Thesis (M.S.)--University of Delaware, 2009. / Principal faculty advisor: Michael A. O'Neal, Dept. of Geography. Includes bibliographical references.

Thesis (M.S.)--Mississippi State University. Department of Geosciences. / Title from title screen. Includes bibliographical references.

Thesis (M.S.)--University of Toledo, 2008. / Typescript. "Submitted as partial fulfillments of the requirements for The Master of Science in Biology." "A thesis entitled"--at head of title. Bibliography: leaves 35-40.

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.

Humans’ ability to combat heat stress through sweat-based evaporative cooling is modulated by air temperature and humidity, rendering human health highly sensitive to humid heat extremes. While the field of climate science has studied extreme dry bulb temperatures for decades, exploration of the physical drivers producing extreme humid heat is nascent in comparison. Two major areas of development for the evolving field are: 1) improving understanding of the local drivers of extreme humid heat, and 2) collating a set of universal physical mechanisms which generate humid heat extremes across the planet. The four chapters of this dissertation together advance each of these goals. Chapter 1 relates the occurrence of extreme humid heat in the Persian Gulf and South Asia to two related modes of intraseasonal climate variability, namely the Madden–Julian oscillation (MJO) and the boreal summer intraseasonal oscillation (BSISO). Wet bulb temperatures (Tw) sufficiently high to impact human health are found to be almost twice as likely during certain oscillation phases than in others. Humid heat anomalies in each region are driven by distinct local circulation patterns and variations in moisture. Chapter 2 evaluates the influence of monsoon onset and subseasonal precipitation variability on the occurrence of extreme Tw across South Asia. Extreme Tw events often occur on rainy days during the monsoon season. However, the influence of precipitation on Tw varies with the background specific humidity climatology. In climatologically drier areas, positive Tw anomalies tend to occur when precipitation increases due to either early onset or wet spells during the monsoon. In contrast, in climatologically humid areas, positive Tw anomalies occur during periods of suppressed precipitation, including delayed onset and dry spells during the monsoon. Chapter 3 analyzes the dynamics of the record-breaking extreme heat event in Rio de Janeiro in November 2023. The heatwave was associated with persistent atmospheric blocking, potentially linked to developing El Niño conditions. Temperatures were intensified by declining soil moisture and elevated local sea surface temperatures, and the event was finally terminated due to the onset of precipitation. This chapter also evaluates the influence of climate change on the frequency of heat extremes, finding a significant increase in the frequency of high heat days throughout Brazil over the past four decades. Further, the frequency of spring heat extremes is expected to increase in the future, though highly dependent upon our future emissions pathway. Chapter 4 explores the combinations of temperature and humidity contributing to humid heat experienced across the globe. In addition to using traditional metrics, this chapter derives a novel variable named “stickiness,” which quantifies the relative contributions of temperature and specific humidity to a given Tw. Consistent across metrics, high magnitudes of Tw tend to occur in the presence of anomalously high moisture, with temperature anomalies of secondary importance. Nonetheless, there is a broad range of stickiness observed for a given Tw across moderate-to-high Tw thresholds relevant to socioeconomic impacts.

MENVSC (Climatology) / Department of Geography and Geo-Information Sciences / Heat waves are warm extreme temperature events that have environmental and socio-economic impacts in many regions across the world. Negative impacts of warm extreme temperatures over South Africa necessitate the need to study the nature of heat waves. Observations and satellite datasets are analysed in the investigation of the nature and trends of heat waves over South Africa in the present (1983-2012) and future (2010-2039, 2040-2069, 2070-2099) climates. Case study and composite analysis of National Centers for Environmental Prediction datasets were done using the Grids Analysis and Display Systems to get an in-depth understanding of the structure of heat waves in South Africa. Future climate model output obtained from the Conformal Cubic Atmospheric Model was used for future heat wave trends in South Africa. The simulations were made using the Representative Concentration Pathways 4.5 and 8.5. Heat waves are unusual events in the present climate (1983-2012) over much of the country, with 20 of the selected 24 stations experiencing an average of less than one heat wave per season. Heat waves are also more frequent and last longer during warm phase of El Niño-Southern Oscillation (ENSO) than in cool phase of ENSO with the north-east being the most prone region. Composite analysis of 500 hPa omega indicates subsidence over the interior of South Africa in both phases of ENSO. Heat waves in South Africa are localized and associated with a middle level high pressure system that persists over the interior inducing anticyclonic flow and subsidence. The anticyclonic circulation over a region experiencing heat wave weakens with decreasing height over land areas which may be due to frictional forces at the surface and the high is placed further south-east at the surface. Advection of dry continental northerly winds also contributes to high maximum temperatures during heat waves in the interior. Maximum temperatures are expected to increase drastically from the present-day climate to the 2070 – 2099 period, with an average increment of about 8°C during DJF in much of the central interior. As a result, heat wave occurrences are expected to be higher in the future warmer climates when climate change signal is higher. Most increases are expected for heat waves lasting for a week than those lasting for over 2 weeks. CCAM outputs also indicated that heat waves in South Africa are expected to last longer and become more intense during the future warmer climates. Longer lasting and more intense heat waves are expected over the Karoo than in other parts of the country.

Indiana University-Purdue University Indianapolis (IUPUI) / During a 2011 summer dominated by headlines about an earthquake and a hurricane along the East Coast, extreme heat that silently killed scores of Americans largely went unnoticed by the media and public. However, despite a violent spasm of tornadic activity that claimed over 500 lives during the spring of the same year, heat-related mortality annually ranks as the top cause of death incident to weather. Two major data groups used in researching vulnerability to extreme heat events (EHE) include socioeconomic indicators of risk and factors incident to urban living environments. Socioeconomic determinants such as household income levels, age, race, and others can be analyzed in a geographic information system (GIS) when formatted as vector data, while environmental factors such as land surface temperature are often measured via raster data retrieved from satellite sensors. The current research sought to combine the insights of both types of data in a comprehensive examination of heat susceptibility using knowledge-based classification. The use of knowledge classifiers is a non-parametric approach to research involving the creation of decision trees that seek to classify units of analysis by whether they meet specific rules defining the phenomenon being studied. In this extreme heat vulnerability study, data relevant to the deadly July 1995 heat wave in Chicago’s Cook County was incorporated into decision trees for 13 different experimental conditions. Populations vulnerable to heat were identified in five of the 13 conditions, with predominantly low-income African-American communities being particularly at-risk. Implications for the results of this study are given, along with direction for future research in the area of extreme heat event vulnerability.

The terrestrial water, energy and carbon cycles are tightly coupled through land-atmosphere (L-A) interactions, not only regulating local plant physiological activities and also modulating regional and global climate. With ongoing anthropogenic greenhouse gas emissions, many of these interactions can be modified and complicated. To better anticipate and adapt to future climate, it is of great importance and necessity to deepen and refine our understanding of the complex L-A interactions. In this dissertation, three topics are investigated across the ecosystem, regional and global scales respectively, throughout which, the critical role of dryness or drying in the context of global warming is highlighted. 𝐂𝐡𝐚𝐩𝐭𝐞𝐫 𝟏: Evapotranspiration (ET) is a key component that connects the continental water, carbon and energy cycles and a proxy that measures the coupling strength between the biosphere and atmosphere. A wide range of biophysical factors, which usually exhibit nonlinearity and strong covariation, collectively modulate ET and complicate the overall understanding of ET dynamics. In the first study, the causal discovery frameworks PCMCI+ and Latent PCMCI are utilized with integrated priori physical knowledge to identify the dominant drivers and constraints of ET in the growing seasons across sites, with a particular focus on the role of site dryness degree. The Dryness Index (DI), defined as the ratio of annual mean net radiation to precipitation, has been introduced to assess the water availability relative to energy supply at different locations. By analyzing the daily observations from 115 flux tower sites and satellite remote sensing, it has been discovered that the feedbacks around ET are mediated by the degree of dryness: at sites with adequate water supply (using PCMCI+, the DI value averaged from such sites is 1.33), the atmospheric conditions, including incoming solar radiation and atmospheric demand for water (indicated by vapor pressure deficit, VPD), prevail in driving ET; in contrast, in semi-arid and arid areas where the water stress is high (using PCMCI+, the DI value averaged from such sites is 3.32), soil water content is the primary factor to constrain ET due to the plant regulation of stomatal conductance as part of the water conservation strategy. Additionally, as DI increases across sites, the sign of the contemporaneous causal relationship between VPD and ET can reverse from positive—indicating that atmospheric demand for water drives ET—to negative—reflecting that plant stomatal closure limits ET in response to the dryer atmosphere. 𝐂𝐡𝐚𝐩𝐭𝐞𝐫 𝟐: As summer heatwaves and droughts are becoming more frequent and intense, such as in Western Europe, there is a growing interest in unraveling the physical mechanisms behind their occurrences and their changes. Soil desiccation is critical for the intensification and propagation of heatwaves, but its relative importance compared to other well-known large-scale atmospheric mechanisms, such as persistent atmospheric blocking systems and horizontal warm advection, remains elusive, especially in the context of a changing climate. In the second study, we utilize machine learning along with intervention experiments to estimate the respective contributions of soil water content 𝐶_𝑠𝑤𝑐 and atmospheric circulation 𝐶_𝑎𝑡𝑚 to daily maximum temperature in Western Europe, with a particular focus on the 2022 summer events. Our results reveal that during the two unparalleled heatwave events that occurred in June and July of 2022, the impact 𝐶_𝑠𝑤𝑐 on the heatwave intensity was on average approximately 40% of 𝐶_𝑎𝑡𝑚, and was comparable to 𝐶_𝑎𝑡𝑚 in continental dry-to-wet transition regions. Reviewing heatwaves in recent three decades, the percentage of heatwave areas that are significantly influenced by soil moisture-air temperature coupling has increased by 11.4% per decade. Additionally, for regions that have experienced heatwaves in at least 5 out of the past 33 years, about 21.7% areas, mostly in the transition zones, witness a significant increase in 𝐶_𝑠𝑤𝑐; while only 2.5% exhibit a substantial increase in 𝐶_𝑎𝑡𝑚. Furthermore, we find within the transitional climates, the intensification of heat extremes is mainly resulted from soil moisture depletion rather than atmospheric anomalies; while in (dry) Spain and the (wet) northern areas of central Europe, it is the variations in atmospheric circulation and soil desiccation that jointly fuel the persistent heatwaves. Our study emphasizes the observation-based large and increasing importance of soil moisture coupling in intensifying summer heatwaves and provides insights into future climates in extra-tropical regions like Western Europe, where a warmer and drier future is projected. 𝐂𝐡𝐚𝐩𝐭𝐞𝐫 𝟑: Earth system models (ESMs) and climate simulations are extensively employed to study the dynamics of climate and project long-term changes in the climate system. Despite their widespread use, large uncertainties persist among these models regarding the estimation of the continental gross primary productivity (GPP) and land carbon sink, which compromise the reliability of projections concerning future atmospheric carbon dioxide (𝐶𝑂₂) concentrations and the assessment of how terrestrial ecosystems respond to and might mitigate some of global warming. In ESMs, convection and clouds are one major source of such uncertainties—they are not only the most uncertain factors in the modeling of ``physical'' climate and also significantly affect the land carbon cycle through complex interactions involving radiation, moisture, and thermal pathways. In the third study, to isolate the role of clouds on the terrestrial carbon cycle, two models—the Community Earth System Model (CESM) and its super-parameterized counterpart (SPCESM, abbreviated as SP), which only differ in their representation of convection and clouds, are analyzed under present-day climatology to assess the impact of cloud representations on GPP. Compared with CESM, SP shows a 12.8% decrease in total cloud fraction within the 60°𝑆 ∼ 60°𝑁 range, which results in a notable GPP decline of 5.6 𝑃𝑔𝐶 𝑦𝑟⁻¹. This divergence, equivalent to 4.4% of terrestrial GPP in CESM, is comparable to the inter-annual variability in GPP and the uncertainty of GPP observed across climate models with diverse representations, extending beyond just cloud-related processes. Further analysis decomposes the GPP divergence between CESM and SP into two additive components and demonstrates that three-quarters of the difference is attributed to the negative impact from reduced cloud cover on light use efficiency (LUE) from CESM to SP, while the remaining one quarter is due to the positive impact from enhanced photosynthetically active radiation (PAR). An explainable machine learning model equipped with SHAP values further identifies two primary mechanisms underlying the lower LUE estimation in SP. Firstly, diminished clouds lead to higher air temperatures and reduced precipitation, creating a drier environment that prompts plants to regulate stomatal conductance to minimize water loss through transpiration, thereby suppressing the exchange rate of 𝐶𝑂₂ between biosphere and atmosphere. Secondly, the reduction in diffused radiation restricts the photosynthesis of shaded leaves. Combined, these two mechanisms reduce plant LUE, outweigh the beneficial impacts of increased PAR on photosynthesis, and ultimately lead to the declined terrestrial biosphere productivity in SP. Overall, we identify the representation of clouds as a key process for the terrestrial carbon cycle.

Indiana University-Purdue University Indianapolis (IUPUI) / In the United States extreme heat events have grown in size and stature over the past 20 years. Urban Heat Islands exacerbate these extreme heat events leaving a sizable portion of people at risk for heat related fatalities. The evidence of this is seen in the Chicago heat wave of 1995 which killed 500 people over the course of a week and the European heat wave of 2003 which killed 7,000 people in the course of a month. The main guiding questions then become how government and the media can most effectively warn people about the occurrence of extreme heat events? Should extreme heat warnings be issued by T.V., newspaper or by radio? Even if warnings are issued will the population at large still change their behavior? Another possible question is whether people most vulnerable to extreme heat will change their behavior? A survey in 2010 by NASA will be the main basis for this analysis. This survey set out to see how well people in Phoenix, Philadelphia, and Dayton responded to extreme heat alerts by changing their behavior.

Indiana University-Purdue University Indianapolis (IUPUI) / Over the past two decades, northern parts of the United States have experienced extreme heat conditions. Some of the notable heat wave impacts have occurred in Chicago in 1995 with over 600 reported deaths and in Philadelphia in 1993 with over 180 reported deaths. The distribution of extreme heat events in Indianapolis has varied since the year 2000. The Urban Heat Island effect has caused the temperatures to rise unusually high during the summer months. Although the number of reported deaths in Indianapolis is smaller when compared to Chicago and Philadelphia, the heat wave in the year 2010 affected primarily the vulnerable population comprised of the elderly and the lower socio-economic groups. Studying the spatial distribution of high temperatures in the vulnerable areas helps determine not only the extent of the heat affected areas, but also to devise strategies and methods to plan, mitigate, and tackle extreme heat. In addition, examining spatial patterns of vulnerability can aid in development of a heat warning system to alert the populations at risk during extreme heat events. This study focuses on the qualitative and quantitative methods used to measure extreme heat events. Land surface temperatures obtained from the Landsat TM images provide useful means by which the spatial distribution of temperatures can be studied in relation to the temporal changes and socioeconomic vulnerability. The percentile method used, helps to determine the vulnerable areas and their extents. The maximum temperatures measured using LST conversion of the original digital number values of the Landsat TM images is reliable in terms of identifying the heat-affected regions.