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Keywords:

  • IASI;
  • microphysical variables;
  • 1D-Var;
  • DFS;
  • channel selection;
  • Mediterranean Sea

Abstract

The Infrared Atmospheric Sounding Interferometer (IASI) provides 8461 channels in the infrared spectrum. In current numerical weather prediction (NWP) models, it is not feasible to assimilate all channels and it is known that the information content between adjacent channels is redundant. This issue has been addressed in NWP centres by employing a channel selection strategy. The goal of this article is to add new channels to the existing IASI operational channel selection, aimed at improving the data assimilation in cloudy conditions and the simultaneous retrieval of cloud microphysical variables, specifically liquid and ice water contents. Cloudy profiles from the French convective-scale model Applications of Research to Operations at MEsoscale (AROME) are used in the study to focus on the retrieval of cloud variables over the Mediterranean region. Three channel selection methodologies were evaluated in this study: a statistical approach based on the degrees of freedom of the signal (DFS), a physical method based on the channel spectral sensitivity to the cloud variables and a random selection. To validate the new selections, an idealized framework is used with observing system simulation experiments (OSSE) in the context of one-dimensional variational retrievals. The current operational IASI selection has already been shown to provide good retrievals of cloud variables. However, all the different channel selections improve the results with small differences in the 1D-Var retrievals. Based on the physical and DFS methods, the final sets of 134 channels sensitive to cloud variables are proposed for future investigation in operational implementation. Additional tests on temperature and water-vapour retrieval results, air-mass dependence and cloud microphysical parametrization have also been conducted.