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Cloud characteristics and channel selection for IASI radiances in meteorologically sensitive areas
Author(s) -
Fourri'e Nadia,
Rabier Florence
Publication year - 2004
Publication title -
quarterly journal of the royal meteorological society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.744
H-Index - 143
eISSN - 1477-870X
pISSN - 0035-9009
DOI - 10.1256/qj.03.27
Subject(s) - environmental science , remote sensing , context (archaeology) , sensitivity (control systems) , advanced very high resolution radiometer , covariance matrix , pixel , robustness (evolution) , channel (broadcasting) , covariance , meteorology , computer science , algorithm , mathematics , satellite , statistics , geology , geography , physics , artificial intelligence , paleontology , computer network , biochemistry , chemistry , astronomy , electronic engineering , engineering , gene
The cloudiness in simulated Infrared Atmospheric Sounding Interferometer (IASI) pixels deduced from the Advanced Very‐High‐Resolution Radiometer (AVHRR) satellite imager is studied specifically in meteorologically sensitive areas during the Fronts and Atlantic Storm‐Track Experiment. It is found that few clear AVHRR observations are located in the IASI pixels in these regions, which are covered by high‐level and low‐level clouds. The IASI channel selection is then studied in the context of the sensitive areas for the pixels with low‐level clouds. The Entropy Reduction (ER) method, which was previously studied in a general context, is compared with two other channel selection methods using selection criteria based on adjoint sensitivity: the sensitivity to observations and the so‐called Kalman‐filter sensitivity. It is found that, even though the ‘sensitive’ methods give slightly better results than the ER one, the latter performs quite robustly and at a lower computational cost. The robustness to the specification of the background‐error covariance matrix is then studied. It is shown that channel selection based on the ER method is particularly robust to the specification of the background‐error covariance matrix, but the analysis step itself requires an accurate determination of the background‐error covariance matrix. In addition it is shown that an independently computed constant channel set gives comparable results to the optimal channel set. Copyright © 2004 Royal Meteorological Society.