Achim Heilig

Changing Arctic snow cover: A review of recent developments and assessment of future needs for observations, modelling, and impacts

Snow is a critically important and rapidly changing feature of the Arctic. However, snow-cover and snowpack conditions change through time pose challenges for measuring and prediction of snow. Plausible scenarios of how Arctic snow cover will respond to changing Arctic climate are important for impact assessments and adaptation strategies. Although much progress has been made in understanding and predicting snow-cover changes and their multiple consequences, many uncertainties remain. In this paper, we review advances in snow monitoring and modelling, and the impact of snow changes on ecosystems and society in Arctic regions. Interdisciplinary activities are required to resolve the current limitations on measuring and modelling snow characteristics through the cold season and at different spatial scales to assure human well-being, economic stability, and improve the ability to predict manage and adapt to natural hazards in the Arctic region.

Experiments and Algorithms to Detect Snow Avalanche Victims Using Airborne Ground-Penetrating Radar

Snow avalanche victims have only a good chance to survive when they are located within a short time. This requires an active beacon for them to wear or a very rapid deployment of a search-and-rescue team with dogs. Customary ground-penetrating radar (GPR) instruments used on the snow surface are not able to reduce fatality numbers because they are slow to search a field. A potential alternative could be an airborne search using radar. An airborne radar search is technologically challenging because a very large data stream has to be processed and visualized in real time, and the interaction of the electromagnetic waves with snow, subsurface, and objects must be understood. We studied a two-step algorithm to locate avalanche victims in real time. The algorithm was validated using realistic test arrangements and conditions using an aerial tramway. The distance dependence of the reflection energy with increased flight heights, the coherence between the use of more antennas and the detectable range, and the reflection images of different avalanche victims were measured. The algorithm detected an object for each investigated case, where the reflection energy of the scans was higher than for the scans of pure snow. Airborne GPR has a large potential to become a rapid search method in dry snow avalanches. However, a fully operational version still requires substantial improvements in hardware and software.

A novel sensor combination (upGPR‐GPS) to continuously and nondestructively derive snow cover properties

Monitoring seasonal snow cover properties is critical for properly managing natural hazards such as snow avalanches or snowmelt floods. However, measurements often cannot be conducted in difficult terrain or lack the high temporal resolution needed to account for rapid changes in the snowpack, e.g., liquid water content (LWC). To monitor essential snowpack properties, we installed an upward looking ground-penetrating radar (upGPR) and a low-cost GPS system below the snow cover and observed in parallel its evolution during two winter seasons. Applying external snow height (HS) information, both systems provided consistent LWC estimates in snow, based on independent approaches, namely measurements of travel time and attenuation of electromagnetic waves. By combining upGPR and GPS, we now obtain a self-contained approach instead of having to rely on external information such as HS. This allows for the first time determining LWC, HS, and snow water equivalent (SWE) nondestructively and continuously potentially also in avalanche-prone slopes.

L-band 3D imaging of an Alpine Glacier: Results from the AlpTomoSAR campaign

In this paper we present results from the tomographic analysis of L-Band SAR data acquired in February/March 2014 over the Mittelbergferner glacier, Austrian Alps, during the ESA campaign AlpTomoSAR. The campaign includes coincident in-situ measurements of snow and ice properties, as well as high-frequency Ground Penetrating Radar (GPR) data acquired over a total length of 18 km. The analyses of three-dimensional TomoSAR data cubes shows the complexity of the glacier sub-surface scattering. Most areas are characterized by surface scattering in proximity of the Lidar surface, plus a complex pattern of in-depth volumetric scattering beneath. Various subsurface features observed in GPR transects at 600 MHz and 200 MHz clearly showed up in TomoSAR sections as well. In particular: firn bodies, crevasses, and even the bedrock down to 50 m below the ice surface.

Imaging the Internal Structure of an Alpine Glacier via L-Band Airborne SAR Tomography

In this paper, we report results from the analysis of 3-D L-band airborne synthetic aperture radar (SAR) acquisitions acquired in March 2014 over the Mittelbergferner glacier, Austrian Alps, during the European Space Agency (ESA) campaign AlpTomoSAR. The campaign included coincident in situ measurements of snow and ice properties and ground-penetrating radar (GPR) data acquired at 600 and 200 MHz over a total length of 18 km. Radar data were acquired by repeatedly flying an L-band SAR along an oval racetrack at an altitude of about 1300 m over the glacier, such that two data stacks from opposite views are obtained. Data from all passes were coherently combined to achieve 3-D resolution capabilities, resulting in the generation of 3-D tomographic SAR (TomoSAR) cubes, where each voxel represents L-band radar reflectivity from a particular location in the 3-D space at a spatial resolution on the order of meters. TomoSAR cubes were finally corrected to account for wave propagation velocity into the ice, which was a necessary step to associate the observed features with their geometrical location, hence enabling a direct comparison to GPR data. The TomoSAR cubes show the complexity of the glacier subsurface scattering. Most areas are characterized by surface scattering in proximity of the ice surface, plus a complex pattern of in-depth volumetric scattering beneath and scattering at the ice/bedrock interface. Various subsurface features observed in GPR transects at 200 MHz clearly showed up in TomoSAR sections as well, particularly firn bodies, crevasses, layer transitions, and bedrock reflection down to 50 m below the ice surface.