Dissertations / Theses: 'Coast changes – Mathematical models'

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Dang, Van To Civil &amp Environmental Engineering Faculty of Engineering UNSW. "Development of a mathematical N-line model for simulation of beach changes." Awarded by:University of New South Wales. School of Civil and Environmental Engineering, 2006. http://handle.unsw.edu.au/1959.4/27394.

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The development of a new N-Line model, which provides a practical tool for simulating regional beach changes induced by short and long-term processes, is described in this thesis. The new N-Line model consists of four main modules that together describe the hydrodynamic and morphological responses. The four constituent modules have been integrated based on a wide range of research including the utility and function of commercial or freeware models. They are RCPWAVE wave module, time-averaged and depth-integrated current module, sediment transport module based on Bailard (1981) and contour change morphological module. Two different time-scales and two staggered grid systems for hydrodynamic and morphological simulations were adopted alternatively. For short-term 2D profile changes, new N-Line model applicability has been examined using data from the laboratory to the field. For ideal beaches, new N-Line can simulate an offshore storm bar generation or an onshore accretion due to high or low energy waves. For SUPERTANK large-scale flume data, the predicted profile matched the measured profile well, especially the bar height and position. For beach profile data from the Gold Coast, storm-induced variations of barred profiles were reasonably modelled. The new N-Line model compared well with other commonly used cross-shore models such as SBEACH and UNIBEST. A new schematisation for a non-monotonic profile and DUNED inclusion were introduced. Sensitivity tests on cross-shore sediment coefficient (Kq), smoothing parameter (??s) and water level fluctuations were performed. For long-term 3D beach changes, the new N-Line model applicability has been tested with various boundary conditions using idealized and real field data. Two periods, 17 and 16 months, of beach changes before and after a major bypass plant commenced operation in 2001 at Letitia Spit were simulated. The profile and shoreline changes were predicted reasonably well. Empirical model parameters were determined after a range of sensitivity and calibration testing. The new N-Line model showed its better performance compared to one-line models. It can handle various boundary conditions, especially bypass conditions. The N-Line model is not only capable of modelling planform variations but also cross-shore profile changes.

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Peterson, Erica Kay. "An Econometric Analysis of Cost Changes in U.S. Trucking and the Implications of Implementing the NAFTA Trucking Provisions." Thesis, North Dakota State University, 2007. https://hdl.handle.net/10365/29800.

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The United States trucking industry underwent deregulation starting in 1980. There was much opposition to the process in fears that trucking companies would be adversely affected by increased competition. There were also many proponents and researchers who proved that the increased competition due to regulatory reform only helped strengthen the industry by forcing firms to become more cost efficient. There has been similar opposition and support for the trucking provisions of NAFTA. Although the provisions have not been fully implemented, the trucking industry is well aware it will only be a matter of time. In early 2002 it was announced that the process to begin implementing the trucking provisions would begin in mid-2002. Many in the industry and other groups have opposed implementing the provisions, concerned that U.S. trucking firms would be subject to competition from Mexican firms, just as they feared trucking firms would be adversely affected by deregulation more than 25 years ago. This thesis analyzes the effects the 2002 announcement of the process to begin implementing the trucking provisions has had on the cost structure of the industry. It uses a translog cost function to determine if firms have become more efficient in the years following the announcement in anticipation of increased competition from Mexican firms after the provisions are fully implemented. The translog cost function is used to determine what effects the NAFTA variable has had on costs and what specific operating characteristics have caused the costs to increase or decrease.

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Demir, Huseyin. "A Process-Based Model for Beach Profile Evolution." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/19811.

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Beach profile models predict the changes in bathymetry along a line perpendicular to the shoreline. These models are used to forecast bathymetric changes in response to storms, sea level rise or human activities such as dredging and beach nourishment. Process-based models achieve this by simulating the physical processes that drive the sediment transport as opposed to behavior models which simulate observed profile changes without resolving the underlying processes. Some of these processes are wave shoaling and breaking, boundary layer streaming, and offshore-directed undertow currents. These hydrodynamic processes control the sediment processes such as sediment pick-up from the bottom, diffusion of the sediment across the water column and its advection with waves and currents. For this study, newly developed sediment transport and boundary layer models were coupled with existing models of wave transformation, nearshore circulation and bathymetry update, to predict beach profile changes. The models covered the region from the dry land to a depth of 6-8 meters, spanning up to 500 meters in the cross-shore direction. The modeling system was applied at storm time scales, extending from a couple of hours to several days. Two field experiments were conducted at Myrtle Beach, SC, involving the collection of wave, current and bathymetric data as a part of this study. The results were used to calibrate and test the numerical models along with data from various laboratory studies from the literature. The sediment transport model computes the variation of sediment concentrations over a wave period and over the water column, solving the advection-diffusion equation using the Crank-Nicholson finite-difference numerical scheme. Using a new approach, erosion depth thickness and sediment concentrations within the bed were also predicted. The model could predict sediment transport rates for a range of conditions, within a factor of two. It successfully computed the sediment concentration profile over the water column and within the bed and its variation throughout a wave period. Erosion depth and sheet flow layer thickness were also predicted reasonably well. Wave heights across the profile were predicted within ten percent when the empirical wave breaking parameter was tuned appropriately. Mean cross-shore velocities contain more uncertainty, even after tuning. The importance of capturing the location of the maximum, near-bottom, cross-shore velocity when predicting bar behavior was shown. Bar formation, erosion, accretion, onshore and offshore bar movement were all computed with the model successfully

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Ng, Max Kin-Fat. "Assessment of tsunami hazards on the British Columbia coast due to a local megathrust subduction earthquake." Thesis, University of British Columbia, 1990. http://hdl.handle.net/2429/29633.

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Strong evidence suggests that the Cascadia subduction zone, off the west coast of Canada and the United States, is strongly seismically-coupled and that a possible megathrust earthquake might occur in that area in the near future. A study of tsunami hazards along the Canadian west coast associated with such a hypothetical earthquake is presented in this report. Numerical simulations of tsunami generation and propagation have been carried out using three models based on shallow water wave theory. Three cases of ground motion representing the ruptures of different crustal segments in the area have been examined. Computed results provide information on tsunami arrival times and a general view of the wave height distribution. The outer coast of Vancouver Island was found to be the most strongly affected area. At the head of Alberni Inlet, wave amplitudes reached up to three times the source magnitude. Inside the Strait of Georgia, the wave heights are significant enough to receive closer attention, especially in low-lying areas.
Science, Faculty of
Physics and Astronomy, Department of
Graduate

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Johnston, Susan Joy. "The development of an operational management procedure for the South African west coast rock lobster fishery." Doctoral thesis, University of Cape Town, 1998. http://hdl.handle.net/11427/22567.

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This thesis considers the development of an operational management procedure (OMP) to provide scientific recommendations for commercial TAC for the South African west coast rock lobster (Jasus lalandii) fishery. This fishery has been under considerable stress in recent years as a result of overfishing and low somatic growth rates. Present catch levels, less than 2000 MT, are substantially smaller than levels recorded in the past. The present biomass (above 75mm carapace length) is estimated to be only six percent of the pristine level. At the start of this research, no long-term management strategy for the resource existed. Neither was there any robust, tested, scientific method available for setting the annual TAC for the fishery, which resulted in a time-consuming and unsatisfactory scientific debate each year in developing a series of ad hoc TAC recommendations. The work presented in this thesis is thus aimed at answering two important questions. i) Can an adequate mathematical model be developed as a basis to simulate the resource and its associated fishery? ii) Can a self-correcting robust OMP be developed for the resource? The first phase of this thesis is the development of a size-structured population model of the resource and the associated fishery. A size-structured model is necessary as lobsters are difficult to age and hence most of the data collected are on a size basis. Furthermore, important management issues, such as the legal minimum size which has changed over time, require a model able to take size-structure into account. This model is fitted to a wide range of data from the fishery, including CPUE (catch-per-unit-effort) and catch-at-size information, by maximising a likelihood function. The model is shown to fit reasonably well to all data, and to provide biologically plausible estimates for its six estimable parameters.

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Coulombe, Daniel. "Voluntary income increasing accounting changes : theory and further empirical investigation." Thesis, University of British Columbia, 1987. http://hdl.handle.net/2429/26983.

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This thesis presents a three step analysis of voluntary income increasing accounting changes. We first propose a theory as to why managers would elect to modify their reporting strategy. This theory builds on research on the economic factors motivating accounting choices, since it is assumed that accounting choices are a function of political costs, manager's compensation plans and debt constraints. Specifically, we claim that adversity motivates the manager to effect an income increasing accounting change. Secondly, the thesis proposes a theoretical analysis of the potential market responses to a change announcement. The stock price effect of a change announcement is examined as a function of investors' rational anticipations of the manager's reporting actions and as a function of the level of information about adversity that investors may have prior to a change announcement. An empirical analysis is presented in the third step of this thesis. Our empirical findings are that: 1- Change announcements, on average, have no significant impact on the market. 2- Relative to the Compustat population as a whole, firms that voluntarily adopt income increasing accounting changes exhibit symptoms of financial distress, suggesting that such change announcements are associated with financial adversity. 3- Firms which voluntarily adopt income increasing accounting changes tend to exhibit symptoms of financial distress one or more years prior to the change year, suggesting that change announcements tend not to be a timely source of information conveying distress to the market. 4- There is a significant negative association between investors' proxies for prior information about adversity and the market impact of the change, especially for the subset of firms with above average leverage, suggesting that the information content of the accounting change signal is inversely related to investors prior information about adversity. The empirical results thus support the view that investors, at the time a change occurs, have information about the prevailing state of the world, and that they have rational anticipations with respect to the manager's reporting behavior. In this respect, the accounting change is, on average, an inconsequential signal that adds little to what investors already knew before the change announcement.
Business, Sauder School of
Graduate

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Andrews, Rick L. "Temporal changes in marketing mix effectiveness." Diss., This resource online, 1992. http://scholar.lib.vt.edu/theses/available/etd-07282008-134759/.

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Santoso, Agus Mathematics &amp Statistics Faculty of Science UNSW. "Evolution of climate anomalies and variability of Southern Ocean water masses on interannual to centennial time scales." Awarded by:University of New South Wales. School of Mathematics and Statistics, 2005. http://handle.unsw.edu.au/1959.4/33355.

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In this study the natural variability of Southern Ocean water masses on interannual to centennial time scales is investigated using a long-term integration of the Commonwealth Scientic and Industrial Research Organisation (CSIRO) coupled climate model. We focus our attention on analysing the variability of Antarctic IntermediateWater (AAIW), Circumpolar DeepWater (CDW), and Antarctic Bottom Water (AABW). We present an analysis of the dominant modes of temperature and salinity (T - S) variability within these water masses. Climate signals are detected and analysed as they get transmitted into the interior from the water mass formation regions. Eastward propagating wavenumber-1, -2, and -3 signals are identied using a complex empirical orthogonal function (CEOF) analysis along the core of the AAIW layer. Variability in air-sea heat uxes and ice meltwater rates are shown by heat and salt budget analyses to control variability of Antarctic Surface Water where density surfaces associated with AAIW outcrop. The dominant mode in the CDW layer is found to exhibit an interbasin-scale of variability originating from the North Atlantic, and propagating southward into the Southern Ocean. Salinity dipole anomalies appear to propagate around the Atlantic meridional overturning circulation with the strengthening and weakening of North Atlantic Deep Water formation. In the AABW layer, T - S anomalies are shown to originate from the southwestern Weddell Sea, driven by salinity variations and convective overturning in the region. It is also demonstrated that the model exhibits spatial patterns of T - S variability for the most part consistent with limited observational record in the Southern Hemisphere. However, some observations of decadal T - S changes are found to be beyond that seen in the model in its unperturbed state. We further assess sea surface temperature (SST) variability modes in the Indian Ocean on interannual time scales in the CSIRO model and in reanalysis data. The emergence of a meridional SST dipole during years of southwest Western Australian rainfall extremes is shown to be connected to a large-scale mode of Indian Ocean climate variability. The evolution of the dipole is controlled by variations in atmospheric circulation driving anomalous latent heat uxes with wind-driven ocean transport moderating the impact of evaporation and setting the conditions favourable for the next generation phase of an opposite dipole.

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Del, Valle Sara Yemimah. "Effects of behavioral changes and mixing patterns in mathematical models for smallpox epidemics." Diss., University of Iowa, 2005. https://ir.uiowa.edu/etd/105.

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In Chapter 1, we study the effects of behavioral changes in a smallpox attack model. Response strategies to a smallpox bioterrorist attack have focused on interventions such as isolation, contact tracing, quarantine, ring vaccination, and mass vaccination. We formulate and analyze a mathematical model in which some individuals lower their daily contact activity rates once an epidemic has been identified in a community. We use computer simulations to analyze the effects of behavior change alone and in combination with other control measures. We demonstrate that the spread of the disease is highly sensitive to how rapidly people reduce their contact activity. In Chapter 2, we study mixing patterns between age groups using social networks. The course of an epidemic through a population is determined by the interactions among individuals. To capture these elements of reality, we use the contact network simulations for the city of Portland, Oregon that were developed as part of the TRANSIMS/EpiSims project to study and identify mixing patterns. We analyze contact patterns between different age groups and identify those groups who are at higher risk of infection. We describe a new method for estimating transmission matrices that describe the mixing and the probability of transmission between the age groups. We use this matrix in a simple differential equation model for the spread of smallpox. Our differential equation model shows that the epidemic size of a smallpox outbreak could be greatly affected by the level of residual immunity in the population. In Chapter 3, we study the effects of mixing patterns in the presence of population heterogeneity. We investigate the impact that different mixing assumptions have on the spread of a disease in an age-structured differential equation model. We use realistic, semi-bias and bias mixing matrices and investigate the impact that these mixing patterns have on epidemic outcomes when compared to random mixing. Furthermore, we investigate the impact of population heterogeneity such as differences in susceptibility and infectivity within the population for a smallpox epidemic outbreak. We find that different mixing assumptions lead to differences in disease prevalence and final epidemic size.

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Familkhalili, Ramin. "Analytical and Numerical Modeling of Long Term Changes to Tides, Storm Surge, and Total Water Level Due to Bathymetric Changes and Surge Characteristics." PDXScholar, 2019. https://pdxscholar.library.pdx.edu/open_access_etds/5014.

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Natural and local anthropogenic changes in estuaries (e.g., sea-level rise, navigation channel construction and loss of wetlands) interact with each other and produce non-linear effects. There is also a growing recognition that tides in estuaries are not stationary. These factors together are changing the estuarine water level regime, however the implications for extreme water levels remain largely unknown. Changes over the past century in many estuaries, such as channel deepening and streamlining for navigation have significantly altered the hydrodynamics of long waves, often resulting in amplified tides (a ~85% increase in Wilmington, NC since 1900) and storm surge in estuaries. This research focuses on establishing analytical and numerical models that simulate a wide range of systems and flow conditions that combine multiple flood sources: astronomical tide, storm surge, and high river flow. To investigate the effects of estuarine bathymetry conditions (e.g., channel depth, convergence length), hurricane conditions (e.g., pressure and wind field), river discharge, and surge characteristics (e.g., time scale and amplitude and relative phase) on tide and storm surge propagation, I develop an idealized analytical model and two numerical models using Delft-3D. The Cape Fear River Estuary, NC (CFRE), and St Johns River Estuary, FL (SJRE) are used as case studies to investigate flood dynamics. The analytical approach has been compared and verified with idealized numerical models. I use data recovery, data analysis, and idealized numerical modeling of the CFRE to investigate the effects of bathymetric changes (e.g., dredging and channel modification) on tidal and storm surge characteristics over the past 130 years. Data analysis and modeling results suggest that long-term changes in tides can be used along with the tidal analysis tools to investigate changes in storm surge. Analysis indicate that tidal range in Wilmington, NC (Rkm 47) has doubled to 1.55m since the 1880s, while a much smaller increase of 0.07m observed close to the ocean in Southport (Rkm 6) since the 1920s. Further, model results suggest that the majority of long term changes in tides of this system have been caused by deepening the system from 7m to 15.5m due to dredging, rather than by changes in the coastal tides. Numerical modeling using idealized, parametric tropical cyclones suggests that the amplitude of the worst-case, CAT-5 storm surge has increased by 40-60% since the nineteenth century. Storm surges are meteorologically forced shallow water waves with time scales that overlap those of the tidal bands. Using data, I show that the surge wave can be decomposed into two sinusoidal waves. Therefore, I analytically model surge via a 3-constituent analytical tide model, where the third constituent is the dominant semi-diurnal tide and friction is linearized via Chebyshev polynomials. A constant discharge is considered to approximate fluvial effects The analytical model is used to study how surge amplitude, surge time scale, and surge-tide relative phase affect the spatial pattern of amplitude growth and decay, and how depth changes caused by channel deepening influence the magnitude of a storm surge. I use non-dimensional numbers to investigate how channel depth, surge time scale and amplitude, surge asymmetry, and relative timing of surge to tides alter the damping or amplification of surge along the estuary. The non-dimensional numbers suggest that increasing depth has similar effects as decreasing the drag coefficient. Similarly, larger time scale has an equivalent effect on tide and surge as increasing depth due to channel deepening. Analytical model results show that the extent of the surge amplification is dependent on the geometry of the estuary (e.g., depth and convergence length) and characteristics of the surge wave. Both models show that much of the alterations of water levels in estuaries is due to channel deepening for navigation purposes and that the largest temporal change occur for surges with a high surge to D2 amplitude ratio and a short time scale. Model results farther indicate that surge amplitude decays more slowly (larger e-folding) in a deeper channel for all surge time scales (12hr-72hr). Another main finding is that, due to nonlinear friction, the location of maximum change in surge wave moves landward as the channel is deepened. Thus, changes in flood risk due to channel deepening are likely spatially variable even within a single estuary. Next, I use the verified analytical model and numerical models to investigate the effects of river flow on surge wave propagation, and spatial and temporal variability of compound flooding along an estuary. To model the historic SJRE, I digitize nautical charts of SJRE to develop a numerical model. Both the numerical and analytical models are used to investigate the contribution of tide, surge, and river flow to the peak water level for historic and modern system configurations. Numerical modeling results for hurricane Irma (2017) show that maximum flood water levels have shifted landward over time and changed the relative importance of the various contributing factors in the SJRE. Deepening the shipping channel from 5.5m to 15m has reduced the impacts of river flow on peak water level, but increased the effects of tide and surge. Sensitivity studies also show that peak water level decreases landward for all river flow scenarios as channel depth increases. Model results show that the timing of peak river flow relative to the time of maximum surge causes very large changes in the amplitude of total water level, and in river flow effects at upstream locations for modern configuration than for the historic model. Changes in surge amplitudes can be interpreted by the non-dimensional friction number, which shows that depth (h), surge time scale (T=1/w), and convergence length-scale (Le) affect the damping/amplification of both tides and surge waves. Overall, this study demonstrates that a system scale alteration in local storm surge dynamics over the past century is likely to have occurred in many systems and should be considered for system management. The results of this research give the scientists and engineer a better understanding of tide, river flow, and surge interactions, and thereby contribute to an understanding of how to predict storm surges and help mitigate their destructive impacts. Future system design studies also need to consider long-term and changes of construction and development activities on storm surge risk in a broader context than has historically been the case.

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Font, Moragón Carme. "Mathematical models for energy and landscape integrated analysis in agroecosystems." Doctoral thesis, Universitat Autònoma de Barcelona, 2016. http://hdl.handle.net/10803/399906.

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Els models matemàtics s'utilitzen per explicar fenòmens naturals. Com que els fenòmens naturals són molt complexes, per tal d'aprofundir en el seu comportament i ser capaç de fer prediccions sobre ells, es necessita passar per un procés de simplificació. En el procés de creació del model, el sistema es tradueix a llenguatge matemàtic que permet l'estudi del sistema des d'un nou punt de vista. En aquesta tesi, es consideren models estadístics per estudiar el comportament dels agroecosistemes a diferents escales espacials. L'objectiu d'aquest treball és estudiar la relació entre fluxos d'energia, canvis de cobertes del sòl, la funcionalitat del paisatge i la biodiversitat que subjau en els agroecosistemes. Per a això, es proposen models basats en tals matèries. Les principals unitats d'anàlisi seran les cobertes del sòl, quan treballem a escala regional, i els usos del sòl, a escala local. En el segon capítol, es presenta un model de pertorbació-complexitat intermèdia (IDC) dels paisatges culturals. Aquest enfocament té com a objectiu avaluar com els diferents nivells de pertorbacions antropogèniques sobre els ecosistemes afecten la capacitat d'acollir la biodiversitat en funció de l'heterogeneïtat d'usos sòl. S'aplica a l'illa de Mallorca, enmig de la zona activa de la biodiversitat mediterrània, a escala regional i de paisatge. El model utilitza la pertorbació exercida pels agricultors que alteren la producció primària neta a través del canvi d'usos del sòl, així com l'eliminació d'una part d'ella, juntament amb l'índex de Shannon-Wiener de la diversitat d'usos del sòl. El model es prova en un disseny experimental a dues escales al llarg de tres punts de temps. La riquesa d'espècies d'aus nidificants i hivernants, preses com a indicador de la biodiversitat, s'utilitza en una anàlisi factorial exploratori. Seguint la idea presentada en el segon capítol, en el tercer capítol es presenta un mètode per descriure la relació entre els indicadors d'heterogeneïtat d'usos del sòl, i l'apropiació humana de la producció primària neta en una regió determinada. Aquestes quantitats són vistes com a funcions del vector de proporcions de les cobertes de sòl, que al seu torn es tracta com un vector aleatori els valors del qual depenen de la unitat de terreny que s'observa. Presentem el mètode suposant, en primer lloc, que el vector de proporcions segueix una distribució uniforme en el símplex. Després, considerem com a punt de partida un conjunt de dades mostals, de manera que primer hem d'obtenir una estimació de la seva distribució de probabilitat teòrica, i en segon lloc, generem una mostra de grans dimensions seguint la distribució estimada. Apliquem aquest procediment a dades de l'illa de Mallorca en tres moments de temps diferents. L'objectiu principal aquí és calcular el valor esperat de la diversitat del paisatge com a funció del nivell d'apropiació humana. Aquesta funció està relacionada amb l'anomenada hipòtesi d'energia i espècies, i amb l'hipòtesi de la Pertorbació Intermèdia. Finalment, el quart capítol està dedicat a tractar els processos interns dels agroecosistemes. Per a aquest propòsit, es proposa un graf que representa el patró de fluxos d'energia en un agroecosistema. Utilitzem aquest graf per calcular el nivell d'emmagatzematge d'energia dins de l'agroecosistema, així com la informació inclosa en aquesta xarxa de fluxos, a escales tant local com de paisatge. Per tant, es proposa un model d'anàlisi integrat d'energia i paisatge (ELIA) que avalua tant la complexitat dels bucles d'energia interna, com la informació continguda en tota la xarxa de fluxos d'energia soci-metabòliques, per tal de correlacionar aquesta interacció d'informació energètica amb l'estructura funcional del paisatge. A l'annex, es suggereix una millora de l'indicador d'informació. ELIA es prova en el Vallès, a la Regió Metropolitana de Barcelona.
Mathematical models are used to better explain natural phenomena. Since natural phenomena are very complex, in order to delve into their behaviour and be able to do predictions over them, a simplification process of such systems is needed. In the process of creating the model, the system is translated into mathematical language that allows the study of the system from a new point of view. In this thesis, statistical models are considered to study the behaviour of agroecosystems at different spatial scales. The aim of this work is to study the relation between energy flows, land cover changes, landscape functionality and the biodiversity that underlies in agroecosystems. For this, models based on such matters are proposed. The main units of analysis will be the land covers, when we work at regional scale, and the land uses, at local scale. In the second chapter, an intermediate disturbance-complexity model (IDC) of cultural landscapes is presented. This approach is aimed at assessing how different levels of anthropogenic disturbance on ecosystems affect the capacity to host biodiversity depending on the land matrix heterogeneity. It is applied to the Mallorca Island, amidst the Mediterranean biodiversity hotspot, at regional and landscape scales. The model uses the disturbance exerted by farmers altering the Net Primary Production (NPP) through land use change, as well as removing a share of it, together with Shannon-Wiener index of land use diversity. The model is tested with a twofold-scalar experimental design of a set of landscape units along three time points. Species richness of breeding and wintering birds, taken as a biodiversity proxy, is used in an exploratory factor analysis. Following the idea presented in the second chapter, in the third chapter we present a method to describe the relation between indicators of the land matrix heterogeneity, and the human appropriation of the net primary production in a given region. These quantities are viewed as functions of the vector of proportions of the different land covers, which is in turn treated as a random vector whose values depend on the particular small terrain cell that is observed. We illustrate the method assuming first that the vector of proportions follows a uniform distribution on the simplex. We then consider as starting point a raw dataset of proportions for each cell, for which we must first obtain an estimate of its theoretical probability distribution, and secondly generate a sample of large size from it. We apply this procedure to real historical data of the Mallorca Island in three different time points. The main goal here is to compute the mean value of the land covers diversity as a function of the level of human appropriation of net primary production. This function is related to the so-called Energy-Species hypothesis and to the Intermediate Disturbance Hypothesis. Finally, fourth chapter is devoted to deal with agroecosystems internal processes. For this purpose, a graph to represent the pattern of energy flows in an agroecosystem is presented. We use this graph model to calculate the level of energy storage within the agroecosystem provided by its ‘internal feedback’, as well as the information embedded in this network of flows, at local and landscape scales. Thus, we propose an Energy-Landscape Integrated Analysis (ELIA) model that assesses both the complexity of internal energy loops, and the information held in the whole network of socio-metabolic energy fluxes, so as to correlate this energy-information interplay with the functional landscape structure. In the annex, an improvement of the information indicator is suggested. ELIA is tested in the Vallès County of the Barcelona Metropolitan Region.

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Yang, Wen. "Drought Analysis under Climate Change by Application of Drought Indices and Copulas." PDXScholar, 2010. https://pdxscholar.library.pdx.edu/open_access_etds/716.

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Drought is a recurrent extreme climate event with tremendous hazard for every specter of natural environment and human lives. Drought analysis usually involves characterizing drought severity, duration and intensity. Similar to most of the hydrological problems, such characteristic variables are usually not independent. Copula, as a model of multivariate distribution, widely used in finance, actuarial analysis, has won increasingly popularity in hydrological study. Here, the study has two major focuses: (1) fit drought characteristics from Streamflow Drought Index (SDI) or Standardized Runoff Index (SRI) to appropriate copulas, then using fitted copulas to estimate conditional drought severity distribution and joint return periods for both historical time period 1920-2009 and future time period 2020-2090. SDI is calculated based on long term observed streamflow while SRI is based on simulated future runoff. Parameters estimation of marginal distribution and copulas are provided, with goodness fit measures as well; (2) investigate the effects of climate change on the frequency and severity of droughts. In order to quantify the impact, three drought indices have been proposed for this study to characterize the drought duration, severity and intensity changes under the climate change in Upper Klamath River Basin. Since drought can be defined as different types, such as meteorological drought, agricultural drought, hydrological drought and social economical drought, this study chooses Standardized Precipitation Index (SPI), Palmer Drought Severity Index (PDSI) and Surface Water Supply Index (SWSI) to estimate the meteorological, agricultural and hydrological drought, respectively. Climate change effects come from three sources: the inherent reason, the human activity and the GCMs uncertainties. Therefore, the results show the long term drought condition by calculating yearly drought indices, and compared in three ways: First, compare drought characteristics of future time periods with base period; second, show the uncertainties of three greenhouse gas emission scenarios; third, present the uncertainties of six General Circulation Models (GCMs).

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Sun, Bo. "Spatio-temporal modelling of landuse and land cover change in arid zone, northwest China." HKBU Institutional Repository, 2010. https://repository.hkbu.edu.hk/etd_ra/1163.

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Yereniuk, Michael A. "Global Approximations of Agent-Based Model State Changes." Digital WPI, 2020. https://digitalcommons.wpi.edu/etd-dissertations/614.

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How can we model global phenomenon based on local interactions? Agent-Based (AB) models are local rule-based discrete method that can be used to simulate complex interactions of many agents. Unfortunately, the relative ease of implementing the computational model is often counter-balanced by the difficulty of performing rigorous analysis to determine emergent behaviors. Calculating existence of fixed points and their stability is not tractable from an analytical perspective and can become computationally expensive, involving potentially millions of simulations. To construct meaningful analysis, we need to create a framework to approximate the emergent, global behavior. Our research has been devoted to developing a framework for approximating AB models that move via random walks and undergo state transitions. First, we developed a general method to estimate the density of agents in each state for AB models whose state transitions are caused by neighborhood interactions between agents. Second, we extended previous random walk models of instantaneous state changes by adding a cumulative memory effect. In this way, our research seeks to answer how memory properties can also be incorporated into continuum models, especially when the memory properties effect state changes on the agents. The state transitions in this type of AB model is primarily from the agents’ interaction with their environment. These modeling frameworks will be generally applicable to many areas and can be easily extended.

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Pettus, Paul Bryce. "Modeling Fecal Bacteria in Oregon Coastal Streams Using Spatially Explicit Watershed Characteristics." PDXScholar, 2013. https://pdxscholar.library.pdx.edu/open_access_etds/1493.

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Pathogens, such as Escherichia coli and fecal coliforms, are causing the majority of water quality impairments in U.S., making up ~87% of this grouping's violations. Predicting and characterizing source, transport processes, and microbial survival rates is extremely challenging, due to the dynamic nature of each of these components. This research built upon current analytical methods that are used as exploratory tools to predict pathogen indicator counts across regional scales. Using a series of non-parametric methodologies, with spatially explicit predictors, 6657 samples from non-estuarine lotic streams were analyzed to make generalized predictions of regional water quality. 532 frequently sampled sites in the Oregon Coast Range Ecoregion, were parsed down to 93 pathogen sampling sites in effect to control for spatial and temporal biases. This generalized model was able to provide credible results in assessing regional water quality, using spatial techniques, and applying them to infrequently or unmonitored catchments. This model's 56.5% explanation of variation, was comparable to other researchers' regional assessments. This research confirmed linkages to land uses related to anthropogenic activities such as animal operations and agriculture, and general riparian conditions.

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Worton, Adrian J. "Using mathematical models to understand the impact of climate change on tick-borne infections across Scotland." Thesis, University of Stirling, 2016. http://hdl.handle.net/1893/24918.

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Ticks are of global interest as the pathogens they spread can cause diseases that are of importance to both human health and economies. In Scotland, the most populous tick species is the sheep tick Ixodes ricinus, which is the vector of pathogens causing diseases such as Lyme borreliosis and Louping-ill. Recently, both the density and spread of I. ricinus ticks have grown across much of Europe, including Scotland, increasing disease risk. Due to the nature of the tick lifecycle they are particularly dependent on environmental factors, including temperature and habitat type. Because of this, the recent increase in tick-borne disease risk is believed to be linked to climate change. Many mathematical models have been used to explore the interactions between ticks and factors within their environments; this thesis begins by presenting a thorough review of previous modelling of tick and tick-borne pathogen dynamics, identifying current knowledge gaps. The main body of this thesis introduces an original mathematical modelling framework with the aim to further our understanding of the impact of climate change on tick-borne disease risk. This modelling framework takes into account how key environmental factors influence the I. ricinus lifecycle, and is used to create predictions of how I. ricinus density and disease risk will change across Scotland under future climate warming scenarios. These predictions are mapped using Geographical Information System software to give a clear spatial representation of the model predictions. It was found that as temperatures increase, so to do I. ricinus densities, as well as Louping-ill and Lyme borreliosis risk. These results give a strong indication of the disease risk implications of any changes to the Scottish environment, and so have the potential to inform policy-making. Additionally, the models identify areas of possible future research.

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Jiang, Jixiang. "Specifying and Detecting Topological Changes to an Areal Object." Fogler Library, University of Maine, 2009. http://www.library.umaine.edu/theses/pdf/JiangJ2009.pdf.

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18

Bush, Timothy. "Response to environmental perturbations in microbial nutrient-cycling ecosystems." Thesis, University of Edinburgh, 2015. http://hdl.handle.net/1842/15789.

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The habitability of Earth is dependent upon the global recycling of elements essential for life, such as nitrogen, sulfur and carbon. Nutrient-cycling by micro-organisms is vital to these biogeochemical cycles because many key steps are mediated primarily, or exclusively, by microbial life. The dynamics of these cycles are highly complex, and environmental perturbations (such as changes in the oceanic oxygen concentration) can have unexpected or catastrophic effects; often causing abrupt switches between chemical states. Despite the importance of these environmental perturbations however, few theoretical models have addressed how they affect the dynamical behaviour of nutrient-cycling microbial ecosystems. In this work, we investigate the effect of environmental perturbations on microbially-mediated nutrient cycles and assess the likelihood of "sudden transitions" between chemical states of the ecosystem occurring in a variety of ecological contexts. To do this, we first use computational modelling of microbial nutrient-cycling, using a "box model" approach. We then move on to an experimental study using the microbial sulfur cycle as a model ecosystem, with freshwater pond sediment/water microcosms. These microcosms have the advantage of retaining many of the features of the real ecosystem (such as microbial diversity, spatial structure, and abiotic interactions) while allowing the controlled manipulation of environmental perturbations. We study these microcosms using a combination of chemical measurements and high-throughput sequencing of the microbial community. Finally, we return to the computational side, and attempt to reproduce chemical data from our experiments in a mathematical model containing realistic abiotic chemical interactions.

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19

Burgess, Peter Mark. "A quantitative forward modelling analysis of the controls on passive rift-margin stratigraphy." Thesis, University of Oxford, 1994. http://ora.ox.ac.uk/objects/uuid:1249833d-ef11-4327-bdbd-5d0c40faa29e.

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A quantitative forward model has been developed to investigate the controls on the deposition, erosion, and preservation of passive rift margin stratigraphy. The model includes thermal subsidence, variable absolute sealevel, flexural isostasy, subaerial and submarine deposition on fluvial and marine equilibrium profiles, and the facility to vary sediment supply through time. Results from the quantitative model can be used to reproduce elements of the sequence stratigraphic depositional model. Conducting sensitivity tests demonstrates that variables such as sediment supply and fluvial profile behaviour are likely to be of equal importance to thermal subsidence and eustasy in passive margin stratigraphy. Sensitivity tests with the quantitative model also demonstrate the problems associated with attempting to use a discretised stratigraphic model to investigate unforced cyclicty resulting from complex interactions in stratigraphic systems. Although the model appears capable of producing such unforced cyclical behaviour, this cyclicity is shown to be due to a numerical instability within the model which occurs with certain initial conditions and assumptions. The applicability of the model to observed stratigraphy is tested by comparing specific model output to patterns of stratigraphy from the North American Atlantic margin. The results from this test demonstrate that although the model is in many respects simplistic when compared to the complexities of natural systems, it is nevertheless capable of reproducing some of the basic elements of the observed stratigraphic patterns.

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20

Tidwell, Amy C. "Assessing the impacts of climate change on river basin management a new method with application to the Nile river/." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/19830.

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Thesis (Ph.D)--Civil and Environmental Engineering, Georgia Institute of Technology, 2007.
Committee Chair: Georgakakos, Aris; Committee Member: Fu, Rong; Committee Member: Peters-Lidard, Christa; Committee Member: Roberts, Phil; Committee Member: Sturm, Terry; Committee Member: Webster, Don.

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Briesemeister, Roberta. "Modelagem matematica para o estudo do oidio em uma plantação de soja sob os efeitos do CO2." [s.n.], 2007. http://repositorio.unicamp.br/jspui/handle/REPOSIP/307575.

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Orientador: Laercio Luis Vendite
Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica
Made available in DSpace on 2018-08-08T21:33:03Z (GMT). No. of bitstreams: 1 Briesemeister_Roberta_M.pdf: 814655 bytes, checksum: bf6c5b877276e48f013d98984a004dde (MD5) Previous issue date: 2007
Resumo: As recentes mudanças climáticas no planeta, estão promovendo alterações na ocorrência e desenvolvimento de doenças de plantas. O principal gás causador desse acontecimento é o dióxido de carbono, CO2. Baseado neste fato, foi desenvolvido pela Embrapa Meio Ambiente, um experimento que trabalha com cenários futuros, tendo em vista a quantidade de CO2 presente na atmosfera. Preliminarmente foi feita uma análise estatística dos dados, verificando a área foliar lesionada, a altura das plantas primárias de soja, a nodulação e o peso seco. Com os resultados obtidos nessa análise, observamos que havia uma diferença significativa no tamanho da área foliar lesionada quando exposto a níveis diferentes de CO2. À partir desses dados, foi elaborado um modelo matemático determinístico para a previsão do crescimento da área foliar lesionada, causada pelo oídio, acoplando na taxa de crescimento da lesão a influência da quantidade de CO2. Algumas simulações foram feitas utilizando o crescimento da quantidade de CO2 da atmosfera. Com os dados existentes de anos anteriores, observamos em todos os casos, que altos níveis de CO2, provocam uma diminuição na área foliar lesionada. Muito embora exista uma diminuição nessa área, a quantidade do patógeno cresce exponecialmente no tempo. O que nos faz concluir, que em cenários futuros, haverá uma grande dissiminação na doença da soja, provocada pelo oídio
Abstract: The recently climate changes of the planet are promoving alteration in the incident and development in the plants diseases. The main gas that cause this event is the carbon dioxide, CO2. Based in this fact, it was developed by Embrapa environmental, the experiment that works with futures scenarios, looking the quality of CO2 present in the atmosphere. First of all it was made a statistic analyses of datas, verifing the leaf area that was damned, the hights of the primary soybeans plants, the nodulation and the dry weight. With the results that was gotten in this analyses, we could notice that it had a significant difference in the size of the leafs area damned when it was expose in differents levels of CO2. Starting from this datas, it was elaborated a deterministical mathematic model for crop the growing leaf area damned, caused by mildew, coupled in the growing rate of the damned area the influence of the CO2 quantity. Some simulation it were done using the growing quantity of CO2 in the atmosphere. With the presents datas of the years, we observe that in all cases, that hight level of CO2 cause the reduction of the damned leafs area. Even thought exists a reduction in this area, the quantity of pathogen grows exponentially in the times. What make us conclude, that in futures scenarios, will have a big spread in the soybean disease, caused py mildew
Mestrado
Mestre em Matemática Aplicada

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22

Psaris, Alexander Michael. "Assessing Hydrologic and Water Quality Sensitivities to Precipitation Changes, Urban Growth and Land Management Using SWAT." PDXScholar, 2014. https://pdxscholar.library.pdx.edu/open_access_etds/1783.

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Precipitation changes and urban growth are two factors altering the state of water quality. Changes in precipitation will alter the amount and timing of flows, and the corresponding sediment and nutrient dynamics. Meanwhile, densification associated with urban growth will create more impervious surfaces which will alter sediment and nutrient loadings. Land and water managers often rely on models to develop possible future scenarios and devise management responses to these projected changes. We use the Soil and Water Assessment Tool (SWAT) to assess the sensitivities of stream flow, sediment, and nutrient loads in two urbanizing watersheds in Northwest Oregon, USA to various climate and urbanization scenarios. We evaluate the spatial patterns climate change and urban growth will have on water, sediment and nutrient yields. We also identify critical source areas (CSAs) and investigate how implementation of vegetative filter strips (VFS) could ameliorate the effects of these changes. Our findings suggest that: 1) Water yield is tightly coupled to precipitation. 2) Large increases in winter and spring precipitation provide enough sub-surface storage to increase summertime water yields despite a moderate decrease in summer precipitation. 3) Expansion of urban areas increases surface runoff and has mixed effects on sediment and nutrients. 4) Implementation of VFS reduces pollutant loads helping overall watershed health. This research demonstrates the usefulness of SWAT in facilitating informed land and water management decisions.

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23

Zhang, Yan. "The radiative effect of aerosols from biomass burning on the transition from dry to wet season over the amazon as tested by a regional climate model." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/26510.

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Thesis (Ph.D)--Earth and Atmospheric Sciences, Georgia Institute of Technology, 2009.
Committee Chair: Fu, Rong; Committee Member: Dickinson, Robert E.; Committee Member: Nenes, Athanasios; Committee Member: Webster,Peter J.; Committee Member: Yu, Hongbin. Part of the SMARTech Electronic Thesis and Dissertation Collection.

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24

Zelenke, Brian Christopher. "An empirical statistical model relating winds and ocean surface currents : implications for short-term current forecasts." Thesis, Connect to the title online, 2005. http://hdl.handle.net/1957/2166.

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Dars, Ghulam Hussain. "Climate Change Impacts on Precipitation Extremes over the Columbia River Basin Based on Downscaled CMIP5 Climate Scenarios." PDXScholar, 2013. https://pdxscholar.library.pdx.edu/open_access_etds/979.

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Hydro-climate extreme analysis helps understanding the process of spatio-temporal variation of extreme events due to climate change, and it is an important aspect in designing hydrological structures, forecasting floods and an effective decision making in the field of water resources design and management. The study evaluates extreme precipitation events over the Columbia River Basin (CRB), the fourth largest basin in the U.S., by simulating four CMIP5 global climate models (GCMs) for the historical period (1970-1999) and future period (2041-2070) under RCP85 GHG scenario. We estimated the intensity of extreme and average precipitation for both winter (DJF) and summer (JJA) seasons by using the GEV distribution and multi-model ensemble average over the domain of the Columbia River Basin. The four CMIP5 models performed very well at simulating precipitation extremes in the winter season. The CMIP5 climate models showed heterogeneous spatial pattern of summer extreme precipitation over the CRB for the future period. It was noticed that multi-model ensemble mean outperformed compared to the individual performance of climate models for both seasons. We have found that the multi-model ensemble shows a consistent and significant increase in the extreme precipitation events in the west of the Cascades Range, Coastal Ranges of Oregon and Washington State, the Canadian portion of the basin and over the Rocky Mountains. However, the mean precipitation is projected to decrease in both winter and summer seasons in the future period. The Columbia River is dominated by the glacial snowmelt, so the increase in the intensity of extreme precipitation and decrease in mean precipitation in the future period, as simulated by four CMIP5 models, is expected to aggravate the earlier snowmelt and contribute to the flooding in the low lying areas especially in the west of the Cascades Range. In addition, the climate change shift could have serious implications on transboundary water issues in between the United States and Canada. Therefore, adaptation strategies should be devised to cope the possible adverse effects of the changing the future climate so that it could have minimal influence on hydrology, agriculture, aquatic species, hydro-power generation, human health and other water related infrastructure.

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Mohobane, Thabiso. "Water resources availability in the Caledon River basin : past, present and future." Thesis, Rhodes University, 2015. http://hdl.handle.net/10962/d1019802.

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The Caledon River Basin is located on one of the most water-scarce region on the African continent. The water resources of the Caledon River Basin play a pivotal role in socio-economic activities in both Lesotho and South Africa but the basin experiences recurrent severe droughts and frequent water shortages. The Caledon River is mostly used for commercial and subsistence agriculture, industrial and domestic supply. The resources are also important beyond the basin’s boundaries as the water is transferred to the nearby Modder River. The Caledon River is also a significant tributary to the Orange-Senqu Basin, which is shared by five southern African countries. However, the water resources in the basin are under continuous threat as a result of rapidly growing population, economic growth as well as changing climate, amongst others. It is therefore important that the hydrological regime and water resources of the basin are thoroughly evaluated and assessed so that they can be sustainably managed and utilised for maximum economic benefits. Climate change has been identified by the international community as one of the most prominent threats to peace, food security and livelihood and southern Africa as among the most vulnerable regions of the world. Water resources are perceived as a natural resource which will be affected the most by the changing climate conditions. Global warming is expected to bring more severe, prolonged droughts and exacerbate water shortages in this region. The current study is mainly focused on investigating the impacts of climate change on the water resources of the Caledon River Basin. The main objectives of the current study included assessing the past and current hydrological characteristics of the Caledon River Basin under current state of the physical environment, observed climate conditions and estimated water use; detecting any changes in the future rainfall and evaporative demands relative to present conditions and evaluating the impacts of climate on the basin’s hydrological regime and water resources availability for the future climate scenario, 2046-2065. To achieve these objectives the study used observed hydrological, meteorological data sets and the basin’s physical characteristics to establish parameters of the Pitman and WEAP hydrological models. Hydrological modelling is an integral part of hydrological investigations and evaluations. The various sources of uncertainties in the outputs of the climate and hydrological models were identified and quantified, as an integral part of the whole exercise. The 2-step approach of the uncertainty version of the model was used to estimate a range of parameters yielding behavioural natural flow ensembles. This approach uses the regional and local hydrological signals to constrain the model parameter ranges. The estimated parameters were also employed to guide the calibration process of the Water Evaluation And Planning (WEAP) model. The two models incorporated the estimated water uses within the basin to establish the present day flow simulations and they were found to sufficiently simulate the present day flows, as compared to the observed flows. There is an indication therefore, that WEAP can be successfully applied in other regions for hydrological investigations. Possible changes in future climate regime of the basin were evaluated by analysing downscaled temperature and rainfall outputs from a set of 9 climate models. The predictions are based on the A2 greenhouse gases emission scenario which assumes a continuous increase in emission rates. While the climate models agree that temperature, and hence, evapotranspiration will increase in the future, they demonstrate significant disagreement on whether rainfall will decrease or increase and by how much. The disagreement of the GCMs on projected future rainfall constitutes a major uncertainty in the prediction of water resources availability of the basin. This is to the extent that according to 7 out of 9 climate models used, the stream flow in four sub-basins (D21E, D22B, D23D and D23F) in the Caledon River Basin is projected to decrease below the present day flows, while two models (IPSL and MIUB) consistently project enhanced water resource availability in the basin in the future. The differences in the GCM projections highlight the margin of uncertainty involved predicting the future status of water resources in the basin. Such uncertainty should not be ignored and these results can be useful in aiding decision-makers to develop policies that are robust and that encompass all possibilities. In an attempt to reduce the known uncertainties, the study recommends upgrading of the hydrological monitoring network within the Caledon River Basin to facilitate improved hydrological evaluation and management. It also suggests the use of updated climate change data from the newest generation climate models, as well as integrating the findings of the current research into water resources decision making process.

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Nemeth, Michael W., and University of Lethbridge Faculty of Arts and Science. "Climate change impacts on streamflow in the upper North Saskatchewan River Basin, Alberta." Thesis, Lethbridge, Alta. : University of Lethbridge, Dept. of Geography, c2010, 2010. http://hdl.handle.net/10133/2477.

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This research focuses on the estimation of the impacts of climate change on water yield, streamflow extremes, and the streamflow regimes in the Cline River Watershed, and consequently, water availability for hydropower generation in this area. The Cline River Watershed comprises the flow into Lake Abraham, the reservoir for Bighorn Dam, is part of the upper North Saskatchewan River basin (UNSRB). This objective was achieved by parameterizing the ACRU agro-hydrological modelling system. After parameterization was complete, ACRU output was calibrated and verified against available observed data, including temperature, snow water equivalent, glacier mass balance, potential evapotranspiration, and streamflow data. After ACRU was properly verified, five selected climate change scenarios to estimate impacts of climate change in this area. Overall water yields are projected to increase over time. A large shift in seasonality is likely the biggest impact climate change will have on water resources in the Cline River Watershed.
xii, 126 leaves : ill., maps ; 29 cm

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Halmstad, Andrew Jason. "Investigating Future Variation of Extreme Precipitation Events over the Willamette River Basin Using Dynamically Downscaled Climate Scenarios." PDXScholar, 2011. https://pdxscholar.library.pdx.edu/open_access_etds/327.

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One important aspect related to the management of water resources under future climate variation is the occurrence of extreme precipitation events. In order to prepare for extreme events, namely floods and droughts, it is important to understand how future climate variability will influence the occurrence of such events. Recent advancements in regional climate modeling efforts provide additional resources for investigating the occurrence of extreme events at scales that are appropriate for regional hydrologic modeling. This study utilizes data from three Regional Climate Models (RCMs), each driven by the same General Circulation Model (GCM) as well as a reanalysis dataset, all of which was made available by the North American Regional Climate Change Assessment Program (NARCCAP). A comparison between observed historical precipitation events and NARCCAP modeled historical conditions over Oregon's Willamette River basin was performed. This comparison is required in order to investigate the reliability of regional climate modeling efforts. Datasets representing future climate signal scenarios, also provided by NARCCAP, were then compared to historical data to provide an estimate of the variability in extreme event occurrence and severity within the basin. Analysis determining magnitudes of two, five, ten and twenty-five year return level estimates, as well as parameters corresponding to a representative Generalized Extreme Value (GEV) distribution, were determined. The results demonstrate the importance of the applied initial/boundary driving conditions, the need for multi-model ensemble analysis due to RCM variability, and the need for further downscaling and bias correction methods to RCM datasets when investigating watershed scale phenomena.

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Pham, Van Tan. "Prediction of Change in Quality of 'Cripps Pink' Apples during Storage." University of Sydney, 2008. http://hdl.handle.net/2123/5133.

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Doctor of Philosophy (PhD)
The goal of this research was to investigate changes in the physiological properties including firmness, stiffness, weight, background colour, ethylene production and respiration of ‘Cripps Pink’ apple stored under different temperature and atmosphere conditions,. This research also seeks to establish mathematical models for the prediction of changes in firmness and stiffness of the apple during normal atmosphere (NA) storage. Experiments were conducted to determine the quality changes in ‘Cripps Pink’ apple under three sets of storage conditions. The first set of storage conditions consisted of NA storage at 0oC, 2.5oC, 5oC, 10oC, 20oC and 30oC. In the second set of conditions the apples were placed in NA cold storage at 0oC for 61 days, followed by NA storage at the aforementioned six temperatures. The third set of conditions consisted of controlled atmosphere (CA) (2 kPa O2 : 1 kPa CO2) at 0oC storage for 102 days followed by NA storage at the six temperatures mentioned previously. The firmness, stiffness, weight loss, skin colour, ethylene and carbon dioxide production of the apples were monitored at specific time intervals during storage. Firmness was measured using a HortPlus Quick Measure Penetrometer (HortPlus Ltd, Hawke Bat, New Zealand); stiffness was measured using a commercial acoustic firmness sensor-AFS (AWETA, Nootdorp, The Netherlands). Experimental data analysis was performed using the GraphPad Prism 4.03, 2005 software package. The Least-Squares method and iterative non-linear regression were used to model and simulate changes in firmness and stiffness in GraphPad Prism 4.03, 2005 and DataFit 8.1, 2005 softwares. The experimental results indicated that the firmness and stiffness of ‘Cripps Pink’ apple stored in NA decreased with increases in temperature and time. Under NA, the softening pattern was tri-phasic for apples stored at 0oC, 2.5oC and 5oC for firmness, and at 0oC and 2.5oC for stiffness. However, there were only two softening phases for apples stored at higher temperatures. NA at 0oC, 2.5oC and 5oC improved skin background colour and extended the storage ability of apples compared to higher temperatures. CA during the first stage of storage better maintained the firmness and stiffness of the apples. However, it reduced subsequent ethylene and carbon dioxide (CO2) production after removal from storage. Steep increases in ethylene and CO2 production coincided with rapid softening in the fruit flesh and yellowing of the skin background colour, under NA conditions. The exponential decay model was the best model for predicting changes in the firmness, stiffness and keeping quality of the apples. The exponential decay model satisfied the biochemical theory of softening in the apple, and had the highest fitness to the experimental data collected over the wide range of temperatures. The softening rate increased exponentially with storage temperature complying with the Arrhenius equation. Therefore a combination of the exponential decay model with the Arrhenius equation was found to best characterise the softening process and to predict changes in the firmness and stiffness of apples stored at different temperatures in NA conditions.

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Ben, Daoued Amine. "Modélisation de la conjonction pluie-niveau marin et prise en compte des incertitudes et de l’impact du changement climatique : application au site du Havre." Thesis, Compiègne, 2019. http://www.theses.fr/2019COMP2528.

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La modélisation des combinaisons de phénomènes d’inondation est une problématique d’actualité pour la communauté scientifique qui s’intéresse en priorité aux sites urbains et nucléaires. En effet, il est fort probable que l’approche déterministe explorant un certain nombre de scénarios possède certaines limites car ces scénarios déterministes assurent un conservatisme souvent excessif. Les approches probabilistes apportent une précision supplémentaire en s’appuyant sur les statistiques et les probabilités pour compléter les approches déterministes. Ces approches probabilistes visent à identifier et à combiner plusieurs scénarios d’aléa possibles pour couvrir plusieurs sources possibles du risque. L’approche probabiliste d’évaluation de l’aléa inondation (Probabilistic Flood Hazard Assessment ou PFHA) proposée dans cette thèse permet de caractériser une (des) quantité(s) d’intérêt (niveau d’eau, volume, durée d’immersion, etc.) à différents points d’un site en se basant sur les distributions des différents phénomènes de l’aléa inondation ainsi que les caractéristiques du site. Les principales étapes du PFHA sont : i) identification des phénomènes possibles (pluies, niveau marin, vagues, etc.), ii) identification et probabilisation des paramètres associés aux phénomènes d’inondation sélectionnés, iii) propagation de ces phénomènes depuis les sources jusqu’aux point d’intérêt sur le site, iv) construction de courbes d’aléa en agrégeant les contributions des phénomènes d’inondation. Les incertitudes sont un point important de la thèse dans la mesure où elles seront prises en compte dans toutes les étapes de l’approche probabiliste. Les travaux de cette thèse reposent sur l’étude de la conjonction de la pluie et du niveau marin et apportent une nouvelle méthode de prise en compte du déphasage temporel entre les phénomènes (coïncidence). Un modèle d’agrégation a été développé afin de combiner les contributions des différents phénomènes d’inondation. La question des incertitudes a été étudiée et une méthode reposant sur la théorie des fonctions de croyance a été utilisée car elle présente des avantages divers par rapport aux autres concepts (modélisation fidèle dans les cas d’ignorance totale et de manque d’informations, possibilité de combiner des informations d’origines et de natures différentes, etc.). La méthodologie proposée est appliquée au site du Havre, en France
The modeling of the combinations of flood hazard phenomena is a current issue for the scientific community which is primarily interested in urban and nuclear sites. Indeed, it is very likely that the deterministic approach exploring several scenarios has certain limits because these deterministic scenarios ensure an often excessive conservatism. Probabilistic approaches provide additional precision by relying on statistics and probabilities to complement deterministic approaches. These probabilistic approaches aim to identify and combine many possible hazard scenarios to cover many possible sources of risk. The Probabilistic Flood Hazard Assessment (PFHA) proposed in this thesis allows to characterize a quantity(ies) of interest (water level, volume, duration of immersion, ect.) at different points of interest of a site based on the distributions of the different phenomena of the flood hazard as well as the characteristics of the site. The main steps of the PFHA are: i) screening of the possible phenomena (rainfall, sea level, waves, ect.), ii) identification and probabilization of the parameters representative of the selected flood phenomena, iii) propagation of these phenomena from their sources to the point of interest on the site, iv) construction of hazard curves by aggregating the contributions of the flood phenomena. Uncertainties are an important topic of the thesis insofar as they will be taken into account in all the steps of the probabilistic approach. The work of this thesis is based on the study of the conjunction of rain and sea level and provide a new method for taking into account the temporal phase shift between the phenomena (coincidence). An aggregation model has been developed to combine the contributions of different flood phenomena. The question of uncertainties has been studied and a method based on the theory of belief functions has been used because it has various advantages (faithful modeling in cases of total ignorance and lack of information, possibility to combine information of different origins and natures, ect.). The proposed methodology is applied on the site of Le Havre in France

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Schwartz, Carmit M. Economics Australian School of Business UNSW. "Individuals' responses to changes in risk: a person-specific analysis." 2007. http://handle.unsw.edu.au/1959.4/40575.

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In this thesis we consider two comparative statics questions of changes in risk. The first question concerns situations where an individual faces some risk and has no control over the uncertain environment. In these situations we ask what kind of changes in risk will cause the individual's expected utility to increase. The second comparative statics question concerns situations where an individual faces some risk and has some control over the uncertain environment. In particular, we consider situations where the individual maximizes her expected utility with respect to some control parameter. Here we ask what kind of changes in risk will cause the individual's optimal value of the control parameter to increase. The existing literature has answered these questions for a class of individuals (for example, the class of risk averse individuals). This thesis differs from existing literature as it focuses on a given individual, and thus reveals some of the person-specific factors that affect individual?s responses to changes in risk. The aim of the thesis is to show how an order on distributions, termed single crossing likelihood ratio (SCLR) order, can intuitively answer both questions for a given individual. The main contributions of the thesis are as follows. First, the thesis presents the SCLR order and its main properties. Second, the thesis shows that the SCLR order can answer the above comparative statics questions in an intuitive way. In particular, the thesis shows that the answer to the above questions, with the use of the SCLR order, depends on a risk reference point which can be interpreted as a "certainty equivalent" point. Thus it is demonstrated that individual's responses to changes in risk are affected by her "certainty equivalent" point. Lastly, the results of the thesis can be used to provide an intuitive explanation of related existing results that were obtained for a class of individuals.

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32

Coonce, Vincent M. "Dynamic simulation of drying and quality changes during malt kilning." Thesis, 1991. http://hdl.handle.net/1957/27148.

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The principal aim of this study was the use and evaluation of dynamic modeling techniques to identify mathematical models for cereal drying rates and quality changes that best describe thin-layer malt drying data. Seven thin-layer malt drying experiments were performed at the Great Western Malting pilot facilities, Vancouver, WA. Malt moisture content, temperature, β-amylase activity, endo-barley-β-glucanase activity, and color were all monitored as the malt was dried with air at various temperature and relative humidity values. A constrained direct search optimization method was used to fit available drying, enzyme deactivation, and color formation models to the data obtained by minimizing the error between predicted and experimental values. Because the deactivation of β- amylase observed during the kiln experiments was less than the error involved in β-amylase measurement, β-amylase modeling efforts were dropped from the study. The end result is a computer simulation of the malt kilning process that can predict malt drying rates, color formation, and endo-barley-β-glucanase deactivation based on the drying air temperature, relative humidity, and time spent in the kiln. Further research is suggested towards modeling malt drying rates at high moisture contents, (above 40%) analysis of drying model applicability when drying conditions fall outside those encountered in this study, and development of assay procedures and models so that the fate of other important malt quality indicators during kiln drying can be predicted.
Graduation date: 1993

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33

Del, Valle Sara Yeminah. "Effects of behavioral changes and mixing patterns in mathematical models for smallpox epidemics." 2005. http://ir.uiowa.edu/etd/105.

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34

Farnham, David J. "Identifying and Modeling Spatio-temporal Structures in High Dimensional Climate and Weather Datasets with Applications to Water and Energy Resource Management." Thesis, 2018. https://doi.org/10.7916/D8321CTB.

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Weather and climate events are costly to society both financially and in terms of human health and well being. The costs associated with extreme climate events have motivated governments, NGOs, private investors, and insurance companies to use the data and tools at their disposal to estimate the past, present, and future hazards associated with a wide range of natural phenomena in an effort to develop mitigation and/or adaptation strategies. The nonstationary nature of climate risks requires the use of numerical climate models, often general circulation models (GCMs), to project future risk. The climate risk field, however, currently finds itself in a predicament because GCMs can be biased and do not provide a clear way to credibly estimate their uncertainty with respect to simulations of future surface climate conditions. In response to this predicament, I lay the groundwork for a set of GCM credibility assessments by identifying the large-scale drivers of surface climate events that evolve over a range of timescales ranging from daily to multi-decadal. I specifically focus on three types of climate events relevant to the water and energy sectors: 1) seasonal precipitation, which impacts drinking water supplies and agricultural productivity; 2) extreme precipitation and the costly associated riverine flooding; and 3) temperature, wind, and solar radiation fields that modulate both electricity demand and potential renewable electricity supply. In chapter I, I derive a set of atmospheric indices and investigate their efficacy to predict distributed seasonal precipitation throughout the conterminous United States. These indices can also be used to diagnose the impact of tropical sea surface temperature heating patterns on conterminous United States precipitation. This is particularly of interest in the aftermath of the unexpected precipitation patterns in the conterminous United States during the 2015-2016 El Niño event. I show that the set of atmospheric indices, which I derive from zonal winds over the conterminous United States and portions of the North Atlantic and Pacific oceans, can skillfully predict precipitation over most regions of the conterminous United States better than previously recognized mid-latitude atmospheric and tropical oceanic indices. This work contributes a set of intermediate atmospheric indices that can be used to assess the efficacy of forecasting and simulation climate models to capture signal that exists between tropical heating, mid-latitude circulation, and mid-latitude precipitation. In chapter II, I first show that the frequency of regional extreme precipitation events, which are predictive of riverine flooding, in the Ohio River Basin are poorly simulated by a GCM relative to historical precipitation observations. I then illustrate that the same GCM is much better able to simulate the statistical characteristics of a set of atmospheric field-derived indices that I show to be strongly related to the precipitation events of interest. Thus, I develop a statistical model that allows for the simulation of the precipitation events based on the GCM's atmospheric fields, which allows me to estimate future hazard based on credibly simulated GCM fields. Lastly, I validate the fully Bayesian statistical model against historical observations and use the statistical model to project the future frequency of the regional extreme precipitation events. I conclude that there is evidence of increasing regional riverine flood hazard in the Central US river basin out to the year 2100, but that there is high uncertainty regarding the magnitude of the trend. This work suggests that the identification of atmospheric circulation patterns that modulate the probability of extreme precipitation and riverine flood risk may improve flood hazard projections by allowing risk analysts to assess GCMs with respect to their ability to simulate relevant atmospheric patterns. In chapter III, I present the first comprehensive assessment of quasi-periodic decadal variations in wind and solar electricity potential and of covariability between heating and cooling electricity demand and potential wind and solar electricity production. I focus on six locations/regions in the conterminous United States that represent different climate zones and contain major load centers. The decadal variations are linked to quasi-oscillatory variations of the global climate system and lead to time-varying risks of meeting heating + cooling demand using wind/solar power. The quasi-cyclical patterns in renewable energy availability have significant ramifications for energy systems planning as we continue to increase our reliance on renewable, weather- and climate-dependent energy generation. This work suggests that certain modes of low frequency climate variability influence potential wind and solar energy supplies and are thus especially important for GCMs to credibly simulate. All of the investigations are designed to be broadly applicable throughout the mid-latitudes and are demonstrated with specific case studies in the conterminous United States. The dissertation sections represent three cases where statistical techniques can be used to understand surface climate and climate hazards. This understanding can ultimately help to mitigate and adapt to climate variabilities and secular changes, which impact society, by assisting in the development, improvement, and credibility assessment of GCMs capable of reliably projecting future climate hazards.

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Branstetter, Marcia Lynne 1963. "Development of a parallel river transport algorithm and applications to climate studies." 2001. http://hdl.handle.net/2152/10545.

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Mascioli, Nora Rose. "Impacts of anthropogenic aerosols on regional climate: extreme events, stagnation, and the United States warming hole." Thesis, 2018. https://doi.org/10.7916/D8X368FV.

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Extreme temperatures, heat waves, heavy rainfall events, drought, and extreme air pollution events have adverse effects on human health, infrastructure, agriculture and economies. The frequency, magnitude and duration of these events are expected to change in the future in response to increasing greenhouse gases and decreasing aerosols, but future climate projections are uncertain. A significant portion of this uncertainty arises from uncertainty in the effects of aerosol forcing: to what extent were the effects from greenhouse gases masked by aerosol forcing over the historical observational period, and how much will decreases in aerosol forcing influence regional and global climate over the remainder of the 21st century? The observed frequency and intensity of extreme heat and precipitation events have increased in the U.S. over the latter half of the 20th century. Using aerosol only (AER) and greenhouse gas only (GHG) simulations from 1860 to 2005 in the GFDL CM3 chemistry-climate model, I parse apart the competing influences of aerosols and greenhouse gases on these extreme events. I find that small changes in extremes in the “all forcing” simulations reflect cancellations between the effects of increasing anthropogenic aerosols and greenhouse gases. In AER, extreme high temperatures and the number of days with temperatures above the 90th percentile decline over most of the U.S., while in GHG high temperature extremes increase over most of the U.S. The spatial response patterns in AER and GHG are significantly anti-correlated, suggesting a preferred regional mode of response that is largely independent of the type of forcing. Extreme precipitation over the eastern U.S. decreases in AER, particularly in winter, and increases over the eastern and central U.S. in GHG, particularly in spring. Over the 21st century under the RCP8.5 emissions scenario, the patterns of extreme temperature and precipitation change associated with greenhouse gas forcing dominate. The temperature response pattern in AER and GHG is characterized by strong responses over the western U.S. and weak or opposite signed responses over the southeast U.S., raising the question of whether the observed U.S. “warming hole” could have a forced component. To address this question, I systematically examine observed seasonal temperature trends over all time periods of at least 10 years during 1901-2015. In the northeast and southern U.S., significant summertime cooling occurs from the early 1950s to the mid 1970s, which I partially attribute to increasing anthropogenic aerosol emissions (median fraction of the observed temperature trends explained is 0.69 and 0.17, respectively). In winter, the northeast and southern U.S. cool significantly from the early 1950s to the early 1990s, which I attribute to long-term phase changes in the North Atlantic Oscillation and the Pacific Decadal Oscillation. Rather than being a single phenomenon stemming from a single cause, both the warming hole and its dominant drivers vary by season, region, and time period. Finally, I examine historical and projected future changes in atmospheric stagnation. Stagnation, which is characterized by weak winds and an absence of precipitation, is a meteorological contributor to heat waves, extreme pollution, and drought. Using CM3, I show that regional stagnation trends over the historical period (1860-2005) are driven by changes in anthropogenic aerosol emissions, rather than rising greenhouse gases. In the northeastern and central United States, aerosol-induced changes in surface and upper level winds produce significant decreases in the number of stagnant summer days, while decreasing precipitation in the southeast US increases the number of stagnant summer days. Outside of the U.S., significant drying over eastern China in response to rising aerosol emissions contributed to increased stagnation during 1860-2005. Additionally, this region was found to be particularly sensitive to changes in local aerosol emissions, indicating that decreasing Chinese emissions in efforts to improve air quality will also decrease stagnation. In Europe, I find a dipole response pattern during the historical period wherein stagnation decreases over southern Europe and increases over northern Europe in response to global increases in aerosol emissions. In the future, declining aerosol emissions will likely lead to a reversal of the historical stagnation trends, with increasing greenhouse gases again playing a secondary role. Aerosols have a significant effect on a number of societally important extreme events, including heat waves, intense rainfall events, drought, and stagnation. Further, uncertainty in the strength of aerosol masking of historical greenhouse gas forcing is a significant source of spread in future climate projections. Quantifying these aerosol effects is therefore critical for our ability to accurately project and prepare for future changes in extreme events.

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"Three essays on panel unit root and cointegration tests with structural changes /cTam, Pui Sun." Thesis, 2008. http://library.cuhk.edu.hk/record=b6074523.

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The first chapter compares two types of univariate endogenous one-break unit root tests, namely the Dickey-Fuller (DF) type and the Schmidt-Phillips Lagrange Multiplier (LM) type tests. To investigate the small-sample properties of these tests, they are applied to the Nelson-Plosser macroeconomic time series with bootstrapped critical values used for unit root inference. Simulation results show that breaks under the null for the observed data are of sufficient magnitude to lead to size distortion for the DF-type tests, whereas the LM-type tests generally exhibit satisfactory size performance and possess the invariance property. Furthermore, in implementing the LM-type tests, the one that uses the minimum sum of squared residuals break selection method demonstrates better performance over the one that employs the minimum statistic break selection method.
The second chapter proposes LM type panel unit root test procedures with structural changes based on the group mean and combination test approaches. The proposed test procedures allow for breaks under both the null and alternative, and capture heterogeneity due to individual specific characteristics. The same set of distributions of the underlying individual LM statistics can be utilized to compute the panel statistics for the cases with no breaks and with intercept breaks as a result of the invariance property. Simulation results demonstrate that the inverse normal test exhibits the best overall finite-sample properties measured in terms of size and power. When break dates are unknown, the minimum sum of squared residuals break selection method is preferred. The bootstrap approach is suggested to account for cross-sectional dependence.
The third chapter studies panel cointegration tests dealing with two manifestations of structural changes, viz. breaks in the cointegrating relationship and breaks in the trend functions of time series. The importance of accounting for these breaks is highlighted using a simulation study. Finite-sample properties of the Gregory-Hansen (GH) type and LM type tests incorporating breaks in the cointegrating relationship are assessed. Two variants of the LM type tests are further examined in the presence of cross-sectional dependence taking on a factor structure. In the course of test comparison, some modifications are also suggested. A novel test procedure, based on the LM approach, is devised when trend functions of time series are subjected to breaks. Unlike existing tests, this procedure permits unknown breaks under both the null and alternative that can differ in locations among the variables under study.
This thesis investigates panel unit root and cointegration tests with structural changes that are generalizations of their univariate counterparts. Small-sample properties of two well-established univariate test procedures are first assessed using the bootstrap approach. Extensions of these procedures in the panel framework are then examined.
"February 2008."
Adviser: Win Lin Chou.
Source: Dissertation Abstracts International, Volume: 69-08, Section: A, page: 3266.
Thesis (Ph.D.)--Chinese University of Hong Kong, 2008.
Includes bibliographical references (p. 298-305).
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. Ann Arbor, MI : ProQuest dissertations and theses, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Abstracts in English and Chinese.
School code: 1307.

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38

Kelley, Colin Patrick. "Recent and future drying of the Mediterranean region: anthropogenic forcing, natural variability and social impacts." Thesis, 2014. https://doi.org/10.7916/D8CR5RFV.

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The Mediterranean region has experienced persistent drying since the middle of the 20th Century and global climate models project further drying in the future as a consequence of increasing greenhouse gases. The Mediterranean region is also known to oscillate between decades of relatively wet and dry conditions due to the strong influence of multidecadal North Atlantic Oscillation (NAO). It is therefore of great importance to understand the relationship between forced long-term drying resulting from human influences and those due to natural variability. To this end, we used observations, reanalyses and comprehensive global climate models in this thesis research. The roles of anthropogenic climate change and internal climate variability in causing the Mediterranean region's late 20th Century extended winter drying trend were examined using 20th Century observations as well as 19 coupled climate models from the CMIP3. The drying was strongly influenced by the robust positive trend in the NAO from the 1960s to the 1990s. Model simulations and observations were used to assess the probable relative roles of radiative forcing and internal variability in explaining the circulation trend that drove much of the precipitation change. It was concluded that the radiatively forced trends were a small fraction of the total observed trends. Instead it was argued that the robust trends in the observed NAO and Mediterranean rainfall during this period were largely due to multidecadal internal variability with a small contribution from the external forcing. Differences between the observed and NAO associated precipitation trends are consistent with those expected as a response to radiative forcing. The radiatively forced trends in circulation and precipitation are expected to strengthen in the current century and these results highlight the importance of their contribution to future precipitation changes in the region. The Mediterranean precipitation climatology and trend were further examined by comparing the newest generation of global climate models (CMIP5) used in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report, to the previous generation (CMIP3) and to observations over the latter half of the 20th Century for both the summer and winter half years. The observed drying trend since 1950 was predominantly due to winter drying, with very little contribution from the summer. However, in the CMIP5 multimodel mean, the precipitation trend since 1950 is evenly divided throughout the seasonal cycle. This may indicate that in observation, multidecadal internal variability, particularly that associated with the NAO, dominates the wintertime trend. An estimate of the observed externally forced trend showed that winter drying dominated in observations but the spatial patterns were grossly similar to the multimodel mean trend. The similarity was particularly robust in the eastern Mediterranean region, indicating a radiatively forced component being stronger there. These results also revealed modest improvement for the CMIP5 multimodel ensemble in representation of the observed six-month winter and summer climatology. We further explored the detailed mechanisms leading to the NAO-associated precipitation change, such as the role of the change in mean circulation versus that of the storm tracks in the regional moisture budget, which had not been investigated previously. We employed a moisture budget analysis using 15 CMIP5 models and the ERA-Interim Reanalysis to investigate the relationship between the NAO and the various moisture budget terms for the six-month winter and summer. Compared with the ERA-Interim, the models performed well in their simulation of the relationship between the naturally varying NAO and the large-scale moisture budget. Our results indicated that the shift in the midlatitude transient eddies induced modest moisture convergence, rather than divergence, over the Mediterranean under a positive NAO. The reduction in precipitation in this region during a positive NAO was dominated by the mean moisture divergence, which opposed the transient contribution. There were significant differences between the patterns of NAO-induced moisture budget anomaly and changes due to external radiative forcing. Under radiative forcing there was enhanced evaporation over the Mediterranean Sea, Italy and eastern Europe and drying by the shift in the wintertime storms over nearly all of Europe and the Mediterranean. Under a positive phase of the NAO, on the other hand, there was modest reduction in evaporation and wetting by the storms over the Mediterranean, and drying over northern Europe. The dependence of the Mediterranean moisture budget on the NAO was similarly explored in the summer half of the year and in this season the models exhibited more disagreement with observations, but otherwise showed the similar results as winter. The stronger anthropogenic induced drying signal over the eastern Mediterranean provided a basis to examine the possible cause and impact of the recent severe and persistent drought in Syria that occurred directly prior to the uprising of 2011. The drought devastated Syrian agriculture, resulting in food shortages, widespread unemployment, the collapse of rural social structure and a mass migration of agricultural refugees to Syria's urban areas. Anger at the government's failure to ameliorate conditions was one spark for the uprising that evolved into civil war. We found that though droughts occur periodically in Syria due to natural causes it is likely that the recent drought was more extreme due to the century long drying trend caused by increased radiative forcing. It was estimated that the anthropogenic trend made a drought of such severity several times more likely. Droughts as persistent as the recent one are projected to be commonplace in a future warmer world.

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Lipat, Bernard. "Quantifying and Understanding the Linkages between Clouds and the General Circulation of the Atmosphere." Thesis, 2018. https://doi.org/10.7916/D8BS08VK.

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Due to the wide range of physical scales involved, clouds cannot be fully resolved in models of the global climate, and so are parameterized. The resultant model deficiencies in simulating important cloud processes within the current climate are strongly implicated in the large uncertainty in model predictions of future climate changes. Previous work has highlighted the uncertainties in predictions of future climate related to thermodynamic cloud changes, understanding of which requires detailed observations of small-scale cloud microphysics. In this thesis, we argue that understanding the linkages between mid-latitude clouds and the general circulation of the atmosphere can advance efforts to constrain their response to climate forcing. We make this argument with three main methods of analysis: 1) observations, 2) state-of-the-art general circulation models, and 3) experiments with an idealized model of the global climate. First, we perform a comprehensive investigation of the observed inter-annual relationships between clouds, their radiative effects, and key indices of the large-scale atmospheric circulation. Using reanalysis data and satellite retrievals, we find a relationship between the edge of the Hadley circulation (HC) and the high cloud field that is largely robust against season and ocean basin. In contrast, shifts of the mid-latitude eddy-driven jet latitude, which had been the focus of previous work on the coupling between mid-latitude clouds and circulation, only correlate with the high cloud field in the wintertime North Atlantic. In that season and basin, poleward shifts of the circulation are associated with anomalous shortwave cloud radiative warming. During all seasons in the Southern Hemisphere, however, poleward shifts of the circulation are associated with anomalous shortwave cloud radiative cooling. Second, we examine Coupled Model Intercomparison Project phase 5 (CMIP5) model output to evaluate the models' simulation of the inter-annual co-variability between the Southern Hemisphere HC extent and the shortwave cloud radiative effect. In the control climate runs, during years when the HC edge is anomalously poleward, most models reduce their cloud cover in the lower mid-latitudes (approximately 30$^\circ$S - 45$^\circ$S) and allow more sunlight to warm the region, although we find no such shortwave radiative warming in observations. We correlate these biases in the co-variability between the HC extent and shortwave cloud radiative anomalies with model biases in the climatological HC extent. Models whose climatological HCs are unrealistically equatorward compared to the observations exhibit weaker climatological subsidence in the lower mid-latitudes and exhibit larger increases in subsidence there with poleward HC extent shifts than models with more realistic climatological HCs. This behavior, based on control climate variability, has important implications for the model response to forcing. In 4$\times$CO$_2$-forced runs, models with unrealistically equatorward HCs in the control climatology exhibit a stronger shortwave cloud radiative warming response in the lower mid-latitudes and tend to have larger values of equilibrium climate sensitivity than models with more realistic HCs in the control climatology. The above correlative analyses suggest that uncertainty in the linkages between mid-latitude clouds and the general circulation of the atmosphere contributes to uncertainty in the model response to forcing. Finally, we use simulations of the global climate in an idealized aquaplanet model to show that the biases in the climatological Southern Hemisphere circulation do indeed contribute to much of the model spread in the cloud-circulation coupling. We find that for the same 1$^\circ$ latitude poleward shift, simulations with narrower climatological HCs exhibit stronger mid-latitude shortwave cloud radiative warming anomalies than simulations with wider climatological HCs. The shortwave cloud radiative warming anomalies result predominantly from a subsidence warming of the planetary boundary layer, which decreases low-level cloud fraction and is stronger for narrower HCs because of a tighter mean meridional circulation. A comparison of the spread across aquaplanet simulations with that across CMIP5 models suggests that about half of the model uncertainty in the mid-latitude cloud-circulation coupling stems from this impact of the circulation on the large-scale temperature structure of the boundary layer, and thus can be removed by improving the representation of the climatological circulation in models. Therefore, a more realistic representation of the Hadley circulation in models can improve their representation of the linkage between mid-latitude clouds and the atmospheric circulation in the current climate and increase overall confidence in predictions of future climate.

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Raymond, Colin Spencer. "Regional Geographies of Extreme Heat." Thesis, 2019. https://doi.org/10.7916/d8-vcx8-8q59.

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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.

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41

Jonko, Alexandra. "Investigating climate feedbacks across forcing magnitudes and time scales using the radiative kernel technique." Thesis, 2012. http://hdl.handle.net/1957/33987.

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Radiative feedbacks associated with changes in water vapor, temperature, surface albedo and clouds remain a major source of uncertainty in our understanding of climate's response to anthropogenic forcing. In this dissertation climate model data is used to investigate variations in feedbacks that result from changing CO�� forcing and the time scales on which feedbacks operate, focusing on the applicability of one method in particular, the radiative kernel technique, to these problems. This computationally efficient technique uses a uniform, incremental change in feedback variables to infer top-of-atmosphere (TOA) radiative flux changes. The first chapters explore the suitability of the linear radiative kernel technique for large forcing scenarios. We show that kernels based on the present-day climate misestimate TOA flux changes for large perturbations, translating into biased feedback estimates. We address this issue by calculating additional kernels based on a large forcing climate state with eight times present day CO�� concentrations. Differences between these and the present-day kernels result from added absorption of radiation by CO�� and water vapor, and increased longwave emission due to higher temperatures. Combining present-day and 8xCO�� kernels leads to significant improvement in the approximation of TOA flux changes and accuracy of feedback estimates. While climate sensitivity remains constant with increasing CO�� forcing when the inaccurate present-day kernels are used, sensitivity increases significantly when new kernels are used. Comparison of feedbacks in climate models with observations is one way towards understanding the disagreement among models. However, climate change feedbacks operate on time scales that are too long to be evaluated from the observational record. Rather, short-term proxies for greenhouse-gas-driven warming are often used to compute feedbacks from observations. The third chapter of this dissertation examines links between the seasonal cycle and global warming using pattern correlations of spatial distribution of feedback variables and radiative flux changes. We find strong correlations between time scales for changes in surface temperature and climate variables, but not for TOA flux anomalies, reaffirming conclusions drawn in previous work. Finally, we investigate the fitness of the radiative kernel technique for evaluation of short-term feedbacks in a comparison with the more accurate, but more computationally expensive, partial radiative perturbations.
Graduation date: 2013

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42

England, Mark Ross. "Understanding Observed and Projected Climate Changes in the Antarctic, and their Global Impacts." Thesis, 2019. https://doi.org/10.7916/d8-w437-kn51.

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The Antarctic climate has undergone complex changes over the last fifty years, driven largely by stratospheric ozone depletion. By the end of this century, under the current trajectory of anthropogenic emissions, the climate of Antarctica is projected to be significantly wetter, warmer and prone to the collapse of ice shelves and loss of sea ice cover. The overarching aim of this thesis is to increase our understanding of recent and projected Antarctic climate change and its drivers. We also investigate the potential global implications of these changes and show that the effects will not be limited to the southern high latitudes. In the first half, we investigate the drivers of Antarctic climate change over the observational period. Specifically, we study the influence of the stratosphere on the southern high latitude surface climate, through stratosphere-troposphere dynamic coupling as well as stratospheric ozone depletion. We examine the impact of these on the Amundsen Sea Low, a key circulation feature near West Antarctica. We demonstrate using reanalysis that stratospheric heat flux extremes are linked to high latitude tropospheric anomalies in the Amundsen Sea region. During extreme negative (positive) events there is a westward (eastward) shift of the Amundsen Sea Low, a warming (cooling) and increase (decrease) of geopotential height over the Amundsen and Bellingshausen Seas. We find that most CMIP5 models are not able to capture this relationship. Next, we demonstrate that, since 1965, stratospheric ozone depletion has acted to deepen the Amundsen Sea Low in austral summer by 1 hPa per decade. This result was consistent across two different comprehensive climate models, each with very different model physics and climate sensitivity. It must be noted that the ozone depletion signal on the Amundsen Sea Low is small compared to the internal climate variability in this region. Using ensembles of model integrations and analysing them over the full period of ozone depletion (which started a couple of decades before the satellite era) is necessary to detect a robust signal. In the second half, we investigate the effects of future Antarctic climate change, specifically the effects of projected sea ice loss over the coming century. Climate model simulations are used to isolate the effect of end-of-the-century Antarctic sea ice loss which is compared and contrasted with the effects of projected Arctic sea ice loss. We first study the effects of projected Antarctic sea ice loss used atmosphere-only simulations. As for the Arctic, results indicated that Antarctic sea ice loss will act to shift the tropospheric jet equatorward, an internal negative feedback to the poleward shift associated with increased greenhouse gases. Antarctic sea ice loss is shown to have an important effect throughout the year whereas Arctic sea ice loss will have more seasonally varying impacts. Building upon these results we the use the same climate model but in a fully coupled setup to study the effects of projected Antarctic sea ice loss on the climate system. We show that both Arctic and Antarctic sea ice loss will have important global effects, causing a ‘mini global warming’ signal. The tropical response to Antarctic sea ice loss is shown to be remarkably similar to that of Arctic sea ice loss, with enhanced warming in the Eastern Tropical Pacific and increased precipitation throughout much of the equatorial Pacific. These results highlight how intimately coupled the Antarctic climate is to the rest of the climate system.

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Punke, Michele Leigh. "Predictive locational modeling of late Pleistocene archaeological sites on the southern Oregon Coast using a Geographic Information System (GIS)." Thesis, 2001. http://hdl.handle.net/1957/28949.

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The search for archaeological materials dating to 15,000 yr BP along the southern Oregon coast is a formidable task. Using ethnographic, theoretical, and archaeological data, landscape resources which would have influenced land-use and occupation location decisions in the past are highlighted. Additionally, environmental data pertaining to the late Pleistocene is examined to determine what landscape features may have been used by human groups 15,000 years ago and to determine how these landscape features may have changed since that time. These landscape resource features are included in the modeling project as independent variables. The dependent variable in this modeling project is relative probability that an area will contain archaeological materials dating to the time period of interest. Two predictive locational models are created to facilitate the search process. These models mathematically combine the independent variables using two separate approaches. The hierarchical decision rule model approach assumes that decision makers in the past would have viewed landscape features sequentially rather than simultaneously. The additive, or weighted-value, approach assumes that a number of conditional preference aspects were evaluated simultaneously and that different environmental variables had varying amounts of influence on the locational choices of prehistoric peoples. Integration of the data and mathematical model structures into a Geographic Information System (GIS) allows for spatial analysis of the landscape and the prediction of locations most likely to contain evidence of human activity dating to 15,000 years ago. The process involved with variable integration into the GIS is delineated and results of the modeling procedures are presented in spatial, map-based formats.
Graduation date: 2002

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Pavlova, Ina 1973. "The biological basis for changes in autofluorescence during neoplastic progression in oral mucosa." Thesis, 2007. http://hdl.handle.net/2152/3627.

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Autofluorescence spectroscopy can improve the early detections of oral cancer. Biochemical and structural changes associated with dysplastic progression alter the optical properties of oral mucosa and cause diagnostically significant differences in spectra from normal and neoplastic sites. This dissertation describes experimental and modeling studies aimed at revealing biological reasons for the diagnostically significant differences observed in depth-resolved fluorescence spectra from normal and neoplastic oral mucosa. An experimental approach, based on high-resolution fluorescence imaging, is used to study the autofluorescence patterns of oral tissue. At UV excitation, most of the epithelial autofluorescence originates from cells occupying the basal and intermediate layers, while stromal signal originates from collagen and elastin crosslinks. With dysplasia, epithelial autofluorescence increases, while autofluorescence from subepithelial stroma drops significantly. Benign lesions also display a drop in autofluorescence from subepithelial stroma, but have different epithelium fluorescence patterns compared to dysplasia. Optical probes that measure mostly stromal fluorescence, may reveal a similar loss of fluorescence intensity and thus fail to distinguish benign inflammation from dysplasia. These results emphasize the importance of using probes with enhanced detection of epithelial fluorescence for improved diagnosis of different types of oral lesions. The second part of this work presents a Monte Carlo model that predicts fluorescence spectra of oral mucosa obtained using a depth-selective probe as a function of tissue optical properties. A model sensitivity analysis determines how variations in optical parameters associated with neoplastic development influence the intensity and shape of spectra, and elucidates the biological basis for differences in spectra from normal and premalignant oral mucosa. Spectra of oral mucosa collected with the depthselective probe, are affected by variations in epithelial optical properties and to a lesser extent by changes in superficial stromal parameters, but not by changes in the optical properties of deeper stroma. Changes in parameters associated with dysplastic progression lead to a decreased fluorescence intensity and a shift of the spectra to longer emission wavelengths. Decreased fluorescence is due to a drop in detected stromal photons, whereas the shift of spectral shape is attributed to an increased fraction of detected photons arising in the epithelium.

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Lu, Mengqian. "From Diagnosis to Water Management: The role of Atmospheric Dynamics and Climate Variability on Hydrological Extremes." Thesis, 2014. https://doi.org/10.7916/D8T72FRW.

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The recent extreme hydrological extremes over the globe highlight the importance of understanding the role of atmospheric dynamics and climate variability on the occurrence of these extreme events and the associated temporal and spatial characteristics of sequences of the precipitation events. Most of the studies have been focusing on overall average impacts of long-term global climate change on extremes. Majority are driven largely by considering the changes of the moisture holding capacity as a function of temperature, as indicated by the Clausius-Clapeyron equation. Given the complex dynamical structure of the atmosphere, one needs to also consider the attendant atmospheric circulation and moisture transport mechanisms that lead to extreme precipitation and subsequent floods as evidenced in the recent major floods. This study first develops insights into the causative climatic factors associated with precipitation induced regional floods events and understand the roles of Atmospheric Rivers (AR) or Tropical Moisture Exports (TME) and atmospheric circulation patterns associated with the frequency and/or persistency of such events in the midlatitudes. The second part explores the spatiotemporal relationship between climate variability and global extreme precipitation occurrence using a graph based approach based upon the concept of reciprocity to investigated the linkages and influences of the slowly changing boundary conditions on the development or propagation of atmospheric circulations, to assess the predictability of global precipitation extremes given the leading modes of identified climate dipole networks. A multi-timescale statistical, climate informed, stochastic streamflow forecast model serves as the bridge linking the first two parts to the application in the third part: application on water resources management by developing a multi-timescale climate informed stochastic hybrid stimulation-optimization model for multi-purpose reservoir systems, which enables the utilization of the streamflow forecast. The novel reservoir operation model attempts to change the game of water resources management from its conservative, rigid rule-following scheme to a robust, market-based, reliable water allocation strategy. Part I. Tropical Moisture Exports, Extreme Precipitation and Major Flood Atmospheric Rivers are being increasingly identified as associated with some extreme floods. More generally, such floods may be associated with tropical moisture exports that exhibit relatively robust teleconnections between moisture source regions and flood regions. First, a large-scale flood event that persisted over Western Europe in January 1995 is studied. During the last ten days of the month, two rare flooding events, associated with heaviest rainfall in 150 years, occurred in two places, one over Brittany (West of France), and the second in the France-Germany border region and parts of neighboring countries. In this study, we explore the month-long evolution of tropical moisture exports (TME) and their connection to the precipitation events that led to the Brittany event. The persistent large-scale atmospheric circulation patterns that led to the birth, death and evolution of these TME as atmospheric rivers with landfalls in Western Europe are identified, and the relationship of daily extreme precipitation to these patterns is examined. Singular value decomposition (SVD) analysis and a generalized linear model (GLM) are used to assess whether knowledge of the atmospheric circulation patterns from the prior record is useful for explaining the occurrence of their rare events. The analysis establishes the importance of both global and regional atmospheric circulation modes for the occurrence of such persistent events and the hydrologic importance of diagnosing global atmospheric moisture pathways. Part II. Seasonal to Interannual Variability of Tropical Moisture Exports, Extremes and ENSO A statistically and physically based framework is put forward that investigates the relationship between Tropical Moisture Exports (TMEs), Extreme Precipitation and Floods. TMEs is the more general phenomena than Atmospheric Rivers (ARs) in terms of (1) facilitates the poleward transport of warm and moist air masses from low latitudes, primarily tropical oceanic areas, to higher latitudes; (2) contributes to the global climatology precipitation and its extremes; (3) closely relates to floods events, especially in the midlatitudes. The TMEs itself has seasonal and interannual variability that is regulated by slowly changing boundary conditions and climate variability, such El Niño Southern Oscillation (ENSO), while the trajectories and movements are presumably led by atmospheric circulations patterns driven by the balance of global energy and water budgets. In this study, we take Northwest US (NE US) to show how the TMEs is related to extreme precipitation and then floods, and the results of the variability of TMEs, coupled with atmospheric circulation patterns, on the extremes. Historical large floods events in NE US in different seasons are studied for their link to the TMEs. Major moisture sources of TMEs that contributes to precipitation, extremes and floods in NE US are identified, together with the sources' seasonally and interannually varying characterizes in terms of both birth and entrance to the NE US, with the consideration of large scale climate regulations and atmospheric circulation patterns. Part III. Correlation Networks for Identifying Predictors for Extended Range Forecasts for Extreme Precipitation Correlation networks identified from financial, genomic, ecological, epidemiological, social and climate data are being used to provide useful topological insights into the structure of high dimensional data. Strong convection over the oceans and the atmospheric moisture transport and flow convergence indicated by atmospheric pressure fields may determine where and when extreme precipitation occurs. Here, the spatiotemporal relationship between climate and extreme global precipitation is explored using a graph based approach that uses the concept of reciprocity to generate cluster pairs of locations with similar spatiotemporal patterns at any time lag. A global time-lagged relationship between pentad sea surface temperatures (SST) anomalies and pentad sea level pressure (SLP) anomalies is investigated to understand the linkages and influence of the slowly changing oceanic boundary conditions on the development of the global atmospheric circulation. We explore the use of this correlation network to predict extreme precipitation globally over the next 30 days, using a Principal Component logistic regression on the strong global dipoles found between SST and SLP. Unprecedented success of the predictive skill under cross validation for 30 days precipitation higher than the 90th percentile is indicated for selected global regions for each wet season considered. Part IV. Applications of Climate Informed Streamflow Forecasts for Water Management Streamflow forecasts at multiple time scales (e.g., season and year ahead) provide a new opportunity for reservoir management to address competing objectives. Market instruments such as forward contracts with specified reliability are considered as a tool that may help address the perceived risk associated with the use of such instruments in lieu of a traditional operation and allocation. A water allocation process that enables multiple contracts with different durations, to facilitate participatory management of the reservoir by users and system operators, is presented here. Since these contracts are based on a verifiable reliability they may in turn be insurable. A Multi-timescale climate informed Stochastic Hybrid Simulation - Optimization Model (McISH) is developed, featuring (1) dynamic flood control storage allocation at a specified risk level; (2) multiple duration energy/water contracts with user specified reliability and prices; and (3) contract sizing and updating to reflect changes in both demands and supplies. The model incorporates multi-timescale (annual and seasonal) streamflow forecasts, and addresses uncertainties across both timescales. The intended use is as part of an interaction between users and water operators to arrive at a set of short-term and long term contracts through disclosure of demand or needs and the value placed on reliability and contract duration. An application is considered using data for the Bhakra Dam, India. The issues of forecast skill and contract performance given a set of parameters are examined to illustrate the approach. Prospects for the application in a general setting are discussed.

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Joubert, Alec Michael. "Modelling present and future climates over Southern Africa." Thesis, 1997. https://hdl.handle.net/10539/25851.

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Thesis submitted to the Faculty of Science, Department of Geography and Environmental Studies, University of the Witwatersrand, Johannesburg, in fulfillment of the requirements for the Degree of Doctor of Philosophy
The representation of contemporary southern African climate by a wide range of general circulation models used in climate studies is evaluated. In addition, projections of regional climate change by the models are interpreted in terms of their present climate performance. Projections of regional climate change by two different types of climate models are considered. First, projections of the equilibrium response to an instantaneous doubling of atmospheric carbon dioxide using atmospheric models linked to simple mixed-layer oceans are assessed. Second, projections of the transient response to gradually-increasing anthropogenic forcing by fully-coupled ocean-atmosphere general circulation models are considered. All of the mixed-layer models considered have been developed since 1990 and are more recent and generally higher-resolution versions of the models considered previously for southern Africa. The improved resolution and model physics result in a general improvement in the representation of several features of circulation around southern Africa. Specifically, these include the meridional pressure gradient, the zonal wind profile, the intensity and seasonal location of the circumpolar trough and the subtropical anticyclones, as well as planetary wave structure at 500 hPa. Atmospheric models forced by observed sea-surface temperatures simulate the large-scale circulation adjustments around southern Africa known to accompany periods of above- and below-average rainfall over the subcontinent. Fully-coupled models simulate the observed features of intra- and intra- annual variability in mean sea-level pressure, although the simulated variability is weaker than observed. Summer rainfall totals throughout southern Africa are overestimated by all of the models, although the pattern of rainfall seasonality over the subcontinent as a whole is well-reproduced. The inclusion of sulphate aerosols in addition to greenhouse gases does not result in a statistically significant improvement in the simulation of contemporary temperature variability over southern Africa. Warming projected by fully-coupled models is smaller than projections by mixed-layer models due to the fact that the transient response of the fully-coupled system and not an equilibrium response of an atmospheric model linked to a mixed-layer ocean is simulated. The inclusion of sulphate aerosols results in a reduction in the magnitude and rate of warming over southern Africa. Projected changes in the diurnal temperature range are seasonally-dependent, with increases in summer and autumn and decreases in winter. Simulated changes in mean sea-level pressure are small but similar in magnitude to observed anomalies associated with extended wet and dry spells over the subcontinent. No change in rainfall seasonality over southern Africa is expected. Nonetheless, little confidence exists in projected changes in total rainfall. While both types of model simulate a 10-15% decrease in summer rainfall on average, projected changes are smaller than the simulation errors and little inter-model consensus in terms of the sign of projected changes exists. No change in the location or intensity of anticyclonic circulation and divergence at 700 hPa in winter is expected. While fully-coupled models provide a more comprehensive treatment of the global climate system and the process of climate change, there is no evidence to conclude that current fully-coupled models should be used to the exclusion of mixed-layer models when developing regional climate change scenarios for southern Africa.
Andrew Chakane 2018

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Lockett, Daniel Edwin IV. "A Bayesian approach to habitat suitability prediction." Thesis, 2012. http://hdl.handle.net/1957/28788.

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For the west coast of North America, from northern California to southern Washington, a habitat suitability prediction framework was developed to support wave energy device siting. Concern that wave energy devices may impact the seafloor and benthos has renewed research interest in the distribution of marine benthic invertebrates and factors influencing their distribution. A Bayesian belief network approach was employed for learning species-habitat associations for Rhabdus rectius, a tusk-shaped marine infaunal Mollusk. Environmental variables describing surficial geology and water depth were found to be most influential to the distribution of R. rectius. Water property variables, such as temperature and salinity, were less influential as distribution predictors. Species-habitat associations were used to predict habitat suitability probabilities for R. rectius, which were then mapped over an area of interest along the south-central Oregon coast. Habitat suitability prediction models tested well against data withheld for crossvalidation supporting our conclusion that Bayesian learning extracts useful information available in very small, incomplete data sets and identifies which variables drive habitat suitability for R. rectius. Additionally, Bayesian belief networks are easily updated with new information, quantitative or qualitative, which provides a flexible mechanism for multiple scenario analyses. The prediction framework presented here is a practical tool informing marine spatial planning assessment through visualization of habitat suitability.
Graduation date: 2012

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Mezuman, Keren. "Fire and Aerosol Modeling for Air Quality and Climate Studies." Thesis, 2019. https://doi.org/10.7916/d8-65gx-tn53.

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Open burning of biomass and anthropogenic waste is a major source of aerosols at the biosphere-atmosphere interface, yet its impact on Earth’s climate and air quality is not fully understood due to the intricate feedbacks between the natural environment and human activities. Earth system models (ESMs) are a vital tool in the study of these aerosol-biosphere-atmosphere interactions. ESMs allow the estimation of radiative forcing and climate impacts in terms of changes to temperature and precipitation as well as the attribution to natural or anthropogenic drivers. To provide coherent results, however, ESMs require rigorous development and evaluation against observations. In my work I use the NASA-GISS ESM: ModelE. One of its strengths lie in its detailed aerosol schemes that include microphysics and thermodynamic partitioning, both necessary for the simulation of secondary inorganic aerosols. To overcome one of ModelE’s weaknesses, namely its lack of interactive biomass burning (BB) emissions, I developed pyre: ModelE’s interactive fire emissions module. pyrE is driven by flammability and cloud-to-ground lightning, both of which are calculated in ModelE, and anthropogenic ignition and regional suppression parameterizations, based on population density data. Notably, the interactive fire emissions are generated from the flaming phase in pyrE (fire count), rather than the scar left behind (burned area), which is commonly used in other interactive fire modules. The performance of pyrE was evaluated against MODIS satellite retrievals and GFED4s inventory, as well as simulations with prescribed emissions. Although the simulated fire count is bias-high compared to MODIS, simulated fire emissions are bias-low compared to GFED4s. However, the bias in total emissions does not propagate to atmospheric composition, as pyrE simulates aerosol optical depth just as well as a simulation with GFED4s prescribed emissions. Upon the development and evaluation of the fire-aerosol capabilities of ModelE, I have utilized it, with the EVA health model, to study the health impacts of outdoor smoke in 1950, 2015, and 2050. I find that chronic exposure to aerosols (PM2.5) is the main driver of premature deaths from smoke exposure, yet by 2050, acute exposure to ozone, formed downwind of BB smoke plumes, is projected to cause more premature deaths than exposure to PM2.5. I estimate the annual premature deaths from BB and waste burning (WB) smoke in 1950 to be ~41,000 and ~19,000, respectively, and in 2015 to be ~310,000 and ~840,000, respectively. By 2050 I project 390,000 and 1.5 million premature deaths from BB and WB respectively. In light of the growing impact of WB smoke exposure I identify the need to scale up viable waste management practices in regions of rapid population growth.

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Song, Ji Hee. "Land use forecasting in regional air quality modeling." Thesis, 2007. http://hdl.handle.net/2152/3036.

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Song, Ji Hee 1980. "Land use forecasting in regional air quality modeling." 2007. http://hdl.handle.net/2152/13209.

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Dissertations / Theses on the topic 'Coast changes – Mathematical models'

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