Top-of-Atmosphere Albedo Estimation from Angular Distribution Models Using Scene Identification from Satellite Cloud Property Retrievals

Norman G. Loeb (1) , Frédéric Parol (2) , Jean-Claude Buriez (3) , Claudine Vanbauce (2)

1 LaRC - NASA Langley Research Center [Hampton]
2 IRN - Interactions Rayonnement Nuages
3 LOA - Laboratoire d’Optique Atmosphérique - UMR 8518

The next generation of earth radiation budget satellite instruments will routinely merge estimates of global top-of-atmosphere radiative fluxes with cloud properties. This information will offer many new opportunities for validating radiative transfer models and cloud parameterizations in climate models. In this study, five months of Polarization and Directionality of the Earth's Reflectances 670-nm radiance measurements are considered in order to examine how satellite cloud property retrievals can be used to define empirical angular distribution models (ADMs) for estimating top-of-atmosphere albedo. ADMs are defined for 19 scene types defined by satellite retrievals of cloud fraction and cloud optical depth. Two approaches are used to define the ADM scene types. The first assumes there are no biases in the retrieved cloud properties and defines ADMs for fixed discrete intervals of cloud fraction and cloud optical depth (fixed-τ approach). The second approach involves the same cloud fraction intervals, but uses percentile intervals of cloud optical depth instead (percentile-τ approach). Albedos generated using these methods are compared with albedos inferred directly from the mean observed reflectance field.

Domaines: Physique Atmosphérique et Océanique [physics.ao-ph]

Norman G. Loeb, Frédéric Parol, Jean-Claude Buriez, Claudine Vanbauce. Top-of-Atmosphere Albedo Estimation from Angular Distribution Models Using Scene Identification from Satellite Cloud Property Retrievals. American Meteorological Society, 2000, 13 (7), pp.1269-1285. ⟨10.1175/1520-0442(2000)013<1269:TOAAEF>2.0.CO;2⟩. ⟨hal-00811524⟩