Validation of coastal sea and lake surface temperature measurements derived from NOAAAVHRR.pdf

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Validation of coastal sea and lake surface temperature measurements derived from NOAAAVHRR.pdf

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Validation of coastal sea and lake surface temperature measurements derived from NOAAAVHRR

int. j. remote sensing, 2001, vol. 22, no. 7, 1285± 1303 Validation of coastal sea and lake surface temperature measurements derived from NOAA/AVHRR data X. LI2 , W. PICHEL3 , P. CLEMENTE-COLO? N3 , V. KRASNOPOLSKY§ and J. SAPPER3 2 Research and Data Systems Corporation, Room 102, E/RA3, WWBG, NOAA Science Center, 5200 Auth Road, Camp Springs, Maryland 20746-4304, USA; e-mail: xiaofeng.li@ 3 NOAA/NESDIS, Room 102, E/RA3, WWBG, 5200 Auth Road, Camp Springs, Maryland 20746-4304,USA §General Sciences Corporation, 6100 Chevy Chase Drive, Laurel, Maryland 20707, USA (Received 11 January 1999; in ? nal form 20 December 1999) Abstract. An interactive validation monitoring system is being used at the NOAA/NESDIS to validate the sea surface temperature (SST) derived from the NOAA-12 and NOAA-14 polar orbiting satellite AVHRR sensors for the NOAA CoastWatch program. In 1997, we validated the SST in coastal regions of the Gulf of Mexico, Southeast US and Northeast US and the lake surface temper- atures in the Great Lakes every other month. The in situ temperatures measured by 24 NOAA moored buoys were used as ground data. The non-linear SST (NLSST) algorithm was used for all AVHRR SST estimations except during the day in the Great Lakes where the linear multichannel SST (MCSST) algorithm was used. The buoy± satellite matchups were made within one image pixel in space (1.1 km at nadir) and ? 1 h in time. For the NOAA-12 satellite, the validation results for the three coastal regions (Gulf of Mexico, Southeast US and Northeast US) showed that the mean temper- ature diVerence between satellite and buoy surface temperature (bias) was about 0.4? C during the day and 0.2? C at night. The standard deviation was about 1.0? C. Great Lakes validation results showed a bias less than 0.3? C during the day. However, due to the early morning fog situation in the summer months in the Great Lakes region, the NLSST night algorithm yielded a fairly large bias of about 1.5? C. The same statistic