Application of ATOVS Radiance-Bias Correction to Typhoon Track Prediction with Ensemble Kalman Filter Data Assimilation

作者：Cui Limei; Sun Jianhua^*; Qi Linlin; Lei Ting

来源：Advances in Atmospheric Sciences, 2011, 28(1): 178-186.

DOI：10.1007/s00376-010-9145-9

• ATOVS radiance
• scan bias correction
• air mass bias correction
• Ensemble Kalman Filter (EnKF)
• Typhoon Prapiroon

In this paper, firstly, the bias between observed radiances from the Advanced TIROS-N Operational Vertical Sounder (ATOVS) and those simulated from a model first-guess are corrected. After bias correction, the observed minus calculated (O-B) radiances of most channels were reduced closer to zero, with peak values in each channel shifted towards zero, and the distribution of O-B closer to a Gaussian distribution than without bias correction. Secondly, ATOVS radiance data with and without bias correction are assimilated directly with an Ensemble Kalman Filter (EnKF) data assimilation system, which are then adopted as the initial fields in the forecast model T106L19 to simulate Typhoon Prapiroon (2006) during the period 2-4 August; 2006. The prediction results show that the assimilation of ATOVS radiance data with bias correction has a significant and positive impact upon the prediction of the typhoon's track and intensity, although the results are not perfect.

• 出版日期2011-1
• 单位中国人民解放军空军装备研究院雷达与电子对抗研究所; 中国海洋大学; 中国科学院大气物理研究所