16th Conference on Satellite Meteorology and Oceanography
Fifth Annual Symposium on Future Operational Environmental Satellite Systems- NPOESS and GOES-R


Combined MODIS / AMSR-E composite SST data for regional weather applications

Gary J. Jedlovec, NASA/MSFC, Huntsville, AL; and J. Vazquez, E. Armstrong, and S. L. Haines

Recent applications of a high resolution MODIS composite SST product have clearly shown the importance of developing high-resolution SST data sets for coastal applications and modeling. In general, coupling between the oceans and atmospheres has been closely linked to SST gradients and fronts, indicating a need for high resolution SSTs, specifically in the areas of large gradients associated with coastal regions. Thus an accurate determination of SST gradients has become critical for determining the appropriate air-sea coupling and the influence on ocean modeling. Recent research is focused on improving the accuracy and spatial coverage of the current operational MODIS SST composite product provided by the Short-term Prediction Research and Transition (SPoRT) project and distributed to the community. GHRSST-PP MODIS data and microwave AMSR-E data are being combined to produce composite data sets for both the West Coast and East Coast of the United States, including the Gulf of Mexico. The use of 1 km MODIS data has explicit advantages over other SST products including its global coverage and high resolution. The AMSR-E data will reduce the latency of the composites. A strategy for utilizing the error characteristics contained in the GHRSST data has been developed. This strategy will include using the error characteristics directly to calculate weights in the SST composites, uncertainty maps based on the composite biases and RMS errors, and latency products calculated in the compositing process. Recent accomplishments include the development of an enhanced compositing approach based on the error-weighted combination of recent clear MODIS SST values, where the error contributions come from measurement error, potential cloud contamination, and data latency sources. Future plans call for the inclusion of AMSR-E SST values with appropriate weights based upon measurement accuracy, MODIS-AMSR-E SST bias, and latency.

extended abstract  Extended Abstract (200K)

Joint Poster Session 8, Operational Products and Transition from Research to Operations
Wednesday, 14 January 2009, 2:30 PM-4:00 PM, Hall 5

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