109 research outputs found

    An improved algorithm for retrieval of snow wetness using C-band AIRSAR

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    This study shows recent results of our efforts to develop and verify an algorithm for snow wetness retrieval from a polarimetric SAR (Synthetic Aperture Radar). Our algorithm is based on the first-order scattering model with consideration of both surface and volume scattering. It operates at C-band and requires only rough information about the ice volume fraction in snowpack. Comparing ground measurements and inferred from JPL AIRSAR data, the results showed that the relative error inferred from SAR imagery was within 25 percent. The inferred snow wetness from different looking geometries (two flight passes) provided consistent results within 2 percent. Both regional and point measurement comparisons between the ground and SAR derived snow wetness indicates that the inversion algorithm performs well using AIRSAR (Airborne Synthetic Aperture Radar) data and should prove useful for routine and large-area snow wetness (in top layer of a snowpack) measurements

    Dr. Eveline Pipp (12.12.1956-05.05.2017): Ein Nachruf

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    Nachruf auf Dr. Eveline Pipp (12.12.1956-05.05.2017) samt einer Bibliographie ihrer Veröffentlichungen

    Velocities of Major Outlet Glaciers of the Patagonia Icefield Observed by TerraSAR-X

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    The capabilities of TerraSAR-X data for feature tracking by amplitude correlation over glacier surfaces are investigated. Methodical aspects of the amplitude correlation approach are described. The TerraSAR-X based velocity fields are compared with former InSAR derived velocities and field measurements on three outlet glaciers on the South Patagonia ice field

    Impact of marine processes on flow dynamics of northern Antarctic Peninsula outlet glaciers

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    ARISING FROM P. A. Tuckett et al., Nature Communications https://doi.org/10.1038/s41467-019-12039-2 (2019)

    Exploiting the ANN Potential in Estimating Snow Depth and Snow Water Equivalent From the Airborne SnowSAR Data at X- and Ku-Bands

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    Within the framework of European Space Agency (ESA) activities, several campaigns were carried out in the last decade with the purpose of exploiting the capabilities of multifrequency synthetic aperture radar (SAR) data to retrieve snow information. This article presents the results obtained from the ESA SnowSAR airborne campaigns, carried out between 2011 and 2013 on boreal forest, tundra and alpine environments, selected as representative of different snow regimes. The aim of this study was to assess the capability of X- and Ku-bands SAR in retrieving the snow parameters, namely snow depth (SD) and snow water equivalent (SWE). The retrieval was based on machine learning (ML) techniques and, in particular, of artificial neural networks (ANNs). ANNs have been selected among other ML approaches since they are capable to offer a good compromise between retrieval accuracy and computational cost. Two approaches were evaluated, the first based on the experimental data (data driven) and the second based on data simulated by the dense medium radiative transfer (DMRT). The data driven algorithm was trained on half of the SnowSAR dataset and validated on the remaining half. The validation resulted in a correlation coefficient R ≃ 0.77 between estimated and target SD, a root-mean-square error (RMSE) ≃ 13 cm, and bias = 0.03 cm. ANN algorithms specific for each test site were also implemented, obtaining more accurate results, and the robustness of the data driven approach was evaluated over time and space. The algorithm trained with DMRT simulations and tested on the experimental dataset was able to estimate the target parameter (SWE in this case) with R = 0.74, RMSE = 34.8 mm, and bias = 1.8 mm. The model driven approach had the twofold advantage of reducing the amount of in situ data required for training the algorithm and of extending the algorithm exportability to other test sites

    A Reconciled Estimate of Ice-Sheet Mass Balance

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    We combined an ensemble of satellite altimetry, interferometry, and gravimetry data sets using common geographical regions, time intervals, and models of surface mass balance and glacial isostatic adjustment to estimate the mass balance of Earth's polar ice sheets. We find that there is good agreement between different satellite methods-especially in Greenland and West Antarctica-and that combining satellite data sets leads to greater certainty. Between 1992 and 2011, the ice sheets of Greenland, East Antarctica, West Antarctica, and the Antarctic Peninsula changed in mass by -142 plus or minus 49, +14 plus or minus 43, -65 plus or minus 26, and -20 plus or minus 14 gigatonnes year(sup 1), respectively. Since 1992, the polar ice sheets have contributed, on average, 0.59 plus or minus 0.20 millimeter year(sup 1) to the rate of global sea-level rise

    Mass balance of the Greenland Ice Sheet from 1992 to 2018

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    In recent decades, the Greenland Ice Sheet has been a major contributor to global sea-level rise1,2, and it is expected to be so in the future3. Although increases in glacier flow4–6 and surface melting7–9 have been driven by oceanic10–12 and atmospheric13,14 warming, the degree and trajectory of today’s imbalance remain uncertain. Here we compare and combine 26 individual satellite measurements of changes in the ice sheet’s volume, flow and gravitational potential to produce a reconciled estimate of its mass balance. Although the ice sheet was close to a state of balance in the 1990s, annual losses have risen since then, peaking at 335 ± 62 billion tonnes per year in 2011. In all, Greenland lost 3,800 ± 339 billion tonnes of ice between 1992 and 2018, causing the mean sea level to rise by 10.6 ± 0.9 millimetres. Using three regional climate models, we show that reduced surface mass balance has driven 1,971 ± 555 billion tonnes (52%) of the ice loss owing to increased meltwater runoff. The remaining 1,827 ± 538 billion tonnes (48%) of ice loss was due to increased glacier discharge, which rose from 41 ± 37 billion tonnes per year in the 1990s to 87 ± 25 billion tonnes per year since then. Between 2013 and 2017, the total rate of ice loss slowed to 217 ± 32 billion tonnes per year, on average, as atmospheric circulation favoured cooler conditions15 and as ocean temperatures fell at the terminus of Jakobshavn Isbræ16. Cumulative ice losses from Greenland as a whole have been close to the IPCC’s predicted rates for their high-end climate warming scenario17, which forecast an additional 50 to 120 millimetres of global sea-level rise by 2100 when compared to their central estimate

    Analyse der Schneeflächen auf Gletschern der tiroler Zentralalpen aus Landsat-Bildern

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    The extent of snow cover at the end of the ablation season on glaciers in the Tyrolean Alps in 1972 and 1973 was determined from Landsat-1 Multispectral Scanner (MSS) images. For snow mapping the MSS-images with a ground resolution of 80 meters were enlarged to a scale of 1:100.000 by photographic methods. Different appearance of snow cover in the 4 MSS-channels is discussed in connection with ground truth control. The accuracy of snow and ice mapping from Landsat images was checked on 15 glaciers with an area from 1 to 10 km**2 by aerial photography and/or ground truth control. These comparisons imply the usefulness of Landsat images for snow mapping on glaciers of a few square kilometers. The altitude of the equilibrium line was determined from Landsat images for 53 glaciers in the Tyrolean Alps. The regional differences in the equilibrium line altitude correspond to the regional precipitation patterns. The equilibrium line was identical with the snow line at the end of the budget year 1971/1972; therefore it was possible to determine the equilibrium line from satellite images. For 1968/69 the equilibrium line was mapped from aerial photographs for several glaciers. In 1972/73 mass balance was strongly negative and the equilibrium line was within the firn area of the glaciers. Therefore it was not possible to distinguish between accumulation and ablation areas from the Landsat images of September 1973; however, snow and ice areas could be clearly differentiated. The ratios of accumulation area or snow area to the total area of the glaciers were determined from satellite images and aerial photography separately for advancing and for retreating glaciers and were related to the mass balance. In the budget years 1968/69 and 1972/73 with negative mass balance the accumulation area ratios of the advancing glaciers were clearly different from the ratios of the retreating glaciers, in 1971/72 with positive or balanced mass budget the differences between advancing and retreating glaciers were not significant
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