A stochastic model of rainfall rate is used to examine the temporal variability of rainfall during heavy convective rain periods. The model represents the microstructure of rainfall rate at time scales that are important for land surface processes associated with infiltration and runoff production. The representation of rainfall rate is based on a marked point process model of raindrop size distributions, which yields a gamma raindrop spectrum with parameters that are time-varying stochastic processes. Raindrop size distribution observations from a Joss-Waldvogel disdrometer in Princeton, New Jersey, during the period May-October 2006 are used along with the stochastic model to examine rainfall rate variability. Analyses focus on a sample of 60-min time periods in which heavy convective rainfall occurred. Central elements of the analyses entail examination of the relationships between rainfall rate and the time-varying model parameters that characterize the raindrop size distribution. We also examine the dependence structure among these processes. "Scaling law" formulations of raindrop size distributions are used to examine variability of raindrop size distributions. Analyses of the Princeton heavy rainfall periods also point to seasonal and diurnal heterogeneities as important elements of the distribution of extreme rainfall rates. Convective intensity, as reflected in cloud-to-ground lightning observations, plays an important role in the distribution of extreme rainfall rates and the evolution of raindrop size distributions associated with heavy rainfall.
All Science Journal Classification (ASJC) codes
- Water Science and Technology