The complex and coupled physical processes taking place in the atmosphere, ocean and land surface are described in Global Circulation Models (GCMs). These models have become the main tools to simulate climate variability and project future climate change. GCMs have the potential to give physically reliable estimates of climate change at global, continental or regional scales, but their projections are currently of too course horizontal resolution to capture the smaller scale features of climate and climate change. This situation stems from the fact that GCM simulations, which are effectively three-dimensional simulations of the coupled atmosphere-ocean-land system, are computationally extremely expensive. Therefore, downscaling techniques are utilised to do perform simulations over preselected areas that are of sufficiently detailed to represent the climate features at the meso-scale. Dynamic regional climate models (RCMs), based on the same laws of physics as GCMs but applied at high resolution over areas of interest, have become the main tools to project regional climate change. The research presented here utilises the Conformal-Cubic Atmospheric Model (CCAM), a variable-resolution global atmospheric model that can be applied in stretched-grid mode to function as a regional climate model. As is the case with RCMs, CCAM has the potential to improve climate simulations along rough topography and coastal areas when applied at high spatial resolution, whilst side-stepping the lateral boundary condition problems experienced by typical limited-area RCMs. CCAM has been developed by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) in Australia. The objective in the study is to test capability of a regional climate model, CCAM, to realistically simulate cumulus convection at different spatial scales over regions with steep topography, such as the eastern escarpment of South Africa. Since both GCMs and RCMs are known to have large biases and shortcomings in simulating rainfall over the steep eastern escarpment of southern Africa and in particular Lesotho, the paper “Model simulations of rainfall over southern Africa and its eastern escarpment” (Chapter 3) has a focus on verifying model performance over this region. In the paper the CCAM simulations include six 200 km resolution Atmospheric Model Intercomparison Project (AMIP) simulations that are forced with sea surface temperatures and one 50 km resolution National Centre for Environmental Prediction (NCEP) reanalysis simulation that is forced with sea surface temperatures and synoptic scale atmospheric forcings. These simulations are verified against rain gauge data sets and satellite rainfall estimates. The results reveal that at these resolutions the model is capable of simulating the key synoptic-scale features of southern African rainfall patterns. However, rainfall totals are often drastically overestimated. A key aspect of model performance is the representation of the diurnal cycle in convection. For the case of South Africa, the realistic representation of the complex patterns of rainfall over regions of steep topography is also of particular importance. At a larger spatial scale, the model also needs to be capable of representing the west-east rainfall gradient found over South Africa. The ability of CCAM to simulate the diurnal cycle in rainfall as well as the complex spatial patterns of rainfall over eastern South Africa is analysed in “High Resolution Rainfall Modelling over the Eastern Escarpment of South Africa” (Chapter 4). The simulations described in the paper have been performed at 8km resolutions in the horizontal and span a thirty-year long period. These are the highest resolution climate simulations obtained to date for the southern African region, and were obtained through the downscaling reanalysis data of the European Centre for Medium-range Weather Forecasting (ECMWF). The simulations provide a test of the robustness of the CCAM convective rainfall parameterisations when applied at high spatial resolution, in particular in representing the complex rainfall patterns of the eastern escarpment of South Africa. / M (Geography and Environmental Management), North-West University, Potchefstroom Campus, 2015

The complex and coupled physical processes taking place in the atmosphere, ocean and land surface are described in Global Circulation Models (GCMs). These models have become the main tools to simulate climate variability and project future climate change. GCMs have the potential to give physically reliable estimates of climate change at global, continental or regional scales, but their projections are currently of too course horizontal resolution to capture the smaller scale features of climate and climate change. This situation stems from the fact that GCM simulations, which are effectively three-dimensional simulations of the coupled atmosphere-ocean-land system, are computationally extremely expensive. Therefore, downscaling techniques are utilised to do perform simulations over preselected areas that are of sufficiently detailed to represent the climate features at the meso-scale. Dynamic regional climate models (RCMs), based on the same laws of physics as GCMs but applied at high resolution over areas of interest, have become the main tools to project regional climate change. The research presented here utilises the Conformal-Cubic Atmospheric Model (CCAM), a variable-resolution global atmospheric model that can be applied in stretched-grid mode to function as a regional climate model. As is the case with RCMs, CCAM has the potential to improve climate simulations along rough topography and coastal areas when applied at high spatial resolution, whilst side-stepping the lateral boundary condition problems experienced by typical limited-area RCMs. CCAM has been developed by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) in Australia. The objective in the study is to test capability of a regional climate model, CCAM, to realistically simulate cumulus convection at different spatial scales over regions with steep topography, such as the eastern escarpment of South Africa. Since both GCMs and RCMs are known to have large biases and shortcomings in simulating rainfall over the steep eastern escarpment of southern Africa and in particular Lesotho, the paper “Model simulations of rainfall over southern Africa and its eastern escarpment” (Chapter 3) has a focus on verifying model performance over this region. In the paper the CCAM simulations include six 200 km resolution Atmospheric Model Intercomparison Project (AMIP) simulations that are forced with sea surface temperatures and one 50 km resolution National Centre for Environmental Prediction (NCEP) reanalysis simulation that is forced with sea surface temperatures and synoptic scale atmospheric forcings. These simulations are verified against rain gauge data sets and satellite rainfall estimates. The results reveal that at these resolutions the model is capable of simulating the key synoptic-scale features of southern African rainfall patterns. However, rainfall totals are often drastically overestimated. A key aspect of model performance is the representation of the diurnal cycle in convection. For the case of South Africa, the realistic representation of the complex patterns of rainfall over regions of steep topography is also of particular importance. At a larger spatial scale, the model also needs to be capable of representing the west-east rainfall gradient found over South Africa. The ability of CCAM to simulate the diurnal cycle in rainfall as well as the complex spatial patterns of rainfall over eastern South Africa is analysed in “High Resolution Rainfall Modelling over the Eastern Escarpment of South Africa” (Chapter 4). The simulations described in the paper have been performed at 8km resolutions in the horizontal and span a thirty-year long period. These are the highest resolution climate simulations obtained to date for the southern African region, and were obtained through the downscaling reanalysis data of the European Centre for Medium-range Weather Forecasting (ECMWF). The simulations provide a test of the robustness of the CCAM convective rainfall parameterisations when applied at high spatial resolution, in particular in representing the complex rainfall patterns of the eastern escarpment of South Africa. / M (Geography and Environmental Management), North-West University, Potchefstroom Campus, 2015

Environmental monitoring of Earth from space has provided invaluable information for understanding the land-atmosphere water and energy exchanges. However, the use of satellite observations in hydrologic applications is often limited by coarse space-time resolutions. This study aims to develop a data assimilation system that integrates remotely-sensed precipitation and soil moisture observations into physically-based models to produce fine-scale precipitation, soil moisture, and other relevant hydrometeorological variables. This is particularly useful with the active Global Precipitation Measurement and Soil Moisture Active Passive missions. The system consists of two major components: (1) a framework for dynamic downscaling of satellite precipitation products using the Weather Research and Forecasting (WRF) model with four-dimensional variational data assimilation (4D-Var) and (2) a variational data assimilation system using spatio-temporally varying background error covariance for directly assimilating satellite soil moisture data into the Noah land surface model coupled with the WRF model. The WRF 4D-Var system can effectively assimilate and downscale six-hour precipitation products of a spatial resolution of about 20 km (i.e., those derived from the National Centers for Environmental Prediction Stage IV data and the Tropical Rainfall Measuring Mission (TRMM) 3B42 dataset) to hourly precipitation with a spatial resolution of less than 10 km. The system is able to assimilate and downscale daily soil moisture products at a gridded 36-km resolution obtained from the Soil Moisture and Ocean Salinity (SMOS) mission to produce hourly 4-by-4 km surface soil moisture forecasts with a reduction of mean absolute error by 35% on average. The results from the system with coupled components show that assimilation of the TRMM 3B42 precipitation improves the quality of both downscaled precipitation and soil moisture analyses, while the effect of SMOS soil moisture data assimilation is largely on the soil moisture analyses. The downscaled WRF precipitation, with and without assimilation of TRMM precipitation, was preliminarily tested with a spatially distributed simulation of streamflow using the TIN (Triangular Irregular Network)-based Real-time Integrated Basin Simulator (tRIBS).

Le système d'upwelling péruvien est l'un des systèmes marins côtiers les plus productifs de l’océan mondial. Le vent de surface le long de la côte est le principal moteur de l'upwelling. Cette thèse vise à étudier la variabilité du vent côtier et ses processus lors du réchauffement de la couche de surface, à différentes échelles de temps: (1) des échelles de temps interannuelles, correspondant aux événements El Niño, et (2) des échelles de temps multi-décadaires résultant du changement climatique régional. Une série de domaines emboités d’un modèle atmosphérique régional est utilisée pour simuler le vent de surface. Dans la première partie de la thèse, on étudie les processus responsables de l'augmentation, contre-intuitive, du vent observée au large du Pérou au cours de la période El Niño 1997-1998. Des expériences de sensibilité montrent que le réchauffement inh de la omogène des eaux de surface, plus important dans le nord, entraîne un gradient de pression accru le long côte, accélérant le vent. Dans une seconde partie de la thèse, l’évolution des vents côtiers est étudiée dans le scénario du «pire cas» du changement climatique RCP8.5. Forcés par le gradient de pression le long de la côte, les vents diminuent en été, tandis qu’ils s’accroissent en hiver, renforçant ainsi légèrement le cycle saisonnier. / The Peruvian upwelling system is one of the most productive coastal marine systems of the world ocean. As in other upwelling systems, alongshore surface wind is the main driver of the coastal upwelling. This thesis aims to study the coastal wind variability and the processes responsible for it during the ocean surface layer warming conditions, at different time scales: (1) interannual time scales, corresponding to El Niño events and (2) multi decadal time scales resulting from regional climate change. A suite of regional atmospheric model embedded domains is used to simulate the surface winds. In the first part of the thesis, the counter-intuitive wind increase observed off Peru during the 1997-1998 El Niño is studied. Sensitivity experiments show that the inhomogenous alongshore surface warming, larger in the north, drives an enhanced alongshore pressure gradient that accelerates the alongshore wind. In the second part of the thesis, the evolution of coastal wind changes is investigated under the “worst case” RCP8.5 climate change scenario. Mainly driven by the alongshore pressure gradient, summer winds decrease whereas winter winds increase, thus slightly reinforcing the seasonal cycle.

The recent elevated North Atlantic hurricane activity has generated considerable interests in the interaction between tropical cyclones (TCs) and climate change. The possible connection between TCs and the changing climate has been indicated by observational studies based on historical TC records; they indicate emerging trends in TC frequency and intensity in some TC basins, but the detection of trends has been hotly debated due to TC track data issues. Dynamical climate modeling has also been applied to the problem, but brings its own set of limitations owing to limited model resolution and uncertainties. The final goal of this study is to project the future changes of North Atlantic TC behavior with global warming for the next 50 years using the Nested Regional Climate Model (NRCM). Throughout the course of reaching this goal, various uncertainties and limitations in simulating TCs by the NRCM are identified and explored. First we examine the TC tracking algorithm to detect and track simulated TCs from model output. The criteria and thresholds used in the tracking algorithm control the simulated TC climatology, making it difficult to objectively assess the model's ability in simulating TC climatology. Existing tracking algorithms used by previous studies are surveyed and it is found that the criteria and thresholds are very diverse. Sensitivity of varying criteria and thresholds in TC tracking algorithm to simulated TC climatology is very high, especially with the intensity and duration thresholds. It is found that the commonly used criteria may not be strict enough to filter out intense extratropical systems and hybrid systems. We propose that a better distinction between TCs and other low-pressure systems can be achieved by adding the Cyclone Phase technique. Two sets of NRCM simulations are presented in this dissertation: One in the hindcasting mode, and the other with forcing from the Community Climate System Model (CCSM) to project into the future with global warming. Both of these simulations are assessed using the tracking algorithm with cyclone phase technique. The NRCM is run in a hindcasting mode for the global tropics in order to assess its ability to simulate the current observed TC climatology. It is found that the NRCM is capable of capturing the general spatial and temporal distributions of TCs, but tends to overproduce TCs particularly in the Northwest Pacific. The overpredction of TCs is associated with the overall convective tendency in the model added with an outstanding theory of wave energy accumulation leading to TC genesis. On the other hand, TC frequency in the tropical North Atlantic is under predicted due to the lack of moist African Easterly Waves. The importance of high-resolution is shown with the additional simulation with two-way nesting. The NRCM is then forced by the CCSM to project the future changes in North Atlantic TCs. An El Nino-like SST bias in the CCSM induced a high vertical wind shear in tropical North Atlantic, preventing TCs from forming in this region. A simple bias correction method is applied to remove this bias. The model projected an increase both in TC frequency and intensity owing to enhanced TC genesis in the main development region, where the model projects an increased favorability of large-scale environment for TC genesis. However, the model is not capable of explicitly simulating intense (Category 3-5) storms due to the limited model resolution. To extrapolate the prediction to intense storms, we propose a hybrid approach that combines the model results and a statistical modeling using extreme value theory. Specifically, the current observed TC intensity is statistically modeled with the General Pareto distribution, and the simulated intensity changes from the NRCM are applied to the statistical model to project the changes in intense storms. The results suggest that the occurrence of Category 5 storms may be increased by approximately 50% by 2055.

Using the regional climate model WRF, and the NCEP-NCAR Reanalysis Project data asboundary and initial conditions, regional precipitation was estimated by means of thedynamical downscaling technique for two selected periods, January 2000 and September2007. These months show very particular climatic characteristics of the precipitationregimen in Central America, like dry (wet) conditions in the Pacific (Caribbean) coast of theCentral American isthmus, in January, and wet (dry) conditions, respectively in each coast,during September. Four-nested-domains, each grids of resolution of 90 km (d01), 30 km(d02), 10 km (d03), and 3.3 km (d04), were configured over this region. The runs werereinitialized each 5 days with 6 hours of spin-up time for adjustment of the model. A total of8 experiments (4 per month) were tested in order to study: a) two important CumulusParameterization Schemes (CPS), Kain-Fritsch (KF) and Grell-Devenyi (GD); and b) thephysical interaction between nested domains (one- and two-way nesting), during eachsimulated month.January 2000 results showed that the modeled precipitation is in agreement withobservations, and also captured the mean climate features of rainfall concerning magnitude,and spatial distribution, like the particular precipitation contrast between the Pacific and theCaribbean coast.Outputs from September 2007 revealed significant differences when a visual comparison ismade to the spatial distribution of each coarse domain (d01, d02, and d03) with theirrespective domain in each experiment. However, the inner grids (d04) in all theexperiments, showed a similar spatial distribution and magnitude estimation, mainly inthose runs using one-way nesting configuration. Furthermore, the results for this mothdiffer substantially with observations, and the latter could be related with associateddeficiencies in the boundary condition that do not reproduce well the transition periodsfrom warm to cold El Niño episodes.Moreover, in all the experiments, the KF scheme calculated more precipitation than the GDscheme and it is associated to the ability of the GD scheme to reproduce spotty but intenserainfall, and apparently, this scheme is reluctant to activate, frequently yielding little or norain. However, when rainfall does develop, it is very intense.Also, the time series do not replicate specific precipitation events, thus, the 5-daysintegration period used in this study, is not enough to reproduce short-period precipitationevents.Finally, physical interaction issues between the nested domains are reflected indiscontinuities in the precipitation field, which have been associated to mass fieldadjustment in the CPS. / Nederbörden i Central Amerika har uppskattats med dynamisk nedskalning för två utvaldaperioder, januari 2000 och september 2007. Global återanalysdata från NCEP-NCARsåteranalysprojekt har använts som randdata och initialdata till den regionalaklimatmodellen WRF. De studerade månaderna uppvisar stora variationer inederbördsmönster, t ex lite (mycket) nederbörd under januari och mycket (lite) nederbördunder september för kustområdena längs Stilla havet (Karibiska havet). Fyra nästladedomäner över Central Amerika har använts med en upplösning på 90 km (d01), 30 km (d02),10 km (d03) och 3,3 km (d04). Simuleringarna initialiserades var 5:e dag och de första 6timmarna efter varje initialisering används för modellens anpassning till initialtillståndet.Totalt 8 experiment genomfördes (4 för varje månad) för att studera: (a) två olika sätt attparameterisera konvektion i Cumulusmoln (CPS), Kain-Fritsch (KF) och Grell-Devenyi (GD)och (b) den fysikaliska interaktionen mellan de nästlade domänerna (en- respektive tvåvägsnästlade scheman).För januari 2000 var det god överensstämmelse mellan modellerad och observeradnederbörd. Modellen beskriver väl såväl mängden nederbörd som den rumsligafördelningen, t ex den stora kontrasten mellan kustområdena längs Stilla havet och Karibiskahavet.För september 2007 uppvisar den modellerade nederbörden stora skillnader i de olikaexperimenten för de yttre domänerna (d01, d02, d03). För den inre domänen (d04) ärresultaten från de olika experimenten betydligt mer lika, särskilt för experimenten medenvägs nästlade scheman. Vidare skiljer sig den modellerade nederbörden väsentligt frånobserverad nederbörd under september 2007. Detta kan förklaras med felaktiga randdatapå grund av problemet i återanalys data att reproducera perioder med övergång från varmtill kall El Niño. I alla experiment gav KF mer nederbörd än GD, det kan förklaras med att GDbättre reproducerar kortvarig, intensiv nederbörd. Det finns en viss tröghet innannederbörden i GD aktiveras, vilket innebär större frekvens av lite eller ingen nederbörd. Närnederbörden väl utvecklas blir den dock intensiv. WRF-modellen klarar inte av att återgespecifika nederbördshändelser för de genomförda experimenten, vilket betyder att 5-dagarär för lång simuleringstid för att kunna reproducera specifika händelser. Slutligen,interaktion mellan de nästlade domänerna skapar diskontinuiteter i nederbördsmöns.

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.

L'analyse de la climatologie des aléas océano-météorologiques tels que les états de mer est fondamentale pour comprendre l'évolution et la dynamique des zones côtières, estimer les risques naturels survenant lors d'événements de tempête majeurs, définir les moyens optimaux de protection des ports et infrastructures onshore et offshore, caractériser la ressource houlomotrice pour des projets de récupération d'énergie des vagues, comprendre les processus d'érosion et accrétion des plages, etc. Pour répondre à ces problématiques dans un contexte de questionnement croissant sur les conséquences potentielles associées au changement climatique, le travail de thèse s'inscrit dans une démarche double : (i) approfondissement de la connaissance du climat de vagues actuel le long des côtes Atlantique, Manche et Mer du Nord en France d'une part, et (ii) estimation des évolutions futures potentielles de cette climatologie des vagues pour différents scénarios d'évolution climatique. L'estimation de l'impact du changement climatique sur le climat de vague se compose de trois éléments principaux : (i) une connaissance détaillée de la variabilité climatique actuelle des états de mer, (ii) l'utilisation de scénarios de changement climatique à l'horizon 2100 et (iii) la définition d'une méthodologie de descente d'échelle adaptée. Pour appréhender ces sujets, l'Atlas Numérique d'Etats de Mer Océanique et Côtier ANEMOC-2 a été construit à l'aide du modèle spectral de 3ème génération TOMAWAC (Benoit et al., 1996) sur la période 1979-2009 et le climat de vagues futur a été simulé à l'horizon 2100 par des méthodes de descente d'échelle dynamique et statistique en considérant les scénarios de changement climatique du quatrième rapport du GIEC (IPCC, 2007).En particulier, un travail original de comparaison de projections d'états de mer par approche dynamique et par approche statistique des types de temps a été réalisé sur la période 2061-2100 pour les scénarios B1, A1B et A2 simulés par le modèle ARPEGE-CLIMAT de Météo-France (Salas-Mélia, et al. 2005). Les résultats des deux approches (à savoir hauteur significative, période moyenne, direction moyenne et flux d'énergie des vagues) ont été comparés en termes de valeurs moyennes, écarts-types, distributions jointes et variabilités saisonnière et interannuelle. Ce travail a abouti à une estimation de l'impact du changement climatique sur la climatologie des états de mer le long des côtes Atlantique, Manche et Mer du Nord françaises sur la période 2061-2100 en tenant compte des incertitudes intrinsèques aux méthodes de descente d'échelle et aux scénarios de changement climatique. En hiver par exemple, nous observons une augmentation des valeurs moyennes et de la variabilité des paramètres de hauteur significative, période moyenne et flux d'énergie des vagues, notamment en Mer du Nord (pour les scénarios B1, A1B et A2) et dans le Golfe de Gascogne pour le scénario B1. En complément, ces paramètres d'états de mer ont tendance à diminuer dans le Golfe de Gascogne pour les saisons printemps, été et automne. Enfin, les paramètres d'états de mer associés aux hauteurs de vagues du quantile 95 tendent à augmenter sur une large emprise de l'Atlantique nord-est / Wave climate analysis is of utmost importance to understand the evolution and dynamics of coastal zones, to estimate the occurrence of extreme events, to design protections for ports, onshore and offshore infrastructure, to characterize wave resources for wave energy conversion, to quantify sediment erosion and accretion processes, et cetera. Thus, this thesis project aims to improve knowledge of wave climatology in the growing context of climate change prediction with a two-step approach: (i) enhancement of the understanding of the present wave climate along the French coastline facing the Atlantic Ocean, English Channel and North Sea and (ii) estimation of possible future wave climate evolution. For this purpose, the estimation of climate change impacts on the wave climate requires three key parameters: (i) detailed knowledge of current wave climate variability, (ii) the application of climate change scenarios from Global Climate Models and (iii) the definition of an appropriate downscaling method. To answer these questions, ANEMOC-2, a hindcast sea-state data base has been built based on the third-generation spectral wave model TOMAWAC (Benoit et al., 1996) over the period 1979-2009, and the future wave climate has been simulated over the period 2061-2100 by means of dynamical and statistical downscaling methods. In particular, an original approach comparing sea-state projections obtained from dynamical and statistical downscaling methods has been applied over the period 2061-2100 for B1, A1B and A2 scenarios (Forth Assessments Reports, IPCC, 2007), based on the ARPEGE-CLIMAT (Salas-Mélia et al., 2005) model simulations. The wave spectral parameters resulting from the projections (i.e. significant wave height, mean period, mean direction and wave energy flux) have been compared in term of mean, joint distribution and seasonal and interannual variability.The possible climate change impacts on the wave climate along the Atlantic, English Channel and North Sea French coastline have also been evaluated. The analysis provides estimations of the inherent uncertainties of climate change scenarios and downscaling methods. Wave climate evolution trends are presented in terms of the mean, joint distribution, and seasonal and interannual variability of significant wave height, mean period, mean direction and wave energy flux

Wind power presently plays a minor role in Western Canada as compared to hydroelectric power in British Columbia and coal and natural gas thermal power generation in Alberta. However, ongoing reductions in the cost of wind power generation facilities and the increasing costs of conventional power generation, particularly if the cost to the environment is included, suggest that assessment of the present and future wind field in Western Canada is of some importance. To assess present wind power, raw hourly wind speeds and homogenized monthly mean wind speeds from 30 stations in Western Canada were analyzed over the period 1971-2000 (past). The hourly data were adjusted using the homogenized monthly means to attempt to compensate for differences in anemometer height from the standard height of 10m and changes in observing equipment at stations. A regional reanalysis product, the North American Regional Reanalysis (NARR), and simulations conducted with the Canadian Regional Climate Model (CRCM) driven with global reanalysis boundary forcing, were compared to the adjusted station wind-speed time-series and probability distributions. The NARR had a better temporal correlation with the observations, than the CRCM. We posit this is due to the NARR assimilating regional observations, whereas the CRCM did not. The NARR was generally worse than the CRCM in reproducing the observed speed distribution, possibly due to the crude representation of the regional topography in NARR. While the CRCM was run at both standard (45 km) and fine (15 km) resolution, the fine grid spacing does not always provide better results: the character of the surrounding topography appears to be an important factor for determining the level of agreement. Multiple simulations of the CRCM at the 45 km resolution were also driven by two global climate models (GCMs) over the periods 1971-2000 (using only historic emissions) and 2031-2060 (using the A2 emissions scenario). In light of the CRCM biases relative to the observations, these simulations were calibrated using quantile-quantile matching to the adjusted station observations to obtain ensembles of 9 and 25 projected wind speed distributions for the 2031-2060 period (future) at the station locations. Both bias correction and change factor techniques were used for calibration. At most station locations modest increases in mean wind speed were found for most of the projected distributions, but with a large variance. Estimates of wind power density for the projected speed distributions were made using a relationship between wind speed and power from a CRCM simulation for both time periods using the 15km grid. As would be expected from the wind speed results and the proportionality of wind power to the cube of wind speed, wind power at the station locations is more likely than not to increase in the 2031-2060 period from the 1971-2000 period. Relative changes in mean wind speeds at station locations were found to be insensitive to the station observations and choice of calibration technique, suggesting that we estimate relative change at all 45km grid points using all pairs of past/future mean wind speeds from the CRCM simulations. Overall, our results suggest that wind energy resources in Western Canada are reasonably likely to increase at least modestly in the future. / Graduate / 0725 / 0608 / jtdaines@uvic.ca

Le changement climatique dû à l'augmentation des émissions de gaz à effet de serre est considéré comme l'un des principaux défis pour les êtres humains dans 21ème siècle. Il conduira à des changements dans les précipitations, l'humidité atmosphérique, augmentation de l'évaporation et probablement augmenter la fréquence des événements extrêmes. Les conséquences de ces phénomènes auront une influence sur de nombreux aspects de la société humaine. Donc, il y a une nécessité d'avoir une estimation robuste et précise de la variation des facteurs naturels dus au changement climatique, au moins dans les événements de cycle et d'inondation hydrologiques pour fournir une base solide pour atténuer les impacts du changement climatique et s'adapter à ces défis. Le but de cette étude est de présenter une méthodologie pour évaluer les impacts de différents scénarios de changement climatique sur une zone inondable du bassin de la rivière côtière dans la région centrale du Viet Nam - bassin versant de Vu Gia Thu Bon. Les simulations hydrologiques sont basées sur un modèle hydrologique déterministe validé qui intègre la géologie, les sols, la topographie, les systèmes fluviaux et les variables climatiques. Le climat de la journée présente, sur la période de 1991-2010 a été raisonnablement simulée par le modèle hydrologique. Climat futur (2091-2100) information a été obtenue à partir d'une réduction d'échelle dynamique des modèles climatiques mondiaux. L'étude analyse également les changements dans la dynamique des inondations de la région de l'étude, le changement hydrologique et les incertitudes du changement climatique simulation. / Climate change due to the increase of greenhouse gas emissions is considered to be one of the major challenges to mankind in the 21st century. It will lead to changes in precipitation, atmospheric moisture, increase in evaporation and probably a higher frequency of extreme events. The consequences of these phenomena will have an influence on many aspects of human society. Particularly at river deltas, coastal regions and developing countries, the impacts of climate change to socio-economic development become more serious. So there is a need for a robust and accurate estimation of the variation of natural factors due to climate change, at least in the hydrological cycle and flooding events to provide a strong basis for mitigating the impacts of climate change and to adapt to these challenges. The aim of this study is to present a methodology to assess the impacts of different climate change scenarios on a flood prone area of a coastal river basin in the central region of Viet Nam – Vu Gia Thu Bon catchment. The hydrological simulations are based on a validated deterministic hydrological model which integrates geology, soil, topography, river systems and climate variables. The present day climate, over the period of 1991-2010 was reasonably simulated by the hydrological model. Future climate (2091-2100) information was obtained from a dynamical downscaling of the global climate models. The study also analyzes the changes in the flood dynamics of the study region, the hydrological shift and the uncertainties of climate change simulation.