Characterising Ice Particle Size Distributions

Cloud microphysics modulates the timing and intensity of precipitation, extent and duration of cloud cover and radiative transfer through the atmosphere. Uncertainties in the representation of Particle Size Distributions (PSDs) cause inaccuracies in the numerical weather prediction (NWP) model output, which has negative impacts on forecast and climate predictions. In this study, observations made during the PICASSO (Parameterising Ice Cloud using Airborne obServationS and triple frequency dOppler radar) field campaign in the UK are used. During this campaign, a research aircraft made several flights through different ice and mixed-phase cloud species at varying altitudes. This captured information on a range of microphysical regimes. We compare these observations against the double moment microphysics scheme CASIM (Cloud AeroSol Interacting Microphysics) which is being developed at the UK Met Office. The parameterised PSD with prognosed moments matched to the observations is compared to the real PSD, allowing us to test the PSD function assumed in different microphysical scenarios. Generally we find that in cold, ice phase regions of the cloud, the model performs well, predicting near identical PSDs to those observed. However in some other regions, CASIM does not accurately represent the observed PSDs – this is particularly noticeable in mixed phase regimes, and regions with multiple ice crystal habits. We explore the impact of these discrepancies on the microphysical evolution of the cloud by computing the corresponding process rates using the observed and parameterised PSDs, and comparing the two.