This study will focus on two questions: (1) how will anthropogenically driven climate change affect California’s climate, especially the hydrologic resources, in the coming decades?; and (2) what water resources will be available in the future, and at what times during the year (e.g., seasonality and amounts of rain and snow)? We apply global and regional climate models to a domain centered upon California to answer these questions. We will use a 40-km (gridpoint) resolution regional climate model (RCM) in order to capture the topographic complexity of the state, and the climate associated with that complexity. This model has been demonstrated to represent well the observed present climate of California. We will specify atmospheric greenhouse gas concentrations as predicted by the Intergovernmental Panel on Climate Change (IPCC) for the next several decades, and calculate the climate that would likely occur under these conditions, as compared to modeled scenarios of present day climate. From this project we will produce climate model results of future climate scenarios. Climate model results (and the statistical significance of the results) for annual and monthly periods of time will be calculated for the ten hydrologic regions of California as defined by the California Department of Water Resources. The quantitative results from this work will be made available for water policy and planning activities in the state, and for archival at the UC Center for Water Resources.

Lake-effect snowstorms are an important element of climate and weather in the Great Lakes region of North America. Here, I investigate how lake-effect snow levels could change in the future with anthropogenic climate change as predicted by a regional climate model (RegCM3) driven by two different sets of global climate model output (from GFDL CM2.1 and CGCM3, experiments run as part of the North American Regional Climate Change Assessment Program, Phase II). I analyze a subset of the domain focused on the Great Lakes area, paying particular attention to the southeastern Lake Ontario Snowbelt and the southeastern Lake Erie Snowbelt, both of which are mainly within New York State. My results show a decrease in lake-effect snow cover in the future (2040-2070) compared to the recent past (1970-2000) for this region. Total precipitation levels are shown to not change significantly, so it is likely that lake-effect snowstorms will be replaced largely by rain in the future. Both magnitudes of values as well as trends for snow levels in specific cities varied significantly depending on which global climate model output was used to drive RegCM3, pointing to a possibly serious source of uncertainty and error in regional climate modeling studies that do not utilize multiple global climate model output.