Effect of Turbulence Parameterization on Assessment of Cloud Organization

Abstract

his study evaluates the cloud and rain cell organization in space and time as forecasted by a cloud-resolving model. The forecast fields, mainly describing mesoscale convective complexes and cold fronts, were utilized to generate synthetic satellite and radar images for comparison with Meteosat Second Generation and S-band radar observations. The comparison was made using a tracking technique that computed the size and lifetime of cloud and rain distributions and provided histograms of radiative quantities and cloud-top height. The tracking technique was innovatively applied to test the sensitivity of forecasts to the turbulence parameterization. The simulations with 1D turbulence produced too many small cloud systems and rain cells with a shorter lifetime than observed. The 3D turbulence simulations yielded size and lifetime distributions more consistent with the observations. As shown for a case study, 3D turbulence yielded longer mixing length, larger entrainment, and stronger turbulence kinetic energy inside clouds than 1D turbulence. The simulation with 3D turbulence had the best scores in high clouds. These features suggest that 1D turbulence did not produce enough entrainment, allowing the formation of more small cloud and rain cells than observed. Further tests were performed on the sensitivity to the mixing length with 3D turbulence. Cloud organization was very sensitive to in-cloud mixing length and the use of a very small value increased the number of small cells, much more than the simulations with 1D turbulence. With a larger in-cloud mixing length, the total number of cells, mainly the small ones, was strongly reduced.