Application of nonlinear multi-channel algorithms for estimating sea surface temperature with NOAA-14 AVHRR data |
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Authors: | Li Xiao-feng |
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Institution: | (1) NOAA Science Center, 20746 Camp Springs, MD, USA |
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Abstract: | NOAA global operational NOAA/AVHRR Nonlinear Sea Surface Temperature (NLSST) retrieval algorithms were used to generate Global
Area Coverage (GAC) sea surface temperature (SST) measurements in the global ocean in 1998. The accuracy of SST retrieved
from daytime split window NLSST algorithm and nighttime triple window NLSST algorithm for NOAA-14 AVHRR data was investigated
in this study. A matchup dataset of drifting buoys and NOAA-14 satellite measurements in the global ocean was generated to
validate these operational split window and triple window algorithms For NOAA-14 in 1998, we had 14095 and 22643 satellite
and buoy matchups that matched within 25 km and 4 hours for daytime, respectively. The satellite derived SST had a bias of
less than 0.1°C and standard deviation of about 0.5°C. This study also showed that the NLSST algorithm provided the same order
of SST accuracy in different time of the year and under a wide range of satellite zenith angle and water vapor represented
by the channel 4 and 5 brightness temperature difference. Therefore NLSST algorithms are usually independent of season, geographic
location, or atmospheric moisture content. Comparison between the low resolution AVHRR GAC data accuracy and high resolution
Local Area Coverage (LAC) data accuracy is also discussed.
Project 49576281 supported by NSFC, and also supported by NOAA Coastwatch Program. |
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Keywords: | sea surface temperature (SST) NOAA/AVHRR nonlinear SST algorithm |
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