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).

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.

Laser in situ scattering and transmissometry (LISST) instruments are used to measure the particle size distributions (PSDs) and volume concentration of individual and groups of phytoplankton in water. The objective of this research was to test the LISST’s ability in detecting monospecific blooms in-situ and the ability to detect aggregation after diatoms were subjected to different temperatures and bacteria concentrations. The PSDs of ten harmful algal bloom (HAB) species were measured with the LISST characterizing the peak location, peak height, peak width, and peak range resulting in a scattering signature for each species. Each species had specific characteristics that would allow for their detection with the LISST, though microscope observations would be needed for complete accuracy. The LISST was able to detect HABs placed in natural seawater collected off the Texas coast. Blooms of four HAB species before they reached full” bloom concentrations were detected making the LISST a possible low cost, effective tool in the early detection and monitoring of HABs. The diatom, Odontella aurita, was used to test how well the LISST could monitor aggregation, an important process in the termination of many phytoplankton blooms. Increasing temperature causes an increase in transparent exopolymer particle (TEP) production in diatoms, which is a critical sticky particle that increases the probability of aggregation. An increase in temperature can also cause an increase in bacteria concentration that can positively effect TEP production and thus aggregation. O. aurita was grown at 20 °C and 28 °C and showed a significant increase in TEP abundance with temperature (p = 0.002), though no relationship between TEP production and bacteria concentration existed. Coomassie stained particles (CSP) are proteinaceous gel-like particles, which are currently understudied. CSP was consistently produced though it did not appear to be dependent upon any single factor. The increase in ocean temperatures has implications for an increase in phytoplankton blooms making the monitoring and understanding of these blooms even more important as they can affect the carbon cycle and potentially the microbial loop.

Extensive research on soot in snow and snow grain size has been carried out in the Polar Regions. However, North American prairie snowpacks lack observations of soot in snow on snow albedo which adds uncertainty to the overall global effect that black carbon on snow has on climate. Measurements in freshly fallen prairie snowpacks in Northwestern Iowa and Central Texas were collected from February 25 to March 3, 2007 and April 6, 2007, respectively. Multi-day monitoring locations and a frozen lake were study sites at which snow samples were collected to measure soot in snow concentrations. Ancillary measurements were collected at a subset of the sample sites that included: temperature, density, depth, and grain size. At some locations snow reflectance and snow radiance was collected with an Analytical Spectral Device visible/near infra-red spectroradiometer (350 ? 1500 nm). Snow impurity, consisting of light-absorbing particulate matter, was measured by filtering meltwater through a nucleopore 0.4 micrometer filter. Filters were examined using a photometer to measure mass impurity concentration. Soot observations indicate prairie snowpack concentrations ranging from 1 ng C gm^-1 to 115 ng C gm^-1 with an average of 34.9 ng C gm^-1. These measurements are within range of previously published values and can lower snow albedo. As expected, spectral albedo was found to decrease with increasing impurities. Additionally, as grain size increased impurity concentration increased. Differences in soot concentration were observed between the two Iowa snowfall events. The Texas event had higher soot concentrations than both Iowa snowfalls. Validation of an ADEOS-II snow product algorithm that compares simulated radiances to measured sensor radiances for retrieval of snow grain size and mass fraction of soot in snow was attempted using satellite images acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS). The algorithm was unable to uniquely identify a particular snow grain size and soot concentration that would lead to a converging radiance solution in the two spectral bands measured and compared by the algorithm. The in situ data at the validation site fell within published ranges for freshly fallen snow for both snow grain size and soot concentration; however; the closest algorithm retrievals were considerably higher than in situ measurements for both grain size and impurity concentrations.

The cryosphere is defined as the portions of the earth where water is in solid form. It represents a very important part of the hydrologic cycle, affecting ecological, human and climate systems. A number of component models describing the energy and mass balances of a snowpack have been developed and these component models are finding their way into watershed models and land surface schemes. The purpose of this thesis is to examine the incorporation of a number of snow processes in the coupled land-surface-hydrological model WATCLASS. The processes under consideration were mixed precipitation, variable fresh snow density, maximum snowpack density, canopy interception and snow-covered area (SCA). The first four of these processes were based on similar work done by Fassnacht (2000) on a watershed in Southern Ontario. In the case of this thesis, the work was completed on a basin in Northern Manitoba. A theory of the relationship between snow-covered area and average snow depth was developed and an algorithm was developed to implement this theory in WATCLASS. Of the five snow processes considered, mixed precipitation was found to have the greatest impact on streamflow while the new canopy interception algorithm was found to have the greatest impact on sensible and latent heat fluxes. The development of a new relationship between SCA and average snow depth was found to have a minimal impact in one study case, but a significant impact on the sensible and latent heat fluxes when snow fell on a pack that had begun to melt and was partially free of snow. Further study of these snow processes in land-surface-hydrologic models is recommended.

Current North American operational satellite passive microwave snow water equivalent (SWE) retrieval algorithms consistently underestimate SWE levels for tundra environments when compared to four years of regional snow surveys conducted in the Northwest Territories and northern Manitoba, Canada. Almost all contemporary SWE algorithms are based on the brightness temperature difference between the 37GHz and 19GHz frequencies found onboard both past and present spaceborne sensors. This underestimation is likely a result of the distribution and deposition of the tundra snow, coupled with the influence of tundra lakes on brightness temperatures at the 19GHz frequency. To better our understanding concerning the underestimation of passive microwave SWE retrievals on the tundra, Environment Canada collected in situ measurements of SWE, snow depth, and density at 87 sites within a 25km by 25km study domain located near Churchill, Manitoba in March 2006. Coincident multi-scale passive microwave airborne (70m & 500m resolution) and spaceborne (regridded to 12.5km & 25km resolution depending on frequency) data were measured at 6.9GHz, 19GHz, 37GHz and 89 GHz frequencies during the same time period. The snow survey data highlighted small-scale localized patterns of snow distribution and deposition on the tundra that likely influences current SWE underestimation. Snow from the open tundra plains is re-distributed by wind into small-scale vegetated features and micro-topographic depressions such as narrow creekbeds, lake edge willows, small stands of coniferous trees and polygonal wedge depressions. The very large amounts of snow deposited in these spatially-constrained features has little influence on the microwave emission measured by large-scale passive microwave spaceborne sensors and is therefore unaccounted for in current methods of satellite SWE estimation. The analysis of the passive microwave airborne data revealed that brightness temperatures at the 19GHz were much lower over some tundra lakes, effectively lowering SWE at the satellite scale by reducing the 37-19GHz brightness temperature difference used to estimate SWE. The unique emission properties of lakes in the wide open expanse of the tundra plains, coupled with an insensitivity to the large amounts of SWE deposited in small-scale features provides an explanation for current passive microwave underestimation of SWE in the tundra environment.

Snow cleaning is one of the important tasks in the winter time in Sweden. Every year government spends huge amount money for snow cleaning purpose. In this thesis we generate a shortest road network of the city and put the depots in different place of the city for snow cleaning. We generate shortest road network using minimum spanning tree algorithm and find the depots position using greedy heuristic. When snow is falling, vehicles start work from the depots and clean the snow all the road network of the city. We generate two types of model. Models are economic model and efficient model. Economic model provide good economical solution of the problem and it use less number of vehicles. Efficient model generate good efficient solution and it take less amount of time to clean the entire road network.

Sammanfattning   Undersökningen i denna studie handlar om förskolebarns tankar om nederbörd och olika nederbördsformer. Genom kvalitativa intervjuer visas barnens tankar kring nederbörd. I undersökningen intervjuades åtta förskolebarn i åldern tre till fem år.   Resultatet som tolkats visar att barns uppfattning av snö och regn är att det kommer från himlen. Majoriteten av barnen vet att regn är vatten.  De kopplar inte ihop moln med nederbörd. Barnen förstår att is är den fasta formen av vatten men inte att även snö är det. Något barn förstår fasövergången mellan flytande till fast. Att is smälter av värme vet barnen och de förstår att temperaturen har betydelse. Däremot visar barnen inte ett tydligt tecken på att de förstår innebörden i avdunstning med vatten i flytande form som övergår till vatten i gasform. Barnen visar ingen förståelse för fenomenet kondensation.      Nyckelord: förskolan, regn, snö, yngre barn / Abstract   The investigation in this study is about preschool children's ideas about precipitation and different forms of precipitation. Through qualitative interviews shows the children's ideas about precipitation. In the survey interviewed eight preschool children in the aged three to five years.   The result which has been interpreted is that children's perception of snow and rain is that it comes from heaven. The majority of the children know that rain is water. They do not associate clouds with precipitation. The children understand that ice is the solid form of water but not that snow is that. One of the children understands the phase transition between liquid to solid. That the ice is melting in heat understand the children and they understand that the temperature is significant. However the children show no clear signs that they understand the meaning of evaporation, that there is water in liquid form which is put into water in gaseous form. The children show no understanding of the phenomenon of condensation.    Keywords: preschool, rain, snow, younger children

The cryosphere is defined as the portions of the earth where water is in solid form. It represents a very important part of the hydrologic cycle, affecting ecological, human and climate systems. A number of component models describing the energy and mass balances of a snowpack have been developed and these component models are finding their way into watershed models and land surface schemes. The purpose of this thesis is to examine the incorporation of a number of snow processes in the coupled land-surface-hydrological model WATCLASS. The processes under consideration were mixed precipitation, variable fresh snow density, maximum snowpack density, canopy interception and snow-covered area (SCA). The first four of these processes were based on similar work done by Fassnacht (2000) on a watershed in Southern Ontario. In the case of this thesis, the work was completed on a basin in Northern Manitoba. A theory of the relationship between snow-covered area and average snow depth was developed and an algorithm was developed to implement this theory in WATCLASS. Of the five snow processes considered, mixed precipitation was found to have the greatest impact on streamflow while the new canopy interception algorithm was found to have the greatest impact on sensible and latent heat fluxes. The development of a new relationship between SCA and average snow depth was found to have a minimal impact in one study case, but a significant impact on the sensible and latent heat fluxes when snow fell on a pack that had begun to melt and was partially free of snow. Further study of these snow processes in land-surface-hydrologic models is recommended.

Current North American operational satellite passive microwave snow water equivalent (SWE) retrieval algorithms consistently underestimate SWE levels for tundra environments when compared to four years of regional snow surveys conducted in the Northwest Territories and northern Manitoba, Canada. Almost all contemporary SWE algorithms are based on the brightness temperature difference between the 37GHz and 19GHz frequencies found onboard both past and present spaceborne sensors. This underestimation is likely a result of the distribution and deposition of the tundra snow, coupled with the influence of tundra lakes on brightness temperatures at the 19GHz frequency. To better our understanding concerning the underestimation of passive microwave SWE retrievals on the tundra, Environment Canada collected in situ measurements of SWE, snow depth, and density at 87 sites within a 25km by 25km study domain located near Churchill, Manitoba in March 2006. Coincident multi-scale passive microwave airborne (70m & 500m resolution) and spaceborne (regridded to 12.5km & 25km resolution depending on frequency) data were measured at 6.9GHz, 19GHz, 37GHz and 89 GHz frequencies during the same time period. The snow survey data highlighted small-scale localized patterns of snow distribution and deposition on the tundra that likely influences current SWE underestimation. Snow from the open tundra plains is re-distributed by wind into small-scale vegetated features and micro-topographic depressions such as narrow creekbeds, lake edge willows, small stands of coniferous trees and polygonal wedge depressions. The very large amounts of snow deposited in these spatially-constrained features has little influence on the microwave emission measured by large-scale passive microwave spaceborne sensors and is therefore unaccounted for in current methods of satellite SWE estimation. The analysis of the passive microwave airborne data revealed that brightness temperatures at the 19GHz were much lower over some tundra lakes, effectively lowering SWE at the satellite scale by reducing the 37-19GHz brightness temperature difference used to estimate SWE. The unique emission properties of lakes in the wide open expanse of the tundra plains, coupled with an insensitivity to the large amounts of SWE deposited in small-scale features provides an explanation for current passive microwave underestimation of SWE in the tundra environment.