Assimilating AMSU-a radiances with the NICAM-LETKF

Abstract

An observation operator to assimilate satellite radiances with the non-hydrostatic icosahedral atmospheric model (NICAM)-based local ensemble transform Kalman filter (LETKF) is newly developed using the radiative transfer for the TIROS Operational Vertical Sounder (RTTOV, version 11.1). Here we assimilate the Advanced Microwave Sounding Unit-A (AMSU-A) brightness temperature observations that are known to bring a large improvement to global numerical weather prediction. We apply the online estimation of bias correction for both airmass and scan biases, or the biases originating from the atmospheric state and scan position. Comparing the two experiments with and without the AMSU-A radiances, we find that the adaptive bias correction methods work appropriately, and that the analysis is significantly improved by assimilating the AMSU-A radiances. This is an important step toward assimilating different types of satellite radiances with NICAM-LETKF.