How the Environmental Lifting Condensation Level Affects the Sensitivity of Simulated Convective Storm Cold Pools to the Microphysics Parameterization

Abstract

Abstract Several studies have documented the sensitivity of convective storm simulations to the microphysics parameterization, but there is less research documenting how these sensitivities change with environmental conditions. In this study, the influence of the lifting condensation level (LCL) on the sensitivity of simulated ordinary convective storm cold pools to the microphysics parameterization is examined. To do this, seven perturbed-microphysics ensembles with nine members each are used, where each ensemble uses a different base state with a surface-based LCL between 500 and 2000 m. A comparison of ensemble standard deviations of cold-pool properties shows a clear trend of increasing sensitivity to the microphysics as the LCL is raised. In physical terms, this trend is the result of lower relative humidities in high-LCL environments that increase low-level rain evaporational cooling rates, which magnifies differences in evaporation already present among the members of a given ensemble owing to the microphysics variations. Omitting supersaturation from the calculation of rain evaporation so that only the raindrop size distribution influences evaporation leads to more evaporation in the low-LCL simulations (owing to more drops), as well as a slightly larger spread in evaporational cooling amounts between members in the low-LCL ensembles. Cold pools in the low-LCL environments are also found to develop earlier and are initially more sensitive to raindrop breakup owing to a larger warm-cloud depth. Altogether, these results suggest that convective storms may be more predictable in low-LCL environments, and forecasts of convection in high-LCL environments may benefit the most from microphysics perturbations within an ensemble forecasting system. Significance Statement Computer simulations of thunderstorms can have grid spacings ranging from tens to thousands of meters. Because individual precipitation particles form on scales smaller than these grid spacings, the bulk effects of precipitation processes in models must be approximated. Past studies have found that models are sensitive to these approximations. In this study, we test whether the sensitivity to these approximations changes with the relative humidity in the lowest 1–2 km of the atmosphere. We found that increasing the relative humidity decreases the sensitivity of simulations to the precipitation process approximations. These results can inform meteorologists about the uncertainties surrounding computer-generated thunderstorm forecasts and suggest environmental conditions where using several computer models with different precipitation process approximations may be beneficial.