Application of Principal Component Algorithm to the direct Assimilation of AIRS in the WRF 4D-Var System
The use of Principal Component (PC) algorithm is explored for the efficient representation observations from high-resolution infrared sounders for the purposes of data assimilation into numerical weather prediction (NWP) models.A new version of the fast radiative transfer model has been developed that exploits principal component analysis and then implemented into the WRF 4D-Var data assimilation system,thus allow the investigation of the direct assimilation of PC scores from Atmospheric Infrared Sounder (AIRS).Testing of a prototype system where 119 AIRS spectra replaced by only 20 PC scores show significant computational saving with no detectable loss of skill in the resulting analyses or forecasts.The methodologies implemented in this regard are examined and the potential for future increased use of the data are explored.
Principal Component Analysis AIRS PCRT Data Assimilation
Yu Yi Zhang Weimin Zhu Mengbin Ye Minhua Sun jing
Computer Science, National University of Defense Technology, Changsha, China ;NO.94865 Troops of Chi Computer Science, National University of Defense Technology, Changsha, China NO.94865 Troops of Chinese Peoples Liberation Army, Hangzhou, China
国际会议
三亚
英文
506-510
2013-06-22（万方平台首次上网日期，不代表论文的发表时间）