Parameterization of Water and Ice Cloud Near-Infrared Single-Scattering Co-Albedo in Broadband Radiation Schemes

Abstract

The parameterization of cloud shortwave absorption poses a difficult problem in broadband radiation schemes that treat the near-IR region as a single interval. This problem arises because the spectral variation of the single-scattering co-albedo 1 ? ? of cloud droplets and ice crystals is enormous in the near-IR region, and because the cloud particle absorption is overlapped by sharply varying water vapor absorption. In this paper, several parameterization methods of cloud near-IR (0.68?4.00 ?m) 1 ? ? are intercompared using a large set of atmospheric columns generated by a GCM. The methods include 1) linear averaging of 1 ? ?, weighting with the TOA solar flux; 2) ?thick averaging? by Edwards and Slingo; 3) Fouquart?s formula, which presents water cloud near-IR 1 ? ? as a function of optical thickness; and 4) the ?correlated ?? technique by Espinoza and Harshvardhan. An extension of the correlated ? technique to ice clouds is suggested. In addition, a new ?adaptive ?? broadband parameterization technique is developed and tested. In this method, the near-IR 1 ? ? of a cloud layer is parameterized in terms of the cloud properties (phase, optical thickness, and effective particle size) and the properties of the overlying atmosphere (slant vapor path and clouds). Two slightly different versions of the method are considered. The results of the intercomparison indicate that the adaptive ? method yields higher accuracy than the other broadband techniques tested. Linear averaging is by far the least accurate method; in particular, it is shown that linear averaging of near-IR 1 ? ? can lead to substantially overestimated absorption in ice clouds also. However, when the near-IR region is subdivided into three bands, the combination of thick averaging for water clouds and linear averaging for ice clouds provides results superior to those of all the broadband methods.