In the absence of federal climate change initiatives, Texas cities have been free to pursue their own local energy and environmental policy objectives. However, recent trends in federal climate change politics have made it clear that the era of federal inaction on climate change is nearing an end. This report argues that these trends will eventually culminate in a comprehensive regulatory structure with serious implications for the entire energy landscape of Texas. Texas cities that adapt quickly to these new conditions will experience greater success in the new low-carbon economy. Determining which adaptation strategy is appropriate for each city, however, is largely a function of the policy priorities of the city in question. This report identifies four, often conflicting, policy perspectives that influence the development of climate change policy priorities: Environmental Protection, Economic Stability, Peak Oil Production, and Energy Security. It then analyzes these perspectives in order to develop criteria for the proper selection of future energy and environmental policies. Finally, this report examines a variety of proposed policy initiatives to identify strategic options for each perspective and opportunities for mutual gain. / text

<p> The Urban Heat Island (UHI) was investigated using satellite data, ground observations, and simulations with an Urban Canopy Parameterization in a numerical weather prediction model. Satellite-observed surface skin temperatures at Xi'an City and Oklahoma City (OKC) were analyzed to compare the UHI intensity for the two inland cities. A larger population density and larger building density in Xi'an City creates a stronger skin-level UHI effect. However, ground observed 2-m surface air temperature (Tair) data showed an urban cooling island (UCI) effect that occurred over an urban region in OKC during the daytime of July 19, 2003. </p><p> The sensitivity and accuracy of an Urban Canopy Model were evaluated by comparing simulation results between the urban and rural areas of OKC. The model reproduced skin temperature differences between the rural and urban area and reproduced a UCI effect in OKC. Furthermore, the Weather Research and Forecasting (WRF)/Noah/Single-Layer Urban Canopy Model (SLUCM) simulations were also compared with ground observations, including wind speeds, wind directions, and energy fluxes. Although the WRF/SLCUM model failed to simulate these variables accurately, it reproduced the diurnal variations of surface temperatures, wind speeds, wind directions and energy fluxes reasonably well.</p>

ABSTRACT In the recent times, due to the increasing rate of global warming, the Southern African region, especially, Lesotho has been experiencing continuous climatic change characterized by drastic reduction in rainfall, increase in the rate of dryness and heat, with depletion of the amount of water, flora and fauna resources. The situation has been so for years without many questions and answers with regard to how it affects food production and security in the country. Against this background, this paper investigates the chain of interactions between climatic change, expressed in the rate of rainfall and drought condition, the indigenous adaptation mechanisms and food production in Lesotho. The paper addresses the estimate of drought condition in Lesotho, Southern Africa, the nature of food production activities in the area and the extent to which continuous climatic change has affected the state of food production.

<p> Low-level clouds found over the eastern subtropical oceans have a substantial cooling effect on Earth&rsquo;s climate since they strongly reflect solar radiation back to space, and their simulation in climate models contributes to large uncertainty in global warming projections. This thesis aims to increase understanding of these marine boundary layer clouds through observational analysis, theoretical considerations, and an evaluation of their simulation in climate models. Examination of statistical relationships between cloud properties and large-scale meteorological variables is a key method employed throughout the thesis. The meteorological environment of marine boundary layer clouds shapes their properties by affecting the boundary layer&rsquo;s depth and structure. </p><p> It is found that enhanced subsidence, typically thought to promote boundary layer cloudiness, actually reduces cloudiness when the confounding effect of the strength of the temperature inversion capping the boundary layer is taken into account. A conceptual model is able to explain this result. Next, fundamental deficiencies in the simulation of subtropical clouds in two generations of climate models are identified. Remarkably, the newer generation of climate models is in some ways inferior to the older generation in terms of capturing key low-level cloud processes. Subtropical mid- and high-level clouds are also found to contribute more to variability in the radiation budget at the top of the atmosphere than previously thought. In the last portion of the thesis, large inter-model spread in subtropical cloud feedbacks is shown to arise primarily from differences in the simulation of the interannual relationship between shortwave cloud radiative effect and sea surface temperature. An observational constraint on this feedback suggests that subtropical marine boundary layer clouds will act as a positive feedback to global warming.</p>

<p> The focus of this mixed-methods study was to identify waste reduction strategies that reduced the impact of California jails and prisons on the environment through waste diversion and reduction. This study also sought to identify barriers that hindered jail and prison personnel from developing such strategies, and pursued recommendations on how those barriers could be overcome.</p><p> Traditionally, California county jails and state prisons are resource intensive, overcrowded housing locations for about 200,000 adult men and women (Glaze &amp; Herberman, 2013). California jails and prisons operate 24 hours a day, seven days a week and utilize resources such as electricity, personnel, food, and other products. Accordingly, they generated significant waste (California Department of Resources and Recovery [CalRecycle], 2012). The prisoners alone generated about four pounds of waste per person each day, consistent with societal averages (CalRecycle, 2012; Corrections Corporation of America, 2007; Environmental Protection Agency [EPA], 2012a). Because of this, jails and prison must do more to reduce waste.</p><p> This study provided examples of organizations currently reducing waste through strategic initiatives and highlighted areas where jails and prisons could begin or further improve waste diversion practices. The study utilized archival data, a web-based survey, and interviews for data collection and analysis. The data from California jails and prisons were analyzed to identify strategies, barriers, and ways to eliminate or reduce barriers to waste reduction programs in California jails and prisons.</p><p> The findings conclude, California state-operated prisons and sheriff-operated county jails are using two primary strategies to divert waste from landfills. The number one strategy is recycling. The second strategy being used is waste prevention and material reuse. The barriers identified by California state-operated prisons and sheriff-operated county jails include finding vendors to collect certain materials as well as finding vendors to travel to remote locations. Other barriers include a lack of personnel and in some instances a lack of knowledge. Sheriff-operated jails and state-operated prisons in California identified waste management program support from leadership as a primary method to eliminate or reduce barriers to implementing a waste reduction program. Implications for action and future research are also discussed as part of this study.</p>

<p> Combined effects of socio-economic, environmental, technological and political factors impact fresh cooling water availability, which is among the most important elements of thermoelectric power plant site selection and evaluation criteria. With increased variability and changes in hydrologic statistical stationarity, one concern is the increased occurrence of extreme drought events that may be attributable to climatic changes. As hydrological systems are altered, operators of thermoelectric power plants need to ensure a reliable supply of water for cooling and generation requirements. The effects of climate change are expected to influence hydrological systems at multiple scales, possibly leading to reduced efficiency of thermoelectric power plants. This study models and analyzes drought characteristics from a thermoelectric systems operational and regulation perspective. A systematic approach to characterize a stream environment in relation to extreme drought occurrence, duration and deficit-volume is proposed and demonstrated. More specifically, the objective of this research is to propose a stochastic water supply risk analysis and projection methods from thermoelectric power systems operation and management perspectives. The study defines thermoelectric drought as a shortage of cooling water due to stressed supply or beyond operable water temperature limits for an extended period of time requiring power plants to reduce production or completely shut down. It presents a thermoelectric drought risk characterization framework that considers heat content and water quantity facets of adequate water availability for uninterrupted operation of such plants and safety of its surroundings. In addition, it outlines mechanisms to identify rate of occurrences of the said droughts and stochastically quantify subsequent potential losses to the sector. This mechanism is enabled through a model based on compound Nonhomogeneous Poisson Process. This study also demonstrates how the systematic approach can be used for better understanding of pertinent vulnerabilities by providing risk-based information to stakeholders in the power sector.</p><p> Vulnerabilities as well as our understanding of their extent and likelihood change over time. Keeping up with the changes and making informed decisions demands a time-dependent method that incorporates new evidence into risk assessment framework. This study presents a statistical time-dependent risk analysis approach, which allows for life cycle drought risk assessment of thermoelectric power systems. Also, a Bayesian Belief Network (BBN) extension to the proposed framework is developed. The BBN allows for incorporating new evidence, such as observing power curtailments due to extreme heat or lowflow situations, and updating our knowledge and understanding of the pertinent risk. In sum, the proposed approach can help improve adaptive capacity of the electric power infrastructure, thereby enhancing its resilience to events potentially threatening grid reliability and economic stability.</p><p> The proposed drought characterization methodology is applied on a daily streamflow series obtained from three United States Geological Survey (USGS) water gauges on the Tennessee River basin. The stochastic water supply risk assessment and projection methods are demonstrated for two power plants on the White River, Indiana: Frank E. Ratts and Petersburg, using water temperature and streamflow time series data obtained from a nearby USGS gauge. </p>

This text/video thesis investigates how Canadian fathers feel about the threat of losing pond hockey, a revered game they love, to climate change. It responds to the David Suzuki Foundation’s (DSF) assertion that under a global ‘business as usual’ rate of producing greenhouse gases, the skating season of the world’s largest ‘rink’--the Rideau Canal--would shrink from a nine week historical average to just one week by century’s end (DSF, 2009a). Seven outdoor-hockey-loving fathers were interviewed, which revealed their willingness to share feelings of concern, sadness, fear, uncertainty, and need for action to mitigate against and adapt to the ill-effects of climate change on this game, and more serious social situations. Despite concerns it was revealed they took few substantial actions against climate change, which they recognized might affect themselves, their children, communities, and future generations. Conversation, at times nostalgic, helped make these issues more salient.

Suspended sediment delivery dynamics in two watersheds at Cape Bounty, Melville Island, Nunavut, Canada were studied to characterize the hydroclimate conditions in which laminated sediments formed. Process work over three years determined snow-water equivalence was the primary factor that controlled sediment yield in both catchments. Cool springs (2003, 2004) enhanced runoff potential and intensity because channelized meltwater was delayed as it tunneled through the snowpack and reached the river channel (sediment supply) within 1-2 days. In warm springs (2005), meltwater channelized on the snowpack and did not immediately reach the river bed (7-10 days). Sediment transport was reduced because flow competence was lower and sediment supplies limited. Sediment deposition in the West Lake depended on surface runoff intensity. Short-lived, intense episodes of turbid inflow generated underflow activity which delivered the majority of seasonal sediment. In 2005, runoff was less intense and few underflows were detected compared to the cooler, underflow dominated 2004 runoff season. As well, grain-size analysis of trapped sediment indicated that deposition rates and maximum grain-size were decoupled, indicative of varied sediment supplies and delivery within the fluvial system. These decoupled conditions have important implications for paleohydrological interpretations from downstream sedimentary records. Two similar 600-year varve records were constructed from the lakes at Cape Bounty. Although these series were highly correlated throughout, time-dependent correlation analysis identified divergence in the early 19th century. Because the varve records were from adjacent watersheds and subject to the same hydroclimatic conditions, the divergence suggests watershed-level changes, such as increased local active layer detachments. The varve record from West Lake was highly correlated with lagged autumn snowfall and spring temperature. Similar relationships between these variables and East Lake were not as strong or significant. Long-term climatic interpretations should be carefully assessed. A single record from either of these lakes might lead to autumn snowfall and/or spring-melt intensity reconstructions, given the process work and weather record correlations. The recent divergence reveals potential changes likely to occur as warming increases variability within the Arctic System. Multidisciplinary monitoring and observations should continue in order to quantify future variability and evaluate the impact on these systems. / Thesis (Ph.D, Geography) -- Queen's University, 2008-09-02 12:11:53.483

No description available.

Climatic change has been observed in many locations and has been seen to have dramatic impact on a wide range of ecosystems. The traditional method to analyse trends in climatic series is regression analysis. Koenker and Bassett (1978) developed a regression-type model for estimating the functional relationship between predictor variables and any quantile in the distribution of the response variable. Quantile regression has received considerable attention in the statistical literature, but less so in the water resources literature. This study aims to apply quantile regression to problems in water resources and climate change studies. The core of the thesis is made up of three papers of which two have been published and one has been submitted. One paper presents a novel application of quantile regression to analyze the distribution of sea ice extent. Another paper investigates changes in temperature and precipitation extremes over the Canadian Prairies using quantile regression. The third paper presents a Bayesian model averaging method for variable selection adapted to quantile regression and analyzes the relationship of extreme precipitation with large-scale atmospheric variables. This last paper also develops a novel statistical downscaling model based on quantile regression. The various applications of quantile regression support the conclusion that the method is useful in climate change studies.