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In this first part of a two-part investigation, large-scale Geostationary Operational Environmental Satellite (GOES) analyses over the Amazonia region have been carried out for March and October of 1999 to provide detailed information on surface radiation budget (SRB) and precipitation variability. SRB fluxes and rainfall are the two foremost cloud-modulated control variables that affect land surface processes, and they require specification at space-time resolutions concomitant with the changing cloud field to represent adequately the complex coupling of energy, water, and carbon budgets. These processes ultimately determine the relative variations in carbon sequestration and carbon dioxide release within a forest ecosystem. SRB and precipitation retrieval algorithms using GOES imager measurements are used to retrieve surface downward radiation and surface rain rates at high space - time resolutions for large-scale carbon budget modeling applications in conjunction with the Large-Scale Biosphere - Atmosphere Experiment in Amazonia. To validate the retrieval algorithms, instantaneous estimates of SRB fluxes and rain rates over 8 km 3 8 km areas were compared with 30-min-averaged surface measurements obtained from tower sites located near Ji-Paranaand Manaus in the states of Rondonia and Amazonas, respectively. Because of large aerosol concentrations originating from biomass burning during the dry season (i.e., September and October for purposes of this analysis), an aerosol index from the Total Ozone Mapping Spectrometer is used in the solar radiation retrieval algorithm. The validation comparisons indicate that bias errors for incoming total solar, photosynthetically active radiation ( PAR), and infrared flux retrievals are under 4%, 6%, and 3% of the mean values, respectively. Precision errors at the analyzed space time scales are on the order of 20%, 20%, and 5%. The visible and infrared satellite measurements used for precipitation retrieval do not directly detect rainfall processes, and yet they are responsive to the rapidly changing cloud fields, which are directly associated with precipitation life cycles over the Amazon basin. In conducting the validation analysis at high space - time scales, the comparisons indicate systematic bias uncertainties on the order of 25%. These uncertainties are comparable to published values from an independent assessment of bias uncertainties inherent to the current highest-quality satellite retrievals, that is, from the Tropical Rainfall Measuring Mission. Because precipitation is a weak direct control on photosynthesis for the Amazon ecosystem, that is, photosynthesis is dominated by the strong diurnal controls of incoming PAR and ambient air-canopy temperatures, such uncertainties are tolerable. By the same token, precipitation is a strong control on soil thermal properties and carbon respiration through soil moisture, but the latter is a time-integrating variable and thus inhibits introduction of modeling errors caused by random errors in the precipitation forcing. The investigation concludes with analysis of the monthly, daily, and diurnal variations intrinsic to SRB and rainfall processes over the Amazon basin, including explanations of how these variations arise during wet-and dry-season periods

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