Abstract
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.
Highlights
Sea surface temperature (SST), one of the ten ocean surface essential climate variables (ECVs) [1], is measured from satellite-borne sensors in both the microwave portion of the electromagnetic spectrum and the infrared portion of the spectrum
A simple AMSR-E footprint was used to generate simulated microwave measurements from 250,000 real high-resolution moderate-resolution imaging spectroradiometer (MODIS) patches according to Equation (3)
Microwave measurements were simulated with Equation (3), using MODIS data as the ground truth, to which we added Gaussian white noise with a standard-deviation of 0.2 K. 0.05 K Gaussian white noise was added to the MODIS data in order to simulate the infrared instrument noise; i.e., the original MODIS field was taken as the true SST field and the simulated AMSR-E and MODIS fields were obtained from the ‘true’ field
Summary
Sea surface temperature (SST), one of the ten ocean surface essential climate variables (ECVs) [1], is measured from satellite-borne sensors in both the microwave portion of the electromagnetic spectrum and the infrared portion of the spectrum. The downside of microwave SST retrievals is that to achieve a reasonable accuracy, the sensor must sample a large area—the spatial resolution of these fields is generally quite coarse, O (60 km). Another important characteristic of SST fields derived from extant microwave sensors is the large overlap in pixels. As will be discussed below (Section 2.1) the sensors of interest sample approximately every 10 km in both the along- and across-track directions, while the radiometer footprint is O (45 × 75 km) These two characteristics of microwave SST retrievals, large pixel size and significant overlap in adjacent pixels, lead to some interesting problems/possibilities, one related to instrument-to-instrument comparisons and the other to enhanced resolution of the microwave SST field
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