Thursday, 13 July 2006: 10:30 AM
Hall of Ideas G-J (Monona Terrace Community and Convention Center)
Stephen J. Cox, SSAI, Hampton, VA; and P. W. Stackhouse Jr., S. K. Gupta, J. C. Mikovitz, T. Zhang, L. M. Hinkelman, M. Wild, and A. Ohmura
Presentation PDF
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Quantifying the interaction of solar (or shortwave) and terrestrial (or longwave) radiation with the Earth's surface is of vital importance in understanding the climate system. The NASA/GEWEX (Global Energy and Water Cycle) Surface Radiation Budget (SRB) project provides estimates of surface fluxes on a 1 degree by 1 degree grid, for the period July 1983 through December 2004. Input information comes from satellite and assimilation products. Water vapor and temperature profiles are from the Goddard Earth Observing System version 4.0.3 (GEOS-4) long-term meteorological assimilation. Surface and cloud radiances and cloud retrievals are computed from ISCCP-DX. Column ozone is computed from TOMS and TOVS. The flux data sets are derived from primary algorithms that provide a more explicit treatment of the atmospheric and surface properties and secondary algorithms that contain parameterization for these processes. Estimates of the Top of Atmosphere fluxes (TOA) are provided with the primary algorithms. This data set is a major contributor to the GEWEX Radiative Flux Assessment activity.
This talk provides an overview of the latest version by first presenting the results of an extensive validation analysis using surface flux measurements from the Baseline Surface Radiation Network (BSRN), Global Energy Balance Archive (GEBA), Atmospheric Radiation Measurement (ARM) networks. We present the global annual means and zonal annual cycle of the flux components including inferred cloud radiative forcing. The validation analysis is used to infer the uncertainties of these quantities. The time series at TOA and surface for global, land, ocean, and tropical areas are presented and analyzed for variability and consistency with other long-term data sets such as from ISCCP-FD. Finally, the results are summarized in such a way to characterize the largest uncertainties of the data set and the future work planned to address the deficiencies.
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