Thesis (Ph. D.)--UCLA, 2008. / Vita. Description based on print version record. Includes bibliographical references (leaves 322-345).

Thesis (Ph.D.)--University of Delaware, 2005. / Principal faculty advisor: Frederick Nelson, Dept. of Geography. Includes bibliographical references.

A lot of research has been conducted in the past decades on urban heat island (UHI) all over the world. Nevertheless, the UHI effect has not been included in weather data used by building services engineers to design buildings and size their heating and cooling plants. This research was carried out to investigate the UHI effect in Greater Manchester by setting up fixed point monitoring stations over the city. Woodford Met Office ground observation station was selected to be the rural reference point. A multiple regression model was developed to incorporate the heat island effect into the Manchester weather data for engineering usage.It was found that the urban heat island intensity (the difference between the rural and urban area temperatures) can be as high as 8°C in summer and 10°C in winter in Manchester. Clear and calm nocturnal temperature data was used (when maximum heat island occurs ) to find the relationship between the UHI intensity and sky view factor (SVF), distance away from the city centre, evapotranspiration fraction (EF), wind speed, cloud cover and rural reference temperature. Results indicate that all factors have a negative linear relationship with UHI intensity. All measured data were fed into a statistical software package to create general linear regression models. Validation showed that these models were capable of predicting average UHI effect to a good accuracy. The maximum heat island effect peaks are not so accurate. However, an analytical model was developed based on energy balance equations to predict the maximum heat island effect. Validation shows a good prediction for summer but not so good for winter. This is probably due to the lower average UHI intensity in winter than in summer.

The urban heat island (UHI) effect is a phenomenon that results in cities being warmer than the surrounding rural areas, due to a large amount of impervious surfaces. The purpose of this study is to evaluate the effectiveness of green roofs to mitigate the effects of solar energy on a building in the southern United States. In order to test the green roofs, temperatures were monitored inside and on top of unconditioned model buildings with green and with traditional roofs. Over the course of the study, the data collected showed that green roofs provided a significant benefit for the buildings by reducing daily high temperatures during summer and daily low temperatures during winter, while also reducing temperature fluctuation. The findings of this study suggest that a green roof will reduce indoor temperature and rooftop temperature, while providing several other benefits for city inhabitants such as reduced air temperature.

No description available.

Hui Shuk Ying. / Thesis submitted in: October 2004. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 135-149). / Abstracts in English and Chinese. / ACKNOWLEDGEMENTS --- p.ii / ABSTRACT --- p.iii / 中文摘要 --- p.v / TABLE OF CONTENTS --- p.vi / LIST OF TABLES --- p.viii / LIST OF FIGURES --- p.ix / LIST OF SYMBOLS --- p.xii / Chapter CHAPTER I --- INTRODUCTION --- p.1 / Chapter 1.1. --- Background --- p.1 / Chapter 1.2. --- Situation in Hong Kong --- p.4 / Chapter 1.3. --- Physical setting of Hong Kong --- p.7 / Chapter 1.4. --- Climate of Hong Kong --- p.9 / Chapter 1.5. --- Objectives of the study --- p.12 / Chapter 1.6. --- Significance of the study --- p.12 / Chapter 1.7. --- Organization of the thesis --- p.13 / Chapter CHAPTER II --- LITERATURE REVIEW --- p.14 / Chapter 2.1. --- Introduction --- p.14 / Chapter 2.2. --- Nature of Urban Heat Island (UHI) --- p.15 / Chapter 2.3. --- Characterization of UHI --- p.16 / Chapter 2.3.1. --- Diurnal variation --- p.17 / Chapter 2.3.2. --- Seasonal variation --- p.19 / Chapter 2.3.3. --- Spatial distribution of UHI --- p.20 / Chapter 2.4. --- Effects of weather factors on UHI intensity --- p.22 / Chapter 2.5. --- Relationship between urban factors and UHI intensity --- p.27 / Chapter CHAPTER III --- WEATHER DATA AND METHODOLOGY --- p.34 / Chapter 3.1. --- Surface meteorological observation --- p.34 / Chapter 3.1.1. --- Meteorological stations --- p.35 / Chapter 3.1.2. --- Methods of observation --- p.40 / Chapter 3.2. --- Acquisition and processing of data --- p.42 / Chapter 3.3. --- Detection of urban heat island in Hong Kong --- p.46 / Chapter 3.4. --- "Characterization of UHI intensity, frequency and temporal patterns" --- p.48 / Chapter 3.5. --- Evaluation of relationship between UHI intensity and weather conditions --- p.49 / Chapter 3.6. --- Evaluation of correlation between UHI intensity and city growth --- p.51 / Chapter CHAPTER IV --- RESULTS AND DISCUSSION --- p.52 / Chapter 4.1. --- Temperature evolution in Hong Kong --- p.52 / Chapter 4.1.1. --- Urban center --- p.52 / Chapter 4.1.2. --- New town --- p.57 / Chapter 4.1.3. --- Rural areas --- p.64 / Chapter 4.1.4. --- Discussion of the temperature changes in Hong Kong --- p.68 / Chapter 4.2. --- Urban heat island in Hong Kong --- p.75 / Chapter 4.2.1. --- Basic characteristics of UHI --- p.75 / Chapter 4.2.2. --- Annual patterns of UHI --- p.83 / Chapter 4.2.3. --- Seasonal patterns of UHI --- p.87 / Chapter 4.2.4. --- Discussion of the UHI phenomenon --- p.96 / Chapter 4.3. --- Weather effect on UHI intensity --- p.102 / Chapter 4.3.1. --- UHI phenomena and weather conditions --- p.103 / Chapter 4.3.2. --- Relationship between UHI intensity and meteorological elements --- p.106 / Chapter 4.3.3. --- Discussion of weather effects on UHI intensity --- p.115 / Chapter 4.4. --- Correlation of urban indicators and UHI intensity --- p.121 / Chapter CHAPTER V --- CONCLUSIONS AND RECOMMENDATIONS --- p.128 / Chapter 5.1. --- Summary of findings --- p.128 / Chapter 5.2. --- Limitation of the research --- p.133 / Chapter 5.3. --- Prospects of the study --- p.134 / REFERENCES --- p.135

Climate change has already increased the frequency, intensity, and duration of heat waves around the world. In the coming decades, this trend will continue and likely accelerate, exposing much of the world’s population to historically unprecedented conditions. In some regions, extreme temperatures (as indexed by the annual maximum temperature) are projected to increase at a faster rate than mean daily maximum temperatures. This dissertation shows that under a high emissions scenario, by 2060 – 2080 models project that the most extreme temperatures could warm by 1 – 2°C more than the warm season average in some regions. This amplified warming of the most extreme temperatures is most pronounced in the eastern U.S., Europe, eastern China, and parts of the Amazon rainforest, and may have substantial implications for heat risk in these regions. This dissertation explores the physical mechanisms driving the projected amplified warming of extremes in climate models and assesses the associated uncertainty. It shows that the amplification is linked to reductions in cloud cover, increased net surface shortwave radiation, and general surface drying as represented by declines in the evaporative fraction. In addition to rising temperatures, atmospheric humidity has been observed to increase in recent decades and models project this trend to continue. As a result, joint heat-humidity metrics indicating heat stress are likely to rapidly increase in the future. This dissertation explores how extreme wet bulb temperatures may change throughout the century and assesses the risk of exceeding a fundamental human heat tolerance limit that has been proposed in prior research. It then combines climate data with spatially explicit population projections to estimate the future population exposure to unprecedented wet bulb temperatures. Several regions stand out as being at particular risk: India, the coastal Middle East, and parts of West Africa are likely to experience extremely high wet bulb temperatures in the future, and rapidly growing populations in these regions will result in large increases in exposure to dangerous heat stress. In some areas, it is possible that wet bulb temperatures could occasionally exceed the proposed human tolerance limit by 2080 under a high emissions scenario, but limiting emissions to a moderate trajectory eliminates this risk. Nevertheless, even with emissions reductions, large portions of the world’s population are projected to experience unprecedented heat and humidity in the future. The projected changes in extreme temperatures will have a variety of impacts on infrastructure and other human systems. This dissertation explores how more frequent and severe hot conditions will impact aircraft takeoff performance by reducing air density and limiting the payload capacity of commercial aircraft. It uses performance models constructed for a variety of aircraft types and projected temperatures to assess the payload reductions that may be required in the future. These payload limits, along with sea level rise, changes in storm patterns, increased atmospheric turbulence, and other effects of climate change, stand to have significant economic and operational impacts on the aviation industry. Finally, this dissertation discusses evidence-based adaptation strategies to reduce the impacts of extreme heat in urban areas. It reviews a body of literature showing that effective strategies exist to both lower urban temperatures on a large scale and drastically reduce heat-related mortality during heat waves. Many adaptation techniques are not costly, but have yet to be widely implemented. Given the rapid increases in climate impacts that are projected in the coming decades, it will be essential to rigorously assess the cost-effectiveness of adaptation techniques and implement the most efficient strategies in both high- and low-income areas.

This study examines the relationship between land use and temperature change in Dallas County, TX. The purpose of this research is to analyze the relationship between temperature and land use and to identify the primary factors contributing to the formation of urban heat islands based on different categories of land use. Specifically, this research analyzes the elements that contribute to the urban heat island effect in Dallas County using temperature data provided by remote sensing imagery and parcel-based land use data using Geographic Information System (GIS) technique and a correlation analysis method, which was employed to analyze the relationship between temperature and land use. The results of this study showed that every land use category has different temperature averages and those patterns were observed similarly in both 2000 and 2005. Parking, airport, commercial, industrial, and residential areas have relatively high temperatures. In contrast, water, undeveloped area and parks showed relatively low temperatures. Another major finding was ratio of land use composition affected the temperature of census tracts. Correlation analyses of land use and temperature in 2000 and 2005 indicate that various types of land use categories have significant relationships with temperature. Among them commercial, industrial, residential, parking, and infrastructure, are positively associated with temperature, while undeveloped, parks, water, and dedicated areas are negatively associated with temperature. Areas with a high ratio of commercial use showed the highest and undeveloped areas showed the lowest relationship. Furthermore, through the analysis of the relationship between land use and temperature change for five years (2000-2005), this study finds that temperature change depends on the ratio of each land use category change. The results of this study can help local planning and policy decisions which are related to urban land use planning concerning temperature change such as zoning, environmental regulations and open space preservation.

Population growth and urban sprawl have contributed to the formation of significant urban heat island phenomena in Houston, Texas, the fourth largest city in the United States. The population growth in Houston was 25.8% between 1990 and 2000 nearly double the national average. The demand for information concerning the effects of urban and suburban development is growing. Houston is currently the only major US city lacking any kind of comprehensive city zoning ordinances. The Normalized Difference Vegetation Index (NDVI) has been used as a surrogate variable to estimate land surface temperatures at higher spatial resolutions, given the fact that a high-resolution remotely sensed NDVI can be created almost effortlessly and remotely sensed thermal data at higher resolutions is much more difficult to obtain. This has allowed researchers to study urban heat island dynamics at a micro-scale. However, this study suggests that a vegetation index alone might not be the best surrogate variable for providing information regarding the independent effects and level of contribution that tree canopy, grass, and low-lying plants have on surface temperatures in residential neighborhoods. This research combines LIDAR (Light Detection and Ranging) feature height data and high-resolution infrared aerial photos to measure the characteristics of the micro-structure of residential areas (residentialstructure), derives various descriptive vegetation measurement statistics, and correlates the spatial distribution of surface temperature to the type and amount of vegetation cover in residential areas. Regression analysis is used to quantify the independent influence that different residential-structures have on surface temperature. In regard to implementing changes at a neighborhood level, the descriptive statistics derived for residential-structure at a micro-scale may provide useful information to decision-makers and may reveal a guide for future developers concerned with mitigating the negative effects of urban heat island phenomena.

Thesis (M. Phil.)--University of Hong Kong, 2009. / Includes bibliographical references (leaves 118-122). Also available in print.