Thesis (M.S.) in Geological Sciences--University of Maine, 2001. / Includes vita. Includes bibliographical references (leaves 205-214).

<p> The empirical analysis in this dissertation comprises two essays investigating the impacts of climate change on agriculture in Morocco, with an emphasis on climate uncertainty and robust adaptation.</p><p> The first essay in Chapter 4 provides estimates of economic impacts of climate change, and estimates on the extent to which the current Moroccan agricultural development and investment strategy, the Plan Maroc Vert (PMV), could help in agricultural adaptation to climate change and uncertainty.</p><p> We simulated three cases. First, we examined the impacts of PMV on the economy in the absence of climate change and found that it could provide about a 2.4% increase in GDP if the targets could be achieved. Subsequently, we did a separate simulation of the impacts of climate change on the Moroccan economy with no PMV (CC-Only) and found that there would be negative GDP impacts ranging between -0.5% and -3% depending on the climate scenario under the without CO₂ case. Including CO₂ fertilization effects induces a slight change in the distribution of impacts, which range from -1.4% to +0.3%. Finally, we evaluated the extent to which PMV could help mitigate the adverse impacts of climate change, and we found that the gain was quite small ranging between +0.02% and +0.04%.</p><p> The ability of the PMV strategy to mitigate the negative effects of climate change is limited at best, if non-existent. This is due to the scope of the PMV simulations limited to the strategic agricultural crop sectors in Morocco, which jointly represent no more than 35% of aggregate agricultural GDP; whereas the rest of the sectors account for 65%. Additionally, the likelihood of meeting the PMV productivity targets is low in light of our benchmark analysis comparing productivity prior to and after the adoption of GMO technologies.</p><p> The second essay examines the interaction of globalization through trade liberalization and climate change. Our hypothesis was that the more trade is liberalized, the higher the potential to compensate for losses due to climate change.</p><p> Our findings suggest that at the global level, our hypothesis is verified. World welfare gains are highest under a multilateral trade liberalization scenario, which induces a total offset of climate change welfare losses. However, under partial trade liberalization, the welfare gains become very small in comparison with the climate change impacts.</p><p> At the regional level, the results are more nuanced and our hypothesis does not hold for all regions. For instance, and focusing on Morocco as a case study, the net welfare impacts associated with trade liberalization are negative on average. But under the multilateral trade liberalization scenario, Morocco experiences net welfare gains under the SRES A1B and B1, which respectively reached US$ +23 million and US$ +16 million. Although trade liberalization induces net allocative efficiency gains under most scenarios, the large negative terms of trade effects offset most of the gains.</p>

<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>

This item was digitized as part of the Million Books Project led by Carnegie Mellon University and supported by grants from the National Science Foundation (NSF). Cornell University coordinated the participation of land-grant and agricultural libraries in providing historical agricultural information for the digitization project; the University of Arizona Libraries, the College of Agriculture and Life Sciences, and the Office of Arid Lands Studies collaborated in the selection and provision of material for the digitization project.

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>

Ice is both an important indicator, and agent, of climate change. In this work we consider conceptual and numerical models of ice in the global climate system on two ends of the climate modeling spectrum. On the simple end of the spectrum, we introduce a low-dimensional global climate model to investigate the role of oceanic heat transport on ice cover, particularly in the initiation of global ice cover, known as Snowball Earth events. We find that oceanic heat transport is effective at keeping the ice margin at high latitudes, and neglecting to include oceanic heat transport can lead to drastically different climate states. On the complex end of the climate modeling spectrum, we implement an iceberg parameterization in the Los Alamos National Laboratory's sea ice model CICE. Novel to our approach is we model icebergs in two frameworks - as Lagrangian particles, and as an Eulerian field. We allow icebergs to interact dynamically with the surrounding sea ice, and the modeled iceberg thermodynamics allow them to melt as they drift, serving as vehicles of freshwater injection into the ocean from land ice sheets. We focus on Antarctic icebergs, which tend to be larger than those found in the Arctic and are more likely to encounter substantial sea ice pack.

<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>

In the United States, the flood frequency analysis guidelines described in Bulletin 17B are followed to provide reliable flood discharge magnitude estimates for urban floodplain planning and flood insurance studies. The statistical analysis in Bulletin 17B has various assumptions, including that floods are generated by the same type of atmospheric mechanism (flood homogeneity). However, these assumptions should be carefully assessed before proceeding since they might not always be valid and could increase the potential for flood risk. This study focuses on flood frequency analysis from the perspective of flood heterogeneity, the hydrometeorological genesis of each flood event, in Arizona. This was done by analyzing the occurrence and magnitude of individual flood events, which were classified by their flood-producing atmospheric mechanism. Flood frequency curves were derived for each mechanism and combined using a new approach involving the Partial Duration Series peaks. The combined frequency curves were then compared to curves derived from the standard Bulletin 17B method. Results showed that in southern Arizona, the dominant flooding mechanism is characterized by brief, intense, and localized convective precipitation in the summer. However, the dominant flood-producing mechanism in the central Arizona topographic transition zone and at higher elevations is characterized by prolonged and widespread precipitation from synoptic activity in the winter. Tropical cyclone-enhanced precipitation is also an important, but infrequent, flood-producing mechanism throughout the state. Overall, the dominant mechanism does not necessarily produce the largest floods. In such cases flood heterogeneity can have a strong influence on the discharge estimates for the most extreme upper tail probabilities calculated from the flood frequency analysis. Thus, the most frequent floods may impose very little risk of flooding while uncommon floods can impose a much larger one. These results suggest that the flood homogeneity assumption is not valid in many Arizona watersheds. To produce the most accurate discharge estimates possible, it is critical that both analysts and flood managers become aware of the potential repercussions if these details are overlooked.