NOAA/NESDIS is responsible for developing and maintaining operational environmental satellite data products. To provide long-term data continuity, ORAD sustains and enhances the current POES and GOES IR SST products, including the NOAA-16, -17 Advanced Very High Resolution Radiometer (AVHRR/3) MCSST, NLSST, aerosol corrected SST (ACSST), and the GOES-9/10/12 SST. To better serve the user community, ORAD also works to develop and implement improved SST operational products that meet user requirements in terms of absolute accuracy, precision, geographic coverage, and sampling resolution (spatial and temporal) in near real-time. This work includes new IR radiative transfer model (RTM) based retrieval algorithms for both current and future sensors. RTM based retrievals provide a means for more rigorous, systematic and accurate products. Among these new products are the GOES-10/12 SST that have been implemented recently into NOAA operations. Because the GOES/M-Q series are specified without split-window (11-12 micron) capability, the GOES-12 RTM algorithms are the first of their kind to rely upon the 3.9 micron short-wave IR channel over sunlit portions of the Earth disk. SSTs derived from geostationary satellites benefit from enhanced temporal sampling frequency. While IR-based retrieval algorithms have the advantage of maximum signal at high spatial resolution, microwave (MW) based retrievals have recently gained more attention because of their insensitivity to atmospheric water vapor, clouds and aerosol. An experimental MW algorithm has been developed for TRMM Microwave Imager (TMI), while a similar algorithm is being developed for the improved WindSat instrument. Ultimately, ORAD’s goal will be to develop and implement multi-platform, optimally blended SST products that are able to incorporate the strengths of IR, MW, geostationary and polar orbiting observing systems.
NOAA/NESDIS is also actively engaged in the reprocessing of historical satellite data with the objective of assembling satellite-derived climatologies. Satellite SST climatologies are available based upon the AVHRR Pathfinder Atmospheres (PATMOS) and Oceans Pathfinder data sets. However, known shortcomings of the AVHRR Pathfinder data sets necessitate additional iterations to derive an SST climatology with optimal accuracy. Such a reprocessing effort is entering the execution phase within ORA, as well as plans to reprocess GOES data back through 1994.
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