Samantha Carr

Date of Award

January 2018

Document Type


Degree Name

Master of Science (MS)


Atmospheric Sciences

First Advisor

Michael Poellot


It is widely assumed that cloud particles are spatially distributed in a random and uncorrelated fashion (a Poissonian distribution); however, previous studies using airborne observations have shown this is not true for small cloud droplets. Previous work using rain gauges and disdrometer networks have also found this to be true for precipitation size particles; however, little research has been done using airborne observations to study such phenomena. Thus, a question to be addressed in this study is whether clustering of precipitation size particles can be examined using airborne observations.

In situ microphysical data collected on the University of North Dakota Citation II research aircraft during the Olympic Mountains Experiment (OLYMPEX) using a Stratton Park Engineering Company (SPEC) High Volume Precipitation Spectrometer Version 3 (HVPS-3) are analyzed. The HVPS-3 captures shadow images of precipitation size particles, which can be used to examine clustering signatures on meter to kilometer size scales. Flight data are also stratified by the synoptic classifications used in OLYMPEX to determine if clustering changes with synoptic forcing. Overall, preliminary results indicate that clustering can be examined using airborne observations and that differences do occur between synoptic regimes. Results from this study also emphasize that non-Poisson statistics should be incorporated into the current radar framework, as a considerable amount of research has indicated that particles are not uniformly distributed in space.