A Monte Carlo Model for Simulation of Rain-on-Snow Events in the Pacific Northwest

Northwestern North America experiences blasts of heavy winter rainfall, when rain plus melting snow can cause high streamflows and erosion. Geographic variability and sporadic occurrence of rain-on-snow complicate study, but some questions can be addressed through modeling. A computer program combines probabilistic and deterministic elements to perform Monte Carlo simulation of ROS events over many years, generating realizations of initial and weather conditions; within each event, snow accumulation/melt and percolation are tracked, and water avail-able for runoff is the output. Frequency distributions are based on data from the Washington Cascades, some as functions of elevation and date, so the model can be applied to specific sites or generalized zones. Validation focuses on Stampede Pass, a major weather station and snow measurement site. The model is evaluated by comparing statistics and frequency relations of the instrumental record and model realizations for precipitation, R+SM and WAR. In early model applications, the regional zone of greatest ROS enhancement to WAR seems to lie at about 750 m; future uses include assessment of ROS in forest clearings, and possible consequences of climatic change.