The conventional approach to the frequency analysis of extreme rainfall is complicated by non-stationarity resulting from climate change. In this study significant trends in extreme rainfall are detected using statistical trend tests (Mann-Kendall test and t-test) for all over the Korean Peninsula. The violation of the stationarity for 1 hour annual maximum series is detected for large part of the area especially for southwestern and northeastern regions. For stations showing non-stationarity, the non-stationary generalized extreme value (GEV) distribution model with a location parameter in the form of linear function of time makes significant improvement in modeling rainfall extremes when compared to the stationary GEV model. The Bartlett-Lewis rainfall model is used to generate annual maximum series for the purpose of generating the Intensity-Duration-Frequency (IDF) curve. Using 100 sets of 50 year synthetic annual maxima, it is found that the observed annual rainfall maximum series are reasonably represented by the model. The observed data is perturbed by change factors to incorporate the climate change scenario from the WRF (Weather Research and Forecasting) regional climate model into IDF estimates. The IDF curves for the future period 2040-2079 show highest estimates for all return periods and rainfall durations. The future IDF estimates show significant difference from the IDF estimates of the historical period (1968-2000). Overall, IDF curves show an increasing tendency over time. A historical and future climate simulation is evaluated over the Colorado River Basin using a 111-year simulation (1969-2079) of the WRF climate change scenario. We find the future projections show statistically significant increases in temperature with larger increases in the northern part of the basin. There are statistically insignificant increases in precipitation, while snowfall shows a statistically significant decrease throughout the period in all but the highest elevations and latitudes. The strongest decrease in snowfall is seen at high elevations in the southern part of the basin and low elevations in the northern part of the basin.

This thesis is in two parts. The first part considers a theoretical relationship between the natural variability of a stochastic model and its response to a small change in forcing. Over a large enough scale, both the real climate and a climate model are characterised as stochastic dynamical systems. The dynamics of the systems are encoded in the probabilities that the systems move from one state into another. When the systems’ states are discretised and listed, then transition matrices of all these transition probabilities may be formed. The responses of the systems to a small change in forcing are expanded in terms of the eigenfunctions and eigenvalues of the Fokker-Planck equations governing the systems’ transition densities, which may be estimated from the eigenvalues and eigenvectors of the transition matrices. Smoothing the data with a Gaussian kernel improves the estimate of the eigenfunctions, but not the eigenvalues. The significance of differences in two systems’ eigenvalues and eigenfunctions is considered. Three time series from HadCM3 are compared with corresponding series from ERA-40 and the eigenvalues derived from the three pairs of series differ significantly. The second part analyses a model of the coupled climate-economic system, which suggests that the pace of economic growth needs to be reduced and the resilience to climate change needs to be increased in order to avoid a collapse of the human economy. The model condenses the climate-economic system into just three variables: a measure of human wealth, the associated accumulation of greenhouse gases, and the consequent level of global warming. Global warming is assumed to dictate the pace of economic growth. Depending on the sensitivity of economic growth to global warming, the model climate-economy system either reaches an equilibrium or oscillates in century-scale booms and busts.

The global climate is changing. Compared with many parts of the world, especially North America and Europe, relatively little is known about how climate has changed over the Arabian Peninsula (AP) in recent decades. Quantifying the climate change in the mean and extreme temperature and precipitation variables and understanding the mechanisms behind these changes are essential for establishing adequate and proper adaptation strategies to ensure sustainability, reduce vulnerability and safeguard livelihoods. Four papers in this thesis contribute to that objective, utilising a combination of in situ high quality meteorological station data and high resolution regional climate model data. The first paper quantifies the trends in monthly, seasonal and annual mean, maximum, minimum temperatures and Diurnal Temperature Range (DTR) variables and total precipitation. The station dataseries are tested for quality control and homogeneity. A non-parametric test is used to calculate the trends and evaluate the trend significance for individual stations, subregions (Non-monsoonal and Monsoonal) and for the whole area average. There is a high significant increase in the temperature variables especially the minimum temperature (during 1980-2008 and over all the AP the trend of annual minimum temperature is 0.55 °C decade^-1 while the annual maximum temperature trend is 0.32 °C decade^-1) which leads to significant decrease in the DTR. The precipitation is decline but insignificantly. The non-monsoonal region located north of 20° N has experienced higher rates of warming than the monsoonal region. Spring and summer seasons witness the highest significant warming. The interannual variability of the AP temperature and precipitation shows marked negative association after 1998. The second paper utilises the AP daily data of maximum temperature, minimum temperature and precipitation to calculate climate extremes indices, evaluate the regional/subregional trends of these indices and assess the trend significance. There is a clear significant decrease of cold temperature extremes and a significant increase in the warm temperature extremes. The increase in the nighttime temperature extremes is remarkable in the last two decades (the rate of increase of the warm night frequency is 3.6% decade^-1 during 1986-2008). The spatial trend patterns reveal a latitudinal distinction whereby the northern AP experiences an increase associated with day-time extremes while for the night-time extremes the trends are higher and significant for the southern region. Precipitation indices trends are weak and although they show general decrease in the last two decades they are insignificant. The changes in the Dew Point (Td) and the Mean Sea Level Pressure (MSLP) indicate possible changes in the regional dynamics. The third paper uses the Providing Regional Climates for Impact Studies (PRECIS) regional climate model forced by the European Centre for ERA-Interim re-analysis (ERA-Interim) to simulate the AP climate during 1990-2008. PRECIS simulation is validated based on climate mean and trends. The model simulation captures the mean climatic conditions and patterns, the increasing temperature tendency, as well as the decreasing precipitation observed in the last two decades. However, PRECIS has cold bias especially with the minimum temperature and it overestimates the precipitation over the high lands or regions close to them over the southwestern mountains and underestimates the precipitation over the southeastern mountains. The model products provide indications on the reasons behind the highest daytime spring warming (decrease of specific humidity) and significant nighttime summer warming (increase of Sea Surface Temperature (SST)). The model fails to simulate the recent increase of the nighttime temperature parameters over AP. The final paper addresses the possible local atmospheric circulations, SST and remote modes of variability associated with the recent AP climate extreme changes. Using the PRECIS simulation, composite difference maps for some surface, upper atmospheric circulation maps and SSTs between two period 1990-1997 and 1998-2008 have been calculated. The composite difference maps reveal significant local changes in these atmospheric and oceanic variables which possibly partly explain the recent regional warming and drying conditions during the last two decades. In addition, relationships of the regional/subregional extremes indices timeseries have been calculated with some known remote modes of variability. There is a clear, strong relation of El Niño Southern Oscillation (ENSO) with the AP climate in all the seasons except in winter. The North Atlantic Caspian Sea Pattern (NCP) influences the regional climate in winter especially the temperature variables.

Made available in DSpace on 2017-07-10T19:24:12Z (GMT). No. of bitstreams: 1 Gisele Gollin 2015.pdf: 3252968 bytes, checksum: 739819d25020783e08e374315f3e2ee1 (MD5) Previous issue date: 2015-08-20 / This study aims to estimate hydric availability in Piquiri River basin based on the historical flow series and precipitation from 1980 to 2010 in order to associate them to the rainfall estimates provided by Eta, a regional weather model, until 2098. The series of annual minimum flows (Q7) and minimum of seven-day flows with a registering period of ten years (Q7,10) were submitted to statistical analysis to identify the probabilistic model that best fitted the data for each station. Thus, in order to obtain the retention curve, a procedure was carried out based on the obtained frequency classes. The average values of annual rainfall, precipitation of the driest quarter, precipitation of the wettest quarter, precipitation of the driest semester and precipitation of the wettest quarter of the basin were determined using the IDW interpolation method using a geographic information system (SIG). From all precipitation and flow obtained values, regressions were performed among (Q7), (Q7,10), (Q 90%), (Q 95%) flows and rainfalls (total annual, the driest quarter, the wettest quarter, the driest semester and the wettest semester) associated with the drainage area. Standard statistical tests were carried out to assure the quality of the generated model.For estimates of future flows, it was necessary to obtain data of future annual rainfall, simulated by the weather model Eta, from 2010 to 2098, which were provided by the Weather Forecasting and Climate Studies Center (CPTEC/INPE). The independent variable that best corresponds to the proposed standards during the study was the total annual rainfall in order to define the rainfall-runoff basin model. According to the future data of annual rainfall and drainage area, through the rainfall-runoff model, it was possible to obtain estimates of future minimum flows and carry out the trend analysis of time series with the series of future flow estimates. Therefore, a simple linear filter was used for smoothing the data series. It was not possible to find a pattern of rainfall related to the driest and wettest months in Piquiri River basin. Multiple linear model fitted best to the data, whose coefficient of determination (R)2was 0.67. The charts concerning generated trend analysis showed little increase in total annual rainfall index, simulated for the future in the studied region, when compared to the historical series. It was also observed that both members of the Eta model showed similar results. The values of minimum flows estimated for the future have provided to the basin an area without water deficit under natural conditions / O objetivo deste trabalho foi estimar a disponibilidade hídrica na bacia hidrográfica do Rio Piquiri por meio das séries históricas de vazão e precipitação no período de 1980 2010 e relacioná-las com as estimativas de precipitação fornecidas pelo modelo climático regional Eta até o ano de 2098. As séries de vazões mínimas anuais (Q7) e vazões mínimas com sete dias de duração com um período de retorno de dez anos (Q7,10) para cada estação foram submetidas à análise estatística, para identificar o modelo probabilístico que melhor se ajustasse aos dados. Para a obtenção da curva de permanência, realizou-se o procedimento baseado na obtenção de classes de frequência. Os valores da média de precipitação anual, precipitação do trimestre mais seco, precipitação do trimestre mais chuvoso, precipitação do semestre mais seco e precipitação do semestre mais chuvoso sobre a bacia foram determinados utilizando o método de interpolação IDW por um sistema de informação geográfica (SIG). A partir de todos os valores de precipitação e vazão encontrados, foram realizadas as regressões entre as vazões (Q7), a (Q7,10), a (Q 90%), a (Q 95%) e as precipitações (total anual, trimestre mais seco, trimestre mais chuvoso, semestre mais seco e semestre mais chuvoso) juntamente com a área de drenagem. Foram realizados testes estatísticos padrão para comprovar a qualidade do modelo gerado. Para a estimativas de vazões futuras, foi necessário obter os dados de precipitação total anual futuros simulados pelo modelo climático Eta, para o período de 2010 a 2098, os quais foram fornecidos pelo Centro de Previsão de Tempo e Estudos Climáticos (CPTEC/INPE).A variável explicativa que melhor correspondeu aos padrões propostos durante o estudo para definir o modelo chuva-vazão da bacia foi a precipitação total anual. De posse dos dados futuros de precipitação total anual e área de drenagem, através do modelo chuva-vazão, foram obtidas as estimativas de vazões mínimas futuras e realizada a análise de tendência da série histórica juntamente com a série de estimativas de vazão futura. Para tanto, empregou-se um filtro linear simples para a suavização da série de dados. Não foi possível encontrar um padrão de pluviosidade em relação aos meses mais secos e mais chuvosos na bacia hidrográfica do rio Piquiri. O modelo linear múltiplo foi o que melhor se ajustou aos dados, cujo coeficiente de determinação (R)2foi igual a 0,67. Os gráficos de análise de tendência gerados indicaram pequeno aumento no índice de precipitação total anual simulado para o futuro na região estudada, em comparação à série histórica, e observouseque os dois membros do modelo Eta apresentaram resultados semelhantes. Os valores de vazões mínimas, estimados para o futuro, conferem à bacia uma área sem restrições hídricas em condições naturais.

Made available in DSpace on 2017-05-12T14:47:28Z (GMT). No. of bitstreams: 1 Gisele Gollin 2015.pdf: 3252968 bytes, checksum: 739819d25020783e08e374315f3e2ee1 (MD5) Previous issue date: 2015-08-20 / This study aims to estimate hydric availability in Piquiri River basin based on the historical flow series and precipitation from 1980 to 2010 in order to associate them to the rainfall estimates provided by Eta, a regional weather model, until 2098. The series of annual minimum flows (Q7) and minimum of seven-day flows with a registering period of ten years (Q7,10) were submitted to statistical analysis to identify the probabilistic model that best fitted the data for each station. Thus, in order to obtain the retention curve, a procedure was carried out based on the obtained frequency classes. The average values of annual rainfall, precipitation of the driest quarter, precipitation of the wettest quarter, precipitation of the driest semester and precipitation of the wettest quarter of the basin were determined using the IDW interpolation method using a geographic information system (SIG). From all precipitation and flow obtained values, regressions were performed among (Q7), (Q7,10), (Q 90%), (Q 95%) flows and rainfalls (total annual, the driest quarter, the wettest quarter, the driest semester and the wettest semester) associated with the drainage area. Standard statistical tests were carried out to assure the quality of the generated model.For estimates of future flows, it was necessary to obtain data of future annual rainfall, simulated by the weather model Eta, from 2010 to 2098, which were provided by the Weather Forecasting and Climate Studies Center (CPTEC/INPE). The independent variable that best corresponds to the proposed standards during the study was the total annual rainfall in order to define the rainfall-runoff basin model. According to the future data of annual rainfall and drainage area, through the rainfall-runoff model, it was possible to obtain estimates of future minimum flows and carry out the trend analysis of time series with the series of future flow estimates. Therefore, a simple linear filter was used for smoothing the data series. It was not possible to find a pattern of rainfall related to the driest and wettest months in Piquiri River basin. Multiple linear model fitted best to the data, whose coefficient of determination (R)2was 0.67. The charts concerning generated trend analysis showed little increase in total annual rainfall index, simulated for the future in the studied region, when compared to the historical series. It was also observed that both members of the Eta model showed similar results. The values of minimum flows estimated for the future have provided to the basin an area without water deficit under natural conditions / O objetivo deste trabalho foi estimar a disponibilidade hídrica na bacia hidrográfica do Rio Piquiri por meio das séries históricas de vazão e precipitação no período de 1980 2010 e relacioná-las com as estimativas de precipitação fornecidas pelo modelo climático regional Eta até o ano de 2098. As séries de vazões mínimas anuais (Q7) e vazões mínimas com sete dias de duração com um período de retorno de dez anos (Q7,10) para cada estação foram submetidas à análise estatística, para identificar o modelo probabilístico que melhor se ajustasse aos dados. Para a obtenção da curva de permanência, realizou-se o procedimento baseado na obtenção de classes de frequência. Os valores da média de precipitação anual, precipitação do trimestre mais seco, precipitação do trimestre mais chuvoso, precipitação do semestre mais seco e precipitação do semestre mais chuvoso sobre a bacia foram determinados utilizando o método de interpolação IDW por um sistema de informação geográfica (SIG). A partir de todos os valores de precipitação e vazão encontrados, foram realizadas as regressões entre as vazões (Q7), a (Q7,10), a (Q 90%), a (Q 95%) e as precipitações (total anual, trimestre mais seco, trimestre mais chuvoso, semestre mais seco e semestre mais chuvoso) juntamente com a área de drenagem. Foram realizados testes estatísticos padrão para comprovar a qualidade do modelo gerado. Para a estimativas de vazões futuras, foi necessário obter os dados de precipitação total anual futuros simulados pelo modelo climático Eta, para o período de 2010 a 2098, os quais foram fornecidos pelo Centro de Previsão de Tempo e Estudos Climáticos (CPTEC/INPE).A variável explicativa que melhor correspondeu aos padrões propostos durante o estudo para definir o modelo chuva-vazão da bacia foi a precipitação total anual. De posse dos dados futuros de precipitação total anual e área de drenagem, através do modelo chuva-vazão, foram obtidas as estimativas de vazões mínimas futuras e realizada a análise de tendência da série histórica juntamente com a série de estimativas de vazão futura. Para tanto, empregou-se um filtro linear simples para a suavização da série de dados. Não foi possível encontrar um padrão de pluviosidade em relação aos meses mais secos e mais chuvosos na bacia hidrográfica do rio Piquiri. O modelo linear múltiplo foi o que melhor se ajustou aos dados, cujo coeficiente de determinação (R)2foi igual a 0,67. Os gráficos de análise de tendência gerados indicaram pequeno aumento no índice de precipitação total anual simulado para o futuro na região estudada, em comparação à série histórica, e observouseque os dois membros do modelo Eta apresentaram resultados semelhantes. Os valores de vazões mínimas, estimados para o futuro, conferem à bacia uma área sem restrições hídricas em condições naturais.

The climate of West Africa is characterised by a monsoonal system that brings rainfall onto the subcontinent during an annual rainy season. From the late 60's to the mid-90's, rainfall levels significantly below average were observed, which brought severe socio-economic implications. The causes of the uncharacteristically long drought period, and indeed the mechanisms underpinning West African climate were poorly understood at the time, but have since attracted growing attention from the scientific community. Amongst the factors identified as critical is the interaction between the Earth surface and the atmosphere. To investigate these interactions over West Africa we have adopted an approach based upon regional climate modelling, an internationally recognised discipline enabling the representation of past and future climates, and the study of specific meteorological mechanisms. Using the regional climate model MAR, we have carried out simulations of the West African climate for the years 1986, 1987, and 1988. To improve the accuracy with which the model represents the biosphere, a new dataset describing the local vegetation was incorporated and a new scheme for the representation of roots implemented. A measure of the internal variability inherent to all results produced with this, and other such models, was determined. Subsequently, the influence of soil moisture anomalies on the model behaviour was investigated. The latest version of the model was validated by comparing it to observational data for selected years. Our results have prooven the ability of the improved MAR to simulate the West African climate, its monsoon and its spatial and temporal behaviour and provide strong evidence of its suitability for further investigation of the surface-atmosphere interactions over West Africa.

The climate of West Africa is characterised by a monsoonal system that brings rainfall onto the subcontinent during an annual rainy season. From the late 60's to the mid-90's, rainfall levels significantly below average were observed, which brought severe socio-economic implications. The causes of the uncharacteristically long drought period, and indeed the mechanisms underpinning West African climate were poorly understood at the time, but have since attracted growing attention from the scientific community. Amongst the factors identified as critical is the interaction between the Earth surface and the atmosphere. To investigate these interactions over West Africa we have adopted an approach based upon regional climate modelling, an internationally recognised discipline enabling the representation of past and future climates, and the study of specific meteorological mechanisms. Using the regional climate model MAR, we have carried out simulations of the West African climate for the years 1986, 1987, and 1988. To improve the accuracy with which the model represents the biosphere, a new dataset describing the local vegetation was incorporated and a new scheme for the representation of roots implemented. A measure of the internal variability inherent to all results produced with this, and other such models, was determined. Subsequently, the influence of soil moisture anomalies on the model behaviour was investigated. The latest version of the model was validated by comparing it to observational data for selected years. Our results have prooven the ability of the improved MAR to simulate the West African climate, its monsoon and its spatial and temporal behaviour and provide strong evidence of its suitability for further investigation of the surface-atmosphere interactions over West Africa.

The impacts of biomass burning smoke on local rainfall and the structure of the atmospheric boundary layer have been actively studied in recent years. However, whether the large-scale biomass burning in the later dry season over Amazonia Region could influence the dry-to-wet transition season have not been examined. Previous observations have shown that the substantial increase of rainfall from dry to wet season over Amazonia are actually caused by small changes of the atmospheric thermodynamic structure relative to those over other monsoon regions. Consequently, the onset date of wet season can vary greatly as influenced by external or internal anomalous forcings. Thus, it is possible that the transition of the atmospheric thermodynamic structure and circulation from dry to wet season is also sensitive to the impacts of biomass burning smoke. To test this hypothesis, we have forced RegCM3 model with direct radiative forcing of smoke inferred from MODIS for the transition season (August to November). The comparison with control run helps us to examine the direct and semi-direct influences of smoke on the transition from dry to wet season. Our preliminary results show that the direct and semi-direct forcings of smoke could significantly influence the rainfall and related atmospheric and land surface conditions during the transition. However, these changes are sensitive to the prescribed vertical distribution of the aerosols.

The presence of nonlinear dependence and chaos has strong implications for predictive modeling and the analysis of dominant processes in hydrology and climate. Analysis of extremes may aid in developing predictive models in hydro-climatology by giving enhanced understanding of processes driving the extremes and perhaps delineate possible anthropogenic or natural causes. This dissertation develops and utilizes different set of tools for predictive modeling, specifically nonlinear dependence, extreme, and chaos, and tests the viability of these tools on the real data. Commonly used dependence measures, such as linear correlation, cross-correlogram or Kendall's tau, cannot capture the complete dependence structure in data unless the structure is restricted to linear, periodic or monotonic. Mutual information (MI) has been frequently utilized for capturing the complete dependence structure including nonlinear dependence. Since the geophysical data are generally finite and noisy, this dissertation attempts to address a key gap in the literature, specifically, the evaluation of recently proposed MI-estimation methods to choose the best method for capturing nonlinear dependence, particularly in terms of their robustness for short and noisy data. The performance of kernel density estimators (KDE) and k-nearest neighbors (KNN) are the best for 100 data points at high and low noise-to-signal levels, respectively, whereas KNN is the best for 1000 data points consistently across noise levels. One real application of nonlinear dependence based on MI is to capture extrabasinal connections between El Nino-Southern Oscillation (ENSO) and river flows in the tropics and subtropics, specifically the Nile, Amazon, Congo, Parana, and Ganges rivers which reveals 20-70% higher dependence than those suggested so far by linear correlations. For extremes analysis, this dissertation develops a new measure precipitation extremes volatility index (PEVI), which measures the variability of extremes, is defined as the ratio of return levels. Spatio-temporal variability of PEVI, based on the Poisson-generalized Pareto (Poisson-GP) model, is investigated on weekly maxima observations available at 2.5 degree grids for 1940-2004 in South America. From 1965-2004, the PEVI shows increasing trends in few parts of the Amazon basin and the Brazilian highlands, north-west Venezuela including Caracas, north Argentina, Uruguay, Rio De Janeiro, Sao Paulo, Asuncion, and Cayenne. Catingas, few parts of the Brazilian highlands, Sao Paulo and Cayenne experience increasing number of consecutive 2- and 3-days extremes from 1965-2004. This dissertation also addresses the ability to detect the chaotic signal from a finite time series observation of hydrologic systems. Tests with simulated data demonstrate the presence of thresholds, in terms of noise to chaotic-signal and seasonality to chaotic-signal ratios, beyond which the set of currently available tools is not able to detect the chaotic component. Our results indicate that the decomposition of a simulated time series into the corresponding random, seasonal and chaotic components is possible from finite data. Real streamflow data from the Arkansas and Colorado rivers do not exhibit chaos. While a chaotic component can be extracted from the Arkansas data, such a component is either not present or can not be extracted from the Colorado data.

Lodgepole pine (Pinus contorta Douglas ex Louden) is the most widespread pine in North America and the single most abundant tree species in British Columbia (BC). Its vast distribution, diversity and economic value make it an important species for timber harvest and subsequent reforestation. Climate change raises serious concerns over the adaptability and effective management of BC’s future forests. The majority of lodgepole pine seedlings requested for replanting are produced from seed obtained from wild stands, but the relationship between climate variation and the seed production of natural populations has yet to be assessed. The purpose of this study is to determine if variation in P. contorta seed yield is related to the climate of BC. Historical cone collection data were obtained from archived records of 1948 seedlots in 22 different natural stand seed planning zones (SPZs) of BC. Collections were made between 1963 and 2013 and seed yield (kg fresh seed/hL cone) was determined for each seedlot. First, natural variation in seed production of lodgepole pine was examined in 18 different SPZs. The Nass Skeena Transition (NST) represents a unique intersection between continental and maritime ecosystems and was found to have a significantly higher mean seed yield compared to all other zones, with the exception of Hudson Hope (HH). However, variance in seed yield for NST was found to be an order of magnitude higher than that of other SPZs, indicating that seed production in this region is exceptionally variable. These findings provide a valuable geographic baseline for the reproductive fitness of lodgepole pine, suggesting that climate adaptation and mitigation strategies for some areas of the province may need to be region-specific. In addition, the relationship between climate variation and the seed production of P. contorta in BC was evaluated. The climate of each region was described using dynamically-downscaled Global Circulation Model (GCM) and reanalysis climate output from the Canadian Regional Climate Model (CRCM). Annual, winter, and summer means were explored for each of the climate variables of interest: total precipitation (mm) and surface air temperature (°C). Temporal correlations between the mean annual seed yield anomaly and the anomaly of both climate variables were significant under a variety of climate schemes in a number of SPZs. Significant overall trends in climate variables were also captured using GCM-driven CRCM output. While these two analyses independently highlighted significant relationships between seed yield and climate, their joint implications were unclear. Shifts in the CRCM boundary conditions revealed that the results lacked robustness during the historical period, inhibiting the investigation of future projections. Ambiguous age ranges for each cone collection and temporal restrictions of the seed collection data may be partially responsible for these inconclusive results. Results from the first half of this thesis suggest that, with few exceptions, seed production is relatively stable across SPZs spanning a wide range of climate regimes. Thus, the investigation of the relationship between reproductive fitness and climate may be complicated by the extraordinary adaptability of lodgepole pine and the high genetic variation in natural populations. / Graduate