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.

An algorithm has been developed for snow recognition (SR) over mountainous areas of Europe from satellite imagery. The algorithm uses Meteosat Second Generations (MSG) instrument Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) data that are acquired in every 15 minutes through whole day. Although SEVIRI has low spatial resolution, its high temporal resolution provides a better discrimination capacity between ice clouds and snow. Discrimination of snow and clouds is the most challenging part of snow recognition algorithm development. The proposed algorithm relies on Satellite Application Facility to support Nowcasting and Very Short Range Forecastings (SAFNWC) cloud products. A final thematic map has been produced which is consisting of 3 different classes: snow, cloud and land. Validation of the SEVIRI SR product was held in three stages.The obtained high performance of the SR product is presented with the analysis results.

Marine aggregates are an important means of carbon transfers downwards to the deep ocean as well as an important nutritional source for benthic organism communities that are the ultimate recipients of the flux. During these last 10 years, data on size distribution of particulate matter have been collected in different oceanic provinces using an Underwater Video Profiler. The cruise data include simultaneous analyses of particle size distributions as well as additional physical and biological measurements of water properties through the water column. First, size distributions of large aggregates have been compared to simultaneous measurements of particle flux observed in sediment traps. We related sediment trap compositional data to particle size (d) distributions to estimate their vertical fluxes (F) using simple power relationships (F=Ad^b). The spatial resolution of sedimentation processes allowed by the use of in situ particle sizing instruments lead to a more detailed study of the role of physical processes in vertical flux. Second, evolution of the aggregate size distributions with depth was related to overlying primary production and phytoplankton size-distributions on a global scale. A new clustering technique was developed to partition the profiles of aggregate size distributions. Six clusters were isolated. Profiles with a high proportion of large aggregates were found in high-productivity waters while profiles with a high proportion of small aggregates were located in low-productivity waters. The aggregate size and mass flux in the mesopelagic layer were correlated to the nature of primary producers (micro-, nano-, picophytoplankton fractions) and to the amount of integrated chlorophyll a in the euphotic layer using a multiple regression technique on principal components. Finally, a mesoscale area in the North Atlantic Ocean was studied to emphasize the importance of the physical structure of the water column on the horizontal and vertical distribution of particulate matter. The seasonal change in the abundance of aggregates in the upper 1000 m was consistent with changes in the composition and intensity of the particulate flux recorded in sediment traps. In an area dominated by eddies, surface accumulation of aggregates and export down to 1000 m occured at mesoscale distances (<100 km).

Thesis (M.S.)--Brigham Young University.

Thesis (Ph.D.)--City University of Hong Kong, 2009. / "Submitted to Department of Electronic Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy." Includes bibliographical references.

Thesis (Ph. D.)--University of Washington, 2003. / Vita. Includes bibliographical references (p. 174-184).

Thesis (Ph. D.) York University, 2001. Graduate Programme in Earth and Space Science. / Typescript. Includes bibliographical references (leaves 222-227). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://wwwlib.umi.com/cr/yorku/fullcit?pNQ67894.

From the Proceedings of the 1975 Meetings of the Arizona Section - American Water Resources Assn. and the Hydrology Section - Arizona Academy of Science - April 11-12, 1975, Tempe, Arizona / Arizona's continued growth and development depends upon sound management of water resources, especially melted snow which is the primary source of water for the 1.1. Million residents of Maricopa county. The method for snowpack information gathering practiced by watershed specialists of the Salt River project in Arizona is described. The method is outlined, describing aircraft reconnaissance, direct enroute mapping of extent and depth of snowpack, and techniques for identifying ice and/or melt conditions. Under optimal conditions, this technique is considered more than acceptable for determining snowpack levels. Limitations of the technique result from the observer's tolerance of vertigo which can arise under flying conditions; cloud cover, which can reduce contrast and shadows thereby reducing accuracy of observation; and vegetation zones where density of plant matter screens much of the snow.

Wet snow accumulating and shedding from overhead transmission lines can lead to a number of serviceability, safety and mechanical reliability issues. An innovative and inexpensive method to reproduce wet snow accretions on a cable in a controlled environment is explained. Wet snow sleeves were experimentally reproduced by using this technique to study their shedding mechanism. A numerical modeling technique using nonlinear finite element analysis is proposed to evaluate the dynamic response of an overhead cable subjected to any snow-shedding scenario. A time function is associated to the mass and weight of each snow element, which enables its virtual removal from the model at the time prescribed by the user. The response of a single span of overhead ground wire subjected to total and partial snow shedding scenarios is evaluated.

In this work, snow data, collected at the Centre for Atmospheric Research Experiments (CARE) site during the winter of 2005/06 as part of the Canadian CALIPSO/CloudSat Validation Project (C3VP) were analyzed with various goals in mind: 1) investigate the effects of surface temperature and system depth on the snow fall velocity and particle size distribution, 2) find the variables that control the relationships between snow fall velocity and size (control variables), 3) retrieve the coefficient and the exponent in the power-law mass-size relations used in snow reflectivity, 4) estimate vertical air motion and 5) describe the shape of snowflakes that can be used in polarimetric studies of snow. It also includes considerable calibration work on the Hydrometeor Velocity and Shape Detector (HVSD); as well as sensitivity testing for radar calibration and Mie-scattering effect on snow density. / Snow events were classified into several categories according to the radar echo vertical extent (H), surface and echo top temperatures (T s, Tt), to find their effects on snow fall velocity and particle size distribution. Several case studies, including situations of strong turbulence, were also examined. / Simple and multiple correlation analyses between control variables and parameters of the power-law size-velocity relationship were carried out for 13 snow cases having a high R2 between their mean snowflakes fall velocity and the v-D fitted curve, in order to find the control variables of power-law v-D relations. Those cases were all characterized by single layered precipitation with different echo depth, surface and echo top temperatures. Results show that the exponent "b" in v-D power-law relationship has little effect on the variability of snow fall velocity; all control variables (T s, Tt, H) correlate much better to the coefficient "a" than to the exponent "b", leading to a snow fall velocity that can be simulated with a varying coefficient "a" and a fixed exponent "b" (v=aD0.15) with good accuracy. Coefficient "a" and exponent "b" for a generic snow v-D relationship were also examined. The results indicate that coefficient "a" of generic snow represents the most frequent coefficient "a" during the events, while the exponent "b" does not show any representative. / Retrieval of the coefficient "a" and exponent "b" in a power-law mass-size relation, which eventually affects the snow reflectivity, was conducted by minimizing the root mean square (RMS) of differences in reflectivity between Vertically pointing McGill X-band Radar (VertiX) and HVSD. Minima of reflectivity differences lay on a diagonal direction of a diagram of the coefficient "a" (x-axis) versus exponent "b" (y-axis). It is shown that as the system deepens, the slope gets less steep. In addition, coefficient and exponent for this mass-size relation change with time, and snow density derived from several combined snow events does not explain the average snow density of the period. / A method to retrieve vertical air motion with good accuracy using VertiX and HVSD is suggested. Several snow shape parameters and relations between the area ratio (Ar) and size of snowflakes (Ar-D relation) are investigated with snow dimensions defined in various ways. These Ar-D relations will be used as a guideline in snow density models.