on average, the use of the IASI radiance data along with AMSU-A radiance data in the hybrid system further increases the track, wind, and specific humidity forecast accuracy compared to the experiment without IASI radiance assimilation.
The impacts of AMSU-A and IASI（Infrared Atmospheric Sounding Interferometer） radiances assimilation on the prediction of typhoons Vicente and Saola（2012） are studied by using the ensemble transform Kalman filter/three-dimensional variational（ETKF/3DVAR） Hybrid system for the Weather Research and Forecasting（WRF） model. The experiment without assimilating radiance data in 3DVAR is compared with two experiments using the 3DVAR and ETKF/3DVAR hybrid systems to assimilate AMSU-A radiance,respectively. The results show that AMSU-A radiance data have slight positive impacts on track forecasts of the 3DVAR system. When the ETKF/3DVAR hybrid system is employed, typhoon track forecast skills are greatly improved. For 36-h forecasts, the hybrid system has a lower root-mean-square error for wind and temperature at most levels, and specific humidity at low levels, compared to 3DVAR. It is also found that, on average, the use of the IASI radiance data along with AMSU-A radiance data in the hybrid system further increases the track, wind, and specific humidity forecast accuracy compared to the experiment without IASI radiance assimilation.
基金
Supported by the National(Key)Basic Research and Development(973)Program of China(2013CB430102)
National Natural Science Foundation of China(41375025)
Innovation Scientific Research Program for College Graduates of Jiangsu Province(CXZZ12-0490)
