In order to improve our knowledge on the current state and variability of the Greenland ice sheet surface mass balance (SMB), a 27-year simulation (1979-2005) has been performed with the coupled atmosphere-snow regional model MAR. This simulation reveals an increase in the main factors of the SMB which are, on the one hand, the snowfall (+ 1.6 ± 1.8 km3 yr-1) in winter and on the other hand, the run-off (+ 4.2 ± 1.9 km3 yr-1) in summer. The net effect of these two competing factors leads to a SMB loss rate of – 2.7 ± 3.0 km3 yr-1, which has a significance of 87%. The melt extent derived from the passive microwave satellite data since 1979 also shows this trend. The melt water supply has increased because the Greenland ice sheet has been warming up by + 0.09 ± 0.04 °C yr-1 since 1979. This warming comes from a uniform increase of downward infra-red radiation which can not be explained by the natural variability. These changes result very likely from the global warming induced by human activities. As a result, it seems that: i) increased melting dominates over increased accumulation in a warming scenario, ii) the Greenland ice sheet has been significantly losing mass since the beginning of the 1980's by an increasing melt water run-off as well as by a probable increase of iceberg discharge into the ocean due to the "Zwally effect" (the melt water-induced ice sheet flow acceleration) and iii) the Greenland ice sheet is projected to continue to lose mass in the future. The Greenland ice sheet melting could have an effect on the stability of the thermohaline circulation (THC) and the global sea level rise. On the one hand, increases in the freshwater flux from the Greenland ice sheet (glacier discharge and run-off) could perturb the THC by reducing the density contrast driving it. On the other hand, the melting of the whole Greenland ice sheet would account for a global mean sea level rise of 7.4 m.

April 1st Snow Water Equivalent (SWE) reconstructions were generated using tree-ring chronologies for the Upper North Platte River Basin (UNPRB), located in north-central Colorado and south-eastern Wyoming. To regionalize April 1st snowpack data from 11 SNOw TELemetry stations (SNOTEL stations), Varimax Rotated Principal Components Analysis (PCA) was used. For the 11 station regionalization, the reconstruction explained 42% of the variance in the instrumental record and extended the record to 1378 (632 years). Retained tree-ring chronologies included those that were stable and positively correlated at 99% confidence levels or higher with the regional snowpack data for a 60–year overlapping period of record from 1940 to 1999. Stepwise Linear Regression was performed for the overlapping (calibration) period to develop regression models for the reconstructions. Eleven stations were individually reconstructed of which three stations (Dry Lake, Old Battle, and Lake Irene) explained variances greater than 40%. A contour plot of the R2 values for all 11 stations revealed that the more statistically skillful reconstructions were for stations spatially adjacent to the tree-ring chronologies used in the regression models. When the two individual stations with the lowest explained variance were removed from the 11 station snowpack regionalization, the new nine station regionalization reconstruction explained 45% of the variance over the same 632 year period.

Thesis (Ph. D.)--University of Washington, 2006. / Vita. Includes bibliographical references (leaves 113-121).

In order to improve our knowledge on the current state and variability of the Greenland ice sheet surface mass balance (SMB), a 27-year simulation (1979-2005) has been performed with the coupled atmosphere-snow regional model MAR. This simulation reveals an increase in the main factors of the SMB which are, on the one hand, the snowfall (+ 1.6 ± 1.8 km3 yr-1) in winter and on the other hand, the run-off (+ 4.2 ± 1.9 km3 yr-1) in summer. The net effect of these two competing factors leads to a SMB loss rate of – 2.7 ± 3.0 km3 yr-1, which has a significance of 87%. The melt extent derived from the passive microwave satellite data since 1979 also shows this trend. The melt water supply has increased because the Greenland ice sheet has been warming up by + 0.09 ± 0.04 °C yr-1 since 1979. This warming comes from a uniform increase of downward infra-red radiation which can not be explained by the natural variability. These changes result very likely from the global warming induced by human activities. As a result, it seems that: i) increased melting dominates over increased accumulation in a warming scenario, ii) the Greenland ice sheet has been significantly losing mass since the beginning of the 1980's by an increasing melt water run-off as well as by a probable increase of iceberg discharge into the ocean due to the "Zwally effect" (the melt water-induced ice sheet flow acceleration) and iii) the Greenland ice sheet is projected to continue to lose mass in the future. The Greenland ice sheet melting could have an effect on the stability of the thermohaline circulation (THC) and the global sea level rise. On the one hand, increases in the freshwater flux from the Greenland ice sheet (glacier discharge and run-off) could perturb the THC by reducing the density contrast driving it. On the other hand, the melting of the whole Greenland ice sheet would account for a global mean sea level rise of 7.4 m.

Complete protection against flood risks by structural measures is impossible. Therefore flood prediction is important for flood risk management. Good explanatory power of flood models requires a meaningful representation of bio-physical processes. Therefore great interest exists to improve the process representation. Progress in hydrological process understanding is achieved through a learning cycle including critical assessment of an existing model for a given catchment as a first step. The assessment will highlight deficiencies of the model, from which useful additional data requirements are derived, giving a guideline for new measurements. These new measurements may in turn lead to improved process concepts. The improved process concepts are finally summarized in an updated hydrological model. In this thesis I demonstrate such a learning cycle, focusing on the advancement of model evaluation methods and more cost effective measurements. For a successful model evaluation, I propose that three questions should be answered: 1) when is a model reproducing observations in a satisfactory way? 2) If model results deviate, of what nature is the difference? And 3) what are most likely the relevant model components affecting these differences? To answer the first two questions, I developed a new method to assess the temporal dynamics of model performance (or TIGER - TIme series of Grouped Errors). This method is powerful in highlighting recurrent patterns of insufficient model behaviour for long simulation periods. I answered the third question with the analysis of the temporal dynamics of parameter sensitivity (TEDPAS). For calculating TEDPAS, an efficient method for sensitivity analysis is necessary. I used such an efficient method called Fourier Amplitude Sensitivity Test, which has a smart sampling scheme. Combining the two methods TIGER and TEDPAS provided a powerful tool for model assessment. With WaSiM-ETH applied to the Weisseritz catchment as a case study, I found insufficient process descriptions for the snow dynamics and for the recession during dry periods in late summer and fall. Focusing on snow dynamics, reasons for poor model performance can either be a poor representation of snow processes in the model, or poor data on snow cover, or both. To obtain an improved data set on snow cover, time series of snow height and temperatures were collected with a cost efficient method based on temperature measurements on multiple levels at each location. An algorithm was developed to simultaneously estimate snow height and cold content from these measurements. Both, snow height and cold content are relevant quantities for spring flood forecasting. Spatial variability was observed at the local and the catchment scale with an adjusted sampling design. At the local scale, samples were collected on two perpendicular transects of 60 m length and analysed with geostatistical methods. The range determined from fitted theoretical variograms was within the range of the sampling design for 80% of the plots. No patterns were found, that would explain the random variability and spatial correlation at the local scale. At the watershed scale, locations of the extensive field campaign were selected according to a stratified sample design to capture the combined effects of elevation, aspect and land use. The snow height is mainly affected by the plot elevation. The expected influence of aspect and land use was not observed. To better understand the deficiencies of the snow module in WaSiM-ETH, the same approach, a simple degree day model was checked for its capability to reproduce the data. The degree day model was capable to explain the temporal variability for plots with a continuous snow pack over the entire snow season, if parameters were estimated for single plots. However, processes described in the simple model are not sufficient to represent multiple accumulation-melt-cycles, as observed for the lower catchment. Thus, the combined spatio-temporal variability at the watershed scale is not captured by the model. Further tests on improved concepts for the representation of snow dynamics at the Weißeritz are required. From the data I suggest to include at least rain on snow and redistribution by wind as additional processes to better describe spatio-temporal variability. Alternatively an energy balance snow model could be tested. Overall, the proposed learning cycle is a useful framework for targeted model improvement. The advanced model diagnostics is valuable to identify model deficiencies and to guide field measurements. The additional data collected throughout this work helps to get a deepened understanding of the processes in the Weisseritz catchment. / Modelle zur Hochwasservorhersage und –warnung basieren auf einer bio-physikalisch Repräsentation der relevanten hydrologischen Prozesse. Eine Verbesserungen der Beschreibung dieser Prozesse kann zuverlässigere Vorhersagen ermöglichen. Dazu wird die Benutzung eines Lernzykluses bestehend aus einer kritische Beurteilung eines existierenden Modells, der Erhebung zusätzlicher Daten, der Bildung eines vertieften Verständnis und einer Überarbeitung des Modells vorgeschlagen. In dieser Arbeit wird ein solcher Lernzyklus aufgegriffen, wobei der Schwerpunkt auf einer verbesserten Modellanalyse und kosteneffizientere Messungen liegt. Für eine erfolgreiche Modellbeurteilung sind drei Fragen zu beantworten: 1) Wann reproduziert ein Modell die beobachteten Werte in einer zufriedenstellenden Weise (nicht)? 2) Wie lassen sich die Abweichungen charakterisieren? und 3) welches sind die Modellkomponenten, die diese Abweichungen bedingen? Um die ersten beiden Fragen zu beantworten, wird eine neue Methode zur Beurteilung des zeitlichen Verlaufs der Modellgüte vorgestellt. Eine wichtige Stärke ist, dass wiederholende Muster ungenügender Modellgüte auch für lange Simulationsläufe einfach identifiziert werden können. Die dritte Frage wird durch die Analyse des zeitlichen Verlaufs der Parametersensitivität beantwortet. Eine Kombination der beiden Methoden zur Beantwortung aller drei Fragen stellt ein umfangreiches Werkzeug für die Analyse hydrologischer Modelle zur Verfügung. Als Fallstudie wurde WaSiM-ETH verwendet, um das Einzugsgebiet der wilden Weißeritz zu modellieren. Die Modellanalyse von WaSiM-ETH hat ergeben, dass die Schneedynamik und die Rezession während trockener Perioden im Spätsommer und Herbst, für eine Beschreibung der Prozesse an der Weißeritz nicht geeignet sind. Die Erhebung zusätzlicher Daten zum besseren Verständnis der Schneedynamik bildet den nächste Schritt im Lernzyklus. Daten über Schneetemperaturen und Schneehöhen wurden mit Hilfe eines neuen, preisgünstigen Verfahrens erhoben. Dazu wurde die Temperatur an jedem Standort mit unterschiedlichen Abständen zum Boden gemessen und mit einem neuen Algorithmus in Schneehöhe und Kältegehalt umgerechnet. Die Schneehöhe und Kältegehalt sind wichtige Größen für die Vorhersage von Frühjahrshochwassern. Die räumliche Variabilität der Schneedecke auf der Einzugsgebietsskala wurde entsprechend der Landnutzung, der Höhenzone und der Ausrichtung stratifiziert untersucht, wobei lediglich der Einfluss der Höhe nachgewiesen werden konnte, während Ausrichtung und Landnutzung keinen statistisch signifikanten Einfluss hatten. Um die Defizite des WaSiM-ETH Schneemodules für die Beschreibung der Prozesse im Weißeritzeinzugsgebiets besser zu verstehen, wurde der gleiche konzeptionelle Ansatz als eigenständiges, kleines Modell benutzt, um die Dynamik in den Schneedaten zu reproduzieren. Während dieses Grad-Tag-Modell in der Lage war, den zeitlichen Verlauf für Flächen mit einer kontinuierlichen Schneedecke zu reproduzieren, konnte die Dynamik für Flächen mit mehreren Akkumulations- und Schmelzzyklen im unteren Einzugsgebiet vom Modell nicht abgebildet werden. Vorschläge zur Verbesserung des Modells werden in der Arbeit gemacht. Zusammenfassend hat sich das Lernzyklus-Konzept als nützlich erwiesen, um gezielt an einer Modellverbesserung zu arbeiten. Die differenzierte Modelldiagnose ist wertvoll, um Defizite im Modellkonzept zu identifizieren. Die während dieser Studie erhobenen Daten sind geeignet, um ein verbessertes Verständnis der Schnee-Prozesse an der Weißeritz zu erlangen.

Highly fluorinated organic compounds are emerging environmental contaminants of concern, due to their persistence, ubiquitous distribution, bioaccumulation potential and toxicity. Ski waxes are sources of highly fluorinated chemicals to the environment that have not been investigated so far. Some contain fluorinated additives such as semifluorinated n-alkanes (SFAs). This thesis investigated the fate of SFAs after abrasion onto snow through skiing activities. Furthermore, perfluorinated alkyl acids (PFAAs) were found to be present in fluorinated ski waxes. A lot of attention has been paid to elucidating the environmental fate of PFAAs during the past decade. However, nothing was known so far about their release from melting snow packs. Analytical methods for quantification of SFAs in different environmental matrices were developed. The methods were used to investigate the fate of SFAs during snow melt and to study their occurrence in ski areas. Laboratory snow melt experiments and model-based fate simulations suggested that SFAs will sorb to the snow grain surface and particles in the bulk snow and, after snowmelt, will end up on the underlying (soil) surface. SFAs were detected and quantified for the first time in snow and soil samples taken from a ski area in Sweden. Comparison of concentrations in snow and soil did not give any evidence for long-term accumulation of SFAs in surface soil, but suggested volatilization of shorter chain homologues during snow melt. Such a volatilization could also explain an observed SFA pattern difference between snow and soil samples. Laboratory scale snow melt experiments were also used to investigate the behavior of PFAAs during snowmelt. PFAAs were released with the melt water from the snow pack in pulses. The pulses occurred early, late or with a so far unknown peak elution in the middle of the snowmelt, depending on the hydrophobicity of the PFAAs. These peak releases were further influenced by the age of the snow pack and thus the snow surface area and to a lesser extent by pH and ion concentrations.

In many parts of the world snow melt runoff influence discharge from combined sewer overflows (CSO) and flooding in urban drainage systems. Despite this, urban snow hydrology is a field that has received little attention from the urban drainage community. The objectives of this research were to better understand urban snow hydrology and through field work and hydrological modelling quantify effects of anthropogenic activities (AA) on snow distribution, and melt in an urban environment. This means in principle how the presence (design geometry) and operation of roads and buildings influence the snow distribution and melt in urban areas. The Risvollan urban catchment (20 ha) located in Trondheim, Norway, was used as a study area. A literature review of urban snow hydrology was also carried out. A gridded urban hydrology model (GUHM) was developed as part of the study. The principal idea of the GUHM is to subdivide an urban catchment into orthogonal equal area grid cells. The snow routine in the GUHM is based on an energy balance approach, which together with a soil-runoff routine is used to calculate a time series of rain, snow water equivalent (SWE), snow melt, and runoff, for each grid cell. In GUHM, processes such as snow clearing of roads, locally low albedos, heat/shadowing from buildings, and effects of slope and aspect are included in the model structure. A technique for observing time series of snow covered area (SCA) for an urban catchment is presented. The method is based on image processing and neural network technology to calculate SCA from a time series of images taken from a tall building in the Risvollan catchment. It was shown that SCA on roads and roofs in general becomes more rapidly snow free during melt periods compared to the park areas of the Risvollan catchment. This can be explained by snow clearing of roads, snowdrift from roofs and high snow melt rates on roofs and roads. The high melt rates was attributed to locally low albedos in vicinity to roads, rooftop snow packs exposure to wind and solar radiation, in addition to anthropogenic heat release from the roofs themselves. Field observations of SWE were carried out in the Risvollan catchment and it was shown that areal mean SWE located on/or nearby roads and buildings were significantly lower during mid and end of the winter, than in park areas. This can be attributed to higher melt rates caused by AA. A time series of SCA and SWE was obtained through field work for the period from 2000 to 2003 in the Risvollan catchment. The GUHM was applied and calibrated for the Risvollan catchment for a three year period. Two seasons were used as validation period. Comparison between the simulated and observed SWE, SCA and runoff data showed that the GUHM was able to simulate snow accumulation and melt for whole seasons with short time resolution (1 hour) satisfactory. The GUHM was used to quantify effects of AA on snow distribution and melt for six different land use scenarios in the Risvollan catchment for the period June 1998 to June 2003. The modelling results showed that when the area coverage of buildings and roads increased, the SCA and SWE more rapidly decreased during melt periods. Because of this more runoff will be produced in the early winter season (Jan-March) compared to if the catchment had been covered with only sparsely vegetated areas. The simulation results showed that when the impervious surface covers of a catchment increase, the peak and volume runoff will also increase, as expected. Both the field observations and the hydrological model study carried out in this work showed that AA lowers SCA and SWE more rapidly in an urban environment compared to more untouched terrain. The reasons for this are redistribution of snow, and strong snow melt rates on roads, roofs, and in snow deposit areas. Low albedos and anthropogenic heat release are the main reasons for the enhanced snow melt rates.

Referat Klimatologisk studie av cyklonbanor över Europa med koppling till snöförhållanden i norra Sverige Jakob Inghammar Under de senaste decennierna har temperaturen i atmosfären ökat. En sannolik effekt av detta är en förändring av förekomst och styrka för de utomtropiska cyklonerna. Deras uppträdande spelar en betydande roll för väder och klimat över de områden där de förekommer, därför är det relevant att undersöka om samvariationer för dem existerar med till exempel snöförhållanden och temperaturer. För att utforska detta har lågtryck över norra Atlanten och Europa identifierats ur återanalysdata (ERA-40) under månaderna oktober-mars för åren 1960-1999. Denna studie visar på en signifikant ökning av lågtrycksförekomst norr om 60°N och ett signifikant avtagande söder om 60°N. För lågtryckens styrka påvisas en signifikant positiv trend för båda dessa områden. Vid en analys för var och en av månaderna oktober-mars visas att det är under framförallt månaderna januari och februari som lågtrycken med tiden förflyttats norrut och att ingen sådan trend finns för oktober och november. Mellan årens högsta uppmätta snödjup i norra Sverige och lågtrycksfrekvensen kring norra Skandinavien finns en positiv korrelation. För medeltemperaturen på norra halvklotet och över vilka breddgrader cykloner mestadels rör sig under december-mars finns en samvariation, vid varmare förhållanden förflyttas cyklonbanorna norrut. En positiv korrelation finns mellan antal lågtryck norr om 60°N och temperaturen i Abisko. För vintrar, som i Abisko hade vitt skilda snöförhållanden, märks en avvikelse för vilka månader som lågtrycksfrekvensen kring norra Skandinavien var hög. Då snötäcket innehöll många isiga lager var lågtrycksfrekvensen hög i början och i slutet av vintern medan den var låg för månaderna i mitten. Det omvända skedde då snötäcket istället var ovanligt poröst. En stark samvariation finns mellan den nordatlantiska oscillationen (NAO) och lågtrycksfrekvens i de olika delarna norr och söder om 60°N av det undersökta området. Vid höga NAO-index ökar frekvensen i det norra området medan det minskar i det södra. Vid låga NAO-index sker det omvända.   Nyckelord: cykloner, lågtryck, återanalysdata, ERA-40, snö, Abisko / Abstract Climatologic study of cyclone tracks over Europe and linkage to snow conditions in northern Sweden Jakob Inghammar In the last decades the temperature in the atmosphere has been increasing. One plausible effect of this is a change in frequency and intensity of the extratropical cyclones. The appearance of the extratropical cyclones is crucial for the weather conditions and climate at the latitudes where they exist. Hence it is relevant to examine if the frequency of them are related to snow conditions and temperatures. This has been investigated over the north part of the Atlantic Ocean and Europe through detection of local minima in reanalysis data (ERA 40) regarding the sea level pressure for the months October-Mars for the years 1960-1999. The result for cyclone frequency display a significant increase in the region north of 60°N and at the same time a significant decrease in the region south of 60°N. In both regions there is a significant increase for the cyclone intensity. This trend with shifting cyclone tracks to the north is most pronounced for the months January and February while no trend can be seen for the months October and November. The maximum snow depth in the northern part of Sweden every year and the frequency of cyclones around northern Scandinavia are positively correlated. The mean temperature of the northern hemisphere and at which latitudes the cyclone tracks mostly exist during December-Mars co-varies. For the same months a positive correlation exists for the number of cyclones in the region north of 60°N and the mean temperature in Abisko. Different winters in Abisko with very diverse snow conditions also experienced diverseness concerning cyclone frequency around northern Scandinavia. During the winters when the snow cover was holding many icy layers; the frequency was high in the beginning and in the end of the winter seasons while the cyclone frequency was low in the middle. When the snow cover instead was very porous, the cyclone frequency occurs in the opposite way. A strong covariance exists between the North Atlantic Oscillation (NAO) and the number of cyclones in each region north and south of 60°N of the examined area. When the NAO-index is positive the frequency of cyclones is elevated in the north region and at the same time reduced in the south region, when the NAO-index is negative the opposite occur. Keywords: cyclones, reanalysis data, ERA-40, snow, Abisko

The water and heat exchange in thesoil-snow-vegetation-atmosphere system was studied in order toimprove the quantitative knowledge of land surface processes.In this study, numerical simulation models and availabledatasets representing arable land, sub-alpine snowpack, andboreal forest were evaluated at both diurnal and seasonaltimescales. Surface heat fluxes, snow depth, soil temperatures andmeteorological conditions were measured at an agriculturalfield in central Sweden during three winters and two summersfrom 1997 to 2000 within the WINTEX project. A one-dimensionalsimulation model (COUP) was used to simulate the water and heatbalance of the field. Comparison of simulated and measured heatfluxes in winter showed that parameter values governing theupper boundary condition were more important for explainingmeasured fluxes than the formulation of the internal mass andheat balance of the snow cover. The assumption of steady stateheat exchange between the surface and the reference height wasinadequate during stable atmospheric conditions. Independentestimates of the soil heat and water balance together with thecomparison of simulated and measured surface heat fluxes showedthat the eddy-correlation estimates of latent heat fluxes fromthe arable field were on average 40 % too low. The ability of a multi-layered snowpack model (SNTHERM) tosimulate the layered nature of a sub-alpine snowpack wasevaluated based on a dataset from Switzerland. The modelsimulated the seasonal development of snow depth and densitywith high accuracy. However, the models ability to reproducethe strong observed snowpack layering was limited by theneglection of the effect of snow microstructure on snowsettling, and a poor representation of water redistributionwithin the snowpack. The representation of boreal forest in the land surfacescheme used within a weather forecast (ECMWF) model was testedwith a three-year dataset from the NOPEX forest site in centralSweden. The new formulation with separate energy balances forvegetation and the soil/snow beneath the tree cover improvedthe simulation of seasonal and diurnal variations in latent andsensible heat flux. Further improvements of simulated latentheat fluxes were obtained when seasonal variation in vegetationproperties was introduced. Application of the COUP model withthe same dataset showed that simulation of evaporation fromintercepted snow contributed to a better agreement with themeasured sensible heat flux above forests, but also indicatedthat the measurements might have underestimated latent heatflux. The winter sensible heat flux above the forest wasfurther improved if an upper limit of the aerodynamicresistance of 500 s m-1 was applied for stable conditions. A comparison of the water and heat balance of arable landand forest confirmed the general knowledge of the differencesbetween these two surface types. The forest contributed withconsiderably more sensible heat flux to the atmosphere than thearable land in spring and summer due to the lower albedo andrelatively less latent heat flux. Latent heat flux from theforest was higher in winter due to the evaporation ofintercepted snow and rain. The net radiation absorbed by theforest was 60 % higher than that absorbed by the arable land,due to the lower surface albedo in winter. Key words:soil; snow; land surface heat exchange;forest; arable land; eddy-correlation. / QC 20100614

In this study I assessed the effect of objects and odors as environmental enrichment for two captive snow leopards (Uncia uncia) at Kolmården Wildlife Park. Five odors (lavender, lemon balm, cumin, cinnamon and catnip) were used to impregnate four different types of enrichment objects (boomer balls®, tennis balls, ropes, logs). During test sessions, one odorized and one non-odorized enrichment object of the same type were introduced in the snow leopards’ outdoor enclosure. The behavior, activity and location of the snow leopards were recorded and compared to their behavior during baseline sessions. During the test sessions I recorded the number and types of interactions with the enrichment objects. Both snow leopards interacted more often with odorized than with non-odorized enrichment objects. The number of interactions differed markedly between the types of enrichment objects and between the different odors. Both snow leopards interacted most often with boomer balls® and least often with logs. They interacted most often with cinnamon and least often with lemon balm (Brahma) and catnip (Binu). The results suggest that both the type of object and the odor play a role in capturing the interest of the snow leopards. The snow leopards behavioral diversity increased during the study and they could increase their performance of species-specific behavior. I did not see any indications of habituation during the testing period. The results indicate that enrichment objects impregnated with odors can be an effective environmental enrichment for captive snow leopards.