objective is to provide a good estimate of the microwave surface emissivity to improve the retrieval of atmospheric profiles or the direct assimilation of radiances in numerical weather prediction (NWP) models using microwave sounder data over land. TELSEM provides emissivity estimates and error-covariance matrices for all land surfaces between 19 and 100 GHz and for all angles and linear polarizations. It is based on a pre-calculated monthly-mean emissivity climatology derived from Special Sensor Microwave/Imager (SSM/I) observations. Results show that when TELSEM is used, radiative-transfer simulations are closer to real observations. This is important when RTTOV is used to generate simulated datasets, to analyze new instrument concepts or for assimilation schemes. Experiments also show that TELSEM can be applied to provide a first guess for the surface emissivity down to 6 GHz and up to 190 GHz (extrapolating the SSM/I emissivities). These emissivities are essential for atmospheric profile retrievals over land: results for water-vapour retrieval show that surface-contaminated channels can be utilized and that the retrieval is improved, in particular for the lower troposphere. Furthermore, TELSEM emissivity first guesses can be improved in emissivity-retrieval schemes.

.[1] In this paper, synergy refers to a process where the use of multiple satellite observations makes the retrieval more precise than the best individual retrieval. Two general strategies can be used in order to use multi-wavelength observations in an inversion scheme. First, the multi-wavelength observations are merged in the input of the retrieval scheme. This means that the various satellite observations are used simultaneously and that their possible interactions can be exploited by the retrieval scheme. Second, each multi-wavelength observations are used independently to retrieve a same geophysical variable and then, these independent retrievals are combined a posteriori using for example a simple weighted averaging. In this paper, it is shown that the first approach provides better synergy results: The retrieval is better suited to optimize the use of all the information available because they are provided to the algorithm simultaneously. In particular, the retrieval process is able, in this case, to exploit the possible interactions between the various input information. The two retrieval approaches are tested and compared using an application for the retrieval of atmospheric profiles and integrated column quantities (temperature, water vapor, and ozone) using MetOp-A observations from IASI, AMSU-A and MHS instruments. Although real satellite observations are considered in this analysis, the results are dependent on the correlation structure in the training data set (i.e. ECMWF analysis) used to calibrate the retrieval algorithm. However, it can be seen that the infrared and microwave observations have a good synergy for the retrieval of atmospheric temperature, water vapor, and for ozone thanks to an indirect synergy.Citation: Aires, F., O. Aznay, C. Prigent, M. Paul, and F. Bernardo (2012), Synergistic multi-wavelength remote sensing versus a posteriori combination of retrieved products: Application for the retrieval of atmospheric profiles using MetOp-A, J. Geophys.

[1] Retrieving atmospheric temperature and water vapor profiles from infrared satellite observations over continental surfaces is a complex problem because of the heterogeneity of land surfaces and the difficulty of modeling their interaction with the radiation. This results in the surface-sensitive observations from sounding instruments over land usually not being assimilated into numerical prediction systems at meteorological operational centers. Correct characterization of the interaction between the atmosphere and the surface would allow considering the information contained in those channels. This requires accurate estimates of the surface emissivities at the spectral resolution of recent instruments such as Infrared Atmospheric Sounding Interferometer (IASI) or Atmospheric Infrared Sounder (AIRS). An emissivity interpolator is developed in this study to estimate the land surface emissivities at a high spectral resolution compatible with IASI or AIRS instrument channels. It is based on Moderate Resolution Imaging Spectroradiometer (MODIS) retrieved emissivities. This surface emissivity is used as a first guess in an innovative surface parameter inversion scheme that simultaneously retrieves the surface emissivity and temperature. Radiative transfer calculations with the resulting surface information show a significantly better agreement with the observations (root mean square error of