Date of Award




Document Type


Degree Name

Doctor of Philosophy (PhD)


Department of Atmospheric and Environmental Sciences

Content Description

1 online resource (xxv, 208 pages) : color illustrations, color maps.

Dissertation/Thesis Chair

Ryan D Torn

Committee Members

Justin R Minder, Robert G Fovell, Christopher Thorncroft


ensemble, parameterization, rainfall, SPPT, stochastic, Rainfall probabilities, Rain and rainfall, Precipitation forecasting, Microphysics

Subject Categories

Atmospheric Sciences | Meteorology


Stochastic model error schemes, such as the stochastic perturbed parameterization tendencies (SPPT) and independent SPPT (iSPPT) schemes, have become an increasingly utilized method to represent model error associated with uncertain subgrid-scale processes in ensemble prediction systems (EPSs). While much of the current literature focuses on how stochastic methods influence ensemble skill, relatively less attention is given to the processes by which these schemes lead to forecast variability. In this vein, this dissertation examines the physical processes by which the application of SPPT and iSPPT to the microphysics, planetary boundary layer (PBL), and radiation parameterization schemes yields rainfall forecast variability. These processes are evaluated in Weather Research and Forecasting (WRF) model ensembles of three meso–synoptic-scale heavy rain events over the northeastern United States and Taiwan.