Abstract

This article is the second part of a two-part article that uses three methods to estimate observation errors and their correlations for clear-sky sounder radiances used in the European Centre for Medium-Range Weather Forecasts (ECMWF) assimilation system. The analysis is based on covariances derived from pairs of first-guess and analysis departures. The methods used are the so-called Hollingsworth/Lonnberg method, a method based on subtracting a scaled version of mapped assumed background errors from first-guess departure covariances and the Desroziers diagnostic. The present article reports the results for the high-spectral-resolution Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI). The findings suggest that mid-tropospheric to stratospheric temperature-sounding channels for AIRS and IASI show little or no interchannel or spatial observation-error correlations, and estimates for the observation error are close to the instrument noise. Channels with stronger sensitivity to the surface show larger observation errors compared with the instrument noise, and some of this error is correlated spatially and between channels. Short-wave temperature-sounding channels also appear more prone to spatial observation-error correlations. The three methods show good consistency for these estimates. Estimation of observation errors for humidity-sounding channels appears more difficult. A considerable proportion of the observation error for humidity-sounding channels appears to be correlated spatially for short separation distances, as well as between channels. Observation-error estimates for humidity channels are generally considerably larger than the instrument noise. An analysis of departure statistics and observation-error correlations by scan position and scan-line difference for IASI shows a pattern that correlates with the direction of the movement of IASI's corner cube mirror. The effect is very small and most likely linked to micro-vibrations of IASI's beam-splitter. The statistics also provide information on the assumed background errors. There are indications that the assumed background errors for tropospheric temperature are inflated (by about 30– 60%), whereas there is little indication for background-error inflation for stratospheric temperatures. Copyright © 2010 Royal Meteorological Society

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