The climate of the Neoproterozoic Snowball Earth is tested in the UKMO Unified Model, specifically the HadCM3 climate model. The model is largely left unchanged, but the boundary conditions, both external and initial, are adjusted to create experiments based on the Snowball Earth hypothesis. The model can reproduce multiple equilibrium climates, as have been seen in energy balance models of the Earth's climate. The modelled present day and Neoproterozoic versions of Earth can both reproduce both ice capped and ice covered climate states. Neither can reproduce a climate which remains ice free throughout the year, even with an equilibrated ocean or elevated levels of C02. In all cases the ice free climate reverts toward the ice capped climate after the first polar winter. The modelled Neoproterozoic ice covered climate, that is the climate of Snowball Earth, has a climate very different from the present day. These changes are mostly driven by the lower thermal inertia, latitudinal temperature differences and the changed meridional circulation that results. The weather of the modelled Snowball Earth climate is also very different, dom- inated by a strong diurnal variation due to solar heating, as opposed to the more varied weather in the present day. The model responds well to the conditions of the Snowball Earth climate, with temperatures similar to those predicted by a simple physical model. The model responds less well to high levels of C02 in the Snowball Earth climate. The ice model also allows excessive heat and moisture to escape from the ocean into the atmosphere compared to that that would be predicted from solid ice coverage of the ocean. The exit from a Snowball Earth state was also tested within the model. Neither an decrease in albedo nor an increase in CO2 is unable to increase the temperature of the climate system sufficiently to exit the Snowball Earth state.

Climate models are common tools for developing design standards in the hydrologic field; however, these models contain uncertainties in multi-model and scenario selections. Along with these uncertainties, biases can be attached to the models. Such biases and uncertainties can present difficulties in predicting future extremes. These hydrologic extremes are believed to be non-stationary in character. Only in the recent past have model users come to terms that the current hydrologic designs are no longer relevant due to their assumption of stationarity. This study describes a systematic method of selecting a best fit model in relationship to location and time, along with the use of that best fit model for evaluation of future extremes. Rain gage stations throughout Florida are used to collect daily precipitation data used in extreme precipitation and quantitative indices. Through these indices conclusions are made on model selection and future extremes, as they relate to hydrologic designs. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2013.

Three major teleconnections, Atlantic Multidecadal Oscillation (AMO), North Atlantic Oscillation (NAO), and the Pacific Decadal Oscillation (PDO), in warm and cool phases, effect precipitation in Florida. The effects of the oscillation phases on the precipitation characteristics are analyzed by using long-term daily precipitation data, on different temporal (annual, monthly, and daily) and spatial scales, utilizing numerous indices, and techniques. Long-term extreme precipitation data for 9 different durations is used to examine the effects of the oscillation phases on the rainfall extremes, by employing different parametric and non-parametric statistical tests, along with Depth-Duration- Frequency analysis. Results show that Florida will experience higher rainfall when AMO is in the warm phase, except in the panhandle and south Florida, while PDO cool phase is positively correlated with precipitation, except for the southern part of the peninsula. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2013.

Shaped by countless influences from the atmosphere, biosphere, hydrosphere, and anthroposphere acting across a wide spectrum of spatiotemporal scales, spatial variations in climate are ubiquitous. Meanwhile, the warming signal from anthropogenically elevated greenhouse-gas concentrations is emerging as an overriding determinant for more and more aspects of the climate system, extreme heat among them. In this dissertation, I explore the interaction of these two effects, and the implications of the patterns they create. A key finding is that rapid increases in extreme heat are already occurring, by some metrics having already doubled in the past 40 years, and further nonlinear increases are expected. Another is the strong dependence of extreme heat-humidity combinations on atmospheric moisture, creating subseasonal and interannual patterns dictated by the principal source of regional warm-season moisture — pre-monsoonal advection in some cases, local evapotranspiration in others. These relationships lead to the demonstrated potential for improvements in predictive power, on the basis of sea-surface temperatures and other canonical modes of large-scale climate variability. In contrast to this overall confidence in current temporal patterns and long-term projections, I show that extreme heat at small spatial scales is much more poorly characterized in gridded products, and that these biases are especially acute along coastlines. While summer daytime temperature differences between the shoreline of the Northeast U.S. and locations 60 km inland are often 5°C or more, I find that recent high-resolution downscaled Earth-system models typically represent no more than 25% of this difference. Across the globe, ERA-Interim reanalysis similarly underestimates extreme humid heat by >3°C, a highly significant margin given the large sensitivity of health and economic impacts to marginal changes in the most extreme conditions. I find that these biases propagate into projections, and their importance is also amplified by the large populations living in the affected areas. Rapid mean warming is pushing the climate system to more and more frequently include extreme heat-humidity combinations beyond that which the human species has likely ever experienced. Such conditions, which had not been previously reported in weather-station data, are described in detail and some of the associated characteristics examined. Several channels of analysis highlight that these events are driven primarily by rising sea-surface temperatures in shallow subtropical gulfs, and the subsequent impingement of marine air on the coastline. Given the severity of potential impacts on infrastructure and agriculture, and the size of the populations exposed, this result underscores that major research and adaptation efforts are needed to avoid calamitous outcomes from the emergence of extreme heat-humidity combinations too severe to tolerate in the absence of artificial cooling. This dissertation discusses strategies for advancing knowledge of extreme heat’s natural variations and its behavior under climate change, in order to design metrics, models, methodologies, and presentation types such that essential findings are translated into tangible action in the most effective way possible. Sustained and integrated efforts are necessary to transition to a climate-system management style encompassing more foresight than the effectively unplanned experiment which has been pursued so far, and which has already exacerbated extreme heat events so much.

Fundação de Amparo a Pesquisa no Estado do Rio Grande do Sul / Extreme climatic events have been occurring with greater intensity and/or frequency over South America. Indicatives for these alterations encompass natural climate variability, land use (deforestation and urbanization), global warming, and increase of greenhouse gases and aerosols in the atmosphere. South America receives a great input of moisture from the Amazon rainforest, as well as a 37% contribution from the Atlantic Ocean. Considering the whole planet, some atmospheric events need to be analyzed when regarding moisture input towards a continent. Ocean circulation can interfere for example in sea surface temperature (SST), either influencing or not the input of moisture to the continent. The objective of the present study was to analyze the variability of atmospheric moisture in South America and its extreme values, as well as the relationships with the sea surface temperature of the adjacent oceans. The present study made use of ECMWF data, ERA-INTERIM reanalysis (pressure at sea level and surface pressure, evaporation, air and dew point temperatures at 2 meters, and zonal and meridional wind at 10 meters) and also sea surface temperature data from the MetOffice Hadley Centre (HADISST). The analysis period of the present study was between 1980 and 2009, encompassing a period of 30 years of data. First, climatology, trends and extremes of moisture and evaporation (frequency, intensity and reoccurrence of events) were calculated. These were followed by lagged compositions to assess the role of sea surface temperature anomalies during extreme moisture and evaporation events. The main results found were regarding an increase of the pressure at sea level gradient and SST in the southwestern Atlantic, increase evaporation in the eastern and northern coasts of South America, and its decrease in the center-southern region of the continent. Moreover, the center-southern region also demonstrated a decrease of dew point temperature and specific moisture, and an increase in the difference between air temperature and dew point temperature. Decrease in the moisture flow magnitude and intensification of dry events over the center-southern region of South America were also observed. Finally, results showed that an SST anomaly cycle during an extreme event in the continent lasted approximately five months and, at least one month prior to the event, signs of this SST anomaly were already observable. In summary, the most significant moisture alterations in South America were found in the center-southern sector of the continent and over the southwestern Atlantic Ocean, near the Brazil-Malvinas Confluence (BMC). Nevertheless, more studies are needed to understand the relationships between SST at the BMC and moisture extremes, particularly in the center-southern portion of South America. / Atualmente os eventos climáticos extremos têm ocorrido com maior intensidade e/ou frequência sobre a América do Sul. Os indicativos para essas alterações circundam a variabilidade natural do clima, uso da terra (desmatamento e urbanização), aquecimento global, aumento da concentração de gases do efeito estufa e aerossóis na atmosfera. A América do Sul recebe um grande aporte de umidade pela existência da floresta Amazônica em seu território e também cerca de 37% de contribuição oriunda do Oceano Atlântico. Considerando todo o globo terrestre, alguns dos eventos atmosféricos precisam ser analisados com relação ao aporte de umidade sobre o continente. Com relação ao oceano, a circulação dos oceanos podem interferir, por exemplo, na temperatura da superfície do mar (TSM), influenciando ou não no aporte de umidade para o continente. O objetivo do presente trabalho foi analisar a variabilidade da umidade atmosférica na América do Sul e de seus valores extremos e as relações com a temperatura da superfície do mar nos oceanos adjacentes. O presente trabalho utilizou dados do ECMWF, da reanálise do ERA-INTERIM (pressão ao nível do mar e pressão em superfície, evaporação, temperatura do ar e temperatura do ponto de orvalho a 2 metros e vento zonal e meridional a 10 metros) e também dados de temperatura da superfície do mar do MetOffice Hadley Centre (HADISST). O período de análise do presente trabalho foi de 1980 a 2009, compreendendo um período de 30 anos de dados. Primeiramente foram calculadas as climatologias, as tendências e os extremos de umidade e evaporação (frequência, intensidade e recorrência dos eventos). Posteriormente, foram realizadas as composições defasadas para verificar o papel das anomalias da temperatura da superfície do mar durante os eventos extremos de umidade e evaporação. Os principais resultados encontrados foram em relação a um aumento da pressão ao nível do mar e da TSM no Atlântico sudoeste, aumento também da evaporação na costa leste e norte da América do Sul, e sua diminuição na região centro-sul do continente. Além disso, a região centro-sul também demonstrou uma diminuição da temperatura do ponto de orvalho e da umidade específica, e um aumento na diferença entre a temperatura do ar e a temperatura do ponto de orvalho. Diminuição da magnitude do fluxo de umidade e intensificação de eventos extremos secos sobre a região centro-sul da América do Sul também foram observados. E por fim, os resultados mostraram que um ciclo de anomalia de TSM durante um evento extremo no continente durou aproximadamente cinco meses e, pelo menos um mês antes do evento, sinais da anomalia de TSM já era observada. Em suma, as alterações mais significativas na umidade sobre a América do Sul foram encontradas no setor centro-sul do continente e sobre o Oceano Atlântico sudoeste, próximo a Confluência Brasil-Malvinas (CBM).

There remain vast knowledge gaps in the global south as to how tourism will affect climate change and vice versa. Recent extreme weather events in southern Africa attributed to climate variability and change have led to speculation that, the Victoria Falls, is under threat from climate change. This research was aimed at examining the two-way linkage between tourism and climate change. The research adopted a pragmatism paradigm in a mixed-method case study. A number of research techniques were used to investigate the problem, namely: an online survey (n=427), secondary data analysis, field observation and interviews. Data analysis was done making use of Mann-Kendall Trend Analysis, QuestionPro analytics, Microsoft Excel Analysis Toolpak, Tools from ArcMap 10.3.1 and SPSS 24. Content analysis and thematic analysis was used to analyse secondary and interview data respectively. It emerged that the Victoria Falls is experiencing climate change, which resulted in statistically significant increase in temperature over the past 40 years of between 0.3°C and 0.75°C per decade. However, no significant changes in rainfall were noted, although there has been a seasonal shift in average rainfall onset. Weather extremes and annual rainfall point to increased occurrence and severity of extreme years of droughts and wetting which has in turn also affected waterflow regime at the waterfalls. The changes have a negative impact on wildlife, tourists, and tourism business in the area. The study also revealed that tourism is an equally significant driver of climate change through carbon emissions throughout its value chain. Carbon emissions from tourism value chain are set to increase in the foreseeable future despite efforts of going green by the industry owing to exponential growth of the industry. There is, therefore, a need for the industry to adapt, mitigate and intensify green tourism efforts to achieve sustainability. The study further suggests that there is a need for better communication and education to build resilience and capacity for the tourism industry to deal with climate change. Further research is suggested to ascertain the tourism threshold for the area, impact of climate change on wildlife and basin changes that led to water flow increase in the Zambezi River. / Environmental Sciences / Ph. D. (Environmental Management)

Large-scale atmospheric disturbances play important roles in determining the general circulation of the atmosphere during the North Pacific boreal winter. A number of scientific questions have been raised due to these disturbances’ spatial and temporal complexity as well as the hydrological implication associated with them. In this dissertation, the principal goal is to further improve our understanding of the atmospheric high frequency (HF) and intermediate frequency (IF) disturbances active over the North Pacific. The study focuses on their energetics, intraseasonal and interannual variability, and the resulting hydrological impact over the eastern North Pacific and Western U.S. including extreme events. To delineate the characteristics of HF and IF disturbances in the troposphere, we first derive a new set of equations governing the local eddy kinetic energy (EKE), and assess the critical processes maintaining local budgets of the HF and IF EKE. The diagnosis assesses the 3-D patterns of energy flux convergence (EFC), barotropic conversion (BT), baroclinic conversion (BC), and cross-frequency eddy-eddy interaction (CFEI). The local EKE budget analysis is followed by an investigation of the modulation of HF and IF eddy activity by different modes of low frequency climate variability. On interannual timescales, the response of various local energetic processes to El Niño-Southern Oscillation (ENSO) determines the HF and IF EKE anomalies and the role of CFEI process is important in producing these anomalies. Also on interannual timescales, winter precipitation deficits associated with suppressed cyclonic activity, i.e., negative HF EKE anomalies, are linked to severe droughts over the U.S. Southern Great Plain (SGP) region. The suppressed cyclonic activity is, in turn, tied to phase changes in the West Pacific (WP) teleconnection pattern. On intraseasonal timescales, variations in HF disturbances (a.k.a. storm tracks) over the North Pacific are closely coupled with tropical convection anomalies induced by the Madden-Julian Oscillation (MJO), and partly drive larger scale intraseasonal flow anomalies in this region through eddy-eddy interactions. Anomalous HF eddy activity induces subseasonal transitions between “wet” and “dry” regimes over the west coast of North America. Also on intraseasonal timescales, the East Asian cold surge (EACS) is found to provide a remote forcing of the winter precipitation anomalies in the western U.S. This modulation is achieved through “atmospheric rivers” (ARs), which are narrow channels of concentrated moisture transport in the atmosphere and are responsible for over 70% of the extreme precipitation events in the western U.S.. EACS effectively modulates the IF disturbance activity over the North Pacific, and the anomalous IF disturbances lead to the formation of an AR over the eastern North Pacific that ultimately induces precipitation anomalies in the western U.S. Analyses of the simulations from the NCAR Community Climate System Model version 4 (CCSM4) demonstrate that the connections among the EACS, AR and western U.S. precipitation are better captured by a model with higher spatial resolutions. The improved simulation of these connections is achieved mainly through a better representation of the IF disturbances, and the associated scale-interaction processes in the higher resolution model.

Thesis (MSc)--Stellenbosch University, 2012. / Severe floods in the Western Cape have caused significant damage to hydraulic structures, roads and other infrastructure over the past decade. The current design criteria for these structures and flood return level calculations are based on the concept of stationarity, which assumes that natural systems vary within an envelope of variability that does not change with time. In the context of regional climate change and projected changes in rainfall intensity, the basis for these calculations may become unrealistic with the passage of time. Hydraulic structures and other infrastructure may become more vulnerable to damaging floods because of changing hydroclimatic conditions. This project assesses the changes in extreme rainfall values over time across the Western Cape, South Africa. Using a Generalised Pareto Distribution, this study examines the changes in return levels across the Western Cape region for the periods 1900-1954 and 1955-2010. Of the 137 rainfall stations used in this research, 85 (62%) showed an increase in 50-year return level, 30 (22%) a decrease in 50-year return level and 22 (16%) stations displayed little change in rainfall intensity over time. While there were no clear spatial patterns to the results, they clearly indicate an increase in frequency of intense rainfalls in the latter half of the 20th and early 21st century. The changes in return level are also accompanied by a change in the frequency of high intensity 2-3 day long storms. 115 (84%) of the 137 rainfall stations showed an increase in the frequency of long duration, high intensity storms over the data record. This change generates a shifting risk profile of extreme rainfalls, which, in turn, creates challenges for the design of hydraulic structures and any infrastructure exposed to the resulting damaging floods. It can therefore be argued that it is inappropriate to design structures or manage water resources assuming stationarity of climate and that these principles should be assessed in order to reduce the risk of flood damage owing to increasing storm intensity. KEY WORDS Flood Risk, Stationarity, Disaster Risk, Hazard, Extreme Rainfall, Generalized Pareto Distribution, Climate

The rising temperature of the earth due to climate change has shown to alter the variations of hydro-climate variables, including their intensities, frequencies and durations. Extreme events such as floods are, in particular, susceptible to any disturbances in climate cycles. As such it is important to provide policymakers with sufficient knowledge about the probable impacts of climate change on hydrologic extremes and most importantly on floods, which have the highest impacts on the societies. For this reason analysis of hydro-climate extremes is commonly performed using data at each site (or grid cell), however due to the limited number of extreme events, these analyses are not robust. Current methods, such as the regional frequency analysis, which combine data from different locations are incapable of incorporating the spatial structure of the data as well as other explanatory variables, and do not explicitly, assess the uncertainties. In this thesis the spatial hierarchical Bayesian model is proposed for hydro-climate extreme analyses using data recorded at each site or grid. This method combines limited number of data from different locations, estimates the uncertainties in different stages of the hierarchy, incorporates additional explanatory variables (covariates), and can be used to estimate extreme events at un-gaged sites. The first project develops a spatial hierarchical Bayesian method to model the extreme runoffs over two spatial domains in the Columbia River Basin, U.S. The model is also employed to estimate floods with different return levels within time slices of fifteen years in order to detect possible trends in runoff extremes. Continuing on the extreme analysis, the impact of climate change on runoff extremes is investigated over the whole Pacific Northwest (PNW). This study aims to address the question of how the runoff extremes will change in the future compared to the historical time period, investigate the different behaviors of the regional climate models (RCMs) regarding the runoff extremes, and assess the seasonal variations of runoff extremes. Given the increasing number of climate model simulations the goal of the third project is to provide a multi-model ensemble average of hydro-climate extremes and characterize the inherent uncertainties. Outputs from several regional climate models provided by NARCCAP are considered for the analysis in all seasons. Three combination scenarios are defined and compared for multi-modeling of extreme runoffs. The biases of each scenario are calculated and the scenario with the least bias is selected for projecting seasonal runoff extremes. The aim of the fourth project is to quantify and compare the uncertainties regarding global climate models to the ones from the hydrologic model structures in climate change impact studies. Various methods have been proposed to downscale the coarse resolution General Circulation Model (GCM) climatological variables to the fine scale regional variables; however fewer studies have been focused on the selection of GCM predictors. Additionally, the results obtained from one downscaling technique may not be robust and the uncertainties related to the downscaling scheme are not realized. To address these issues, in the fifth study we employed Independent Component Analysis (ICA) for predictor selection which determines spatially independent GCM variables (as discussed in Appendix A). Cross validation of the independent components is employed to find the predictor combination that describes the regional precipitation over the upper Willamette basin with minimum error. These climate variables along with the observed precipitation are used to calibrate three downscaling models: Multi Linear Regression (MLR), Support Vector Machine (SVM) and Adaptive-Network-Based Fuzzy Inference System (ANFIS).