This study examines the linkage between surface level ozone and planetary boundary layer meteorological variables in the Phoenix Metropolitan region during the summer North American Monsoon period for years 2010 through 2020. Data used in this study was obtained and derived from both 1200 UTC radiosonde observations launched from the Phoenix National Weather Service office, and 8-hour average ozone concentration measurements from Maricopa County monitoring stations. Specific boundary layer meteorological variables examined in this study included inversion temperature, mixing level pressure, mixing level height, and the surface level variables of temperature, dew point temperature, pressure, wind speed, and meridional and zonal wind directions. The daily maximum, 8-hour average ozone concentrations among all Maricopa County monitoring stations were used in this study. To determine ozone’s linkage to meteorological variables, normality tests, determination of Pearson product moment correlation coefficient and/or the Spearman rank correlation coefficient, and the discriminative Student’s two-sided t-test statistic between ozone exceedance and non-exceedance days were used. Statistically significant coefficients indicate weak negative correlations between surface level ozone and surface level pressure, and mixing level pressure, and weak positive correlations between surface level ozone and surface level temperature, surface level zonal wind direction, mixing level height, and inversion temperature. These correlations were linear for surface level pressure, surface level temperature, and inversion temperature. The two-sided Student’s t-test statistic indicates a significant difference in the mean on ozone exceedance and non-exceedance days for surface level temperature, and the upper-air variables of mixing level height, mixing level pressure, and inversion temperature. Both correlations and differences in the mean of upper-air variables showed statistically significant results. These findings suggest that further research should be completed to determine the forecasting ability of morning sounding analyses on surface level ozone in locations exhibiting similar emissions and geographic features as the Phoenix Valley.

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.

Arizona’s population has been increasing quickly in recent decades and is expected to rise an additional 40%-80% by 2050. In response, the total annual energy demand would increase by an additional 30-60 TWh (terawatt-hours). Development of solar photovoltaic (PV) can sustainably contribute to meet this growing energy demand.

This dissertation focuses on solar PV development at three different spatial planning levels: the state level (state of Arizona); the metropolitan level (Phoenix Metropolitan Statistical Area); and the city level. At the State level, this thesis answers how much suitable land is available for utility-scale PV development and how future land cover changes may affect the availability of this land. Less than two percent of Arizona's land is considered Excellent for PV development, most of which is private or state trust land. If this suitable land is not set-aside, Arizona would then have to depend on less suitable lands, look for multi-purpose land use options and distributed PV deployments to meet its future energy need.

At the Metropolitan Level, ‘agrivoltaic’ system development is proposed within Phoenix Metropolitan Statistical Area. The study finds that private agricultural lands in the APS (Arizona Public Service) service territory can generate 3.4 times the current total energy requirements of the MSA. Most of the agricultural land lies within 1 mile of the 230 and 500 kV transmission lines. Analysis shows that about 50% of the agricultural land sales would have made up for the price of the sale within 2 years with agrivoltaic systems.

At the City Level, the relationship between rooftop PV development and demographic variables is analyzed. The relationship of solar PV installation with household income and unemployment rate remain consistent in cities of Phoenix and Tucson while it varies with other demographic parameters. Household income and owner occupancy shows very strong correlations with PV installation in most cities. A consistent spatial pattern of rooftop PV development based on demographic variables is difficult to discern.

Analysis of solar PV development at three different planning levels would help in proposing future policies for both large scale and rooftop solar PV in the state of Arizona.

The El Niño Southern Oscillation (ENSO) consists of a linkage between changes in sea-surface temperatures and atmospheric pressure across the Tropical Pacific. ENSO encompasses three phases: neutral events, warm/El Niño events in which sea-surface temperatures are warmer-than-normal and the pressure gradient decreases across the Equatorial Pacific, and cold/La Niña events in which Tropical Pacific sea-surface temperatures are cooler-than-normal and the pressure gradient increases. Previous studies have determined a connection between variations in ENSO phase and weather patterns across the globe, focusing particularly on surface temperature and precipitation patterns in the United States. However, little research exists that attempts to link changes in ENSO phase with severe weather in Arizona. Therefore, in this study, I analyzed how variations in ENSO phase affect the frequency, intensity, and spatial distribution of four types of severe weather from 1959 to 2016 in Arizona, including a) tornado events, b) severe thunderstorm wind events, c) hail events, and d) heavy rain and flash flood events. I collected data on the Oceanic Niño Index (ONI), a measure of ENSO, as well as storm reports for each severe weather phenomenon dating back to 1959. Then, I analyzed the frequency of each Arizona severe weather event type within each of the twelve annual months and over the entire study period. I also analyzed mean intensity values (Fujita/Enhanced Fujita Scale rating, path width, and path length for tornadoes; hail diameter in millimeters for hail; and wind gust speed for severe thunderstorm wind events) for each severe weather phenomenon, excluding the heavy rain and flash flood events. Finally, I used the Mean Center and Directional Distribution tools in ArcGIS to determine variations in the spatial distribution and mean centers between each ENSO phase for each severe weather event type. I found that ENSO phase, particularly La Niña, does impact the frequency and intensity of tornadoes, hail, thunderstorm wind, and heavy rain/flash flood events in Arizona. However, it appears that ENSO does not affect the spatial distribution of these Arizona severe weather phenomena. These findings attempt to fill in the gap in the literature and could help meteorologists better forecast changes in Arizona severe weather, in turn allowing Arizonans to better prepare for and mitigate the effects of severe weather across the state.

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.

Large, violent storms come through the Phoenix area during monsoon season, and currently, the best ways to predict them are not very accurate. The primary goal of this investigation is to see if a mechanism can be developed for the prediction of these storms in Phoenix during monsoon season. In order to answer this question, two data sets (a remote sensing satellite imagery and a ground-based weather information set) will be used and their measurements will be compared against one another using a corresponding time as the related variable. The goal is to try and identify some type of correlation or explanation of correlation. Events known as moisture surges (from the gulf surge \u2014 which comes from the California Gulf) will be identified and then compared in some detail. These chutes of moisture surge through Arizona, primarily up through Yuma in a northeasterly direction. The point of the investigation is to prove or disprove that satellite imagery can be used as an analog for dew point measurements in areas where ground measurements are not available. If this can be demonstrated, then, because of the high temporal resolution of the remote sensing data, satellite imagery could be used as an identifier of oncoming storms.

The North American Monsoon (NAM) is a late summer increase in precipitation fundamentally caused by a wind shift that is evident in the southwestern United States and northwest Mexico from approximately June-August. Increased precipitation during these months bring an increased regional threat from heavy rains, blowing dust, and damaging storms. (Adams and Comrie 1997). Researchers in Phoenix, AZ theorized that using surface dewpoint measurements was an objective way to officially mark the start of the NAM in Phoenix, AZ (and Tucson, AZ). Specifically, they used three consecutive days at or above a certain dewpoint temperature (Franjevic 2017). The justification for this method was developed by Reitan (1957) who established that 25.4mm (1.00”) of integrated precipitable water (IPW) was a sufficient threshold to create storm activity in the NAM region. He also determined (Reitan 1963) that a strong correlation existed between (IPW) and surface dewpoint (Td), whereas, Td could be used as a proxy to determine IPW.

I hypothesize that the correlation coefficients between IPW and Td will be greatest when using seasonal mean averages of IPW and Td, and they will decrease with shortened mean timescales (from seasonal to three-days). Second, I hypothesize that there is a unique relationship between IPW/Td that may signal monsoon onset. To conduct this study, I used the North American Regional Reanalysis (NARR) dataset (1979-2015). For ten locations in the Southwest, I conducted a series of statistical analyses between IPW, Td, and accumulated precipitation. I determined that there is a correlation between the two as set forth by Reitan (1963) as well as (Benwell 1965; Smith 1966; Ojo 1970). However, from the results I concluded this relationship is highly variable, spatially and temporally. Additionally, when comparing the three-hour, three-day, and the weekly mean measurements, I can conclude that, for my study, timescale averaging did enhance the IPW/Td relationship from three-hour to weekly as expected. The temporal and spatial evolution of the IPW/Td correlation as presented in this thesis may provide a framework for future research that reevaluates the NAM’s domain and the associated methods for determining its onset.

This thesis examines the synoptic characteristics associated with ozone exceedance events in Arizona during the time period of 2011 to 2013. Finding explanations and sources to the ground level ozone in this state is crucial to maintaining the state’s adherence to federal air quality regulations. This analysis utilizes ambient ozone concentration data, surface meteorological conditions, upper air analyses, and HYSPLIT modeling to analyze the synoptic characteristics of ozone events. Based on these data and analyses, five categories were determined to be associated with these events. The five categories all exhibit distinct upper air patterns and surface conditions conducive to the formation of ozone, as well as distinct potential transport pathways of ozone from different nearby regions. These findings indicate that ozone events in Arizona can be linked to synoptic-scale patterns and potential regional transport of ozone. These results can be useful in the forecasting of high ozone pollution and influential on the legislative reduction of ozone pollution.