Parameterization of wind gustiness for the computation of ocean surface fluxes at different spatial scales

Analysis of the Goddard cloud-ensemble (GCE) model output forced by observational data over the tropical western Pacific and eastern tropical North Atlantic has shown that ocean surface latent and sensible heat fluxes averaged in a typical global-model grid box are reproduced well using bulk algorithms with grid-box-average scalar wind speed but could be significantly underestimated under weak wind conditions using average vector wind speed. This is consistent with previous observational and modeling studies. The difference between scalar and vector wind speeds represents the subgrid wind variability (or wind gustiness) that is contributed by boundary layer large eddies, convective precipitation, and cloudiness. Based on the GCE data analysis for a case over the tropical western Pacific, a simple parameterization for wind gustiness has been developed that considers the above three factors. This scheme is found to fit well the GCE data for two other cases over the tropical western Pacific and eastern tropical North Atlantic. Its fit is also much better than that of the traditional approach that considers the contribution to wind gustiness by boundary layer large eddies alone. A simple formulation has also been developed to account for the dependence of the author's parameterization on spatial scales (or model grid size). Together, the preliminary parameterization and formulation can be easily implemented into weather and climate models with various horizontal resolution.