scholarly journals Surface elevation change and mass balance of Icelandic ice caps derived from swath mode CryoSat-2 altimetry

2016 ◽  
Vol 43 (23) ◽  
pp. 12,138-12,145 ◽  
Author(s):  
L. Foresta ◽  
N. Gourmelen ◽  
F. Pálsson ◽  
P. Nienow ◽  
H. Björnsson ◽  
...  
Keyword(s):  
Mass Balance ◽  
Surface Elevation ◽  
Elevation Change ◽  
Ice Caps ◽  
Surface Elevation Change

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 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.

scholarly journals Glacier mass-balance determination by remote sensing and high-resolution modelling

2000 ◽  
Vol 46 (154) ◽  
pp. 491-498 ◽  
Author(s):  
Alun Hubbard ◽  
Ian Willis ◽  
Martin Sharp ◽  
Douglas Mair ◽  
Peter Nienow ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Mass Balance ◽  
Mass Flux ◽  
Surface Elevation ◽  
Surface Velocity ◽  
Elevation Change ◽  
Flux Divergence ◽  
Flow Modelling ◽  
Surface Elevation Change ◽  
Divergence Field

AbstractAn indirect methodology for determining the distribution of mass balance at high spatial resolution using remote sensing and ice-flow modelling is presented. The method, based on the mass-continuity equation, requires two datasets collected over the desired monitoring interval: (i) the spatial pattern of glacier surface-elevation change, and (ii) the mass-flux divergence field. At Haut Glacier d’Arolla, Valais, Switzerland, the mass-balance distribution between September 1992 and September 1993 is calculated at 20 m resolution from the difference between the pattern of surface-elevation change derived from analytical photogrammetry and the mass-flux divergence field determined from three-dimensional, numerical flow modelling constrained by surface-velocity measurements. The resultant pattern of mass balance is almost totally negative, showing a strong dependence on elevation, but with large localized departures. The computed distribution of mass balance compares well (R2 = 0.91) with mass-balance measurements made at stakes installed along the glacier centre line over the same period. Despite the highly optimized nature of the flow-modelling effort employed in this study, the good agreement indicates the potential this method has as a strategy for deriving high spatial and temporal-resolution estimates of mass balance.

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 Thinning of the Monte Perdido Glacier in the Spanish Pyrenees since 1981

2016 ◽  
Vol 10 (2) ◽  
pp. 681-694 ◽  
Author(s):  
Juan Ignacio López-Moreno ◽  
Jesús Revuelto ◽  
Ibai Rico ◽  
Javier Chueca-Cía ◽  
Asunción Julián ◽  
...  
Keyword(s):  
Mass Balance ◽  
Laser Scanning ◽  
Airborne Lidar ◽  
Surface Elevation ◽  
Aerial Photographs ◽  
Climate Data ◽  
Elevation Change ◽  
Factors Affecting ◽  
Digital Elevation ◽  
Surface Elevation Change

Abstract. This paper analyzes the evolution of the Monte Perdido Glacier, the third largest glacier in the Pyrenees, from 1981 to the present. We assessed the evolution of the glacier's surface area by analysis of aerial photographs from 1981, 1999, and 2006, and changes in ice volume by geodetic methods with digital elevation models (DEMs) generated from topographic maps (1981 and 1999), airborne lidar (2010) and terrestrial laser scanning (TLS, 2011, 2012, 2013, and 2014) data. We interpreted the changes in the glacier based on climate data from nearby meteorological stations. The results indicate that the degradation of this glacier accelerated after 1999. The rate of ice surface loss was almost three times greater during 1999–2006 than during earlier periods. Moreover, the rate of glacier thinning was 1.85 times faster during 1999–2010 (rate of surface elevation change  = −8.98 ± 1.80 m, glacier-wide mass balance  = −0.73 ± 0.14 m w.e. yr−1) than during 1981–1999 (rate of surface elevation change  = −8.35 ± 2.12 m, glacier-wide mass balance  = −0.42 ± 0.10 m w.e. yr−1). From 2011 to 2014, ice thinning continued at a slower rate (rate of surface elevation change  = −1.93 ± 0.4 m yr−1, glacier-wide mass balance  = −0.58 ± 0.36 m w.e. yr−1). This deceleration in ice thinning compared to the previous 17 years can be attributed, at least in part, to two consecutive anomalously wet winters and cool summers (2012–2013 and 2013–2014), counteracted to some degree by the intense thinning that occurred during the dry and warm 2011–2012 period. However, local climatic changes observed during the study period do not seem sufficient to explain the acceleration of ice thinning of this glacier, because precipitation and air temperature did not exhibit statistically significant trends during the study period. Rather, the accelerated degradation of this glacier in recent years can be explained by a strong disequilibrium between the glacier and the current climate, and likely by other factors affecting the energy balance (e.g., increased albedo in spring) and feedback mechanisms (e.g., heat emitted from recently exposed bedrock and debris covered areas).

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

2015 ◽  
Vol 9 (5) ◽  
pp. 1895-1913 ◽  
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 timescales. 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 ratio 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 ± 0.20 m (winter 2010/11 to winter 2011/12), 1.39 ± 0.20 m (2011/12 to 2012/13) and 0.36 ± 0.20 m (2012/13 to 2013/14); for a total surface elevation loss of 2.75 ± 0.20 m over this 3-year period. In contrast, the uncertainty in height change 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.

scholarly journals Surface elevation change on ice caps in the Qaanaaq region, northwestern Greenland

Polar Science ◽  
2016 ◽  
Vol 10 (3) ◽  
pp. 239-248 ◽  
Author(s):  
Jun Saito ◽  
Shin Sugiyama ◽  
Shun Tsutaki ◽  
Takanobu Sawagaki
Keyword(s):  
Surface Elevation ◽  
Elevation Change ◽  
Ice Caps ◽  
Surface Elevation Change

Clustering patterns of volume change to classify glacier states and fates

2021 ◽  
Author(s):  
Lea Hartl ◽  
Kay Helfricht ◽  
Martin Stocker-Waldhuber ◽  
Bernd Seiser ◽  
Andrea Fischer
Keyword(s):  
Mass Balance ◽  
In Situ Monitoring ◽  
Surface Elevation ◽  
Elevation Change ◽  
Surface Change ◽  
Mountain Ranges ◽  
Digital Terrain ◽  
Terrain Models ◽  
Surface Elevation Change

<div> <p>Historically unprecedented glacier retreat rates are observed in mountain ranges all over the world. These high recession rates are expected to continue during the next decades. There is currently a window of opportunity to learn from the first vanishing Alpine glaciers and develop monitoring strategies to track the pace and extent of a deglaciation phase. </p> </div><div> <p>Austria has a long history of in-situ mass balance monitoring at select glaciers, as well as a rich data basis of regional glacier inventories and multi-temporal digital terrain models from aerial surveys. As such, monitoring programs are in an ideal position to track the ongoing, rapid changes and place them in a historical context. With increasing rates of change it becomes all the more important to leverage the specific advantages of different data sets and combine them for a complete picture of regional changes and local processes.  </p> </div><div> <p>To this end, we compare long time series of annual mass balance data measured in-situ via the direct glaciological method at select monitoring sites in western Austria with results derived from remote sensing based digital terrain models. We use the latter to extract histograms of surface elevation change at hundreds of individual glaciers, over multiple time periods. This allows us to quantify the variability of surface elevation change and how it has changed in the past decades, and provides a basis for discussions of regional representativity of in-situ monitoring sites.  </p> </div><div> <p>Additionally, we use a self-organizing maps algorithm to cluster the individual “profiles” of surface elevation change into groups. This helps to visualize recurring patterns of change in specific geographic regions or elevation zones while preserving the characteristics of different, individual glaciers and their response to climatic forcing, and gives us a sense of the state of disequilibrium of certain mountain ranges. </p> </div><div> <p>All available data indicates that recent years have been characterized by large area and volume losses, strongly negative mass balance values, and disintegration especially of low-lying glacier tongues. Firn cover has been strongly depleted so that some glaciers effectively no longer have accumulation zones. Variability of surface elevation change has generally increased at lower elevations and remained mostly constant at higher elevations, but this varies significantly between individual glaciers. The long-term in-situ monitoring sites skew to very large glaciers compared to the regional average.  Larger glaciers, including most of the monitoring sites, tend to exhibit a strong elevation gradient of surface change, with large losses at low elevations. Small glaciers typically have a less pronounced gradient, if any, and especially very small glaciers at lower elevations have significantly less negative elevation change values as large glaciers, in the same elevation zone. When clustering individual glaciers into types, we find a clear shift to surface change distribution curves that suggest processes of disintegration. This tendency is strongest in the most recent time period. At current rates of mass loss, glaciers are projected to retreat entirely to above 2800m in the Ötztal and Stubai ranges by 2050. </p> </div>

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