Search Results

You are looking at 1 - 2 of 2 items for :

  • Author or Editor: William Ridgway x
  • Journal of Climate x
  • Refine by Access: All Content x
Clear All Modify Search
Alexander Marshak
,
Anthony Davis
,
Warren Wiscombe
,
William Ridgway
, and
Robert Cahalan

Abstract

In this paper, the effect of cloud structure on column absorption by water vapor is investigated. Radiative fluxes above and below horizontally inhomogeneous liquid water clouds are computed using an efficient Monte Carlo technique, the independent pixel approximation, and plane-parallel theory. Cloud inhomogeneity is simulated by two related fractal models that use bounded cascades for the horizontal distribution of optical depth. The first (“clumpy”) model has constant cloud top and base, hence a constant geometrical thickness but varying extinction; the second (“bumpy”) model has constant extinction and cloud base, hence variable cloud-top and geometrical thickness. The spectral range between 0.9 and 1.0 μm (with strong water vapor absorption and negligible cloud liquid water absorption) is selected for a detailed study, not only of domain-averaged quantities, but also radiation fields. Column-absorption fields are calculated as the difference between the two net fluxes above and below clouds. It is shown that 1) redistribution of cloud liquid water decreases column absorption, that is, plane-parallel absorption is larger than the independent pixel approximation one by 1%–3%; 2) 3D radiative effects enhance column absorption by about 0.6% for the clumpy model and 2% for the bumpy model, that is, Monte Carlo absorption is larger than independent pixel approximation absorption—this effect is most pronounced for the bumpy cloud model at solar zenith angle ≈45°; and 3) plane-parallel absorption is larger than 3D Monte Carlo absorption for high solar elevations and nearly equal to it for low solar elevations. Thus, for extended clouds of thickness 1–2 km or less, in an important water vapor absorption band (0.94 μm), the authors do not find a significant enhancement of cloud absorption due to horizontal inhomogeneity.

Full access
Ming-Dah Chou
,
David P. Kratz
, and
William Ridgway

Abstract

Parameterizations for infrared radiation (IR) in clear atmosphere can be made fast and accurate by grouping spectral regions with similar radiative properties, and by separating the low pressure region of the atmosphere from the high pressure region. Various approaches are presented in this study to parameterizing the broadband transmission functions for use in numerical climate models. For water vapor and carbon dioxide (CO2) bands, the transmission functions are parameterized separately for the middle atmosphere (0.01–30 mb) and for the region below. In the middle atmosphere where the dependence of absorption on pressure and temperature is not strong, the diffuse transmission functions are derived from that at a reference pressure and temperature. In the lower stratosphere and the troposphere, the spectra are grouped into band-center regions and band-wing regions. One-parameter scaling is applied to approximate a nonhomogeneous path with an equivalent homogeneous path, and the diffuse transmittances are either fit by analytical functions or interpolated from precomputed tables.

As opposed to the one-parameter scaling, which applies only to a relatively narrow pressure range, the two-parameter scaling (commonly called the Curtis-Godson approximation) is applied to parameterizing the carbon dioxide (CO2) and ozone (O3) transmission functions in both the middle and the lower atmosphere. The diffuse transmission functions are simply interpolated from three small precomputed tables. The accuracies of cooling rates in the 15-μm band computed using the approximation for both the middle and the lower atmospheres are comparable with that using the parameterizations separately for the middle and the lower atmospheres. The radiative effect of nitrous oxide (N2O) and methane (CH4) is also examined. Parameterizations are presented for the N2O and CH4 diffuse transmission functions.

Full access