This thesis evaluates regional hydrology using output from the Canadian Regional Climate Model (CRCM 4.1) and examines changes in the hydrological processes over the Churchill River Basin (CRB) by employing the Variable Infiltration Capacity (VIC) hydrology model. The CRCM evaluation has been performed by combining the atmospheric and the terrestrial water budget components of the hydrological cycle. The North American Regional Reanalysis (NARR) data are used where direct observations are not available. The outcome of the evaluation reveals the potential of the CRCM for use in long-term hydrological studies. The CRCM atmospheric moisture fluxes and storage tendencies show reasonable agreement with the NARR. The long-term moisture flux over the CRB was found to be generally divergent during summer. A systematic bias is observed in the CRCM precipitation and temperature. A quantile-based mapping of the cumulative distribution function is applied for precipitation adjustments. The temperature correction only involves shifting and scaling to adjust mean and variance. The results indicate that the techniques employed for correction are useful for hydrological studies. Bias-correction is also applied to the CRCM future climate. The CRCM bias-corrected data is then used for hydrological modeling of the CRB. The VIC-simulated streamflow exhibits acceptable agreement with observations. The VIC model's internal variables such as snow and soil moisture indicate that the model is capable of simulating internal process variables adequately. The VIC-simulated snow and soil moisture shows the potential of use as an alternative dataset for hydrological studies. Streamflow along with precipitation and temperature are analyzed for trends. No statistically significant trend is observed in the daily precipitation series. Results suggest that an increase in temperature may reduce accumulation of snow during fall and winter. The flow regime may be in transition from a snowmelt dominated regime to a rainfall dominated regime. Results from future climate simulations of the A2 emission scenario indicate a projected increase of streamflow, while the snow depth and duration exhibit a decrease. Soil moisture response to future climate warming shows an overall increase with a greater likelihood of occurrences of higher soil moisture.

Regional climate models are commonly used for downscaling global climate simulations to the regional scale using nested limited-area models. One of the main goals of this work was the application of regional model RegCM in very high resolution for the region with complex topography in the framework of EC FP6 project CECILIA. RegCM was employed to downscale climate change scenario simulations performed by ECHAM5 model according to the IPCC A1B emission scenario for Central and Eastern Europe in 10km resolution. Validation of model performance, assessed by nesting RegCM in ERA-40 reanalysis, shows improvement of regional climate patterns mainly in mountainous areas. Temperature is well represented with mostly cold bias around -1 žC. Precipitation is affected by large biases around 80 %, in mountainous areas up to 400 % overestimation in winter. Downscaled climate change signal shows average warming 0.5­1.5 žC in period 2021­2050 and 2­4 žC in period 2071­2100. Precipitation changes are mostly within ±0.5 mm/day. RegCM3­beta version with adjusted precipitation scheme parameters shows improvement of the precipitation bias, difference in climate change is rather negligible. Experiments with different convection schemes of RegCM in a case study for Africa performed in the framework of CORDEX project are...

abstract: This research work uses the Weather Research and Forecasting Model to study the effect of large wind farms with an area of 900 square kilometers and a high power density of 7.58 W/m2 on regional climate. Simulations were performed with a wind farm parameterization scheme turned on in south Oregon. Control cases were also run with the parameterization scheme turned off. The primary emphasis was on offshore wind farms. Some analysis on onshore wind farms was also performed. The effects of these wind farms were studied on the vertical profiles of temperature, wind speed, and moisture as well as on temperature and on wind speed near the surface and at hub height. The effects during the day and at night were compared. Seasonal variations were also studied by performing simulations in January and in July. It was seen that wind farms produce a reduction in wind speed at hub height and that the downward propagation of this reduction in wind speed lessens as the atmosphere becomes more stable. In all the cases studied, the wind farms produced a warming effect near the surface, with greater atmospheric stability leading to higher near-surface temperatures. It was also observed that wind farms caused a drying effect below the hub height and a moistening effect above it, because they had facilitated vertical transport of moisture in the air from the lower layers of the atmosphere to the layers of the atmosphere above the wind farm. / Dissertation/Thesis / Masters Thesis Mechanical Engineering 2016

Predictive anisotropy is a phenomenon referring to unequal predictability of surface wind components in different directions. This study addresses the question of whether predictive anisotropy resulting from statistical prediction is influenced by physical factors or by types of regression methods (linear vs nonlinear) used to construct the statistical prediction. A systematic study of statistical predictability of surface wind components at 2109 land stations across the globe is carried out. The results show that predictive anisotropy is a common characteristic for both linear and nonlinear statistical prediction, which suggests that the type of regression method is not a major influential factor. Both strong predictive anisotropy and poor predictability are more likely to be associated with wind components characterized by relatively weak and non-Gaussian variability and in areas characterized by surface heterogeneity. An idealized mathematical model is developed separating predictive signal and noise between large-scale (predictable) and local (unpredictable) contributions to the variability of surface wind, such that small signal-to-noise ratio (SNR) corresponds to low and anisotropic predictability associated with non-Gaussian local variability. The comparison of observed and simulated statistical predictability by Regional Climate models (RCM) and reanalysis in the Northern Hemisphere indicates that small-scale processes that cannot be captured well by RCMs contribute to poor predictability and strong predictive anisotropy in observations. A second idealized mathematical model shows that spatial variability in specifically the minimum directional predictability, resulting from local processes, is the major contributor to predictive anisotropy. / Graduate

An analysis of the air temperature and precipitation for historical and future experiments of regional climate models from Euro-CORDEX activity is presented. A validation of models was performed for the time period 1989 - 2005 using the comparison of model results with E-OBS dataset which represents real values. For this period results show good agreement for temperature, much worse agreement appears for precipitation where their overestimation is more typical. The future evaluation based on the scenarios of greenhouse gases RCP4.5 and RCP8.5 was investigated for periods 2021 - 2050 and 2071 - 2100 in comparison with the period 1971 - 2000 as reference. For the simulations of the future climate we can notice an approximately linear increase of temperatures which is most significant in the northeast Europe. For precipitation models predict their increase in the north Europe and decrease in the south Europe.

Title: Assessment of regional climate models performance in simulating present-day climate over the area of the Czech Republic Author: Lenka Crhová Department: Department of Meteorology and Environment Protection Supervisor:doc. RNDr. Jaroslava Kalvová, CSc. Supervisor's e-mail address: Jaroslava.Kalvova@mff.cuni.cz Abstract: Today a great attention is turned to climate changes and their impacts. Since eighties the Regional Climate Models (RCMs) are developed for assessment of future climate at regional scales. But their outputs suffer from many uncertain- ties. Therefore, it is necessary to assess models ability to simulate observed climate characteristics and uncertainties in their outputs before they are applied in consecu- tive studies. In the first chapters of this thesis the sources of uncertainties in climate model outputs and selected methods of climate models performance evaluation are reviewed. Several methods of model performance assessment are then applied to si- mulations of the Czech regional climate model ALADIN-Climate/CZ and selected RCMs from the ENSEMBLES project for the reference period 1961-1990 in the area of the Czech Republic. The attention is paid especially to comparison of simulated and observed spatial and temporal variability of several climatic elements. Within this thesis the...

Continentality of climate is one of the basic climate phenomena, describing the climate at current place according to annual changes of basic meteorological elements such as temperature, precipitation, etc. Its measure is usually expressed by indices and is being determined either according to observations using collected data or simulated by climate models. The goal is usually to determine the ability of climate models to represent the present state of climate and to determine and analyse the scenarios of future evolvement for Europe as an examined area. In present diploma thesis are briefly introduced terms like continentality, its indices, global and regional climate models, the ERA-Interim reanalysis, as well as the EURO-CORDEX iniciative. Subsequently individual simulations are processed, analysed and compared with the observations according to the E-OBS dataset.

Weather and climate models applied with sufficiently fine mesh grids to enable a large part of atmospheric deep convection to be explicitly resolved have shown a significantly improved representation of local, short-duration and intense precipitation events compared to coarser scale models. In this thesis, two studies are presented aimed at exploring the dependence of horizontal resolution and of parameterization of convection on the simulation of precipitation. The first examined the ability of HARMONIE Climate (HCLIM) regional climate model to reproduce the recent climate in Europe with two different horizontal resolutions, 15 and 6.25 km. The latter is part of the ”grey-zone” resolution interval corresponding to approximately 3-10 km. Particular focus has been given to rainfall and its spatial and temporal variability and other characteristics, for example intensity distributions. The model configuration with the higher resolution is much better at simulating days of large accumulated precipitation amounts, most evident when the comparison is made against high-resolution observations. Otherwise, the two simulations show similar skill, including the representation of the spatial structure of individual rainfall areas of primarily convective origin. The results suggest a ”scale-awareness” in HCLIM, which supports a central feature of the model’s description of deep convection as it is designed to operate independently of the horizontal resolution. In the second study, summer season precipitation over the Alps region, as simulated by HCLIM at different resolutions, is investigated. Similar model configurations as in the previous study were used, but in addition a simulation at the ”convection-permitting” 2 km resolution has been made over Central Europe. The latter considerably increases the realism compared to the former regarding the distribution and intensities of precipitation, as well as other important characteristics including the duration of rain spells, particularly on sub-daily time scales and for extreme events. The simulations with cumulus parameterization active underestimate short-duration heavy rainfall, and rainspells with low peak intensities are too persistent. Furthermore, even though the 6.25 km simulation generally reduces the biases seen in the 15 km run, definitive conclusions of the benefit of ”grey-zone” resolution is difficult to establish in context of the increased requirement of computer resources for the higher-resolution simulation.

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Warmer air temperatures projected for the mid-21st century under climate change are expected to translate to increased evaporation and a re-distribution of precipitation around the world, including in the mid-latitude, continental Athabasca River region in northern Alberta, Canada. This study examines how these projected changes will affect the water balance of various lake sizes. A thermodynamic lake model, MyLake, is used to determine evaporation over three theoretical lake basins – a shallow lake, representative of perched basins in the Peace-Athabasca Delta near Fort Chipewyan; an intermediate-depth lake representative of industrial water storage near Fort McMurray; and a deep lake representative of future off-stream storage of water by industry, also near Fort McMurray. Bias-corrected climate data from an ensemble of Regional Climate Models are incorporated in MyLake, and the water balance is completed by calculating the change in storage as the difference between precipitation and evaporation. Results indicate that evaporation and precipitation are projected to increase in the future by similar magnitudes, thus not significantly changing the long-term water balance of the lakes. However, intra-annual precipitation and evaporation patterns are projected to shift within the year, changing seasonal water level cycles, and the magnitudes and frequencies of extreme 1-, 3- and 5-day weather events are projected to increase. These results demonstrate that future climate change adaptation and mitigation strategies should take into account increases in intra-annual variability and extreme events on water levels of lakes in mid-latitude, interior hydroclimatic regimes. / Graduate / 0368 / walkerg@uvic.ca