Operational estimation of land surface temperature, emissivity and atmospheric temperature and moisture profiles from IASI infrared radiances

Abstract

An operational statistical method suitable for nearly real-time estimate of land surface and atmospheric parameters was developed and applied to the Infrared Atmospheric Sounding Interferometer (IASI) observations. The proposed method utilized three steps to solve the ill-posed problems and to stabilize the solution in a fast speed regression manner: 1) the atmospheric profiles and land surface emissivity spectra were expressed by their eigenvectors to reduce the number of unknowns; 2) a ridge regression procedure was introduced to improve the conditioning of the problem and to lessen the influence of noises; 3) a set of optimal channels was selected to decrease the effect of forward model errors or uncertainties of trace gases, and to increase computational efficiency. The retrieval results using the independent simulated data indicate the proposed method is promising. The root mean squared error (RMSE) of land surface temperature is 3.5 K, the RMSE of land surface emissivity at the selected channels is 0.01, and the RMSE of atmospheric temperature and moisture profile are about 2.0K and 0.001g/g, respectively.