CLOUDINESS PARAMETERIZATION AND VERIFICATION IN A LARGE-SCALE ATMOSPHERIC MODEL

This paper addresses the problem of predicting cloud cover and its rad iative impact in a large-scale atmospheric model. A convective and str atiform condensation scheme including cloud water content as a predict ive variable is implemented in the Canadian global spectral model. An important aspect of the scheme is that the cloud amount estimation is a part of the condensation scheme and is a key element in the sub-grid scale stratiform condensation parameterization. The cloud cover from the scheme is verified quantitatively using satellite data. The depend ence of the grid-scale relative humidity threshold on the horizontal a nd vertical resolutions is examined. The possibility of parameterizing stratiform clouds as vertically sub-grid clouds and its verification is investigated. It is shown that the total cloud cover is better esti mated as the sum of separate estimates of convective and stratiform cl oudiness within the framework of the condensation processes parameteri zed in the model. The convective cloud cover is found to be very impor tant to the radiative budget. An improvement in the model forecast, hy drological balance and cloudiness prediction is noticed when the strat iform relative humidity threshold decreases with height. The study als o presents a new 3-dimensional view of the cloudiness estimated by the original scheme and provides a simple vertical and horizontal sub-gri d scale cloud cover parameterization. Vertically sub-grid stratiform c louds combined with horizontally sub-grid convective clouds provide a remarkable improvement in the estimation of total cloud cover.