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Impacts of Landscape Modifications on Urban Boundary Layer Dynamics in Current and Projected Climate
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grass) offers unique opportunities to mitigate climate change through avoided fossil fuel use and associated greenhouse gas reduction. Although conversion of existing agriculturally intensive lands (e.g., maize and soy) to perennial bioenergy cropping systems has been shown to reduce near-surface temperatures, unintended consequences on natural water resources via depletion of soil moisture may offset these benefits. In the effort of the cross-fertilization across the disciplines of physics-based modeling and spatio-temporal statistics, three topics are investigated in this dissertation aiming to provide a novel quantification and robust justifications of the hydroclimate impacts associated with bioenergy crop expansion. Topic 1 quantifies the hydroclimatic impacts associated with perennial bioenergy crop expansion over the contiguous United States using the Weather Research and Forecasting Model (WRF) dynamically coupled to a land surface model (LSM). A suite of continuous (2000–09) medium-range resolution (20-km grid spacing) ensemble-based simulations is conducted. Hovmöller and Taylor diagrams are utilized to evaluate simulated temperature and precipitation. In addition, Mann-Kendall modified trend tests and Sieve-bootstrap trend tests are performed to evaluate the statistical significance of trends in soil moisture differences. Finally, this research reveals potential hot spots of suitable deployment and regions to avoid. Topic 2 presents spatio-temporal Bayesian models which quantify the robustness of control simulation bias, as well as biofuel impacts, using three spatio-temporal correlation structures. A hierarchical model with spatially varying intercepts and slopes display satisfactory performance in capturing spatio-temporal associations. Simulated temperature impacts due to perennial bioenergy crop expansion are robust to physics parameterization schemes. Topic 3 further focuses on the accuracy and efficiency of spatial-temporal statistical modeling for large datasets. An ensemble of spatio-temporal eigenvector filtering algorithms (hereafter: STEF) is proposed to account for the spatio-temporal autocorrelation structure of the data while taking into account spatial confounding. Monte Carlo experiments are conducted. This method is then used to quantify the robustness of simulated hydroclimatic impacts associated with bioenergy crops to alternative physics parameterizations. Results are evaluated against those obtained from three alternative Bayesian spatio-temporal specifications.
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Blue colors are often iridescent in nature and the effect of iridescence on warning signal function was unknown. I reared B. philenor larvae under varied food deprivation treatments. Iridescent colors did not have more variation than pigment-based colors under these conditions; variation which could affect predator learning. Learning could also be affected by changes in appearance, as iridescent colors change in both hue and brightness as the angle of illuminating light and viewer change in relation to the color surface. Iridescent colors can also be much brighter than pigment-based colors and iridescent animals can statically display different hues. I tested these potential effects on warning signal learning by domestic chickens (Gallus gallus domesticus) and found that variation due to the directionality of iridescence and a brighter warning signal did not influence learning. However, blue-violet was learned more readily than blue-green. These experiments revealed that the directionality of iridescent coloration does not likely negatively affect its potential effectiveness as a warning signal.
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Numerical simulations using a state-of-the-science regional climate model are utilized to address a trio of scientifically relevant questions with wide global applicability. The importance of an accurate representation of land use and land cover is first demonstrated through comparison of numerical simulations against observations. Second, the simulated effect of anthropogenic heating is quantified. Lastly, numerical simulations are performed using pre-historic scenarios of land use and land cover to examine and quantify the impact of Mexico City's urban expansion and changes in surface water features on its regional climate.
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Exertional heat stroke continues to be one of the leading causes of illness and death in sport in the United States, with an athlete’s experienced microclimate varying by venue design and location. A limited number of studies have attempted to determine the relationship between observed wet bulb globe temperature (WBGT) and WBGT derived from regional weather station data. Moreover, only one study has quantified the relationship between regionally modeled and on-site measured WBGT over different athletic surfaces (natural grass, rubber track, and concrete tennis court). The current research expands on previous studies to examine how different athletic surfaces influence the thermal environment in the Phoenix Metropolitan Area using a combination of fieldwork, modeling, and statistical analysis. Meteorological data were collected from 0700–1900hr across 6 days in June and 5 days in August 2019 in Tempe, Arizona at various Sun Devil Athletics facilities. This research also explored the influence of surface temperatures on WBGT and the changes projected under a future warmer climate. Results indicate that based on American College of Sports Medicine guidelines practice would not be cancelled in June (WBGT≥32.3°C); however, in August, ~33% of practice time was lost across multiple surfaces. The second-tier recommendations (WBGT≥30.1°C) to limit intense exercise were reached an average of 7 hours each day for all surfaces in August. Further, WBGT was calculated using data from four Arizona Meteorological Network (AZMET) weather stations to provide regional WBGT values for comparison. The on-site (field/court) WBGT values were consistently higher than regional values and significantly different (p<0.05). Thus, using regionally-modeled WBGT data to guide activity or clothing modification for heat safety may lead to misclassification and unsafe conditions. Surface temperature measurements indicate a maximum temperature (170°F) occurring around solar noon, yet WBGT reached its highest level mid-afternoon and on the artificial turf surface (2–5PM). Climate projections show that WBGT values are expected to rise, further restricting the amount of practice and games than can take place outdoors during the afternoon. The findings from this study can be used to inform athletic trainers and coaches about the thermal environment through WBGT values on-field.
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The first paper of this dissertation found that divergent design intentions lead to unique trajectories for LSA, the urban heat island effect, and bird community at two urban riparian sites in the Phoenix metropolitan area. The second paper examined institutional shifts that occurred during Cuba’s “special period in time of peace” and found that the resulting land tenure changes both modified and maintained the LSA of the country, changing cropland but preserving forest land. The third paper found that globalized forces may be contributing to the homogenizing urban form of large, populous cities in China, India, and the United States—especially for the ten largest cities in each country—with implications for surface urban heat island intensity. Expanding knowledge on social drivers of land system and environmental change provides insights on designing landscapes that optimize for a range of social and ecological trade-offs.