Observational evidence is mounting on the reduction of winter precipitation and an earlier snowmelt in the southwestern United States. It is unclear, however, how these changes, along with forest thinning, will impact water supplies due to complexities in the precipitation-streamflow transformation. In this study, I use the Triangulated Irregular Network-based Real-time Integrated Basin Simulator (tRIBS) to provide insight into the independent and combined effects of climate change and forest cover reduction on the hydrologic response in the Beaver Creek (~1100 km2) of central Arizona. Prior to these experiments, confidence in the hydrologic model is established using snow observations at two stations, two nested streamflow gauges, and estimates of spatially-distributed snow water equivalent over a long-term period (water years 2003-2018). Model forcings were prepared using station observations and radar rainfall estimates in combination with downscaling and bias correction techniques that account for the orographic controls on air temperature and precipitation. Model confidence building showed that tRIBS is able to capture well the variation in snow cover and streamflow during wet and dry years in the 16 year simulation period. The results from this study show that the climate change experiments increased average annual streamflow by 1.5% at +1°C of warming. However, a 28% decrease in streamflow occurs by +6°C of warming as evapotranspiration (ET) increases by 10%. Forest thinning shifted the warming threshold where ET increases reduce streamflow yield until +4°C of warming as compared to no forest thinning when this threshold occurs at +2°C. An average increase in streamflow of 12% occurs after forest thinning across all climate scenarios. While the snow covered area is unaffected by thinning, the volume of snowmelt increases and is linked to the higher water yield. These findings indicate that water managers can expect decreases in streamflow due to climate change but may be able to offset these impacts up to a warming threshold by thinning forested areas within the Beaver Creek.

The Mid-South region, which consists of west Tennessee, northeast Arkansas, north Mississippi, and the Missouri bootheel, is one of many areas in the United States that frequently faces the threats to life and property posed by tornadoes. Forecasting the occurrence of tornadoes is arguably the biggest challenge for meteorologists responsible for the region. This study analyzes synoptic scale weather conditions associated with tornadoes in the Mid-South with the hopes of identifying patterns conducive to tornadic activity and that these patterns can be used to better forecast potential tornado days. It is hypothesized that patterns associated with tornado formation can be identified and that certain patterns may be more favorable to stronger tornadoes or tornado outbreaks than others.
To find these patterns, I analyzed surface and upper air features were analyzed on days where multiple tornadoes occurred from January 1999 to March 2018. Specifically, the surface low pressure, 500hPa trough, and 850 and 300hPa jets were analyzed. Using a floating nine point grid system, I identified the location of the Mid-South in relation to the feature. In the end, eight patterns of similar grid locations were identified to be related to tornado days. For example, the Mid-South was frequently to the southeast of the surface low. However, no correlation appears to exist between the patterns and the number or intensity of tornadoes. It is recommended that in the future these patterns be tested as a forecast method and/or compared to non-tornado days to verify that they are valid tools.

The Great Plains region of the central United States and southern Canada is a promising location for wind energy resource development. Wind energy site assessments and forecasts can benefit from better understanding the variability that may result from several teleconnections affecting North America. This thesis investigates how the El Niño/Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and the Pacific/North American Pattern (PNA) impact mean monthly wind speeds at 850 hPa over the Great Plains. Using wind speeds from the NCAR/NCEP Reanalysis 1, correlations were computed between the mean monthly wind speeds and average monthly teleconnection index values. A difference of means test was used to compute the change in wind speeds between the positive and negative phases of each index. ENSO was not found to have a significant impact on wind speeds, while the NAO and PNA patterns weakly affected wind speeds. The NAO index was positively (negatively) correlated with wind speeds over the northern (southern) plains, while the PNA index was negatively correlated with wind speeds over most of the plains. Even a small change in wind speed can have a large effect on the potential power output, so the effects of these teleconnections should be considered in wind resource assessments and climatologies.