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International LST and Emissivity Group

The International Land Surface Temperature and Emissivity Working Group (ILSTE-WG) aims to provide advice and recommendations to the wider scientific and user communities on the best practices for retrieval, validation and exploitation of Land Surface Temperature (LST), Ice Surface Temperature (IST), Lake Surface Water Temperature (LSWT), and Land Surface Emissivity (LSE).

Authors: C. Jimenez, C. Prigent, S. Ermida and J.-L. Moncet


Inversions of the Earth observation satellite (EOS) Advanced Microwave Scanning Radiometer (AMSR-E) brightness temperatures (Tbs) to derive the land surface temperature (Ts) are presented based on building a global transfer function by neural networks trained with AMSR-E Tbs and retrieved microwave Ts. The only required inputs are the Tbs and monthly climatological emissivities, minimizing the dependence on ancillary data. The inversions are accompanied by a coarse estimation of retrieval uncertainty, an estimate of the quality of the retrieval, and a series of flags to signal difficult inversion situations. For 75% of the land surface the Root Mean Square Difference (RMSD) between the training target Ts and the neural network retrieved Ts is below 2.8 K. The RMSD when comparing with the Moderate Resolution Imaging Spectroradiometer (MODIS) clear-sky Ts is below 3.9 K for the same conditions. Over 10 ground stations, AMSR-E and MODIS Ts were compared with the in situ data. Overall, MODIS agrees better with the station Ts than AMSR-E (all-station mean RMSD of 2.4 K for MODIS and 4.0 for AMSR-E), but AMSR-E provides a larger number of Ts estimates by being able to measure under cloudy conditions, with an approximated ratio of 3 to 1 over the analyzed stations. At many stations the RMSD of the AMSR-E clear and cloudy-sky are comparable, highlighting the ability of the microwave inversions to provide Ts under most atmospheric conditions. Closest agreement with the in situTs happens for stations with dense vegetation, where AMSR-E emissivity is less varying.



Example of AMSR-E retrieved surface temperature for the 2nd of February, May, August, and November, 2008. The nighttime overpass retrieval is given in left column, the daytime overpass in the right. The gaps over land correspond to areas where there are no AMSR-E data available for the inversions; most of them are due to the AMSR-E swath, but missing portion of orbits are also visible during the night.


Link to the paper

Jimenez C., C. Prigent, S. Ermida, and J.-L. Moncet (2017), Inversion of AMSR-E observations for land surface temperature estimation - Part 1: Methodology and evaluation with station temperature, J. Geophys. Res., 122, doi:10.1002/2016JD026144.