scholarly journals Antarctic firn compaction rates from repeat-track airborne radar data: I. Methods

2015 ◽  
Vol 56 (70) ◽  
pp. 155-166 ◽  
Author(s):  
B. Medley ◽  
S.R.M. Ligtenberg ◽  
I. Joughin ◽  
M.R. Van den Broeke ◽  
S. Gogineni ◽  
...  
Keyword(s):  
Accumulation Rate ◽  
Radar Data ◽  
Temporal Variations ◽  
Mass Change ◽  
Surface Elevation ◽  
Elevation Change ◽  
Compaction Rate ◽  
Thickness Change ◽  
Surface Elevation Change ◽  
Spatio Temporal

AbstractWhile measurements of ice-sheet surface elevation change are increasingly used to assess mass change, the processes that control the elevation fluctuations not related to ice-flow dynamics (e.g. firn compaction and accumulation) remain difficult to measure. Here we use radar data from the Thwaites Glacier (West Antarctica) catchment to measure the rate of thickness change between horizons of constant age over different time intervals: 2009–10, 2010–11 and 2009–11. The average compaction rate to ~25 m depth is 0.33 m a−1, with largest compaction rates near the surface. Our measurements indicate that the accumulation rate controls much of the spatio-temporal variations in the compaction rate while the role of temperature is unclear due to a lack of measurements. Based on a semi-empirical, steady-state densification model, we find that surveying older firn horizons minimizes the potential bias resulting from the variable depth of the constant age horizon. Our results suggest that the spatio-temporal variations in the firn compaction rate are an important consideration when converting surface elevation change to ice mass change. Compaction rates varied by up to 0.12 m a−1 over distances <6 km and were on average >20% larger during the 2010–11 interval than during 2009–10.

scholarly journals Modeling of firn compaction for estimating ice-sheet mass change from observed ice-sheet elevation change

2011 ◽  
Vol 52 (59) ◽  
pp. 1-7 ◽  
Author(s):  
Jun Li ◽  
H. Jay Zwally
Keyword(s):  
Accumulation Rate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Temporal Variations ◽  
Mass Change ◽  
Surface Elevation ◽  
Effective Density ◽  
Elevation Change ◽  
Surface Elevation Change ◽  
Elevation Changes

AbstractChanges in ice-sheet surface elevation are caused by a combination of ice-dynamic imbalance, ablation, temporal variations in accumulation rate, firn compaction and underlying bedrock motion. Thus, deriving the rate of ice-sheet mass change from measured surface elevation change requires information on the rate of firn compaction and bedrock motion, which do not involve changes in mass, and requires an appropriate firn density to associate with elevation changes induced by recent accumulation rate variability. We use a 25 year record of surface temperature and a parameterization for accumulation change as a function of temperature to drive a firn compaction model. We apply this formulation to ICESat measurements of surface elevation change at three locations on the Greenland ice sheet in order to separate the accumulation-driven changes from the ice-dynamic/ablation-driven changes, and thus to derive the corresponding mass change. Our calculated densities for the accumulation-driven changes range from 410 to 610 kgm–3, which along with 900 kgm–3 for the dynamic/ablation-driven changes gives average densities ranging from 680 to 790 kgm–3. We show that using an average (or ‘effective’) density to convert elevation change to mass change is not valid where the accumulation and the dynamic elevation changes are of opposite sign.

scholarly journals Heterogeneous spatial and temporal pattern of surface elevation change and mass balance of the Patagonian icefields between 2000 and 2016

2018 ◽  
Author(s):  
Wael Abdel Jaber ◽  
Helmut Rott ◽  
Dana Floricioiu ◽  
Jan Wuite ◽  
Nuno Miranda
Keyword(s):  
Spatial Pattern ◽  
Mass Balance ◽  
Temporal Trend ◽  
Temporal Variations ◽  
Sar Interferometry ◽  
Surface Elevation ◽  
Radar Signal ◽  
Elevation Change ◽  
Mass Losses ◽  
Surface Elevation Change

Abstract. The Northern and Southern Patagonian icefields (NPI and SPI) have been subject to accelerated retreat during the last decades with considerable variability in magnitude and timing among individual glaciers. We derive spatially detailed maps of surface elevation change (SEC) of NPI and SPI from bistatic SAR interferometry data of SRTM and TanDEM-X for two epochs, 2000–2012 and 2012–2016 and provide data on changes in surface elevation and ice volume for the individual glaciers and for the icefields at large. We apply advanced TanDEM-X processing techniques allowing to cover 90 % and 95 % of the area of NPI and 97 % and 98 % of the area of SPI for the two epochs, respectively. Particular attention is paid to precisely coregistering the DEMs, assessing and accounting for possible effects of radar signal penetration through backscatter analysis, and correcting for seasonality biases in case of deviations in repeat DEM coverage from full annual time spans. The results show a different temporal trend between the two icefields and reveal a heterogeneous spatial pattern of SEC and mass balance caused by different sensitivities in respect to direct climatic forcing and ice flow dynamics of individual glaciers. The estimated volume change rates for NPI are −4.26 ± 0.20 km3 a−1 for epoch 1 and −5.60 ± 0.71 km3 a−1 for epoch 2, while for SPI these are −14.87 ± 0.51 km3 a−1 for epoch 1 and −11.86 ± 1.90 km3 a−1 for epoch 2. This amounts to 0.047 ± 0.005 mm a−1 eustatic sea level rise for both icefields during the epoch 2000–2016. On SPI the spatial pattern of surface elevation change is more complex than on NPI and the temporal trend is less uniform. On terminus sections of the main calving glaciers of SPI temporal variations of flow velocities are a main factor for differences in SEC between the two epochs. Striking differences are observed even on adjoining glaciers, such as Upsala Glacier with decreasing mass losses associated with slowdown of flow velocity between the two epochs, contrasting with acceleration and increase of mass losses on Viedma Glacier.

scholarly journals Classifying disequilibrium of small mountain glaciers from patterns of surface elevation change distributions

2021 ◽  
pp. 1-16
Author(s):  
Lea Hartl ◽  
Kay Helfricht ◽  
Martin Stocker-Waldhuber ◽  
Bernd Seiser ◽  
Andrea Fischer
Keyword(s):  
High Elevation ◽  
Distinct Pattern ◽  
Surface Elevation ◽  
Elevation Change ◽  
Self Organizing Maps ◽  
Data Set ◽  
Thickness Change ◽  
Mountain Glaciers ◽  
Surface Elevation Change ◽  
Time Periods

Abstract The overall trend of rapid retreat of Alpine glaciers contains considerable variability of responses at the scale of individual glaciers. As a step towards a regional assessment of glacier state that allows a detailed differentiation of single glaciers, we explore the potential of a self-organizing maps (SOM) algorithm to identify and cluster recurring patterns of thickness change at glaciers in western Austria. Using digital elevation models and glacier inventories for three time periods, we compute the frequency distribution of surface elevation change over the area of each glacier in the data set, for each period. The results of the SOM clustering show a distinct pattern shift over time: From 1969 to 1997, surface elevation change occurred at relatively uniform rates across a given glacier. Since 1997, the distribution of surface elevation change at individual glaciers has been far less uniform, indicating accelerated processes of disintegration. Tracking the evolution of individual glaciers throughout the time periods via the clusters highlights both the broader regional trend as well as glaciers that deviate from this trend, e.g. some very small, high elevation glaciers that have reverted to reduced and more uniform volume loss patterns.

scholarly journals Rapid changes of Alpine glaciers in Austria tracked by ALS surveys 

2021 ◽  
Author(s):  
Kay Helfricht ◽  
Lea Hartl ◽  
Martin Stocker-Waldhuber ◽  
Bernd Seiser ◽  
Andrea Fischer
Keyword(s):  
Relative Volume ◽  
Surface Elevation ◽  
Ice Thickness ◽  
Mountain Range ◽  
Volume Loss ◽  
Elevation Change ◽  
Thickness Change ◽  
Alpine Glaciers ◽  
Glacier Changes ◽  
Surface Elevation Change

&lt;p&gt;Unprecedented glacier changes are reported for many mountain regions on earth based on surveys with different spatial resolution and repeat intervals. Eastern Alpine glaciers have been receding since the LIA maximum, with increasing relative volume loss at the beginning of the 21&lt;sup&gt;st&lt;/sup&gt; century. New high-resolution data of surface elevation from ALS surveys enable the analysis of most recent glacier changes at three mountain ranges in western Austria as an impact of climate change.&lt;/p&gt;&lt;p&gt;Surface elevation change rates between 2007 and 2018 increased again in comparison to former periods. Volume loss takes place even in the highest elevation zones, and most of the glaciers are out of an equilibrium state, such that consolidation of mass balance towards zero appears impossible under present climate conditions. The disintegration of low lying glacier tongues and a strong depletion of the firn cover are further signs of rapid glacier changes. The frequency distributions of surface elevation change throughout the area of each glacier show distinct shifts in peak ice thickness change and patterns of surface change distribution that suggest ongoing processes of glacier disintegration. Combining recent surface elevation changes and estimations of the spatial distribution of ice thickness in Austria shows that most of glaciers will vanish in 50 years or less. Only glaciers currently larger than 5 km&amp;#178; can be expected to exist longer at reduced size. At current rates of mass loss, glaciers are projected to retreat entirely to above 2800m in the &amp;#214;tztal and Stubai ranges by 2050. Further concerns arise regarding methods of tracking the future development of the remaining ice bodies. In particular, in the Silvretta mountain range, the majority of glacier margins have to be delineated in debris-covered glacier zones. It is debatable whether some of the smallest glaciogenic features should still be accounted for in glacier inventories or moved to an inventory of transient cryogenic landforms.&lt;/p&gt;

scholarly journals Heterogeneous spatial and temporal pattern of surface elevation change and mass balance of the Patagonian ice fields between 2000 and 2016

2019 ◽  
Vol 13 (9) ◽  
pp. 2511-2535 ◽  
Author(s):  
Wael Abdel Jaber ◽  
Helmut Rott ◽  
Dana Floricioiu ◽  
Jan Wuite ◽  
Nuno Miranda
Keyword(s):  
Spatial Pattern ◽  
Mass Balance ◽  
Temporal Trend ◽  
Sar Interferometry ◽  
Surface Elevation ◽  
Radar Signal ◽  
Elevation Change ◽  
Mass Losses ◽  
Digital Elevation ◽  
Surface Elevation Change

Abstract. The northern and southern Patagonian ice fields (NPI and SPI) have been subject to accelerated retreat during the last decades, with considerable variability in magnitude and timing among individual glaciers. We derive spatially detailed maps of surface elevation change (SEC) of NPI and SPI from bistatic synthetic aperture radar (SAR) interferometry data of the Shuttle Radar Topography Mission (SRTM) and TerraSAR-X add-on for Digital Elevation Measurements (TanDEM-X) for two epochs, 2000–2012 and 2012–2016, and provide data on changes in surface elevation and ice volume for the individual glaciers and the ice fields at large. We apply advanced TanDEM-X processing techniques allowing us to cover 90 % and 95 % of the area of NPI and 97 % and 98 % of SPI for the two epochs, respectively. Particular attention is paid to precisely co-registering the digital elevation models (DEMs), accounting for possible effects of radar signal penetration through backscatter analysis and correcting for seasonality biases in case of deviations in repeat DEM coverage from full annual time spans. The results show a different temporal trend between the two ice fields and reveal a heterogeneous spatial pattern of SEC and mass balance caused by different sensitivities with respect to direct climatic forcing and ice flow dynamics of individual glaciers. The estimated volume change rates for NPI are -4.26±0.20 km3 a−1 for epoch 1 and -5.60±0.74 km3 a−1 for epoch 2, while for SPI these are -14.87±0.52 km3 a−1 for epoch 1 and -11.86±1.99 km3 a−1 for epoch 2. This corresponds for both ice fields to an eustatic sea level rise of 0.048±0.002 mm a−1 for epoch 1 and 0.043±0.005 mm a−1 for epoch 2. On SPI the spatial pattern of surface elevation change is more complex than on NPI and the temporal trend is less uniform. On terminus sections of the main calving glaciers of SPI, temporal variations in flow velocities are a main factor for differences in SEC between the two epochs. Striking differences are observed even on adjoining glaciers, such as Upsala Glacier, with decreasing mass losses associated with slowdown of flow velocity, contrasting with acceleration and increase in mass losses on Viedma Glacier.

scholarly journals Small-scale spatio-temporal characteristics of accumulation rates in western Dronning Maud Land, Antarctica

2008 ◽  
Vol 54 (185) ◽  
pp. 315-323 ◽  
Author(s):  
Helgard Anschütz ◽  
Daniel Steinhage ◽  
Olaf Eisen ◽  
Hans Oerter ◽  
Martin Horwath ◽  
...  
Keyword(s):  
Accumulation Rate ◽  
Temporal Variations ◽  
Spatial Variations ◽  
Small Scale ◽  
Accumulation Rates ◽  
Order Of Magnitude ◽  
Dronning Maud Land ◽  
Spatio Temporal ◽  
Ground Penetrating ◽  
Firn Core

AbstractSpatio-temporal variations of the recently determined accumulation rate are investigated using ground-penetrating radar (GPR) measurements and firn-core studies. The study area is located on Ritscherflya in western Dronning Maud Land, Antarctica, at an elevation range 1400–1560 m. Accumulation rates are derived from internal reflection horizons (IRHs), tracked with GPR, which are connected to a dated firn core. GPR-derived internal layer depths show small relief along a 22 km profile on an ice flowline. Average accumulation rates are about 190 kg m−2 a−1 (1980–2005) with spatial variability (1σ) of 5% along the GPR profile. The interannual variability obtained from four dated firn cores is one order of magnitude higher, showing 1σ standard deviations around 30%. Mean temporal variations of GPRderived accumulation rates are of the same magnitude or even higher than spatial variations. Temporal differences between 1980–90 and 1990–2005, obtained from two dated IRHs along the GPR profile, indicate temporally non-stationary processes, linked to spatial variations. Comparison with similarly obtained accumulation data from another coastal area in central Dronning Maud Land confirms this observation. Our results contribute to understanding spatio-temporal variations of the accumulation processes, necessary for the validation of satellite data (e.g. altimetry studies and gravity missions such as Gravity Recovery and Climate Experiment (GRACE)).

scholarly journals CryoSat-2 delivers monthly and inter-annual surface elevation change for Arctic ice caps

2015 ◽  
Vol 9 (3) ◽  
pp. 2821-2865 ◽  
Author(s):  
L. Gray ◽  
D. Burgess ◽  
L. Copland ◽  
M. N. Demuth ◽  
T. Dunse ◽  
...  
Keyword(s):  
Snow Accumulation ◽  
Surface Elevation ◽  
Radar Altimeter ◽  
Elevation Change ◽  
Ice Caps ◽  
Ice Cap ◽  
Winter Snow ◽  
Surface Elevation Change ◽  
Devon Ice Cap ◽  
Arctic Ice

Abstract. We show that the CryoSat-2 radar altimeter can provide useful estimates of surface elevation change on a variety of Arctic ice caps, on both monthly and yearly time scales. Changing conditions, however, can lead to a varying bias between the elevation estimated from the radar altimeter and the physical surface due to changes in the contribution of subsurface to surface backscatter. Under melting conditions the radar returns are predominantly from the surface so that if surface melt is extensive across the ice cap estimates of summer elevation loss can be made with the frequent coverage provided by CryoSat-2. For example, the average summer elevation decreases on the Barnes Ice Cap, Baffin Island, Canada were 2.05 ± 0.36 m (2011), 2.55 ± 0.32 m (2012), 1.38 ± 0.40 m (2013) and 1.44 ± 0.37 m (2014), losses which were not balanced by the winter snow accumulation. As winter-to-winter conditions were similar, the net elevation losses were 1.0 ± 0.2 m (winter 2010/2011 to winter 2011/2012), 1.39 ± 0.2 m (2011/2012 to 2012/2013) and 0.36 ± 0.2 m (2012/2013 to 2013/2014); for a total surface elevation loss of 2.75 ± 0.2 m over this 3 year period. In contrast, the uncertainty in height change results from Devon Ice Cap, Canada, and Austfonna, Svalbard, can be up to twice as large because of the presence of firn and the possibility of a varying bias between the true surface and the detected elevation due to changing year-to-year conditions. Nevertheless, the surface elevation change estimates from CryoSat for both ice caps are consistent with field and meteorological measurements. For example, the average 3 year elevation difference for footprints within 100 m of a repeated surface GPS track on Austfonna differed from the GPS change by 0.18 m.

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