Sensitivity of retrieved atmospheric profiles from infrared radiances to physical and statistical parameters of the data assimilation system |
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| Authors: | Louis Garand |
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| Institution: | Mteorological Service of Canada , 2121 Trans‐Canada Highway, Dorval, P. Quebec, H9P 1J3, Canada E-mail: louis.garand@ec.gc.ca |
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| Abstract: | Abstract The direct assimilation of satellite radiances is now operational in a few forecast centres, providing global temperature (T) and moisture (Q) information. The critical parameters which influence the quality of the resulting analysis are mainly the selection of channels, the respective errors of the background field and radiance observations, and the quality of the radiative transfer model. These various aspects are studied from sensitivity experiments based on 1‐D variational assimilations using the ensemble of 19 infrared channels (HIRS) of the NOAA‐14 satellite. It is shown that significant improvements in the retrievals would be obtained if the radiance observation error (measurement plus radiative transfer), currently estimated to be about equal to that of the background (in radiance units), were decreased. This could in principle be achieved by improving the forward radiative transfer model (RTM). Two RTMs suitable for radiance assimilation are compared in terms of analyzed increments, Jacobians, brightness temperature and equivalent background error. Important differences are noted for all of these interrelated measures. The existence of air‐mass dependent biases of fast radiative transfer models of the order of 1.5 K is confirmed in several channels from additional comparison with a line‐by‐line model. The importance of correctly specifying surface emissivity and the effective angle for downward calculations is demonstrated. The paper also evaluates, in some detail, the impact of uncertainties on the background error covariance matrix. The uncertainty on the skin temperature (TJ error affects mostly the retrieval of that parameter; it has a modest impact on the T and Q profiles in the low troposphere. The uncertainty on the Q‐Q elements has more impact than that on the T‐T elements. Off‐diagonal elements of the background error covariance matrix are very important as they impose smoothness and level‐to‐level consistency, especially for Q retrievals. Finally, Ts‐T correlations, often ignored, could result in significant improvements in the retrieval of temperature at low levels. Research issues are discussed in the conclusion. |
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