|Title||An evaluation of radiative transfer modelling errors in AMSU-A data|
|Year of Publication||2016|
|Authors||Lupu, C, Geer, AJ, Bormann, N, English, S|
|Secondary Title||Technical Memorandum|
Systematic biases are observed between AMSU-A observations and simulations from numerical weather prediction models. They are not just a simple offset but instead exhibit a complex global pattern that appears to be related to the temperature profile. These errors could arise from inaccuracies in the radiative transfer model calculations used to simulate AMSU-A radiances from the model fields, from poorly-characterised aspects of the instrument calibration and spectral response function, or from errors in the forecast model state. Two hypotheses to explain and model the biases in AMSU-A are examined in this work. First, the optical depth of the atmosphere may not be sufficiently well-modelled due to unknown systematic errors in the the radiative transfer model. In order to correct this, an empirically-derived multiplicative scaling can be applied to the simulated optical depths (the so-called gamma-correction). Second, the reported locations of AMSU-A passbands may be incorrect, with empirically-derived corrections of up to 68 MHz having been suggested. Corrections to the radiative transfer modelling based on these hypotheses have been tested in the ECMWF data assimilation system and evaluated in terms of first-guess departure fits to independent observations and forecast scores, or in terms of residual biases to the AMSU-A data itself.