An extended observation operator in HIRLAM 4D‐VAR for the assimilation of cloud‐affected satellite radiances

• Published in: Quarterly journal of the Royal Meteorological Society 2010-04, Vol.136 (649), p.1064-1074
• Main Authors: Stengel, M., Lindskog, M., Undén, P., Gustafsson, N., Bennartz, R.
• Format: Article
• Language: English
• Subjects: Assimilation; cloud scheme; Clouds; cloudy radiances; Earth, ocean, space; Exact sciences and technology; External geophysics; Infrared; limited‐area NWP model; Mathematical models; Meteorology; Moisture; Operators; Physics of the high neutral atmosphere; Satellite observation; Satellites; Weather analysis and prediction
• ISSN: 0035-9009; 1477-870X; 1477-870X
• DOI: 10.1002/qj.621

An extended observation operator for the direct assimilation of cloud‐affected infrared satellite radiances in the High Resolution Limited Area Model (HIRLAM) is examined. The operator includes a simplified moist‐physics scheme, which enables the diagnosis of cloudiness in itself using background values of temperature, moisture and surface pressure. Subsequently, a radiative transfer model provides simulated cloud‐affected radiances to be used as background equivalents to the satellite observations. The observation operator was evaluated by using infrared observations measured by the Spinning Enhanced Visible and Infrared Imager (SEVIRI). An observation‐screening procedure, which incorporates SEVIRI cloud‐retrieval products, supports an improved selection of usable cloudy scenes, leading to good agreement between the observations and background equivalents. The tangent‐linear observation operator was verified against finite differences from its nonlinear formulation. The increments revealed a near‐linear behaviour for the selected channels for a large number of cases. The adjoint observation operator was used to derive brightness‐temperature sensitivities with respect to temperature and moisture changes in the presence of radiance‐affecting clouds. Differences from the clear‐sky sensitivities were found in and below clouds. In a four‐dimensional variational data assimilation experiment, cloud‐affected SEVIRI observations were assimilated, resulting in additional increments in both moisture and wind fields. The corresponding analysis fields revealed a reduced deviation from the observations for the majority of all cloudy scenes and a reduced bias for wind and temperature in the upper troposphere against independent radiosonde observations. Overall, our results highlight the capability of this observation operator in the HIRLAM assimilation system and encourage its application for the extended usage of cloudy satellite observations in numerical weather prediction. Copyright © 2010 Royal Meteorological Society