Impact of cloud microphysical processes on hurricane intensity, part 2: Sensitivity experiments

Summary Seven different microphysical sensitivity experiments were designed with an objective to evaluate their respective impacts in modulating hurricane intensity forecasts using mesoscale model MM5. Microphysical processes such as melting of graupel, snow and cloud ice hydrometeors, suppression of evaporation of falling rain, the intercept parameter and fall speed of snow and graupel hydrometeors are modified in the existing NASA Goddard Space Flight Center (GSFC) microphysical parameterization scheme. We studied the impacts of cloud microphysical processes by means of track, intensity, precipitation, propagation speed, kinematic and thermodynamic vertical structural characteristics of hurricane inner core. These results suggest that the set of experiments where (a) melting of snow, graupel and cloud ice were suppressed (b) melting of snow and graupel were suppressed and (c) where the evaporation of rain water was suppressed all produced most intense storms. The major findings of this study are the interconversion processes such as melting and evaporation among hydrometeors and associated feedback mechanism are significantly modulate the intensity of the hurricane. In particular an experiment where the melting of graupel, snow and cloud ice hydrometeors was eliminated from the model parameterization scheme produced the most explosively intensified storm. In the experiment where rain water evaporation was eliminated from the model, it produced a stronger storm as compared to the control run but it was not as strong as the storms produced from absence of melting processes. The impact on intensity due to variations made in intercept parameters of the hydrometeors (i.e., snow and graupel) were not that evident compared to other experiments. The weakest storm was noted in the experiment where the fall speeds of the snow hydrometeors were increased two fold. This study has isolated some of the factors that contributed to a stronger hurricane and concludes with a motivation that the findings from this study will help in further improvement in the design of sophisticated explicit microphysical parameterization for the mesoscale non-hydrostatic model for realistic hurricane intensity forecasts.