|Title||Optimal flow-dependent selection of channels from advanced sounders in the presence of cloud|
|Year of Publication||2014|
|Secondary Title||Technical Memorandum|
|Type of Work||Technical Memorandum|
This study aims to illustrate a general procedure based on well-known information theory concepts to select the channels from advanced satellite sounders which it is most advantageous to assimilate in all-sky conditions i.e., both in clear sky and in the presence of cloud using a flow-dependent estimate of forecast uncertainty. To this end, the standard iterative channel selection method, which is used to select the most informative channels from advanced infrared sounders for operational assimilation, was revisited so as to allow its use with measurements that have correlated errors. The method is here applied to determine a small set (namely, 24) relatively to a total of 8461 channels that are available on the Infrared Atmospheric Sounding Interferometer (IASI) on board the EUMETSAT Polar System Metop satellites of humidity-sensitive channels, which can be used to perform all-sky data assimilation experiments, in addition to those currently used for operational data assimilation of IASI data at ECMWF. Care was taken to use in the channel selection procedure a realistic specification of forecast error uncertainty, which was determined from an ensemble of data assimilation (EDA) forecast fields for a case study in July 2012. Also, (cumulative) weighting functions that provide a vertically-resolved picture of the (total) number of degrees of freedom for signal expressed by a given set of measurements were introduced, which allow us to define a novel channel selection merit function that can be used to select measurements that are most sensitive to variations of a given parameter over a given atmospheric region (e.g., in the troposphere).