Glaciers and Ice Caps 1

Satellite altimetry has been traditionally used in the past to infer elevation of land ice, quantify changes in ice topography and estimate mass balance over large and remote areas such as the Greenland and Antarctic ice sheets. Radar Altimetry (RA) is particularly well suited to this task due to its all-weather year-round capability for observing the ice surface. However, monitoring of ice caps has proven more challenging. The large footprint of a conventional radar altimeter and relatively coarse ground track coverage are less suited to monitor comparatively small regions with complex topography, so that mass balance estimates from RA rely on extrapolation methods to regionalize elevation change.
Since 2010, the Synthetic Interferometric Radar Altimeter (SIRAL) on board the ESA radar altimetry CryoSat mission has collected ice elevation measurements over ice caps. Ground track interspacing (~4km at 60°) is one order of magnitude smaller than ERS/ENVISAT missions and half of ICESAT’s, providing dense spatial coverage. Additionally the Synthetic Aperture Radar Interferometric (SARIn) mode of CryoSat provides a reduced footprint and the ability to locate accurately the position of the surface reflection. Conventional altimetry provides the elevation of the Point Of Closest Approach (POCA) within each waveform, every ~350 m along the flight path. Time evolution of POCA elevation is then used to investigate ice elevation change.
Here, we present an assessment of the geodetic mass balance of Icelandic ice caps using the novel swath altimetry processing approach applied to CryoSat SARIn mode data. In swath mode altimetry, elevation beyond the POCA is extracted from the waveform when coherent echoes are present providing a 10-100 fold increase in the number of elevations when compared to POCA. We generate maps of ice elevation change that are then used to compute geodetic mass balance for the period 2010 to 2015.  We compare our results to estimates generated using only POCA as well as to validation datasets, and we discuss the impact of swath mode altimetry on the spatial resolution and precision of the resulting elevation change and mass balance estimates.

Glaciers and ice caps (GICs) are sensitive indicators of climate change and are large contributors to present global eustatic sea level rise.  The peripheral GICs of the Greenland Ice Sheet cover an area of 89,700 km² or approximately 12% of the total global area of GICs. Between 2003 and 2009 it is estimated that the Greenland GICs were losing mass at a rate of 38 ± 7 gt/yr, which is about 15% of the estimated global mass loss from GICs (Gardner et al., 2013) and around 16% of the estimated mass loss from the main ice sheet (Shepherd et al., 2012). Here we present more recent volume change estimates of Greenland’s peripheral ice caps for the period from 2010 to 2015 using data from the CryoSat-2 mission. We show how the improved capabilities of CryoSat-2 in regions of complex terrain has led to more than a five-fold increase in the density of elevation change estimates in the region compared to estimates from earlier altimeter missions. Estimates of elevation change are evaluated using contemporaneous measurements from IceBridge airborne altimetry revealing excellent levels of agreement. We investigate emerging and evolving signals of volume change through comparison with earlier estimates from ICESat (Bolch et al., 2013). Finally, initial elevation changes results using CryoSat-2 SARIn mode swath processing over Disko Island, West Greenland, are presented.

Mapping the velocity fields of the continental ice sheets and their outlet glaciers is important in order to monitor and model the response of the cryosphere to global climate change. Since the mid 1990s, space-based SAR data have enabled measurement of ice velocities on a continental scale. Compared to interferometry, Offset Tracking techniques excel in terms of robustness and ease of automation. With the launch of Sentinel-1A in 2014 and Sentinel-1B in 2016, the potential coverage and revisit frequency have greatly improved, allowing monitoring of temporal changes in the ices sheet velocity fields.

Two Greenland-wide RADARSAT-2 campaigns were carried out during January-March 2014, and a smaller one in December 2014-February 2015. Ice velocity maps from both campaigns will be presented. A preliminary ice velocity map from the former campaign is attached with this abstract, while the latter awaits processing.

The first Sentinel-1A Greenland-wide observation campaign was carried out in January-March 2015, and ice velocity fields with nearly complete coverage has already been demonstrated [1]. A preliminary IV map using the DTU IPP processor (not all pairs processed) is attached with this abstract.

The overlapping temporal coverage of the second RADARSAT-2 campaign and the first Sentinel-1 campaign allows a comparison of the two sensors in terms of:

Impact of differing imaging modes (stripmap vs TOPS). The better coverage of Sentinel-1 is at the cost of a reduced azimuth resolution, however with a better range-resolution than RADARSAT-2 in standard beam mode. (RS2: 13.5m x 7.7m versus S1: 3m x 21m). Especially on the fast-flowing outlet glaciers, where the offset-tracking relies on the presence of features like glacier crevasses, a high resolution is important. Over the central Greenland ice sheet, where the backscatter is more homogeneous, offset-tracking relies instead on speckle tracking, reducing the need for high resolution. With more than one revisit, Sentinel-1 can generate 24-day baselines, and this allows a comparison of the two sensor modes without the influence of the temporal baseline.

The impact of temporal baseline, 24 days vs 12 days (6 when S1B is commissioned). The smaller temporal baseline of Sentinel-1 eases feature-tracking on fast-moving glaciers, and improves coherence (and thus speckle tracking) over more homogeneous regions. On the other hand, noise and ionospheric scintillations introduce errors on the ice velocity estimate inversely proportional with the temporal baseline.

Data quality (coverage, noise, geometric calibration).

DTU Space has implemented an operational interferometric post processing facility, IPP, which has been upgraded with a highly automated offset tracking capability in the frame of ESA’s Climate Change Initiative. The IPP processor ingests RADARSAT-2 SLC data, Sentinel-1 Interferometric Wideswath (IW) bursted SLC product, and several other past and current sensors (ERS/ENVISAT/ALOS/CosmoSkyMed/TerraSAR-X). Using the same processor ensures that observed differences lies in the data products/sensors rather than being due to different processing techniques.

 [1] T.Nagler et. al, ” The Sentinel-1 Mission: New Opportunities for IceSheet Observations”, Journal of Remote Sensing, 2015, 7, 9371-9389

Ice fields and ice caps are not only important contributors to sea level rise but they act also as water storage and supply in various regions of the Earth. Dramatic losses in the ice volume of temperate glaciers are observed worldwide during the routine quality control of TanDEM-X digital elevation models at DLR. The present satellite based investigations allow a global view of the development of glaciers during the last 4 years and thus complement conventional glaciological work which focuses mainly on studies of individual glaciers. In order to achieve the main goal of the TanDEM-X mission - the generation of a global SAR Digital Elevation Model (DEM) - parts of the Earth surface had to be covered several times according to the complexity of their topography and/or their backscattering properties. For coastal and mountainous areas (some of them including also glaciers) repeat coverage was necessary in order to apply special processing techniques (e.g. multibaseline processing) which reduce information loss due to phase unwrapping errors. Moreover for these difficult mountainous areas the helix formation of the satellites was re-adjusted between August 2013 and April 2014 allowing imaging from the opposite imaging geometry. Since the operational start of the TanDEM-X mission multitemporal datasets have been acquired in regions including, among others, rapidly changing features like ice fields, icecaps and outlet glaciers. This allows the accurate quantification of short time changes in ice elevation, and consequently in volume and mass from December 2010 up to the present.

We generate DEMs from acquired raw data or from intermediate CoSSC products with the Integrated TanDEM-X Processor (ITP) at DLR. Dual baseline processing is applied when appropriate data are available thus reducing complex topography areas affected by phase unwrapping. Surface elevation changes are computed from differencing the TanDEM-X DEMs. This approach has the advantage of using data acquired by the same InSAR sensor in a time span of 1 to 4 years. The biases due to different spatial resolution or different radar frequencies are thus excluded. A very accurate vertical and horizontal coregistration of the DEMs can be achieved by measuring the mean vertical offset between the pairs of TanDEM-X DEMs and the recently released SRTM v3 DEM on flat icefree and unvegetated calibration areas. Nevertheless we must take into account that the position of the scattering phase center may vary with the physical parameters of the snow/ice surface at the time of the overflight and the radar beam incidence angle. The ice elevation changes integrated over the glacier surface deliver the volume change in the time interval between the DEM data acquisitions. This value can in turn be converted into mass changes through the density of the lost or gained volume. In most of the cases the density of ice is taken all over the glacier.

This study focuses at short term elevation changes of major outlet glaciers of the Patagonia Icefields. Our previous investigations based on TerraSAR-X, TanDEM-X and SRTM data revealed thinning, front retreat and acceleration of most of the outlet glaciers in the region due mainly to atmospheric warming. The TanDEM-X DEM differencing gives additional details on the evolution of these glaciers during the last 3-4 years.

The Glaciers_cci project is developing algorithms and creating products for the ECV ‘Glaciers and Ice caps’ using satellite data. From the wide range of glacier related variables that can be observed from space, we have selected glacier outlines, elevation changes (from altimetry and DEM differencing) and ice velocity (from optical and microwave sensors). These products can be derived from a multitude of sensors, which cover different time periods and sample information at different spatial resolutions. Accordingly, a variety of methods have been developed to derive the products in a consistent and reproducible way. While in its first phase the focus of Glaciers_cci was on establishing the algorithms for automated and efficient data production as well as contributing to the completion of the Randolph Glacier Inventory (RGI), the focus of phase 2 is on global application of the methods to create time series of each product for climate change impact assessment.

The glacier outlines in the RGI served as a baseline dataset for a large number of regional to global scale calculations. For the first time it was possible to realistically estimate the number of glaciers on Earth (200,000), their area covered (727,000 km²), their total volume (170 million km³) and sea-level equivalent when they would completely melt (41 cm), their thickness distribution and length as well as their past and future evolution. The outlines also provided the extent for which other glacier-specific products were calculated. For example, this allowed for the first time to determine the annual mass loss of the local glaciers and ice caps on Greenland separately from the ice sheet as well as the high spatial variability of glacier mass changes in large parts of high mountain Asia, where field measurements are sparse or even absent. Flow velocities were calculated mostly automatically in different parts of the world and covering large regions and different time periods, revealing new insights in glacier dynamics. They reveal glaciers with dynamic instabilities that might be a threat for local communities, and show globally decreasing velocity trends in agreement with observed glacier decline.

In the future we will use the velocity datasets also to improve estimates of ice mass fluxes and thickness distribution. Data from the freely available sensors on Sentinel 1 and 2 offer much improved possibilities for obtaining this information globally and with high accuracy. Forthcoming sensors (such as ICESat 2) and DEMs (such as the global TanDEM-X DEM) will provide unprecedented opportunities for quantification of glacier mass changes in space and time, including determination of the regional representativeness of the field-based mass balance measurements. The 10 m resolution of the Sentinel 2 MSI sensor will provide a marked advance in the quality of glacier outlines due to the better visibility of debris-covered glacier parts and the higher repetition rate (5 days with S2b in orbit) will help acquiring optimal scenes in critical maritime regions that so far suffered from frequent adverse snow and cloud conditions.

Session: Earth Observation and Cryosphere Science meeting