Estimation of satellite observations bias correction for limited area model

Assimilation of satellite radiances requires systematic bias correction. Biases are mainly from instrument characteristics, inaccuracies of the radiative transfer model and of the assimilating model and also in the observation preprocessing. Accurate bias correction methods have been worked out for the assimilation of satellite radiances in global models. Bias correction computed with global models comprises synoptic situations and different seasonal conditions (summer and winter hemispheres). Question arises when estimating the bias correction for a limited area model (LAM) regarding the period of computation to have the "most representative" bias characteristics. Our previous study showed that bias correction characteristics estimated using the global model could not guaranty stable positive impact in a LAM. This paper investigates the impact of different predictors and different periods in the computation of the bias correction characteristics for a LAM assimilation system.