Inversion of AMSR‐E observations for land surface temperature estimation: 1. Methodology and evaluation with station temperature. Issue 6 (29th March 2017)

• Record Type: Journal Article
• Authors: Jiménez, C.; Prigent, C.; Ermida, S. L.; Moncet, J.‐L.
• Is Part Of: Journal of geophysical research. Volume 122:Issue 6(2017)
• Page Start: 3330
• Page End: 3347
• Publication Date: 2017-03-29
• Subjects: land surface temperature -- microwaves; Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1002/2016JD026144
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: Inversions of the Earth Observation Satellite (EOS) Advanced Microwave Scanning Radiometer (AMSR‐E) brightness temperatures ( T bs ) to derive the land surface temperature ( T s ) are presented based on building a global transfer function by neural networks trained with AMSR‐E T bs and retrieved microwave T s *. The only required inputs are the T bs 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 T s * and the neural network retrieved T s is below 2.8 K. The RMSD when comparing with the Moderate Resolution Imaging Spectroradiometer (MODIS) clear‐sky T s is below 3.9 K for the same conditions. Over 10 ground stations, AMSR‐E and MODIS T s were compared with the in situ data. Overall, MODIS agrees better with the station T s 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 T s 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 T s under most atmospheric conditions. Closest agreement with the in situ T s happens for stations with dense vegetation, where AMSR‐E emissivity is less varying. Key Points: Development of a land surface temperature ( T s ) product from AMSR‐E observations Evaluation at ground stations together with MODIS infrared T s to highlight issues and difficulties of the inversions Overall, MODIS agrees better with the station T s, but AMSR‐E can provide 3 times more estimates