A Parameterization of the Cloudiness Associated with Cumulus Convection; Evaluation Using TOGA COARE Data

Abstract

A new parameterization of the cloudiness associated with cumulus convection is proposed for use in climate models. It is based upon the idea that the convection scheme predicts the local concentration of condensed water (the in-cloud water content) produced at the subgrid scale, and that a statistical cloud scheme predicts how this condensed water is spatially distributed within the domain. The cloud scheme uses a probability distribution function (PDF) of the total water whose variance and skewness coefficient are diagnosed from the amount of condensed water produced at the subgrid scale by cumulus convection and at the large scale by supersaturation, from the degree of saturation of the environment, and from the lower bound of the total water distribution that is taken equal to zero. This parameterization is used in a single-column model forced by the Tropical Ocean Global Atmosphere Coupled Ocean?Atmosphere Response Experiment (TOGA COARE) data, and including the cumulus convection scheme of Emanuel whose humidity prediction has been optimized using these data. Simulations are carried out during the 120 days of operation of the TOGA COARE intensive observation period. The model is able to reproduce some of the main characteristics of the cloudiness observed over the warm pool. This includes the occurrence of different populations of clouds (shallow, midlevel, and deep convective), a minimum cloud cover between 600 and 800 hPa, some relationship between the distribution of cloud tops and the presence of stable atmospheric layers, the formation of long-lasting upper-tropospheric anvils associated with the maturation of the convective cloud systems, and the presence of an extensive layer of thin cirrus clouds just below the tropopause. Nevertheless, shallow-level clouds are likely to be underestimated. The behavior of the predicted cloud fields is consistent with some statistical features suggested by cloud-resolving model simulations of tropical cloud systems over oceans. The radiative fluxes calculated interactively by the model from the predicted profiles of humidity, temperature, and clouds are in reasonable agreement with satellite data. Sea surface temperatures predicted by the model using its own radiative and turbulent fluxes calculated at the ocean surface differ from observations by a few tenths of a degree. Sensitivity tests show that the performance of the cloudiness parameterization does not critically depend upon the choice of the PDF. On the other hand, they show that the prediction of radiative fluxes is improved when the statistical moments of the PDF are predicted from both large-scale variables and subgrid-scale convective activity rather than from large-scale variables only.