Abstract
The eastern and the western tropical oceans usually show a considerable zonal asymmetry in the extent and depth of deep cumulus convection. Earlier versions of a simple cumulus parameterization based on GATE observations have revealed some limitations in differentiating this type of zonal asymmetry. The aim of the proposed scheme is to provide global statistical corrections to a Kuo-type cumulus parameterization scheme and thus to optimize the moistening, heating and rainfall rates over different regions. The base data for this study are the recently analyzed global FGGE IIIb datasets. Three months of daily datasets during the global experiment were utilized in order to evaluate the coefficients of a multiple regression analysis. These multiple regression coefficients vary in space and provide different measures of a moistening parameter b and a mesoscale convergence parameter η. A clear distinction in the strength of convection is found, based on the regression parameters, between the western and the eastern oceans. This generalization of a modified Kuo-type scheme is derived for a spectral resolution of 42 waves. The impact of the aforementioned scheme is investigated in several medium range prediction experiments. Forecast comparison with a simpler version of the Kuo scheme is also carried out. Our interest in these experiments is an evaluation of precipitation forecasts, for which the proposed global cumulus parameterization is compared with other experiments that were based on GATE coefficients and with the observed measures of precipitation. The results of the global forecasts show a very marked improvement in the short range (1 to 2 day) prediction from the use of the globally varying parameterization coefficients. On the other hand, the precipitation amounts predicted from an application of the local GATE coefficients underestimate the rainfall rates over most regions.
