HR: 17:20h
AN: OS34A-05    [Abstracts]
TI: Global 9 km multi-satellite, multi-sensor sea surface temperatures from MODIS, AMSR-E, and TMI
AU: * Gentemann, C L
EM: gentemann@remss.com
AF: Remote Sensing Systems, 438 First St, #200 , Santa Rosa, CA 95401, United States
AU: * Gentemann, C L
EM: gentemann@remss.com
AF: University of Miami - RSMAS, 4600 Rickenbacker Cswy, Miami, FL 33149, United States
AB: Current global sea surface temperature (SST) datasets do not take full advantage of the numerous satellites and different sensors now retrieving SST. Existing operational SST products depend on a single sensor to produce global datasets. This results in a lower spatial and temporal resolution than what is possible with a multi satellite, multi sensor SST analysis. Initial efforts indicate that blending data from different sensors requires much more rigorous bias and error characterization than is necessary when only including data from a single sensor type. Therefore, creating a high-quality multi-sensor SST requires careful inter-calibration of different satellite sensors, calculation of sensor-specific observation errors that consider environmental variables, location of observation, and sensor calibration problems; and development of techniques for relating and combining measurements at different spatial resolutions and times of the day. A global daily 9 km optimally interpolated SST has been calculated from MODIS, AMSR-E and TMI SST data. Initial methodology, validation results, and future work will be discussed. This improved global daily SST should be useful for a wide range of scientific and operational activities.
UR: http:www.misst.org
DE: 4227 Diurnal, seasonal, and annual cycles (0438)
DE: 4504 Air/sea interactions (0312, 3339)
DE: 4572 Upper ocean and mixed layer processes
SC: Ocean Sciences [OS]
MN: 2007 Joint Assembly