| Description |
This dissertation examines three separate data analysis studies which sought to estimate the spatial and temporal characteristics of seasonal snowpack variables in the mountainous areas of the western United States. Research began with the analysis of historical daily snow data from Snowpack Telemetry (SNOTEL) sites, located in the mountainous areas of the western United States. Three snowpack characteristics were analyzed from a climatological perspective: snow water equivalent (SWE); snow depth (SD); and snow density, all three being interrelated. Analysis of 7 years of data showed that at a given location, during the winter season, interannual snowpack density variability was smaller than the corresponding SD and SWE changes. Hence, reliable climatological estimates of snow density could be obtained from a relatively short record period. Additionally, the spatial pattern of snowpack densi fication was qualitatively characterized using cluster analysis. The second part of research developed a regional regression-based approach to creating monthly climatological SWE grids over the western United States. The western United States was partitioned into smaller, homogenous regions in consideration of seasonal snowpack accumulation and ablation processes. Using stepwise regression, various geographic and meteorological variables were investigated as potential predictors of change in climatological SWE within each subregion. Results indicate that a simple regional regression approach, coupled with readily available geographic and meteorological parameters as predictors, is reliable for mapping SWE climatology from October to March. For the period of April, however, the regional equations produced increased error, especially in the North Pacifi c and Southwest regions. Lastly, performance of space-borne passive microwave SWE retrieval algorithms for the Colorado River Basin was examined by comparing daily SWE estimates from selected algorithms with SNOTEL SWE measurements for each winter month. |
