Snow is a common overlying surface during winter-time and the redistribution of snow by wind is a very important concept for any hydrological research project located within the cryosphere. Wind redistributes snow by eroding it from areas of high wind speed, such as ridge tops and windward slopes, and deposits it in areas of lower wind speeds, such as the lees of ridge tops, vegetation stands, and topographic depressions. The accurate modelling of blowing snow processes such as erosion, deposition, and sublimation have proven to be rather problematic. The largest issue that many modellers must deal with is the accurate collection of solid precipitation throughout the winter season. Without this, incorrect energy and mass balances can occur. This thesis makes use of a new method of acquiring solid precipitation values through the use of an SR50a ultrasonic snow depth sensor and then incorporates it into a version of the Cold Regions Hydrological Model (CRHM) which includes the Prairie Blowing Snow Model (PBSM) and the Minimal Snowmelt Model (MSM) modules. The model is used to simulate seasonal snow depth over an agricultural field in southern Ontario, Canada and is driven with half-hourly locally acquired meteorological data for 83 days during the 2008-2009 winter season. Semi-automated snow surveys are conducted throughout the winter season and the collected in situ snow depth values are compared to the simulated snow depth values at multiple scales. Two modelling approaches are taken to temporally and spatially test model performance. A lumped approach tests the model‟s ability to simulate snow depth from a small point scale and from a larger field scale. A distributed approach separates the entire field site into three hydrological response units (HRUs) and tests the model‟s ability to spatially discretize at the field scale. HRUs are differentiated by varying vegetation heights throughout the field site. Temporal analysis compares the simulated results to each day of snow survey and for the entire field season. Model performance is statistically analyzed through the use of a Root Mean Square Difference (RMSD), Nash-Sutcliffe coefficient (NS), and Model Bias (MB). Both the lumped and distributed modelling approaches fail to simulate the early on-set of snow but once the snow-holding capacities are reached within the field site the model does well to simulate the average snow depth during the latter few days of snow survey as well as throughout the entire field season. Several model limitations are present which prevent the model from incorporating the scaling effects of topography, vegetation, and man-made objects as well as the effects from certain energy fluxes. These limitations are discussed further.

Snow is a common overlying surface during winter-time and the redistribution of snow by wind is a very important concept for any hydrological research project located within the cryosphere. Wind redistributes snow by eroding it from areas of high wind speed, such as ridge tops and windward slopes, and deposits it in areas of lower wind speeds, such as the lees of ridge tops, vegetation stands, and topographic depressions. The accurate modelling of blowing snow processes such as erosion, deposition, and sublimation have proven to be rather problematic. The largest issue that many modellers must deal with is the accurate collection of solid precipitation throughout the winter season. Without this, incorrect energy and mass balances can occur. This thesis makes use of a new method of acquiring solid precipitation values through the use of an SR50a ultrasonic snow depth sensor and then incorporates it into a version of the Cold Regions Hydrological Model (CRHM) which includes the Prairie Blowing Snow Model (PBSM) and the Minimal Snowmelt Model (MSM) modules. The model is used to simulate seasonal snow depth over an agricultural field in southern Ontario, Canada and is driven with half-hourly locally acquired meteorological data for 83 days during the 2008-2009 winter season. Semi-automated snow surveys are conducted throughout the winter season and the collected in situ snow depth values are compared to the simulated snow depth values at multiple scales. Two modelling approaches are taken to temporally and spatially test model performance. A lumped approach tests the model‟s ability to simulate snow depth from a small point scale and from a larger field scale. A distributed approach separates the entire field site into three hydrological response units (HRUs) and tests the model‟s ability to spatially discretize at the field scale. HRUs are differentiated by varying vegetation heights throughout the field site. Temporal analysis compares the simulated results to each day of snow survey and for the entire field season. Model performance is statistically analyzed through the use of a Root Mean Square Difference (RMSD), Nash-Sutcliffe coefficient (NS), and Model Bias (MB). Both the lumped and distributed modelling approaches fail to simulate the early on-set of snow but once the snow-holding capacities are reached within the field site the model does well to simulate the average snow depth during the latter few days of snow survey as well as throughout the entire field season. Several model limitations are present which prevent the model from incorporating the scaling effects of topography, vegetation, and man-made objects as well as the effects from certain energy fluxes. These limitations are discussed further.

Wind transport and sublimation of snow particles are common phenomena across high altitude and latitude cold regions and play important roles in hydrological and atmospheric water and energy budgets. In spite of this, blowing snow processes have not been incorporated in many mesoscale hydrological models and land surface schemes. A physically based blowing snow model, the Prairie Blowing Snow Model (PBSM), initially developed for prairie environments was used to model snow redistribution and sublimation by wind over two sites representative of mountainous regions in Canada: Fisera Ridge in the Rocky Mountain Front Ranges in Alberta, and Granger Basin in the Yukon Territory. Two models were used to run PBSM: the object-oriented hydrological model, Cold Regions Hydrological Modelling Platform (CRHM) and Environment Canadas hydrological-land surface scheme, Modélisation Environmentale Communautaire Surface and Hydrology (MESH). PBSM was coupled with the snowcover energy and mass-balance model (SNOBAL) within CRHM. Blowing snow algorithms were also incorporated into MESH to create MESH-PBSM. CRHM, MESH and MESH-PBSM were used to simulate the evolution of snowcover in hydrological response units (HRUs) over both Fisera Ridge and Granger Basin.<p> To test the models of blowing snow redistribution and ablation over a relatively simple sequence of mountain topography, simulations were run from north to south over a linear ridge in the Canadian Rocky Mountains. Fisera Ridge snowcover simulations with CRHM were performed over two winters using two sets of wind speed forcing: (1) station observed wind speed, and (2) modelled wind speed from a widely applied empirical, terrain-based windflow model. Best results were obtained when using the site meteorological station wind speed data. The windflow model performed poorly when comparing the magnitude of modelled and observed wind speeds. Blowing snow sublimation, snowmelt and snowpack sublimation quantities were considerably overestimated when using the modelled wind speeds. As a result, end-of-winter snow accumulation was considerably underestimated on windswept HRUs. MESH and MESH-PBSM were also used to simulate snow accumulation and redistribution over these same HRUs. MESH-PBSM adequately simulated snow accumulation in the HRUs up until the spring snowmelt period. MESH without PBSM performed less well and overestimated accumulation on windward slopes and the ridge top whilst underestimating accumulation on lee slopes. Simulations in spring were degraded by a large overestimation of melt by MESH. The early and overestimated melt warrants a detailed examination that is outside the scope of this thesis.<p> To parameterize snow redistribution in a mountain alpine basin, snow redistribution and sublimation by wind were calculated for three winters over Granger Basin using CRHM. Snow transport fluxes were distributed amongst HRUs using inter-HRU snow redistribution allocation factors. Three snow redistribution schemes of varying complexity were evaluated. CRHM model results showed that end-of-winter snow accumulation can be most accurately simulated when the inter-HRU snow redistribution schemes take into account wind direction and speed and HRU aerodynamic characteristics, along with the spatial arrangement of HRUs in the catchment. As snow transport scales approximately with the fourth power of wind speed (u4), inter-HRU snow redistribution allocation factors can be established according to the predominant u4 direction over a simulation period or can change at each time step according to an input measured wind direction. MESH and MESH-PBSM were used to simulate snow accumulation and ablation over these same HRUs. MESH-PBSM provided markedly better results than MESH without blowing snow algorithms.<p> That snow redistribution by wind can be adequately simulated in computationally efficient HRUs over mountainous terrain has important implications for representing snow transport in large-scale hydrology models and land surface schemes. Snow redistribution by wind caused mountain snow accumulation to vary from 10% to 161% of seasonal snowfall within a headwater catchment in the Canadian Rocky Mountains, and blowing snow sublimation losses ranged from 10 to 37% of seasonal snowfall.

Wind transport and sublimation of snow particles are common phenomena across high altitude and latitude cold regions and play important roles in hydrological and atmospheric water and energy budgets. In spite of this, blowing snow processes have not been incorporated in many mesoscale hydrological models and land surface schemes. A physically based blowing snow model, the Prairie Blowing Snow Model (PBSM), initially developed for prairie environments was used to model snow redistribution and sublimation by wind over two sites representative of mountainous regions in Canada: Fisera Ridge in the Rocky Mountain Front Ranges in Alberta, and Granger Basin in the Yukon Territory. Two models were used to run PBSM: the object-oriented hydrological model, Cold Regions Hydrological Modelling Platform (CRHM) and Environment Canadas hydrological-land surface scheme, Modélisation Environmentale Communautaire Surface and Hydrology (MESH). PBSM was coupled with the snowcover energy and mass-balance model (SNOBAL) within CRHM. Blowing snow algorithms were also incorporated into MESH to create MESH-PBSM. CRHM, MESH and MESH-PBSM were used to simulate the evolution of snowcover in hydrological response units (HRUs) over both Fisera Ridge and Granger Basin.<p> To test the models of blowing snow redistribution and ablation over a relatively simple sequence of mountain topography, simulations were run from north to south over a linear ridge in the Canadian Rocky Mountains. Fisera Ridge snowcover simulations with CRHM were performed over two winters using two sets of wind speed forcing: (1) station observed wind speed, and (2) modelled wind speed from a widely applied empirical, terrain-based windflow model. Best results were obtained when using the site meteorological station wind speed data. The windflow model performed poorly when comparing the magnitude of modelled and observed wind speeds. Blowing snow sublimation, snowmelt and snowpack sublimation quantities were considerably overestimated when using the modelled wind speeds. As a result, end-of-winter snow accumulation was considerably underestimated on windswept HRUs. MESH and MESH-PBSM were also used to simulate snow accumulation and redistribution over these same HRUs. MESH-PBSM adequately simulated snow accumulation in the HRUs up until the spring snowmelt period. MESH without PBSM performed less well and overestimated accumulation on windward slopes and the ridge top whilst underestimating accumulation on lee slopes. Simulations in spring were degraded by a large overestimation of melt by MESH. The early and overestimated melt warrants a detailed examination that is outside the scope of this thesis.<p> To parameterize snow redistribution in a mountain alpine basin, snow redistribution and sublimation by wind were calculated for three winters over Granger Basin using CRHM. Snow transport fluxes were distributed amongst HRUs using inter-HRU snow redistribution allocation factors. Three snow redistribution schemes of varying complexity were evaluated. CRHM model results showed that end-of-winter snow accumulation can be most accurately simulated when the inter-HRU snow redistribution schemes take into account wind direction and speed and HRU aerodynamic characteristics, along with the spatial arrangement of HRUs in the catchment. As snow transport scales approximately with the fourth power of wind speed (u4), inter-HRU snow redistribution allocation factors can be established according to the predominant u4 direction over a simulation period or can change at each time step according to an input measured wind direction. MESH and MESH-PBSM were used to simulate snow accumulation and ablation over these same HRUs. MESH-PBSM provided markedly better results than MESH without blowing snow algorithms.<p> That snow redistribution by wind can be adequately simulated in computationally efficient HRUs over mountainous terrain has important implications for representing snow transport in large-scale hydrology models and land surface schemes. Snow redistribution by wind caused mountain snow accumulation to vary from 10% to 161% of seasonal snowfall within a headwater catchment in the Canadian Rocky Mountains, and blowing snow sublimation losses ranged from 10 to 37% of seasonal snowfall.

L'augmentation de l'accumulation de neige simulée en Antarctique de l'Est pour le siècle à venir est une contribution négative à la hausse du niveau moyen des mers. Les modèles climatiques simulant cette augmentation ne possèdent pas de paramétrisation du transport éolien de neige or ce dernier joue un rôle primordial sur l'accumulation d'après les observations. Les modèles climatiques régionaux possédant une paramétrisation du transport éolien permettent d'estimer l'incertitude des modèles climatiques sur la hausse du niveau moyen des mers en ne représentant pas ce processus. Cependant aucune donnée de transport ne permet une validation précise de ces modèles en Antarctique. Dans ce contexte, cette thèse décrit la constitution d'une base de données de transport éolien de neige en Antarctique ainsi qu'une validation d'un modèle climatique régional incluant le transport éolien de neige. Un instrument acoustique, le FlowCapt, a été choisi pour acquérir les données. Une comparaison avec un appareil de mesure optique du transport, le Snow Particle Counter, a été menée dans les Alpes françaises. Cette comparaison a permis de déterminer les limites des deux générations de FlowCapt existantes pour la détection des événements de transport et la quantification du flux de neige. Une base de données de trois années a été acquise en Terre Adélie, Antarctique, pour permettre une comparaison avec un modèle climatique régional. Elle a permis de calculer la hauteur de rugosité et la vitesse de frottement seuil avec leurs incertitudes. Les épisodes de transport éolien de neige et une borne inférieure de la quantité de neige déplacée en un point ont été estimés. Deux comparaisons ont été menées avec le Modèle Atmosphérique Régional, un modèle climatique régional incluant de nombreuses rétroactions du transport sur l'écoulement. Les deux simulations utilisées pour les comparaisons ont été faites sur un petit domaine à fine échelle sur une période d'un mois. Le modèle simule bien les épisodes de transport sauf lorsque de la fonte s'est produite juste avant un épisode ou lorsque les épisodes ont une hauteur maximale de transport inférieure à cinquante centimètres. Le modèle sous-estime les quantités de neige transportée. / Predicted accumulation by global numerical climate models for the next century increases in East Antarctica and negatively contributes to the mean sea level rise. None of the climate models integrates a blowing snow parametrisation. However few smaller scale regional climate models include a blowing snow parametrisation and thus can assess the climate models uncertainty on the mean sea level rise by not representing this process. Yet none of the blowing snow data available in Antarctica allows for a precise validation of a regional climate model. In this context, this PhD described the establishment of an Antarctica blowing snow database and the validation of a regional climate model including a blowing snow parametrisation. An acoustic blowing snow sensor, the FlowCapt, has been chosen to collect data in Antarctica. A comparison with an optic blowing snow sensor, the Snow Particle Counter, has been conducted in the French Alps. The capacity of the two existing FlowCapt generation has been determined on the blowing snow event and the flux quantification. A three years blowing snow model-oriented database is now available in Adélie Land, Antarctica. The threshold friction velocity and the roughness height have been calculated with their uncertainty. Blowing snow variability has been determined as well as the minimum transport rate at one field point. Two comparisons have been done with the Modèle Atmosphérique Regional (MAR), a regional climate model including a blowing snow parametrisation. Both simulations represent a small domain with a high vertical and horizontal resolution over one month. The model is able to reproduce the blowing snow event except when melting occurs or when the blowing snow height is encompassed within the first fifty centimetres above the ground. The model underestimate the snow quantity transported at the field measurement point.