Date of Award
Doctor of Philosophy (PhD)
Atmospheric & Oceanic Sciences
George H. Bryan
John J. Cassano
Jeffrey P. Thayer
Owen B. Toon
Dual-polarization radar, disdrometer, lightning, and model data are analyzed to determine 1) the usefulness and accuracy of disdrometer and attenuation-corrected X-band mobile radar data from severe thunderstorms, 2) the effect of cloud condensation nuclei (CCN) concentration on idealized supercell thunderstorms, and 3) the synoptic weather, dual-polarization radar, and lightning characteristics of Colorado plowable hailstorms.
The results in Chapter 2 demonstrate that the best agreement (1 dB in reflectivity Z and 0.2 dB in differential reflectivity ZDR) between the disdrometer and X-band radar data was obtained when the radar signal quality index (SQI) was at least 0.8 and large hail was not present. Disagreement in Z (ZDR) increased to 6 dB (1.6 dB) and 13 dB (0.6 dB) in large hail and SQI < 0.8, respectively. Since better agreement was obtained under these conditions when the disdrometer measurements were compared to S-band radar data, the X-band attenuation-correction scheme was likely responsible for the disagreement.
In Chapter 3, results from idealized supercell thunderstorm simulations in which the CCN concentration was varied from 100-10 000 cm-3 for several different environmental soundings are presented. Changes in the microphysical process rates saturated at CCN = 3000 cm-3. In heavily polluted conditions (CCN = 10 000 cm-3), supercell thunderstorms formed up to 30% larger rain and 3% larger hail particles, produced up to 25 mm more precipitation near the updraft, and tracked more poleward. The area and size of the cold pool were also sensitive to the CCN concentration, especially when the low-level relative humidity was fairly dry (~60%).
Chapter 4 analyzes the synoptic weather, radar, and lightning characteristics from four severe thunderstorms that produced "plowable" hail accumulations of 15-60 cm along the Colorado Front Range. Westerly flow at 500 hPa at slow speeds (5-15 m s-1), combined with moist upslope low-level flow, accompanied each hailstorm. The accumulated hail mass derived from the radar data pinpointed the times and locations of deep hail, with estimated hail depths of greater than 5 cm (less than 1.5 cm) in areas with plowable (non-plowable) hail. An increase in lightning flash rate also preceded deep hail accumulations.
Kalina, Evan Anthony, "Using Disdrometer, Radar, Lightning, and Model Data to Investigate Severe Thunderstorm Microphysics" (2015). Atmospheric & Oceanic Sciences Graduate Theses & Dissertations. 50.