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Robert Pincus, Malgorzata Szczodrak, Jiujing Gu, and Philip Austin

Abstract

The uncertainty in optical depths retrieved from satellite measurements of visible wavelength radiance at the top of the atmosphere is quantified. Techniques are briefly reviewed for the estimation of optical depth from measurements of radiance, and it is noted that these estimates are always more uncertain at greater optical depths and larger solar zenith angles. The lack of radiometric calibration for visible wavelength imagers on operational satellites dominates the uncertainty retrievals of optical depth. This is true for both single-pixel retrievals and for statistics calculated from a population of individual retrievals. For individual estimates or small samples, sensor discretization (especially for the VAS instrument) can also be significant, but the sensitivity of the retrieval to the specification of the model atmosphere is less important. The relative uncertainty in calibration affects the accuracy with which optical depth distributions measured by different sensors may be quantitatively compared, while the absolute calibration uncertainty, acting through the nonlinear mapping of radiance to optical depth, limits the degree to which distributions measured by the same sensor may be distinguished.

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Jiujing Gu, Eric A. Smith, Harry J. Cooper, Andrew Grose, Guosheng Liu, James D. Merritt, Maarten J. Waterloo, Alessandro C. de Araújo, Antonio D. Nobre, Antonio O. Manzi, Jose Marengo, Paulo J. de Oliveira, Celso von Randow, John Norman, and Pedro Silva Dias

Abstract

In this first part of a two-part investigation, large-scale Geostationary Operational Environmental Satellite (GOES) analyses over the Amazônia 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 Amazônia. To validate the retrieval algorithms, instantaneous estimates of SRB fluxes and rain rates over 8 km × 8 km areas were compared with 30-min-averaged surface measurements obtained from tower sites located near Ji-Paraná and Manaus in the states of Rondônia 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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