Climate Publications

Oreopoulos, L., S. Platnick, G. Hong, P. Yang, and R. F. Cahalan, 2008: The shortwave radiative forcing bias of liquid and ice clouds from MODIS observations. J. Climate.

Abstract
We analyze the plane-parallel bias of the shortwave cloud radiative forcing SWCRF of liquid and ice clouds at 1 deg scales using global MODIS (Terra and Aqua) cloud optical property retrievals for four months of 2005 representative of the meteorological seasons. The (negative) bias is estimated as the difference of the SWCRF calculated using the Plane-Parallel Homogeneous (PPH) method and the Independent Column Approximation (ICA). These calculations require MODIS-derived means (for PPH calculations) and distributions (for ICA calculations) of cloud optical thickness and effective radius as well as ancillary surface albedo and atmospheric information consistent with the MODIS retrievals, that are inserted into a broadband solar radiative transfer code. The absolute value of global SWCRF bias of liquid clouds at the top of the atmosphere is ~6 Wm-2 for MODIS overpass times while the SWCRF bias for ice clouds is smaller in absolute terms by ~0.7 Wm-2, but with stronger spatial variability. If effective radius variability is neglected (only optical thickness horizontal variations are accounted for), the absolute SWCRF biases increase by about 0.3-0.4 Wm-2 on average. Marine clouds of both phases exhibit greater (more negative) SWCRF biases than continental clouds. Finally, morning (Terra)–afternoon (Aqua) differences in SWCRF bias are much more pronounced for ice than liquid clouds, up to about ~15% (Aqua producing stronger negative bias) on global scales, with virtually all contribution to the difference coming from land areas. The substantial magnitude of the SWCRF bias, which for clouds of both phases is collectively about 4 Wm-2 for diurnal averages, should be a strong motivation to accelerate efforts that link cloud schemes accounting for subgrid condensate variability with appropriate radiative transfer schemes in global climate models.
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September 15, 2008 in Personnel
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