INVESTIGATING THE EFFECT OF SIZE SORTING ON THE VERTICAL VARIATION OF RAIN DROP SIZE DISTRIBUTIONS USING PARSIVEL DISDROMETERS AND WSR-88D RADARS DURING VORTEX-SE
Creators: name: Terrell, Marcus
Publisher: name: Purdue University Graduate School
Year: 2021
Subjects: Atmospheric sciences not elsewhere classified

description: Rain drop size distributions (DSDs) in severe convective storms are highly variable in time and space. DSDs can be derived from polarimetric radar observations at high spatiotemporal resolution but these observations are often lacking near the surface owing to radar horizon issues. Disdrometers provide “ground-truth” measurements and validation of radar-derived DSDs but are by nature limited point measurements. Moreover, substantial evolution of the DSD can occur between the lowest radar elevation angle and the surface. Recent studies have shown that hydrometeor size sorting (HSS) is an important and even dominant process contributing to DSD evolution in severe storms; many physical processes such as the strength of the updraft, transient effects, and storm-relative mean winds are contributing factors to continued size sorting. In this study, we focus on strong storm-relative mean winds that induce sustained size sorting owing to the different residence times of hydrometeors of different sizes as they fall in severe storms. The resulting differential advection leads to a distinct horizontal spread of hydrometeors of different sizes at the bottom of a given layer. The goal of this study is to evaluate the impact of size sorting on DSD evolution from the radar level to the surface. To accomplish this, we develop and apply a raindrop trajectory model to compute the evolution of DSDs between radar observations aloft and the surface. For simplicity and to isolate the effects of size sorting, we neglect processes such as breakup, collection, and evaporation, and assume a horizontally homogeneous wind profile. We use disdrometer and radar data, which measure DSDs at the surface and provide the observed quantities aloft, respectively. The disdrometer data was collected from portable disdrometers as a collaboration between Purdue University, University of Oklahoma, University of Massachusetts, and the National Severe Storms Laboratory during the VORTEX-SE 2017 field campaign. NEXRAD data from KHTX Huntsville, AL and KGWX Columbus Air Force Base, MS was retrieved from the National Centers for Environmental Information (NCEI).<br>We evaluate three separate cases, a tornadic QLCS on 30 April 2017, a cluster storm on 27 March 2017, and a squall line on 25 March 2017. After the radar data is pre-processed, we retrieve the DSDs from the radar by assuming a gamma distribution and discretize them into PARSIVEL bins to produce a gridded dataset of DSDs. We then apply the raindrop trajectory model to compute the DSDs at the surface which are then compared directly with disdrometer observations. Analysis and comparisons from all cases yield similar results in that-the sorted radar DSDs at the surface are overall closer to the disdrometer observations than the original radar DSDs aloft. Results also show that the spatial variation of DSDs is higher at the surface due to size sorting by the storm-relative mean winds.<br>