Search

The Greenland Climate Network (GC-Net) consists of 31 automatic weather stations (AWS) at 30 sites across the Greenland ice sheet. The first site was initiated in 1990, and the project has operated almost continuously since 1995 under the leadership of the late Prof. Konrad Steffen. The GC-Net AWS measured air temperature, relative humidity, wind speed, atmospheric pressure, downward and reflected shortwave irradiance, net radiation, ice and firn temperatures. The majority of the GC-Net sites were located in the ice sheet accumulation area (17 AWS), while 11 AWS were located in the ablation area and two sites (three AWS) were located close to the equilibrium line altitude. Additionally, three AWS of similar design to the GC-Net AWS were installed by Prof. K. Steffen’s team on the Larsen C ice shelf, Antarctica. After more than three decades of operation, the GC-Net AWS are being decommissioned and replaced by new AWS operated by the Geological Survey of Denmark and Greenland (GEUS). Therefore, making a reassessment of the historical GC-Net AWS data is necessary. We present a full reprocessing of the historical GC-Net AWS dataset with increased attention to the filtering of erroneous measurements, data correction, and derivation of additional variables: continuous surface height, instrument heights, surface albedo, turbulent heat fluxes, 10 m ice and firn temperatures. This new augmented GC-Net Level 1 (L1) AWS dataset is now available at https://doi.org/10.22008/FK2/VVXGUT (Steffen et al. 2022) and will continue to be refined. The processing scripts, latest data and a data-user forum are available at https://github.com/GEUS-Glaciology-and-Climate/GC-Net-level-1-data-processing. In addition to the AWS data, a comprehensive compilation of valuable metadata is provided: maintenance reports, yearly pictures of the stations and the station positions through time. This unique dataset provides more than 320 station-years of high quality atmospheric data and is available following FAIR data and code practices.

Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994-2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm(-2)) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.An international team of researchers finds high potential for improving climate projections by a more comprehensive treatment of largely ignored Arctic vegetation types, underscoring the importance of Arctic energy exchange measuring stations.

Every year, numerous field teams travel to remote field locations on the Greenland ice sheet to carry out polar research, geologic exploration, and other commercial, military, strategic, and recreational activities. In this region, extreme weather can lead to decreased productivity, equipment failure, increased stress, unexpected logistical challenges, and, in the worst cases, a risk of physical injury and loss of life. Here we describe methods for calculating the probability of a “scienceable” day defined as a day when wind, temperature, snowfall, and sunlight conditions are conducive to sustained outdoor activity. Scienceable days have been calculated for six sites on the ice sheet of southern Greenland using meteorological station data between 1996-2016, and compared with indices of large scale atmospheric circulation patterns: the Greenland Blocking Index (GBI) and the North Atlantic Oscillation (NAO). Our findings show that the probability of a scienceable day between 2010 and 2016 in the Greenland Ice Sheet.'s accumulation zone was 46 ± 17% in March-May and 86 ± 11% in July-August on average. Decreases in scienceability due to lower temperatures at higher elevations are made up for by weaker katabatic winds, especially in the shoulder seasons. We also find a strong correlation between the probability of a scienceable day and GBI (R = 0.88, p < 0.001) resulting in a significant decrease in April scienceability since 1996. The methodology presented can help inform expedition planning, the setting of realistic field goals and managing expectations, and aid with accurate risk assessment in Greenland and other harsh, remote environments.

This poster was originally created for the swissuniversities Open Science Action Plan: Kick-Off Forum, and showed to the audience on 17.10.2019. It illustrates how the environmental data portal EnviDat provides the tools for fostering Open Science and Reproducibility of scientific research at WSL. Supporting open science is a highly relevant user requirement for EnviDat and for implementing FAIR (Findability, Accessibility, Interoperability and Reusability) principles at dataset level. EnviDat encourages WSL scientists to complement data publication with a complete description of research methods and the inclusion of the open source software, code or scripts used for processing the dataset or for obtaining the published results. By openly publishing open software (e.g. as Jupyter notebooks) alongside research data sets, researchers can contribute to mitigate reproducibility issues. EnviDat also promotes and supports, where possible and practical, the publication of software as Jupyter notebooks. Jupyter notebooks provide a solution for improved documentation and interactive execution of open code in a wide range of programming languages (Python, R, Octave/Matlab, Java or Scala). These programming languages are widely used in environmental research at WSL and well supported by the Jupyter-compatible kernels. We have sucessfully interfaced EnviDat-hosted notebooks with the WSL High-Performance Computing (HPC) Linux Cluster through a JupyterHub/JuypterLab beta installation on the HPC cluster implemented in close collaboration with the WSL IT-Services. For existing software that cannot be easily migrated to Jupyter Notebooks, the Open Science and Reproducibility is assisted by containerisation. We have proven that several Singularity containers can successfully run on WSL's HPC cluster. Finally, the researchers can upload the data/results complemented by code (e.g. as Jupyter Notebooks, or Singularity containers) and any additional documentation in EnviDat. Consequently, they will receive a DOI for the entire dataset, which they can reference in their science paper in order to publish a more reproducible research. _License_: This poster is released by WSL and the EnviDat team to the public domain under a Creative Commons 4.0 CC0 "No Rights Reserved" international license. You can reuse this poster in any way you want, for any purposes and without restrictions.

Glacier surface mass-balance measurements on Greenland started more than a century ago, but no compilation exists of the observations from the ablation area of the ice sheet and local glaciers. Such data could be used in the evaluation of modelled surface mass balance, or to document changes in glacier melt independently from model output. Here, we present a comprehensive database of Greenland glacier surface mass-balance observations from the ablation area of the ice sheet and local glaciers. The database spans the 123 a from 1892 to 2015, contains a total of ~3000 measurements from 46 sites, and is openly accessible through the PROMICE web portal (http://www.promice.dk). For each measurement we provideX, YandZcoordinates, starting and ending dates as well as quality flags. We give sources for each entry and for all metadata. Two thirds of the data were collected from grey literature and unpublished archive documents. Roughly 60% of the measurements were performed by the Geological Survey of Denmark and Greenland (GEUS, previously GGU). The data cover all regions of Greenland except for the southernmost part of the east coast, but also emphasize the importance of long-term time series of which there are only two exceeding 20 a. We use the data to analyse uncertainties in point measurements of surface mass balance, as well as to estimate surface mass-balance profiles for most regions of Greenland.

This work is funded by the Netherland Polar Programme, Netherlands Earth System Science Centre (NESSC), NSF OPP research grant 0732946, NERC/GEF grants NE/L006707/1, NE/L005409/1, NE/E012914/1, GEF loans 863, 890, 1028. The surface mass balance (SMB) of the Larsen C ice shelf (LCIS), Antarctica, is poorly constrained due to a dearth of in situ observations. Combining several geophysical techniques, we reconstruct spatial and temporal patterns of SMB over the LCIS. Continuous time series of snow height (2.5–6 years) at five locations allow for multi-year estimates of seasonal and annual SMB over the LCIS. There is high interannual variability in SMB as well as spatial variability: in the north, SMB is 0.40 ± 0.06 to 0.41 ± 0.04 m w.e. year−1, while farther south, SMB is up to 0.50 ± 0.05 m w.e. year−1. This difference between north and south is corroborated by winter snow accumulation derived from an airborne radar survey from 2009, which showed an average snow thickness of 0.34 m w.e. north of 66° S, and 0.40 m w.e. south of 68° S. Analysis of ground-penetrating radar from several field campaigns allows for a longer-term perspective of spatial variations in SMB: a particularly strong and coherent reflection horizon below 25–44 m of water-equivalent ice and firn is observed in radargrams collected across the shelf. We propose that this horizon was formed synchronously across the ice shelf. Combining snow height observations, ground and airborne radar, and SMB output from a regional climate model yields a gridded estimate of SMB over the LCIS. It confirms that SMB increases from north to south, overprinted by a gradient of increasing SMB to the west, modulated in the west by föhn-induced sublimation. Previous observations show a strong decrease in firn air content toward the west, which we attribute to spatial patterns of melt, refreezing, and densification rather than SMB. Publisher PDF

Ocean waters melt the margins of Antarctic and Greenland glaciers, and individual glaciers' responses and the integrity of their ice shelves are expected to depend on the spatial distribution of melt. The bases of the ice shelves associated with Pine Island Glacier (West Antarctica) and Petermann Glacier (Greenland) have similar geometries, including kilometer-wide, hundreds-of-meter high channels oriented along and across the direction of ice flow. The channels are enhanced by, and constrain, oceanic melt. New meter-scale observations of basal topography reveal peculiar glaciated landscapes. Channel flanks are not smooth, but are instead stepped, with hundreds-of-meters-wide flat terraces separated by 5-50m high walls. Melting is shown to be modulated by the geometry: constant across each terrace, changing from one terrace to the next, and greatly enhanced on the ∼45° inclined walls. Melting is therefore fundamentally heterogeneous and likely associated with stratification in the ice-ocean boundary layer, challenging current models of ice shelf-ocean interactions. Key Points Basal topography of melting ice shelves is complex Basal terraces appear ubiquitous under melting ice shelves Melting concentrates on walls between terraces © 2014. American Geophysical Union. All Rights Reserved.

Water stable isotopes in Greenland ice core data provide key paleoclimatic information, and have been compared with precipitation isotopic composition simulated by isotopically enabled atmospheric models. However, post-depositional processes linked with snow metamorphism remain poorly documented. For this purpose, monitoring of the isotopic composition (δ18O, δD) of near-surface water vapor, precipitation and samples of the top (0.5 cm) snow surface has been conducted during two summers (2011–2012) at NEEM, NW Greenland. The samples also include a subset of 17O-excess measurements over 4 days, and the measurements span the 2012 Greenland heat wave. Our observations are consistent with calculations assuming isotopic equilibrium between surface snow and water vapor. We observe a strong correlation between near-surface vapor δ18O and air temperature (0.85 ± 0.11‰ °C−1 (R = 0.76) for 2012). The correlation with air temperature is not observed in precipitation data or surface snow data. Deuterium excess (d-excess) is strongly anti-correlated with δ18O with a stronger slope for vapor than for precipitation and snow surface data. During nine 1–5-day periods between precipitation events, our data demonstrate parallel changes of δ18O and d-excess in surface snow and near-surface vapor. The changes in δ18O of the vapor are similar or larger than those of the snow δ18O. It is estimated using the CROCUS snow model that 6 to 20% of the surface snow mass is exchanged with the atmosphere. In our data, the sign of surface snow isotopic changes is not related to the sign or magnitude of sublimation or deposition. Comparisons with atmospheric models show that day-to-day variations in near-surface vapor isotopic composition are driven by synoptic variations and changes in air mass trajectories and distillation histories. We suggest that, in between precipitation events, changes in the surface snow isotopic composition are driven by these changes in near-surface vapor isotopic composition. This is consistent with an estimated 60% mass turnover of surface snow per day driven by snow recrystallization processes under NEEM summer surface snow temperature gradients. Our findings have implications for ice core data interpretation and model–data comparisons, and call for further process studies., Climate of the Past, 10 (1), ISSN:1814-9324, ISSN:1814-9332

For the first time in serveral years, the El Nino-Southern Oscillation did not dominate regional climate conditions around the globe. A weak La Ni a dissipated to ENSOneutral conditions by spring, and while El Nino appeared to be emerging during summer, this phase never fully developed as sea surface temperatures in the eastern conditions. Nevertheless, other large-scale climate patterns and extreme weather events impacted various regions during the year. A negative phase of the Arctic Oscillation from mid-January to early February contributed to frigid conditions in parts of northern Africa, eastern Europe, and western Asia. A lack of rain during the 2012 wet season led to the worst drought in at least the past three decades for northeastern Brazil. Central North America also experienced one of its most severe droughts on record. The Caribbean observed a very wet dry season and it was the Sahel's wettest rainy season in 50 years. Overall, the 2012 average temperature across global land and ocean surfaces ranked among the 10 warmest years on record. The global land surface temperature alone was also among the 10 warmest on record. In the upper atmosphere, the average stratospheric temperature was record or near-record cold, depending on the dataset. After a 30-year warming trend from 1970 to 1999 for global sea surface temperatures, the period 2000-12 had little further trend. This may be linked to the prevalence of La Ni a-like conditions during the 21st century. Heat content in the upper 700 m of the ocean remained near record high levels in 2012. Net increases from 2011 to 2012 were observed at 700-m to 2000-m depth and even in the abyssal ocean below. Following sharp decreases in to the effects of La Ni a, sea levels rebounded to reach records highs in 2012. The increased hydrological cycle seen in recent years continued, with more evaporation in drier locations and more precipitation in rainy areas. In a pattern that has held since 2004, salty areas of the ocean surfaces and subsurfaces were anomalously salty on average, while fresher areas were anomalously fresh. Global tropical cyclone activity during 2012 was near average, with a total of 84 storms compared with the 1981-2010 average of 89. Similar to 2010 and 2011, the North Atlantic was the only hurricane basin that experienced above-normal activity. In this basin, Sandy brought devastation to Cuba and parts of the eastern North American seaboard. All other basins experienced either near-or below-normal tropical cyclone activity. Only three tropical cyclones reached Category 5 intensity-all in Bopha became the only storm in the historical record to produce winds greater than 130 kt south of 7 N. It was also the costliest storm to affect the Philippines and killed more than 1000 residents. Minimum Arctic sea ice extent in September and Northern Hemisphere snow cover extent in June both reached new record lows. June snow cover extent is now declining at a faster rate (-17.6% per decade) than September sea ice extent (-13.0% per decade). Permafrost temperatures reached record high values in northernmost Alaska. A new melt extent record occurred on 11-12 July on the Greenland ice sheet; 97% of the ice sheet showed some form of melt, four times greater than the average melt for this time of year. The climate in Antarctica was relatively stable overall. The largest maximum sea ice extent since records begain in 1978 was observed in September 2012. In the stratosphere, warm air led to the second smallest ozone hole in the past two decades. Even so, the springtime ozone layer above Antarctica likely will not return to its early 1980s state until about 2060. Following a slight decline associated with the global 2 emissions from fossil fuel combustion and cement production reached a record 9.5 +/- 0.5 Pg C in 2011 and a new record of 9.7 +/- 0.5 Pg C is estimated for 2012. Atmospheric CO2 concentrations increased by 2.1 ppm in 2012, to 392.6 ppm. In spring 2012, 2 concentration exceeded 400 ppm at 7 of the 13 Arctic observation sites. Globally, other greenhouse gases including methane and nitrous oxide also continued to rise in concentration and the combined effect now represents a 32% increase in radiative forcing over a 1990 baseline. Concentrations of most ozone depleting substances continued to fall.

Correlation analysis of Greenland coastal weather station temperatures against the North Atlantic Oscillation (NAO) and the Atlantic Multidecadal Oscillation (AMO) indices for the summer season (when Ice Sheet melt and runoff occur) reveals significant temporal variations over the last 100 years, with periods of strongest correlations in the early twentieth century and during recent decades. During the mid-twentieth century, temperature changes at the stations are not significantly correlated with these circulation indices. Greenland coastal summer temperatures and Greenland Ice Sheet (GrIS) runoff since the 1970s are more strongly correlated with the Greenland Blocking Index (GBI) than with the NAO Index (NAOI), making the GBI a potentially useful predictor of ice-sheet mass balance changes. Our results show that the changing strength of NAOI-temperature relationships found in boreal winter also extends to summer over Greenland. Greenland temperatures and GrIS runoff over the last 30-40 years are significantly correlated with AMO variations, although they are more strongly correlated with GBI changes. GrIS melt extent is less significantly correlated with atmospheric and oceanic index changes than runoff, which we attribute to the latter being a more quantitative index of Ice Sheet response to climate change. Moreover, the four recent warm summers of 2007-2010 are characterised by unprecedented high pressure (since at least 1948 - the start of the NCEP/NCAR reanalysis record) in the tropospheric column. Our results suggest complex and changing atmospheric forcing conditions that are not well captured using the NAO alone, and support theories of an oceanic influence on the recent increases in Greenland temperatures and GrIS runoff.

Global warming due to human-made gases, mainly CO2, is already 0.8{\deg}C and deleterious climate impacts are growing worldwide. More warming is 'in the pipeline' because Earth is out of energy balance, with absorbed solar energy exceeding planetary heat radiation. Maintaining a climate that resembles the Holocene, the world of stable shorelines in which civilization developed, requires rapidly reducing fossil fuel CO2 emissions. Such a scenario is economically sensible and has multiple benefits for humanity and other species. Yet fossil fuel extraction is expanding, including highly carbon-intensive sources that can push the climate system beyond tipping points such that amplifying feedbacks drive further climate change that is practically out of humanity's control. This situation raises profound moral issues as young people, future generations, and nature, with no possibility of protecting their future well-being, will bear the principal consequences of actions and inactions of today's adults., Comment: 28 pages, 6 figures; version submitted to Proceedings of the National Academy of Sciences

We present a reconstruction of the Greenland Ice Sheet surface mass balance (SMB) from 1870 to 2010, based on merged Twentieth Century Reanalysis (20CR) and European Centre for Medium-Range Weather Forecasts (ECMWF) meteorological reanalyses, and we compare our new SMB series with global and regional climate and atmospheric circulation indices during this period. We demonstrate good agreement between SMB annual series constructed from 20CR and ECMWF reanalyses for the common period of overlap and show statistically significant agreement of long-term modeled snowfall with ice-core-based accumulation data. We analyze variations in SMB for the last 140 years and highlight the periods with significantly increased runoff and decreased SMB since 1870, which have both been enhanced in the period since 1990, as well as interannual variations in SMB linked to Greenland climate fluctuations. We show very good agreement of our SMB series variations with existing, independently derived SMB series (RACMO2) variations for the past few decades of overlap but also a significant disparity of up to ∼200 km3 yr-1 in absolute SMB values due to poorly constrained modeled accumulation reflecting a lack of adequate validation data in southeast Greenland. There is no significant correlation between our SMB time series and a widely referenced time series of North Atlantic icebergs emanating from Greenland for the past century, which may reflect the complex nature of the relationship between SMB and ice dynamical changes. Finally, we discuss how our analysis sheds light on the sensitivity and response of the Greenland Ice Sheet to ongoing and future global climate change, and its contribution to global sea level rise. Copyright 2011 by the American Geophysical Union.

We assess climate impacts of global warming using ongoing observations and paleoclimate data. We use Earth’s measured energy imbalance, paleoclimate data, and simple representations of the global carbon cycle and temperature to define emission reductions needed to stabilize climate and avoid potentially disastrous impacts on today’s young people, future generations, and nature. A cumulative industrial-era limit of ∼500 GtC fossil fuel emissions and 100 GtC storage in the biosphere and soil would keep climate close to the Holocene range to which humanity and other species are adapted. Cumulative emissions of ∼1000 GtC, sometimes associated with 2°C global warming, would spur “slow” feedbacks and eventual warming of 3–4°C with disastrous consequences. Rapid emissions reduction is required to restore Earth’s energy balance and avoid ocean heat uptake that would practically guarantee irreversible effects. Continuation of high fossil fuel emissions, given current knowledge of the consequences, would be an act of extraordinary witting intergenerational injustice. Responsible policymaking requires a rising price on carbon emissions that would preclude emissions from most remaining coal and unconventional fossil fuels and phase down emissions from conventional fossil fuels., PLoS ONE, 8 (12), ISSN:1932-6203

Here, we present an analysis of monthly, seasonal, and annual long-term precipitation time-series compiled from coastal meteorological stations in Greenland and Greenland Ice Sheet (GrIS) ice cores (including three new ice core records from ACT11D, Tunu2013, and Summit2010). The dataset covers the period from 1890 to 2012, a period of climate warming. For approximately the first decade of the new millennium (2001-2012) minimum and maximum mean annual precipitation conditions are found in Northeast Greenland (Tunu2013 c. 120mm water equivalent (w.e.) year(-1)) and South Greenland (Ikerasassuaq: c. 2300mm w.e. year(-1)), respectively. The coastal meteorological stations showed on average increasing trends for 1890-2012 (3.5mm w.e. year(-2)) and 1961-2012 (1.3mm w.e. year(-2)). Years with high coastal annual precipitation also had a: (1) significant high number of precipitation days (r(2) = 0.59); and (2) high precipitation intensity measured as 24-h precipitation (r(2) = 0.54). For the GrIS the precipitation estimated from ice cores increased on average by 0.1mm w.e. year(-2) (1890-2000), showing an antiphase variability in precipitation trends between the GrIS and the coastal regions. Around 1960 a major shift occurred in the precipitation pattern towards wetter precipitation conditions for coastal Greenland, while drier conditions became more prevalent on the GrIS. Differences in precipitation trends indicate a heterogeneous spatial distribution of precipitation in Greenland. An Empirical Orthogonal Function analysis reveals a spatiotemporal cycle of precipitation that is linked instantaneously to the North Atlantic Oscillation and the Atlantic Multidecadal Oscillation and with an approximate to 6 years lag time response to the Greenland Blocking Index.

We assess climate impacts of global warming using ongoing observations and paleoclimate data. We use Earth’s measured energy imbalance, paleoclimate data, and simple representations of the global carbon cycle and temperature to define emission reductions needed to stabilize climate and avoid potentially disastrous impacts on today’s young people, future generations, and nature. A cumulative industrial-era limit of ~500 GtC fossil fuel emissions and 100 GtC storage in the biosphere and soil would keep climate close to the Holocene range to which humanity and other species are adapted. Cumulative emissions of ~1000 GtC, sometimes associated with 2°C global warming, would spur “slow” feedbacks and eventual warming of 3–4°C with disastrous consequences. Rapid emissions reduction is required to restore Earth’s energy balance and avoid ocean heat uptake that would practically guarantee irreversible effects. Continuation of high fossil fuel emissions, given current knowledge of the consequences, would be an act of extraordinary witting intergenerational injustice. Responsible policymaking requires a rising price on carbon emissions that would preclude emissions from most remaining coal and unconventional fossil fuels and phase down emissions from conventional fossil fuels.

Observations at Summit, Greenland suggest that the annual mean near-surface air temperature increased at 0.090.01 degrees C/a over the 1982-2011 climatology period. This rate of warming, six times the global average, places Summit in the 99th percentile of all globally observed warming trends over this period. The rate of warming at Summit is increasing over time. During the instrumental period (1987-2011), warming has been greatest in the winter season, although the implications of summer warming are more acute. The annual maximum elevation of the equilibrium line and dry snow line has risen at 44 and 35m/a over the past 15 and 18years, respectively. Extrapolation of this observed trend now suggests, with 95% confidence intervals, that the dry snow facies of the Greenland Ice Sheet will inevitably transition to percolation facies. There is a 50% probability of this transition occurring by 2025.

Remote sensing is a fundamental tool to measure the dynamics of ice sheets and provides valuable information for ice sheet projections under a changing climate. There is, however, the potential to further reduce the uncertainties in these projections by developing innovative remote sensing methods. One of these remote sensing techniques, the polarimetric synthetic aperture radar interferometry (Pol-InSAR), is known since decades to have the potential to assess the geophysical properties below the surface of ice sheets, because of the penetration of microwave signals into dry snow, firn, and ice. Despite this, only very few studies have addressed this topic and the development of robust Pol-InSAR applications is at an early stage. Two potential Pol-InSAR applications are identified as the motivation for this thesis. First, the estimation and compensation of the penetration bias in digital elevation models derived with SAR interferometry. This bias can lead to errors of several meters or even tens of meters in surface elevation measurements. Second, the estimation of geophysical properties of the subsurface of glaciers and ice sheets using Pol-InSAR techniques. There is indeed potential to derive information about melt-refreeze processes within the firn, which are related to density and affect the mass balance. Such Pol-InSAR applications can be a valuable information source with the potential for monthly ice sheet wide coverage and high spatial resolution provided by the next generation of SAR satellites. However, the required models to link the Pol-InSAR measurements to the subsurface properties are not yet established. The aim of this thesis is to improve the modeling of the vertical backscattering distribution in the subsurface of ice sheets and its effect on polarimetric interferometric SAR measurements at different frequencies. In order to achieve this, polarimetric interferometric multi-baseline SAR data at different frequencies and from two different test sites on the Greenland ice sheet are investigated. This thesis contributes with three concepts to a better understanding and to a more accurate modeling of the vertical backscattering distribution in the subsurface of ice sheets. First, the integration of scattering from distinct subsurface layers. These are formed by refrozen melt water in the upper percolation zone and cause an interesting coherence undulation pattern, which cannot be explained with previously existing models. This represents a first link between Pol-InSAR data and geophysical subsurface properties. The second step is the improved modeling of the general vertical backscattering distribution of the subsurface volume. The advantages of more flexible volume models are demonstrated, but interestingly, the simple modification of a previously existing model with a vertical shift parameter lead to the best agreement between model and data. The third contribution is the model based compensation of the penetration bias, which is experimentally validated. At the investigated test sites, it becomes evident that the model based estimates of the surface elevations are more accurate than the interferometric phase center locations, which are conventionally used to derive surface elevations of ice sheets. This thesis therefore improves the state of the art of subsurface scattering modeling for Pol-InSAR applications, demonstrates the model-based penetration bias compensation, and makes a further research step towards the retrieval of geophysical subsurface information with Pol-InSAR.

Snow avalanches are a natural hazard in mountainous areas which endanger roads, villages and human lives. To inform the public on the current avalanche situation, avalanche warning services regularly publish avalanche bulletins in winter. However, forecasting snow avalanches is very challenging. Currently, it is not possible to predict the exact timing, location or size of snow avalanches. Avalanche forecasters therefore estimate the degree of avalanche danger at the scale of a region, by linking point observations of the snowpack, consisting of observations of snow stratigraphy and snow instability, with past and future weather. While snowpack observations are very time consuming and thus rather scarce, numerical snow cover models can considerably increase the spatial and temporal resolution of such data, especially if they provide information on snow instability. In our current understanding of avalanche formation, avalanche release is a fracture mechanical problem and snow instability is best understood in terms of failure initiation and crack propagation. Detailed snow cover models exists which can simulate snow stratigraphy, but snow instability information is partly missing or inaccurate. In view of applying snow cover models for avalanche forecasting, the aim of this thesis was to model spatially distributed snow instability. The snow cover model SNOWPACK simulates criteria for failure initiation and crack propagation for each snow layer, namely the stability index and the critical crack length. While the stability index had been validated with field observations and was related to the probability of skier triggering, this was not the case for the critical crack length, which was parameterized based on layer properties including density, shear strength and the elastic modulus. In a first step, we therefore validated the evolution of snow layer properties and the critical crack length in SNOWPACK with novel field measurements. Daily measurements with the snow micro-penetrometer allowed for direct comparison with SNOWPACK. Our results showed that the evolution of layer density was fairly well captured by the model, especially the first two months after deposition. For the validation of the critical crack length, we used results from the propagation saw test performed on a weekly basis over three winter seasons. A comparison to SNOWPACK highlighted some discrepancies, and we thus refined the parameterization with a fit factor depending on weak layer density and grain size. With the refined parameterization, spatially distributed modeling of snow instability in terms of failure initiation and crack propagation became tangible. Spatially distributed snow cover simulations require interpolation and downscaling of meteorological data, which may introduce uncertainties. How these uncertainties impact modeled snow stability remained mostly unknown. For the first time, we therefore investigated the sensitivity of modeled snow instability to meteorological input uncertainty with a global sensitivity analysis. Early in the season, during the period of weak layer formation, modeled instability metrics were mostly sensitive to air temperature and precipitation. After weak layer burial, during the period of slab formation, modeled instability metrics were mostly sensitive to precipitation. These results highlighted that accurate spatial snow depth distributions are required to obtain realistic snow instability patterns. In a last step, we used the distributed snow cover model Alpine3D to simulate snow instability for the region of Davos, Switzerland. Meteorological data from automatic weather stations were interpolated to a grid with 100 m resolution. Precipitation was scaled with highly resolved snow depth measurements from airborne laser scanning to account for realistic snow depth patterns. Modeled snow instability patterns were plausible, e.g south-facing slopes stabilized faster in spring. However, instability metrics were lower for south-facing slopes during the winter months, which was not in line with the forecasted avalanche danger level. While spatial patterns of modeled snow instability still have to be validated, spatially distributed snow cover modeling can greatly improve numerical avalanche forecasting. However, given a lack of accurate input data, simple virtual slopes instead of highly resolved modeling approaches is probably enough at this point in time.

In recent decades, glaciers worldwide have lost a significant part of their volume due to increasing atmospheric temperatures. In the future, these large storages of fresh water resources will continue to shrink. Glacio-hydrological models predict that glacier retreat will first induce an increased release of melt water until a certain peak is reached, followed by a decrease in runoff due to a reduction in glacier size and volume. For some glaciers, this peak has already occurred. By 2100, many regions of the world will likely lose more than 75% of their current glacier volume. Declining glacier volumes, in turn, will lead to a smaller contributions of glacier meltwater to streamflow, resulting in direct consequences for agriculture, drinking water and hydropower for instance. The anticipated trend in future glacier runoff is very similar across glacio-hydrological models. However, different sources of errors in the models themselves and in the model input, lead to large uncertainties in the predictions. This thesis, composed of three main studies, examines the uncertainties linked to the models’ input, namely the meteorological forecasts and the glacier-related datasets (i.e. Digital Surface Models (DSMs), ice thickness or snow height distribution). The ultimate goal is to help improving the next generation of runoff forecasts. The first study is related to the model meteorological inputs. The aim was to assess how the skill (i.e. the quality) of temperature and precipitation forecasts are influencing the skill of the resulting runoff predictions. A synthetic experiment was set up in which meteorological forecasts ranging over a spectrum of different skills were created. The meteorological forecasts were fed into a glacio-hydrological model, and the skill of the resulting runoff forecasts was assessed. The same experiment was performed for catchments with different degrees of glacierization. The results show that temperature and precipitation have an influence on runoff that depends on the catchment’s degree of glacierization, with the importance of accurate precipitation forecasts increasing at the expenses of accurate temperature projections with a decreasing degree of glacierization. The second and third studies are related to the models' glacier-related inputs. The aim was to investigate the potential of Unmanned Aerial Vehicle (UAV) photogrammetry to derive datasets including high-resolution ortho-images, DSMs of the glacier surface, and ice-flow velocity fields. First, the focus was set on assessing the accuracy of the DSMs, and how the number of Ground Control Points (GCPs), used to geo-reference the DSMs, affects them. To answer this question, several UAV surveys were performed on three alpine glaciers during different seasons. The results show that not only the number but also the distribution of GCPs affects the accuracy of UAV-derived DSMs. Once the recipe to derive accurate datasets was found, the ortho-images and DSMs were used to derive surface velocity fields, which is the subject of the third study. The goal was to develop a new procedure that derives (a) robust surface displacements and (b) an estimate of the result’s accuracy. The procedure consists of generating many different surface displacements based on various filters and matching functions, and to stack the so-obtained ensemble of results into a final surface velocity field. This procedure was embedded in a new tool that works in a semi-automated way. The tool was tested on three different types of glaciers, namely a calving glacier, an alpine glacier and a rock glacier. The experiments showed that it successfully generated robust velocity fields for all test sites and that the vector fields cover a large spatial extent. This thesis demonstrates that in high mountain areas, UAV photogrammetry allows to obtain high-resolution datasets with centimeter to decimeter accuracy. The potential of UAV photogrammetry to derive insightful snow and glacier-related datasets is high, but the method is currently limited to small catchments of several square kilometers, due to short flying time and geo-referencing requirements. Technical advancements and innovation in the field are fast, and UAV photogrammetry might become a valuable tool for surveying larger areas in the near future.

The Earth’s climate and its evolution are heavily influenced by the state of cryosphere snow cover and its subnivean ground through their determinative role in the exchange of water, heat, and greenhouse gases between land and the atmosphere. Previous research has shown that L-band radiometry can be used for the estimation of snow mass density rho_S and ground permittivity epsilon_G. In this thesis an unprecedented approach for the estimation of snow liquid water content (wetness) and the beginning of snow melt, using L-band radiometry and the L-band Specific Microwave Emission Model of Layered Snowpack (LS–MEMLS), is proposed. Two snow wetness retrieval data products are computed using tower-based radiometry over snow-covered natural ground and areas with a metal grid placed on the ground beneath the accumulating snow. It is experimentally demonstrated that the metal grid isolates snowpack’s own emission from the emission of the underlying ground. This allows considering the snow wetness retrievals derived from brightness temperatures measured over this artificially prepared area as references for comparison with snow wetness retrievals from brightness temperatures over natural ground. Furthermore, the disruptive effects of “geophysical noise” on (rho_S, epsilon_G) retrievals are investigated for dry snow conditions. Results indicate robust performance of the two-parameter retrieval approach against spatial variabilities of snow cover and subnivean soil. This is a promising base for the application of this two-parameter retrieval approach with coarse resolution satellite data. Further synthetic and experimental sensitivity analyses of the melting effects, in form of snow wetness and ground permittivity heterogeneities, are conducted which quantify their disruptive effects on the (rho_S, epsilon_G) retrievals. Results indicate reliable retrievals during snow free and cold winter periods. With the beginning of the early spring period, retrievals’ accuracy decrease and increased time-correlation is recognized between retrievals rho_S and epsilon_G. Retrieval quality flags are raised based on this type of retrievals’ correlation which is very useful for the application with space-borne radiometry data. Other achievements of this thesis work include the establishment of the Davos-Laret Remote Sensing Field Laboratory and significant improvement of radiometry data–measured with ELBARA-II radiometer–calibration and quality assessment. The latter includes a new more-accurate Radio Frequency Interference (RFI) filtering approach based on Gaussian curve fitting and time-dependent correction of transmission losses taking into account the transmission line ageing effects, for instance.

During a snowfall, chemical compounds from the atmosphere are deposited on the ground. If the snow does not melt completely, as is the case on polar and alpine glaciers, these impurities remain inside the snow cover. Compacted by subsequent snowfalls, the snow gradually turns into firn and later into ice. Deposits thus trapped in the glacier ice form invaluable archives of past climates and original atmospheric composition. These archives can be brought back to the surface through ice cores for later analysis. However, in order to make the information contained therein comprehensible, the processes that led to the embedding must be understood. In particular, the recrystallization of the snow cover by snow metamorphism can lead to a redistribution or a loss of the embedded compounds. Because snow on the Earth's surface is physically relatively close to its melting point, there is a high vapor pressure. Similar to red-hot structural steel, which is highly ductile and continuously transforms its shape, the snow structure also changes. Inside the snow cover, the high vapor pressure causes water molecules of the snow crystals to be released constantly (sublimation) and to be deposited on adjacent ice surfaces (re-sublimation). This structural transformation can also have an influence on the contaminants present and can cause the movement of chemical compounds to different positions in the snow cover. Thus, a closer examination of the processes taking place during this rearrangement is needed, because the chemical composition found in the ice might no longer correspond to that originally deposited by the snow crystals, leading to errors when estimating past atmospheric conditions from ice cores. In this thesis we investigated the influence of snow metamorphism on the (re)distribution of ions, trace elements and stable water isotopes in the snow cover. They all represent important environmental indicators of past atmospheric conditions and play an important role in the interpretation of ice cores.