Alpine Turbulence and Blowing Snow

Blowing snow in mountainous terrain is a complex nonlinear phenomenon driven by turbulent eddies with length scales ranging from millimetres to kilometres. Turbulent motions across a wide spectrum of sizes are superimposed on each other, interacting through a non-stationary energy and momentum cascade. In cold regions, snow redistribution by these turbulent motions impacts hydrology, glaciology, avalanche safety, and civil engineering. Blowing snow models typically rely on relating time-averaged turbulence statistics, which may oversimplify the complexity of the flow, especially in complex mountainous terrain, to steady-state snow transport. The present research sought to improve the understanding of the dominant structures in ASL turbulence relevant to snow transport, as well as characterize the short timescale response of blowing snow to specific eddy structures. A fundamental experiment was designed utilizing high-speed videography of laser illuminated near-surface blowing snow saltation coupled with adjacent 3D sonic anemometer wind measurements at two heights. The experiments were conducted at Fortress Mountain Snow Laboratory in the Canadian Rockies of Alberta during nighttime blowing snow storms. Novel applications of particle tracking velocimetry and binarization algorithms to blowing snow recordings allowed extraction of time resolved snow particle velocities synchronized with instantaneous wind velocities, as well as time series of volumetric averages of blowing snow density in the first 30 mm above the surface. High-speed blowing snow video and measurements revealed the importance of the often- overlooked creep mode of transport to both transport initiation and flux. Blowing snow velocity and flux profiles were found to be temporally variable and dependent on instantaneous wind speed, with dominant modes of transport varying during turbulent gusts. Sweep and ejection wind events were coupled to blowing snow responses on sub-second timescales, with each quadrant event playing a unique role in transport initiation and sustaining snow fluxes. Finally, large low-frequency turbulent motions, hypothesized to follow a top-down characterization, were found to modulate the amplitude of near-surface turbulence, as well as directly contribute to blowing snow fluxes. The role of intermittent coherent turbulent structures challenges the ability of time-averaged turbulence statistics to represent the complexity of wind-snow coupling, especially in mountainous terrain. The strong relationship found between large-scale turbulence modulating eddies and near-surface turbulence, also challenges the efficacy of applying steady- state laboratory-derived flux relationships to model transport in the ASL. The results presented here, along with recent advances on coherent turbulent structures provide an optimistic semi- deterministic avenue for improving blowing snow models in complex mountainous terrain

Explicitly modelling microtopography in permafrost landscapes in a land surface model (JULES vn5.4_microtopography)

Microtopography can be a key driver of heterogeneity in the ground thermal and hydrological regime of permafrost landscapes. In turn, this heterogeneity can influence plant communities, methane fluxes, and the initiation of abrupt thaw processes. Here we have implemented a two-tile representation of microtopography in JULES (the Joint UK Land Environment Simulator), where tiles are representative of repeating patterns of elevation difference. Tiles are coupled by lateral flows of water, heat, and redistribution of snow, and a surface water store is added to represent ponding. Simulations are performed of two Siberian polygon sites, (Samoylov and Kytalyk) and two Scandinavian palsa sites (Stordalen and Iškoras). The model represents the observed differences between greater snow depth in hollows vs. raised areas well. The model also improves soil moisture for hollows vs. the non-tiled configuration (“standard JULES”) though the raised tile remains drier than observed. The modelled differences in snow depths and soil moisture between tiles result in the lower tile soil temperatures being warmer for palsa sites, as in reality. However, when comparing the soil temperatures for July at 20 cm depth, the difference in temperature between tiles, or “temperature splitting”, is smaller than observed (3.2 vs. 5.5 ∘C). Polygons display small (0.2 ∘C) to zero temperature splitting, in agreement with observations. Consequently, methane fluxes are near identical (+0 % to 9 %) to those for standard JULES for polygons, although they can be greater than standard JULES for palsa sites (+10 % to 49 %). Through a sensitivity analysis we quantify the relative importance of model processes with respect to soil moisture and temperatures, identifying which parameters result in the greatest uncertainty in modelled temperature. Varying the palsa elevation between 0.5 and 3 m has little effect on modelled soil temperatures, showing that using only two tiles can still be a valid representation of sites with a range of palsa elevations. Mire saturation is heavily dependent on landscape-scale drainage. Lateral conductive fluxes, while small, reduce the temperature splitting by ∼ 1 ∘C and correspond to the order of observed lateral degradation rates in peat plateau regions, indicating possible application in an area-based thaw model

Trajectories of land surface evolution in polygonal tundra

In the past three decades, an abrupt acceleration in the thaw of ice wedges has spurred rapid surface deformation (i.e., thermokarst) in polygonal tundra landscapes spanning the Arctic. The ensuing conversion of low-centered polygons (LCPs) and flat terrain into high-centered polygons (HCPs) has profound impacts on regional hydrology and carbon fluxes between the soil and atmosphere. However, pathways of ice wedge degradation and the stability of the deformed terrain are uncertain, complicating efforts to project feedbacks on global climate change. In this dissertation, I explore trajectories of surface deformation in ice wedge polygons, using a combination of calibration-constrained numerical experiments, remote sensing, and machine learning. In the first two chapters, numerical simulations of the soil hydrologic and thermal regimes reveal that, relative to terrain unaffected by thermokarst, the permafrost beneath HCPs tends to be well-buffered against climate extremes, promoting landscape stability. Ice wedges at HCP boundaries are less vulnerable to thaw during warm summers, reinforcing prior field-based observations that thermokarst is typically a self-arresting process. Simultaneously, the cooling of thermokarst-affected ice wedges in winter tends to be inhibited by snow accumulation in degraded troughs, reducing the likelihood of renewed ice wedge cracking and restoration of LCP microtopography. Overall, these results indicate that the microtopography of polygons already affected by thermokarst will likely remain stable over the next century. In the second half of this dissertation, a novel machine-learning-based tool is introduced for delineating and measuring the microtopography associated with ice wedge polygons in high-resolution digital elevation models. The tool is used to map polygonal geomorphology across ~1,000 km² of tundra south of Prudhoe Bay, Alaska, visualizing in unprecedented detail the heterogeneous extent to which thermokarst has affected a modern polygonal landscape. This map of polygonal geomorphology provides useful context for upscaling point- to plot-scale observations of gas exchange in ice wedge polygons to landscape-scale estimates of carbon fluxes. It also provides an extensive baseline dataset for quantifying contemporary rates of land surface deformation, through future surveys at the site.Geological Science

Optimisation of flow resistance and turbulent mixing over bed forms

Previous work on the interplay between turbulent mixing and flow resistance for flows over periodic rib roughness elements is extended to consider the flow over idealized shapes representative of naturally occurring sedimentary bed forms. The primary motivation is to understand how bed form roughness affects the carrying capacity of sediment-bearing flows in environmental fluid dynamics applications, and in engineering applications involving the transport of particulate matter in pipelines. For all bed form shapes considered, it is found that flow resistance and turbulent mixing are strongly correlated, with maximum resistance coinciding with maximum mixing, as was previously found for the special case of rectangular roughness elements. Furthermore, it is found that the relation between flow resistance to eddy viscosity collapses to a single monotonically increasing linear function for all bed form shapes considered, indicating that the mixing characteristics of the flows are independent of the detailed morphology of individual roughness elements

The application of terrestrial laser scanning to measure small scale changes in aeolian bedforms

Traditional methods used to measure aeolian sediment transport rely on point based sampling, such as sand traps or saltation impact sensors, which ignore the spatial heterogeneity displayed in the transport system. Obtaining an accurate transport rate is important to parameterise predictive models, which currently show large deviations between measured and predicted rates.Terrestrial laser scanning (TLS) is a tool that is rapidly emerging in the field of geomorphology. It provides the ability to capture surface elevation data of in-situ bedforms at the spatial and temporal scale necessary to link change, such as ripple migration, to the processes that drive them. Repeat scans provide digital elevation models which can be differenced to provide volumetric rates of change, in a process known as the morphologic method. However, utilising data at such high resolutions requires an accurate estimation of error in order to provide meaningful results.Typically the morphologic method documents surface change between geomorphic events. However, due to the high temporal variability displayed by the aeolian transport system, measuring topographic change during a transport event would be beneficial. Using TLS during active transport removes the ability to take multiple convergent scans. Therefore current methods of approximating error in TLS derived surfaces by using convergent scans from multiple scan locations cannot be applied.The influence of scanning geometry and survey set up is explored in order to quantify and reduce errors when scanning small scale bedforms from a single location. This is then applied to an active transport event to measure wind ripple migration, and derive a sediment transport rate using the morphologic method. The results suggest TLS is a viable tool for capturing in-situ aeolian ripples. Scan incidence angle is shown to significantly affect point density and therefore point cloud accuracy. The influence of incidence angle is different depending on the extent of the bedform studied. Ripples were measured during an active transport event in the Great Sand Dunes National Park, Colorado. Ripple morphologies and migration rates were within previously observed ranges. Applying the morphologic method highlighted ripple migration patterns, surface change and enabled an overall sediment budget to be calculated

Development of a spatially distributed model of Arctic thermal and hydrologic processes (MATH)

Thesis (Ph.D.) University of Alaska Fairbanks, 1998A process based, spatially distributed hydrologic model with the acronym MATH (Model of Arctic Thermal and Hydrologic Processes) is constructed to quantitatively simulate the energy and mass transfer processes and their interactions within arctic regions. The impetus for development of this model was the need to have spatially distributed soil moisture data for use in models of trace gas fluxes (carbon dioxide and methane) generated from the carbon-rich soils of this region. The model is applied against the data from the Imnavait watershed (2.2 \rm km\sp2) and the Upper Kuparuk River basin (146 \rm km\sp2) located on the North Slope of Alaska. Both point and spatially distributed data such as precipitation, radiation, air temperature, and other meteorological data have been used as model inputs. Based on the digital elevation data, one component of the model determines drainage area, channel networks, and the flow directions in a watershed that is divided into many triangular elements. Simulated physical processes include hydraulic routing of subsurface flow, overland flow and channel flow, evapotranspiration (ET), snow ablation, and active layer thawing and freezing. This hydrologic model simulates the dynamic interactions of each of these processes and can predict spatially distributed snowmelt, soil moisture, and ET over a watershed at each time step as well as discharge at any point(s) of interest along a channel. Modeled results of spatially distributed soil moisture content, discharge at gauging stations and other results yield very good agreement, both spatially and temporally, with independently derived data sets, such as Synthetic Aperture Radar (SAR) generated soil moisture data, field measurements of snow ablation, measured discharge data and water balance computations. The timing of simulated discharge results do not compare well to the measured data during snowmelt periods because the effect of snow damming on runoff generation is not considered in the model. It is concluded that this model can be used to simulate spatially distributed hydrologic processes within the arctic regions provided that suitable data sets for input are available. This physically based model also has the potential to be coupled with atmospheric and biochemical models

Spatial variability of aircraft-measured surface energy fluxes in permafrost landscapes

Arctic ecosystems are undergoing a very rapid change due to global warming and their response to climate change has important implications for the global energy budget. Therefore, it is crucial to understand how energy fluxes in the Arctic will respond to any changes in climate related parameters. However, attribution of these responses is challenging because measured fluxes are the sum of multiple processes that respond differently to environmental factors. Here, we present the potential of environmental response functions for quantitatively linking energy flux observations over high latitude permafrost wetlands to environmental drivers in the flux footprints. We used the research aircraft POLAR 5 equipped with a turbulence probe and fast temperature and humidity sensors to measure turbulent energy fluxes along flight tracks across the Alaskan North Slope with the aim to extrapolate the airborne eddy covariance flux measurements from their specific footprint to the entire North Slope. After thorough data pre-processing, wavelet transforms are used to improve spatial discretization of flux observations in order to relate them to biophysically relevant surface properties in the flux footprint. Boosted regression trees are then employed to extract and quantify the functional relationships between the energy fluxes and environmental drivers. Finally, the resulting environmental response functions are used to extrapolate the sensible heat and water vapor exchange over spatio-temporally explicit grids of the Alaskan North Slope. Additionally, simulations from the Weather Research and Forecasting (WRF) model were used to explore the dynamics of the atmospheric boundary layer and to examine results of our extrapolation

A gravel-sand bifurcation:a simple model and the stability of the equilibrium states

A river bifurcation, can be found in, for instance, a river delta, in braided or anabranching reaches, and in manmade side channels in restored river reaches. Depending on the partitioning of water and sediment over the bifurcating branches, the bifurcation develops toward (a) a stable state with two downstream branches or (b) a state in which the water discharge in one of the branches continues to increase at the expense of the other branch (Wang et al., 1995). This may lead to excessive deposition in the latter branch that eventually silts up. For navigation, flood safety, and river restoration purposes, it is important to assess and develop tools to predict such long-term behavior of the bifurcation. A first and highly schematized one-dimensional model describing (the development towards) the equilibrium states of two bifurcating branches was developed by Wang et al (1995). The use of a one-dimensional model implies the need for a nodal point relation that describes the partitioning of sediment over the bifurcating branches. Wang et al (1995) introduce a nodal point relation as a function of the partitioning of the water discharge. They simplify their nodal point relation to the following form: s*=q*k , where s* denotes the ratio of the sediment discharges per unit width in the bifurcating branches, q* denotes the ratio of the water discharges per unit width in the bifurcating branches, and k is a constant. The Wang et al. (1995) model is limited to conditions with unisize sediment and application of the Engelund & Hansen (1967) sediment transport relation. They assume the same constant base level for the two bifurcating branches, and constant water and sediment discharges in the upstream channel. A mathematical stability analysis is conducted to predict the stability of the equilibrium states. Depending on the exponent k they find a stable equilibrium state with two downstream branches or a stable state with one branch only (i.e. the other branch has silted up). Here we extend the Wang et al. (1995) model to conditions with gravel and sand and study the stability of the equilibrium states

Monitoring and modelling mire hydrology for conservation management

PhD ThesisThe functional hydrological components of the ombrotrophic mire water balance are, considered in terms of their ecological relevance. It is proposed that numerical models provide a suitable framework for mire hydro-systems and their potential as quantitative tools for mire restoration and conservation management is demonstrated. Existing models previously applied to mires are reviewed. The USGS 3-D groundwater model MODFLOW is selected and a new shallow surface and groundwater model GSHAW5 is developed for application to mires. Extensive ecohydrological case studies are undertaken at two mire sites and the models are tested using data collected at the sites. Field studies at Wedholme Flow, Cumbria, extended over four years and the data collected were combined with historical records to form a 10-year hydrological data set. Studies at Trough End Bog, Northumbria, extended over a 3-year period. Topographic, soil and vegetation surveys were carried out at both sites. Watertable fluctuation was recorded manually on a weekly basis and electronically at a 20-minute interval along with automatic meteorological records. New hydrometric techniques were developed in the Surface Water Monitoring Plot, SWaMP, constructed at Trough End to record hydrological exchanges within the hummock-hollow complex of the mire acrotelm. The models operate on very different spatial and temporal scales. GSHAW5 is applied to reproduce ground and surface exchanges in the acrotel. MODFLOW is used to simulate large-scale exchanges in undisturbed areas and between regenerating and active peat cutting areas. Predictive MODFLOW simulations are used to examine the impact of different peat cutting regimes on mire hydrology and potential regeneration. Both models produce simulations strongly correlated to observed hydrological exchanges. The usefulness of numerical models as tools for mire management is considered in light of the model test results from both case studies. It is concluded that both models provide insight and quantitative estimates of hydrological exchanges not possible by other means. MODFLOW simulations reveal considerable water loss from the Wedholme Flow mire reserve to an active peat cutting area. Simulations of Trough End bog reveal hydrological acrotelm processes strongly related to vegetation assemblages. An extensified GSHAW5 acrotelm model is recommended for the simulation of intact ombrotrophic mires.English Nature University of Newcastle Ridley Fellowship