In this study, we use a hazard-based modeling as an alternative statistical framework to time series methods as applied to climate data. Data collected from the Kentucky Mesonet will be used to study the distributional properties of the duration of high and low-energy wind events relative to an arbitrary threshold. Our objectiveswere to fit bathtub models proposed in literature, propose a generalized bathtub model, apply these models to Kentucky Mesonet data, and make recommendations as to feasibility of wind power generation. Using two different thresholds (1.8 and 10 mph respectively), results show that the Hjorth bathtub model consistently performed better than all other models considered with coefficient of R-squared values at 0.95 or higher. However, fewer sites and months could be included in the analysis when we increased our threshold to 10 mph. Based on a 10 mph threshold, Bowling Green (FARM), Hopkinsville (PGHL), and Columbia (CMBA) posted the top 3 wind duration times in February of 2009. Further studies needed to establish long-term trends.

Station siting, exposure, instrumentation, and time of observations influence longterm climatic records. This thesis compared and analyzed temperature data from four Kentucky Mesonet stations located in Fayette (LXGN), Franklin (LSML), Clark (WNCH), and Bullitt (CRMT) counties to two nearby Automated Surface Observation Systems (ASOS) stations in Kentucky. The ASOS stations are located at Louisville International Airport (Standiford Field - KSDF) and at Lexington Airport (Blue Grass Field - KLEX). The null hypothesis states that there is no significant difference in temperature measurements between the two types of stations. To quantify the differences in temperature measurements, geoprofiles and the following statistical procedures were used: coefficient of determination (R2), coefficient of efficiency (E), index of agreement (d), root mean square error (RMSE), and mean absolute error (MAE). Geoprofiles were developed using GIS, and take into account elevation, slope, hillshading, land use, and aspect for each site to help better understand the influence of local topography. It was found that temperature differences could be related to the advancement of weather patterns, vegetation growth and decay, and changes in the landscape at the stations. KSDF consistently recorded higher temperatures than those at CRMT. The positive bias ranged between 0.27 and 2.41 ºC during the time period of September 2009 to August 2010. KLEX was found to be warmer or cooler, with temperature differences that ranged from -1.42 to 0.22 ºC for LXGN, LSML, and WNCH. The index of agreement at KSDF for mean hourly temperatures, when compared to the Bullitt County mesonet station, ranged from 0.88 to 0.99. Meanwhile, the index of agreement at KLEX was 0.96 to 1.00 when compared to the Franklin, Fayette, and Clark mesonet stations. KLEX recorded temperatures that were higher or lower compared to the Franklin, Fayette, and Clark mesonet stations. At the seasonal scale, fall and summer showed larger differences between the Mesonet and ASOS observations. KSDF consistently recorded higher temperatures ranging up to 2.41 °C during the summer. The index of agreement at KSDF in the fall, when compared to the Bullitt County mesonet station average temperatures, ranged from 0.89 to 0.95, while in the summer it was 0.88 to 0.96. The d index indicates a good agreement between ASOS and mesonet stations in winter. KLEX indicates that the index of agreement, RMSE, and MAE are best during winter for all three stations, while in the fall and summer the agreement was not as strong when compared to the Franklin, Fayette, and Clark mesonet stations. In summary, results indicate that the Kentucky Mesonet and ASOS temperature measurements show significant differences throughout the year; therefore, the alternative hypothesis is accepted. These differences are attributed to biases associated with ASOS observations, nearby artificial sources of heating, equipment/maintenance procedures, and land use and land cover at the site.

On January 29-30, 2008 a squall line of thunderstorms moved through the Ohio Valley resulting in four deaths and one injury. Such events highlight the importance of accurate forecasting for public safety. Mesoscale Modeling plays an important role in any forecast of a potential squall line. The focus of this study was to examine the performance of several parameterization scheme combinations in the Weather Research and Forecasting Model version three (WRF) as they related to this event. These examinations included cloud microphysics (WRF Single-Moment 3-class, 6-class, and Goddard), cumulus parameterization (Kain-Fritsch and Bets-Miller-Janjic) and planetary boundary layer schemes (Yonsei-University and Mellor-Yamada-Janjic). A total of 12 WRF simulations were conducted for all potential scheme combinations. Data from the WRF simulations for several locations in south central Kentucky were analyzed and compared using Kentucky Mesonet observations for four locations: Bowling Green, Russellville, Murray and Liberty, KY. A fine model resolution of 1 km was used over these locations. Coarser resolutions of 3 km and 9 km were used on the outer two domains, which encompassed the Ohio and Tennessee Valleys. The model simulation performance was assessed using established statistical measures for the above four locations and by visually comparing the North American Regional Reanalysis dataset (NARR) along with modeled simulations. The most satisfactory scheme combination was the WRF Single-Moment 3-class Microphysics scheme, Kain-Fritsch cumulus parameterization scheme and Yonsei University scheme for the planetary boundary layer. The planetary boundary layer schemes were noted to have the greatest influence in determining the most satisfactory model simulations. There was limited influence from different selections of microphysics and cumulus parameterization schemes. The preferred physics parameters from these simulations were then used in six additional simulations to analyze the affect different initialization data sets have with regards to model output. Data sets used in these simulations were the Final Operational Analysis global data, North American Regional Reanalysis (3 and 6 hour) and the North American Mesoscale Model at 1, 3 and 6 hour timesteps, for a total of six simulations. More timesteps or an increase in model resolution did not materially improve the model performance.