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Norman G. Loeb, Frédéric Parol, Jean-Claude Buriez, and Claudine Vanbauce

Abstract

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.

Albedos based on ADMs that assume cloud properties are unbiased (fixed-τ approach) show a strong systematic dependence on viewing geometry. This dependence becomes more pronounced with increasing solar zenith angle, reaching ≈12% (relative) between near-nadir and oblique viewing zenith angles for solar zenith angles between 60° and 70°. The cause for this bias is shown to be due to biases in the cloud optical depth retrievals. In contrast, albedos based on ADMs built using percentile intervals of cloud optical depth (percentile-τ approach) show very little viewing zenith angle dependence and are in good agreement with albedos obtained by direct integration of the mean observed reflectance field (<1% relative error). When the ADMs are applied separately to populations consisting of only liquid water and ice clouds, significant biases in albedo with viewing geometry are observed (particularly at low sun elevations), highlighting the need to account for cloud phase both in cloud optical depth retrievals and in defining ADM scene types. ADM-derived monthly mean albedos determined for all 5° × 5° lat–long regions over ocean are in good agreement (regional rms relative errors <2%) with those obtained by direct integration when ADM albedos inferred from specific angular bins are averaged together. Albedos inferred from near-nadir and oblique viewing zenith angles are the least accurate, with regional rms errors reaching ∼5%–10% (relative). Compared to an earlier study involving Earth Radiation Budget Experiment ADMs, regional mean albedos based on the 19 scene types considered here show a factor-of-4 reduction in bias error and a factor-of-3 reduction in rms error.

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Nicolas Ferlay, François Thieuleux, Céline Cornet, Anthony B. Davis, Philippe Dubuisson, Fabrice Ducos, Frédéric Parol, Jérôme Riédi, and Claudine Vanbauce

Abstract

New evidence from collocated measurements, with support from theory and numerical simulations, that multidirectional measurements in the oxygen A band from the third Polarization and Directionality of the Earth’s Reflectances (POLDER-3) instrument on the Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) satellite platform within the “A-Train” can help to characterize the vertical structure of clouds is presented. In the case of monolayered clouds, the standard POLDER cloud oxygen pressure product P O2 is shown to be sensitive to the cloud geometrical thickness H in two complementary ways: 1) P O2 is, on average, close to the pressure at the geometrical middle of the cloud layer (MCP) and methods are proposed for reducing the pressure difference P O2 − MCP and 2) the angular standard deviation of P O2 and the cloud geometrical thickness H are tightly correlated for liquid clouds. Accounting for cloud phase, there is thus the potential to obtain a statistically reasonable estimate of H. Such derivation from passive measurements, as compared with or supplementing other observations, is expected to be of interest in a broad range of applications for which it is important to define better the macrophysical cloud parameters in a practical way.

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