Matching Items (37)
Description
The characteristics of the wintertime 500hPa height surface, the level of non-divergence and used for identifying/observing synoptic-scale features (ridges and troughs), and their impact on precipitation are of significance to forecasters, natural resource managers and planners across the southwestern United States. For this study, I evaluated the location of the 500hPa mean Pacific ridge axis over the winter for the period of 1948/49 to 2011/12 and derived the mean ridge axis in terms of location (longitude) and intensity (geopotential meters) from the NCEP/NCAR Reanalysis dataset. After deriving a mean ridge axis climatology and analyzing its behavior over time, I correlated mean location and intensity values to observed wintertime precipitation in select U.S. Climate Divisions in Arizona, Colorado, Nevada, Utah and New Mexico. This resulted in two findings. First specific to the 500hPa ridge behavior, the ridge has been moving eastward and also has been intensifying through time. Second, results involving correlation tests between mean ridge location and intensity indicate precipitation across the selected Southwest Climate Divisions are strongly related to mean ridge intensity slightly more than ridge location. The relationships between mean ridge axis and observed precipitation also are negative, indicating an increase of one of the ridge parameters (i.e. continued eastward movement or intensification) lead to drier winter seasons across the Southwest. Increased understanding of relationships between upper-level ridging and observed wintertime precipitation aids in natural resource planning for an already arid region that relies heavily on winter precipitation.
ContributorsNolte, Jessica Marie (Author) / Cerveny, Randall S. (Thesis advisor) / Selover, Nancy J. (Committee member) / Brazel, Anthony J. (Committee member) / Arizona State University (Publisher)
Created2013
Description
Global climate change (GCC) is among the most important issues of the 21st century. Adaptation to and mitigation of climate change are some of the salient local and regional challenges scientists, decision makers, and the general public face today and will be in the near future. However, designed adaptation and mitigation strategies do not guarantee success in coping with global climate change. Despite the robust and convincing body for anthropogenic global climate change research and science there is still a significant gap between the recommendations provided by the scientific community and the actual actions by the public and policy makers. In order to design, implement, and generate sufficient public support for policies and planning interventions at the national and international level, it is necessary to have a good understanding of the public's perceptions regarding GCC. Based on survey research in nine countries, the purpose of this study is two-fold: First, to understand the nature of public perceptions of global climate change in different countries; and secondly to identi-fy perception factors which have a significant impact on the public's willingness to sup-port GCC policies or commit to behavioral changes to reduce GHG emissions. Factors such as trust in GCC information which need to be considered in future climate change communication efforts are also dealt with in this dissertation. This study has identified several aspects that need to be considered in future communication programs. GCC is characterized by high uncertainties, unfamiliar risks, and other characteristics of hazards which make personal connections, responsibility and engagement difficult. Communication efforts need to acknowledge these obstacles, build up trust and motivate the public to be more engaged in reducing GCC by emphasizing the multiple benefits of many policies outside of just reducing GCC. Levels of skepticism among the public towards the reality of GCC as well as the trustworthiness and sufficien-cy of the scientific findings varies by country. Thus, communicators need to be aware of their audience in order to decide how educational their program needs to be.
ContributorsHagen, Bjoern (Author) / Pijawka, David (Thesis advisor) / Brazel, Anthony (Committee member) / Chhetri, Netra (Committee member) / Guhathakurta, Subhrajit (Committee member) / Arizona State University (Publisher)
Created2013
Description
Droughts are a common phenomenon of the arid South-west USA climate. Despite water limitations, the region has been substantially transformed by agriculture and urbanization. The water requirements to support these human activities along with the projected increase in droughts intensity and frequency challenge long term sustainability and water security, thus the need to spatially and temporally characterize land use/land cover response to drought and quantify water consumption is crucial. This dissertation evaluates changes in `undisturbed' desert vegetation in response to water availability to characterize climate-driven variability. A new model coupling phenology and spectral unmixing was applied to Landsat time series (1987-2010) in order to derive fractional cover (FC) maps of annuals, perennials, and evergreen vegetation. Results show that annuals FC is controlled by short term water availability and antecedent soil moisture. Perennials FC follow wet-dry multi-year regime shifts, while evergreen is completely decoupled from short term changes in water availability. Trend analysis suggests that different processes operate at the local scale. Regionally, evergreen cover increased while perennials and annuals cover decreased. Subsequently, urban land cover was compared with its surrounding desert. A distinct signal of rain use efficiency and aridity index was documented from remote sensing and a soil-water-balance model. It was estimated that a total of 295 mm of water input is needed to sustain current greenness. Finally, an energy balance model was developed to spatio-temporally estimate evapotranspiration (ET) as a proxy for water consumption, and evaluate land use/land cover types in response to drought. Agricultural fields show an average ET of 9.3 mm/day with no significant difference between drought and wet conditions, implying similar level of water usage regardless of climatic conditions. Xeric neighborhoods show significant variability between dry and wet conditions, while mesic neighborhoods retain high ET of 400-500 mm during drought due to irrigation. Considering the potentially limited water availability, land use/land cover changes due to population increases, and the threat of a warming and drying climate, maintaining large water-consuming, irrigated landscapes challenges sustainable practices of water conservation and the need to provide amenities of this desert area for enhancing quality of life.
ContributorsKaplan, Shai (Author) / Myint, Soe Win (Thesis advisor) / Brazel, Anthony J. (Committee member) / Georgescu, Matei (Committee member) / Arizona State University (Publisher)
Created2014
Description
Winter storms decrease the safety of roadways as it brings ice and snow to the roads and increases accidents, delays, and travel time. Not only are personal vehicles affected, but public transportation, commercial transportation, and emergency vehicles are affected as well. Portland, Oregon, and Seattle, Washington, both suffer from mild, but sometimes extreme, storms that affect the entire city. Taking a closer look at the number of crashes reported by the City of Portland and the City of Seattle, it is seen that there is an increase in percent of crashes with reported road conditions of snow and ice. Both cities appear to have nearly the same reported crash percentages. Recommendations in combating the issue of increased accidents and the disruption of the city itself include looking into communication between the climate research institution and city planners that could help with planning for better mitigation during storms, a street or gas tax, although an impact study is important to keep in mind to make sure no part of the population is at risk; and engineering revolutions such as Solar Roadways that could benefit all cities.
ContributorsHoots, Danielle (Author) / Crewe, Katherine (Thesis advisor) / Golub, Aaron (Committee member) / Brazel, Anthony (Committee member) / Arizona State University (Publisher)
Created2015
Description
This doctoral dissertation research aims to develop a comprehensive definition of urban open spaces and to determine the extent of environmental, social and economic impacts of open spaces on cities and the people living there. The approach I take to define urban open space is to apply fuzzy set theory to conceptualize the physical characteristics of open spaces. In addition, a 'W-green index' is developed to quantify the scope of greenness in urban open spaces. Finally, I characterize the environmental impact of open spaces' greenness on the surface temperature, explore the social benefits through observing recreation and relaxation, and identify the relationship between housing price and open space be creating a hedonic model on nearby housing to quantify the economic impact. Fuzzy open space mapping helps to investigate the landscape characteristics of existing-recognized open spaces as well as other areas that can serve as open spaces. Research findings indicated that two fuzzy open space values are effective to the variability in different land-use types and between arid and humid cities. W-Green index quantifies the greenness for various types of open spaces. Most parks in Tempe, Arizona are grass-dominant with higher W-Green index, while natural landscapes are shrub-dominant with lower index. W-Green index has the advantage to explain vegetation composition and structural characteristics in open spaces. The outputs of comprehensive analyses show that the different qualities and types of open spaces, including size, greenness, equipment (facility), and surrounding areas, have different patterns in the reduction of surface temperature and the number of physical activities. The variance in housing prices through the distance to park was, however, not clear in this research. This dissertation project provides better insight into how to describe, plan, and prioritize the functions and types of urban open spaces need for sustainable living. This project builds a comprehensive framework for analyzing urban open spaces in an arid city. This dissertation helps expand the view for urban environment and play a key role in establishing a strategy and finding decision-makings.
ContributorsKim, Won Kyung (Author) / Wentz, Elizabeth (Thesis advisor) / Myint, Soe W (Thesis advisor) / Brazel, Anthony (Committee member) / Guhathakurta, Subhrajit (Committee member) / Arizona State University (Publisher)
Created2011
Description
Isentropic analysis is a type of analysis that is based on using the concept of potential temperatures, the adiabatically established temperature at 1000 hPa. In the 1930s and 1940s this type of analysis proved to be valuable in indicating areas of increased moisture content and locations experiencing flow up or down adiabatic surfaces. However, in the early 1950s, this type of analysis faded out of use and not until the twenty-first century have some researchers started once again to examine the usefulness of isentropic analysis. One aspect in which isentropic analysis could be practical, based on prior research, is in severe weather situations, due to its ability to easily show adiabatic motion and moisture. As a result, I analyzed monthly climatological isentropic surfaces to identify distinct patterns associated with tornado occurrences for specific regions and months across the contiguous United States. I collected tornado reports from 1974 through 2009 to create tornado regions for each month across the contiguous United States and corresponding upper air data for the same time period. I then separated these upper air data into tornado and non-tornado days for specific regions and conducted synoptic and statistical analyses to establish differences between the two. Finally, I compared those results with analyses of individual case studies for each defined region using independent data from 2009 through 2010. On tornado days distinct patterns can be identified on the isentropic surface: (1) the average isentropic surface lowered on tornado days indicating a trough across the region, (2) a corresponding increase in moisture content occurred across the tornado region, and (3) wind shifted in such a manner to produce flow up the isentropic trough indicating uplift. When comparing the climatological results with the case studies, the isentropic pattern for the case studies in general was more pronounced compared to the climatological pattern; however, this would be expected as when creating the average the pattern/conditions will be smoothed. These findings begin to bridge the large gap in literature, show the usefulness of isentropic analysis in monthly and daily use and serve as catalysts to create a finer resolution database in isentropic coordinates.
ContributorsPace, Matthew Brandon (Author) / Cerveny, Randall S. (Thesis advisor) / Selover, Nancy J (Committee member) / Brazel, Anthony J. (Committee member) / Arizona State University (Publisher)
Created2012
Description
Large-scale cultivation of perennial bioenergy crops (e.g., miscanthus and switch-
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.
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.
ContributorsWang, Meng, Ph.D (Author) / Kamarianakis, Yiannis (Thesis advisor) / Georgescu, Matei (Thesis advisor) / Fotheringham, A. Stewart (Committee member) / Moustaoui, Mohamed (Committee member) / Reiser, Mark R. (Committee member) / Arizona State University (Publisher)
Created2018
Description
Severe weather affects many regions of the United States, and has potential to greatly impact many facets of society. This study provides a climatological spatial analysis by county of severe weather warnings issued by the National Weather Service (NWS) between January 1st, 1986 to December 31st, 2017 for the contiguous United States. The severe weather warnings were issued for county-based flash flood, severe thunderstorm, and tornado phenomena issued through the study period and region. Post 2002 severe weather warnings issued by storm warning area were included in this study in the form of county-based warnings simultaneously issued for each affected county. Past studies have researched severe weather warnings issued by the NWS, however these studies are limited in geographic representation, study period, and focused on population bias. A spatial analysis of severe weather warning occurrences by county identify that (a) highest occurrences of flash flood warnings are located in the desert Southwest and Texas, (b) severe thunderstorm warning occurrence is more frequent in Arizona, portions of the Midwest, the South, and the Mid and South Atlantic states, (c) the tornado activity regions of Tornado Alley and Dixie Alley (i.e. Colorado, Kansas, Oklahoma, Arkansas, Texas, Louisiana, Mississippi, Alabama, Tennessee, and Illinois) contained the highest occurrences of tornado warnings, and (d) the highest instances of aggregate warning occurrences are found in the desert Southwest, the Midwest, and the Southern regions of the United States. Generally, severe weather warning “hot spots” tend to be located in those same regions, with greater coverage. This study concludes with a comparison of local maxima and general hot spot regions to expected regions for each phenomenon. Implications of this study are far reaching, including emergency management, and has potential to reduce risk of life.
ContributorsLawhorn, Brandon (Author) / Cerveny, Randall S. (Thesis advisor) / Balling, Robert C. (Committee member) / Vose, Russel S (Committee member) / Krahenbuhl, Daniel (Committee member) / Arizona State University (Publisher)
Created2019
Description
Monsoon hazards routinely affect the community, economy, and environment of the American Southwest. A common link for hazard development during the North American Monsoon concerns the interplay between temperature, moisture, and wind in the vertical atmosphere controlled by an unstable monsoon circulation. This dissertation investigates vertical atmospheric patterns using in-situ sounding data, specifically, 1) environments favorable for severe hail on the Colorado Plateau, 2) significant parameters distinguishing unhealthy versus healthy ozone days in Phoenix, Arizona, and 3) vertical profile alignments associated with distinct ranges in ozone concentrations observed in Phoenix having defined health impacts.
The first study (published in the Journal of the Arizona-Nevada Academy of Science) determines significant variables on Flagstaff, Arizona 12Z rawinsonde data (1996-2009) found on severe hail days on the Colorado Plateau. Severe hail is related to greater sub-300 hectopascals (hPa) moisture, a warmer atmospheric column, lighter above surface wind speeds, more southerly to southeasterly oriented winds throughout the vertical (except at the 700 hPa pressure level), and higher geopotential heights.
The second study (published in Atmospheric Environment) employs principal component, linear discriminant, and synoptic composite analyses using Phoenix, Arizona rawinsonde data (2006-2016) to identify common monsoon patterns affecting ozone accumulation in the Phoenix metropolitan area. Unhealthy ozone occurs with amplified high-pressure ridging over the Four Corners region, 500 hPa heights often exceeding 5910 meters, surface afternoon temperatures typically over 40°C, lighter wind speeds in the planetary boundary layer under four ms-1, and persistent light easterly flow between 700-500 hPa countering the daytime mountain-valley circulation.
The final study (under revision in Weather and Forecasting) assesses composite atmospheric sounding analysis to forecast Air Quality Index ozone classifications of Good, Moderate, and collectively categories exceeding the U.S. EPA 2015 standard. The analysis, using Phoenix 12Z rawinsonde data (2006-2017), identifies the existence of “pollutant dispersion windows” for ozone accumulation and dispersal in Phoenix.
Ultimately, monsoon hazards result from a complex and evolving vertical atmosphere. This dissertation demonstrates the viability using available in-situ vertical upper-air data to anticipate recurring atmospheric states contributing to specific hazards. These results will improve monsoon hazard prediction in an effort to protect public and infrastructure.
The first study (published in the Journal of the Arizona-Nevada Academy of Science) determines significant variables on Flagstaff, Arizona 12Z rawinsonde data (1996-2009) found on severe hail days on the Colorado Plateau. Severe hail is related to greater sub-300 hectopascals (hPa) moisture, a warmer atmospheric column, lighter above surface wind speeds, more southerly to southeasterly oriented winds throughout the vertical (except at the 700 hPa pressure level), and higher geopotential heights.
The second study (published in Atmospheric Environment) employs principal component, linear discriminant, and synoptic composite analyses using Phoenix, Arizona rawinsonde data (2006-2016) to identify common monsoon patterns affecting ozone accumulation in the Phoenix metropolitan area. Unhealthy ozone occurs with amplified high-pressure ridging over the Four Corners region, 500 hPa heights often exceeding 5910 meters, surface afternoon temperatures typically over 40°C, lighter wind speeds in the planetary boundary layer under four ms-1, and persistent light easterly flow between 700-500 hPa countering the daytime mountain-valley circulation.
The final study (under revision in Weather and Forecasting) assesses composite atmospheric sounding analysis to forecast Air Quality Index ozone classifications of Good, Moderate, and collectively categories exceeding the U.S. EPA 2015 standard. The analysis, using Phoenix 12Z rawinsonde data (2006-2017), identifies the existence of “pollutant dispersion windows” for ozone accumulation and dispersal in Phoenix.
Ultimately, monsoon hazards result from a complex and evolving vertical atmosphere. This dissertation demonstrates the viability using available in-situ vertical upper-air data to anticipate recurring atmospheric states contributing to specific hazards. These results will improve monsoon hazard prediction in an effort to protect public and infrastructure.
ContributorsMalloy, Jonny William (Author) / Cerveny, Randall S. (Thesis advisor) / Selover, Nancy J (Committee member) / Brazel, Anthony J. (Committee member) / Balling, Robert C. (Committee member) / Arizona State University (Publisher)
Created2019
Description
The Western Continental United States has a rapidly changing and complex ecosystem that provides valuable resources to a large portion of the nation. Changes in social and environmental factors have been observed to be significantly correlated to usable ground and surface water levels. The assessment of water level changes and their influences on a semi-national level is needed to support planning and decision making for water resource management at local levels. Although many studies have been done in Ground and Surface Water (GSW) trend analysis, very few have attempted determine correlations with other factors. The number of studies done on correlation factors at a semi-national scale and near decadal temporal scale is even fewer. In this study, freshwater resources in GSW changes from 2004 to 2017 were quantified and used to determine if and how environmental and social variables are related to GSW changes using publicly available remotely sensed and census data. Results indicate that mean annual changes of GSW of the study period are significantly correlated with LULC changes related to deforestation, urbanization, environmental trends, as well as social variables. Further analysis indicates a strong correlation in the rate of change of GSW to LULC changes related to deforestation, environmental trends, as well as social variables. GSW slope trend analysis also reveals a negative trend in California, New Mexico, Arizona, and Nevada. Whereas a positive GSW trend is evident in the northeast part of the study area. GSW trends were found to be somewhat consistent in the states of Utah, Idaho, and Colorado, implying that there was no GSW changes over time in these states.
ContributorsReynolds, Ryan (Author) / Myint, Soe (Thesis advisor) / Werth, Susanna (Committee member) / Brazel, Anthony (Committee member) / Arizona State University (Publisher)
Created2018