Monday, 10 July 2006
Grand Terrace (Monona Terrace Community and Convention Center)
Paul W. Stackhouse Jr., NASA/LaRC, Hampton, VA; and D. P. Kratz, G. R. McGarragh, S. K. Gupta, and E. B. Geier
Handout
(2.9 MB)
The Clouds and the Earth's Radiant Energy System (CERES) project is currently producing world-class climate data products derived from measurements taken aboard Terra and Aqua spacecraft. While of exceptional fidelity, these data products require a considerable amount of processing to assure quality and verify accuracy and precision. The result is, CERES data is typically released many months after acquisition of the initial measurements. For climate studies, such delays are of little consequence especially considering the improved quality of the released data products. There are, however, many uses for the CERES data products on a near real-time basis. These include CERES instrument calibration and subsystem quality checks, CloudSat operations, seasonal predictions, land and ocean assimilations, support of field campaigns, outreach programs such as S'COOL and application projects for agriculture and energy industries. The FLASHFlux project was envisioned as a conduit whereby CERES data could be provided to the community within a week of the initial measurements, with the trade-off that some degree of fidelity would be sacrificed to gain speed.
In this presentation, we will report on some very encouraging initial results from the FLASHFlux project in which we compared the FLASHFlux instantaneous surface fluxes to the CERES surface-only flux algorithm data products. Overpass products from Terra and Aqua containing cloud, aerosol, surface and radiative flux products (Top-of-atmosphere and surface) are now being produced operationally and are in being used as described above. By the time of this presentation, the FLASHflux project will produce global gridded daily averaged flux products, initially with a 1° X 1° resolution, using a simplified time and space averaging algorithm that blends both Terra and Aqua results. Ultimately, it is planned to blend geosynchronous observations into these time and space averaging algorithms.
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