Validation of the remotely sensed nighttime sea surface temperature in the shallow waters at the Dongsha Atoll

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2017-06
Authors
Pan, Xiaoju
Wong, George T. F.
DeCarlo, Thomas M.
Tai, Jen-Hua
Cohen, Anne L.
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10.3319/TAO.2017.03.30.01
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Sea surface temperature
Validation
Remote sensing
Dongsha Atoll
Shallow waters
Calibration
Abstract
Fine scale temperature structures, which are commonly found in the top few meters of shallow water columns, may result in deviations of the remotely sensed night-time sea surface temperatures (SST) by the MODIS-Aqua sensor (SSTsat) from the bulk sea surface temperatures (SSTbulk) that they purport to represent. The discrepancies between SSTsat and SSTbulk recorded by temperature loggers at eight stations with bottom depths of 2 - 20 m around the Dongsha Atoll (DSA) between June 2013 and May 2015 were examined. The SSTsat had an average cool bias error of -0.43 ± 0.59°C. The bias error was larger in the warmer (> 26°C) waters which were presumably more strongly stratified. The root mean square error (RMSE) between SSTsat and SSTbulk, ±0.73°C, was 25% larger than that reported in the open northern South China Sea. An operational calibration algorithm was developed to increase the accuracy in the estimation of SSTbulk from SSTsat. In addition to removing the cool bias error, this algorithm also reduced the RMSE to virtually the same level as that found in the open northern South China Sea. With the application of the algorithm, in June 2015, the average SST in the lagoon of the DSA was raised by about 0.5°C to 31.1 ± 0.4°C, and the area of lagoon with SSTbulk above 31°C, the median value of the physiological temperature threshold of reef organisms, was increased by 69% to about three quarters of the lagoon.
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© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Terrestrial, Atmospheric and Oceanic Sciences 28 (2017): 517-524, doi:10.3319/TAO.2017.03.30.01.
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Terrestrial, Atmospheric and Oceanic Sciences 28 (2017): 517-524
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