This is the first 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/Lönnberg 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 three Advanced TIROS Operational Vertical Sounder (ATOVS) instruments: the Advanced Microwave Sounding Unit (AMSU)-A, High-Resolution Infrared Radiation Sounder (HIRS) and Microwave Humidity Sounder (MHS).
The findings suggest that all AMSU-A sounding channels show little or no interchannel or spatial observation-error correlations, except for surface-sensitive channels over land. Estimates for the observation error are mostly close to the instrument noise. In contrast, HIRS temperature-sounding channels exhibit some interchannel error correlations, and these are stronger for surface-sensitive channels. There are also indications for stronger spatial-error correlations for the HIRS short-wave channels. There is good agreement between the estimates from the three methods for temperature-sounding channels.
Estimating observation errors for humidity-sounding channels of MHS and HIRS appears more difficult. A considerable proportion of the observation error for humidity-sounding channels appears 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.
Observation error estimates from this study are consistently lower than those assumed in the ECMWF assimilation system. As error correlations are small for AMSU-A, the study suggests that the current use of AMSU-A data in the ECMWF system in terms of observation-error or thinning-scale choices is fairly conservative. Copyright © 2010 Royal Meteorological Society