학술논문
A Multivariate Regression Approach to Adjust AATSR Sea Surface Temperature to In Situ Measurements
Document Type
Periodical
Author
Source
IEEE Geoscience and Remote Sensing Letters IEEE Geosci. Remote Sensing Lett. Geoscience and Remote Sensing Letters, IEEE. 6(1):8-12 Jan, 2009
Subject
Language
ISSN
1545-598X
1558-0571
1558-0571
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%).