Paper
19 May 2015 A deterministic inversion technique for sea surface temperature retrieval from MODIS radiances
Prabhat K. Koner, Andy Harris
Author Affiliations +
Abstract
The MODIS advanced sensor contains 16 channels in the thermal infrared band, makes it an attractive instrument for atmospheric and oceanic sciences. Even for satellite-derived sea surface temperature (SST) retrievals, the dynamics of atmospheric conditions are intended to be characterized by the satellite measurement sufficiently to retrieve good quality SST. The Group for High Resolution SST (GHRSST), which is an international scientific body, provides MODIS SST to date using only two and/or three channels by employing regression method. The few coefficients used in regression based retrieval methods are unable to compensate for wide atmospheric variability and as a result, significant errors are embedded in the retrieved SST. We will demonstrate in this work that the MODIS SST can be retrieved with approximately double the accuracy compared GHRSST operational SST, by using more channels and our physical deterministic-based modified total least squares (MTLS) method. This study also includes the SST4/NLSST and optimal estimation based SST retrieval for comparison purposes. The information content and noise analysis of these retrievals, and the retrieval error due to the quality of cloud detection is discussed.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Prabhat K. Koner and Andy Harris "A deterministic inversion technique for sea surface temperature retrieval from MODIS radiances", Proc. SPIE 9459, Ocean Sensing and Monitoring VII, 94590Y (19 May 2015); https://doi.org/10.1117/12.2179868
Lens.org Logo
CITATIONS
Cited by 5 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Clouds

MODIS

Error analysis

Satellites

Atmospheric modeling

Data modeling

Aerosols

Back to Top