A Multivariate Regression Approach to Adjust AATSR Sea Surface Temperature to In Situ Measurements

Type Article
Date 2009
Language English
Author(s) Tandeo Pierre1, Autret Emmanuelle1, Piolle Jean-Francois1, Tournadre Jean1, Ailliot Pierre2
Affiliation(s) 1 : IFREMER, Lab Oceanog Spatiale, F-29280 Plouzane, France.
2 : Univ Bretagne Occidentale, Dept Math, F-29200 Brest, France.
Source IEEE Geoscience and Remote Sensing Letters (1545-598X) (IEEE), 2009 , Vol. 6 , N. 1 , P. 8-12
DOI 10.1109/LGRS.2008.2006568
WOS© Times Cited 4
Keyword(s) Validation, Sea surface temperature (SST), Remote sensing, Advanced Along Track Scanning Radiometer (AATSR)
Abstract The Advanced Along-Track Scanning Radiometer (AATSR) onboard Envisat is designed to provide very accurate measurements of sea surface temperature (SST). Using colocated in situ drifting buoys, a dynamical matchup database (MDB) is used to assess the AATSR-derived SST products more precisely. SST biases are then computed. Currently, Medspiration AATSR SST biases are discrete values and can introduce artificial discontinuities in AATSR level-2 SST fields. The new AATSR SST biases presented in this letter are continuous. They are computed, for nighttime and best proximity confidence data, by linear regression with different MDB covariables (wind speed, latitude, aerosol optical depth, etc.). As found, the difference between dual-view and nadir-only SST products explains most of the variability (26%).
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