Papineau, John M., author2022-04-292022-04-291998https://hdl.handle.net/10217/234895Summer 1998.This study demonstrates the utility of the Regional Atmospheric Modeling System (RAMS) in analyzing the distribution of precipitation along Alaska's Kenai Peninsula during the September 19-21, 1995 heavy precipitation and flood event. The model generated heavy precipitation over the coastal mountains, with lighter amounts at both lower elevations and to the lee of the windward barrier. The model precipitation was in reasonably good agreement with the limited set of observations. Included in this study are series of simulations that are designed to test the models sensitivity to initial values of wind speed, wind direction, moisture, and atmospheric stability. The results show that the areal and vertical distribution of model generated precipitation is quite sensitive to realistic perturbations in the initial fields, primarily as a result of the change in the vertical velocity structure of the model atmosphere. It is apparent that since most mountainous regions are also data sparse, initializing a model is a serious challenge. Large uncertainty in initial conditions as well as the highly nonlinear nature of the precipitation process, necessitates an ensemble approach to quantitative precipitation forecasting (QPF). Using 15 six hour model simulations an ensemble QPF is generated. The results indicate an order of magnitude variance in precipitation over the mountains, using perturbations that are within observational uncertainty. Since mesoscale models have adjustable grids, it is important to understand the relationship between grid interval, terrain resolution and model generated precipitation. Findings from this study suggest that as the grid interval decreases from 15 km to 10 km, precipitation increased by 33%. A further decrease in grid interval from 10 km to 5 km increased precipitation by an additional 26%. This grid interval dependency is in part due to changes in terrain height and slope angles in conjunction with the increased density of grid points. This dependency is also a function of energy propagation across a finite-difference grid.reportsengCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.Precipitation (Meteorology) -- Simulation methodsWeather -- Effect of mountains onOrographic cloudsText