Open AccessExperiments with Cloud Properties: Impact on Surface Radiative Fluxes
Author(s) -
H. Wang,
R. T. Pinker,
Patrick Minnis,
Mandana M. Khaiyer
Publication year - 2008
Publication title -
journal of atmospheric and oceanic technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.774
H-Index - 124
eISSN - 1520-0426
pISSN - 0739-0572
DOI - 10.1175/2007jtecho546.1
Subject(s) - radiative transfer , environmental science , radiance , cloud forcing , satellite , shortwave , radiative forcing , shortwave radiation , remote sensing , atmospheric radiative transfer codes , cloud computing , meteorology , longwave , cloud albedo , radiative flux , parametrization (atmospheric modeling) , cloud cover , snow , atmospheric sciences , radiation , computer science , physics , geology , aerosol , quantum mechanics , astronomy , operating system
Solar radiation reaching the earth’s surface provides the primary forcing of the climate system, and thus, information on this parameter is needed at a global scale. Several satellite-based estimates of surface radiative fluxes are available, but they differ from each other in many aspects. The focus of this study is to highlight one aspect of such differences, namely, the way satellite-observed radiances are used to derive information on cloud optical properties and the impact this has on derived parameters such as surface radiative fluxes. Frequently, satellite visible radiance in a single channel is used to infer cloud transmission; at times, several spectral channels are utilized to derive cloud optical properties and use these to infer cloud transmission. In this study, an evaluation of these two approaches will be performed in terms of impact on the accuracy in surface radiative fluxes. The University of Maryland Satellite Radiation Budget (UMD/SRB) model is used as a tool to perform such an evaluation over the central United States. The estimated shortwave fluxes are evaluated against ground observations at the Atmospheric Radiation Measurement Program (ARM) Central Facility and at four ARM extended sites. It is shown that the largest differences between these two approaches occur during the winter season when snow is on the ground.