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An innovative physical scheme to retrieve simultaneously surface temperature and emissivities using high spectral infrared observations from IASI

Paul M., Aires F., Prigent C., Trigo I.F., Bernardo F.
Journal Geophysycal Research, 117, D11302

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Abstract

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 1.7 K on average over bands 1 and 2 of the IASI spectrum), as compared to calculations using the first guess information (root mean square error of 3.5 K). The retrieved surface skin temperatures are compared to the Land Surface Analysis Satellite Applications Facility (LSA SAF) estimates derived from Spinning Enhanced Visible and Infrared Imager (SEVIRI) measurements, and the root mean square difference is below 2 K.