Using Stochastically Generated Subcolumns to Represent Cloud Structure in a Large-Scale Model

A new method for representing subgrid-scale cloud structure in which each model column is decomposed into a set of subcolumns has been introduced into the Geophysical Fluid Dynamics Laboratory’s global atmospheric model AM2. Each subcolumn in the decomposition is homogeneous, but the ensemble reproduces the initial profiles of cloud properties including cloud fraction, internal variability (if any) in cloud condensate, and arbitrary overlap assumptions that describe vertical correlations. These subcolumns are used in radiation and diagnostic calculations and have allowed the introduction of more realistic overlap assumptions. This paper describes the impact of these new methods for representing cloud structure in instantaneous calculations and long-term integrations. Shortwave radiation computed using subcolumns and the random overlap assumption differs in the global annual average by more than 4 W m 2 from the operational radiation scheme in instantaneous calculations; much of this difference is counteracted by a change in the overlap assumption to one in which overlap varies continuously with the separation distance between layers. Internal variability in cloud condensate, diagnosed from the mean condensate amount and cloud fraction, has about the same effect on radiative fluxes as does the ad hoc tuning accounting for this effect in the operational radiation scheme. Long simulations with the new model configuration show little difference from the operational model configuration, while statistical tests indicate that the model does not respond systematically to the sampling noise introduced by the approximate radiative transfer techniques introduced to work with the subcolumns. 1. Cloud vertical structure in the global atmospheric model AM2 Current global models of the atmosphere, such as those used to predict short-term weather or long-term climate change, have horizontal grid spacings of tens to hundreds of kilometers. At these resolutions, many processes, including the treatment of clouds and radiation, must be treated statistically. In particular, calculations of radiation and precipitation fluxes require a conceptual model of subgrid-scale cloud structure. This model usually accounts for the possibility of horizontal variations within each grid cell: some parts of the grid may be cloudy and others clear, for example, and some parts of the cloud may be thicker than others. The conceptual model also describes the relationship between the subgrid-scale structures in different vertical layers. In the global atmospheric model developed by the Geophysical Fluid Dynamics Laboratory (AM2; GFDL Global Atmospheric Model Development Team 2004), cloud structure is relatively simple. Within each grid cell, the model predicts the areal fraction occupied by clouds and the grid-mean mass concentrations of cloud ice and liquid and uses the random overlap assumption Corresponding author address: Dr. Robert Pincus, CIRES/ Climate Diagnostics Center, 325 Broadway, R/CDC1, Boulder, CO 80305. E-mail: [email protected] 3644 M O N T H L Y W E A T H E R R E V I E W VOLUME 134 © 2006 American Meteorological Society