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Open AccessArticle

Determining the AMSR-E SST Footprint from Co-Located MODIS SSTs

1
Graduate School of Oceanography, University of Rhode Island, 215 South Ferry Road, Narragansett, RI 02882, USA
2
Department of Computer Science and Statistics, University of Rhode Island, 9 Greenhouse Road, Suite 2, Kingston, RI 02881, USA
3
Earth and Space Research, Seattle, WA 98121, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(6), 715; https://doi.org/10.3390/rs11060715
Received: 19 February 2019 / Revised: 10 March 2019 / Accepted: 21 March 2019 / Published: 25 March 2019
(This article belongs to the Collection Sea Surface Temperature Retrievals from Remote Sensing)
This study was undertaken to derive and analyze the advanced microwave scanning radiometer-Earth observing satellite (EOS) (AMSR-E) sea surface temperature (SST) footprint associated with the remote sensing systems (RSS) level-2 (L2) product. The footprint, in this case, is characterized by the weight attributed to each 4 × 4 km square contributing to the SST value of a given (AMSR-E) pixel. High-resolution L2 SST fields obtained from the moderate-resolution imaging spectroradiometer (MODIS), carried on the same spacecraft as AMSR-E, are used as the sub-resolution “ground truth” from which the AMSR-E footprint is determined. Mathematically, the approach is equivalent to a linear inversion problem, and its solution is pursued by means of a constrained least square approximation based on the bootstrap sampling procedure. The method yielded an elliptic-like Gaussian kernel with an aspect ratio ≈1.58, very close to the AMSR-E 6.93 GHz channel aspect ratio, ≈1.74. (The 6.93 GHz channel is the primary spectral frequency used to determine SST.) The semi-major axis of the estimated footprint is found to be aligned with the instantaneous field-of-view of the sensor as expected from the geometric characteristics of AMSR-E. Footprints were also analyzed year-by-year and as a function of latitude and found to be stable—no dependence on latitude or on time. Precise knowledge of the footprint is central for any satellite-derived product characterization and, in particular, for efforts to deconvolve the heavily oversampled AMSR-E SST fields and for studies devoted to product validation and comparison. A preliminary analysis suggests that use of the derived footprint will reduce the variance between AMSR-E and MODIS fields compared to the results obtained ignoring the shape and size of the footprint as has been the practice in such comparisons to date. View Full-Text
Keywords: SST; AMSR-E; MODIS; footprint; constrained least square; bootstrap SST; AMSR-E; MODIS; footprint; constrained least square; bootstrap
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MDPI and ACS Style

Boussidi, B.; Cornillon, P.; Puggioni, G.; Gentemann, C. Determining the AMSR-E SST Footprint from Co-Located MODIS SSTs. Remote Sens. 2019, 11, 715.

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