Application of a Monte Carlo Solar Radiative Transfer Model in a conventional GCM

English Abstract:

GCM simulations with the McICA radiative transfer method have demonstrated that large amounts of uncorrelated, unbiased radiative noise can be injected at their inner spatial- and temporal-scales with minor side effects. To date, operational applications of McICA have employed two-stream approximations (TSA) of the radiative transfer equation (RTE); but any 1D solution could be used. It is shown that surprisingly few photons are needed to limit the noise of a 1D Monte Carlo solution of the solar RTE to levels that are known to be “safe” for the TSA McICA. The primary benefit realized by swapping a TSA for a Monte Carlo is that detailed phase functions can be used to eliminate well-documented biases as a function of cosine of solar zenith angle μ₀.

In addition, a 2D stochastic cloud generator is presented and assessed using cloud fields inferred from A-train satellite data. This generator resembles those used by McICA in that it is initialized by profiles of cloud properties that GCMs provide. It is shown, using over 32,000 A-train domains each of length 256 km, that neglect of phase function details and horizontal transport of radiation by TSAs foster m₀-dependent biases that, for the most part, have the same sign and together amount to mean biases in surface irradiance of -12 W m^-2 at μ₀ near 1, and 2 W m^-2 at μ₀ near 0.1. Sensitivities of the CCCma GCM to replacement of the conventional TSA McICA with 2D clouds and a Monte Carlo model are shown.