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CCI Products
CCI products are generated for the seven Greenland Ice Sheet Essential Climate Variables (ECVs), including the new R&D Machine Learning-based SGL product.
NOTE: from November 2024 newly generated products can only be found on the websites of the Partners:
- Surface Elevation Change (SEC) from ERS-1, ERS-2, Envisat, CryoSat-2 and Sentinel-3 data by DTU Space
- Monthly surface elevation changes from CryoSat-2 data (dSEC) by DTU Space
- 2014-present Greenland ice velocity (IV) timeseries from Copernicus Sentinel-1 SAR by ENVEO
- Greenland Icesheet CCI Experimental Ice Uplift/Subsidence from InSAR Line-of-sight velocity by DTU-N
- Ice Velocity from Sentinel-2 data for 9 outlet key glaciers by S&T NO (OptIV)
- Gravimetric mass balance of the Greenland Ice Sheet from the GRACE and GRACE-FO satellite gravimetry mission by TU Dresden
- Greenland mass balance (GMB) product for the Greenland Ice Sheet from GRACE(-FO) satellite gravimetry (CSR RL06) by DTU Space, computed with the mass point inversion method
- 2014-2023 Mass Flux Ice Discharge based on IV and SEC by GEUS.
- Greenland Ice Sheet CCI Experimental SupraGlacial Lakes (SGL) volume estimate from Sentinel-2 and IceSat-2 missions by S&T NO
Surface Elevation Change (SEC)
The surface elevation change (SEC) is directly linked to mass balance of the ice sheet. The surface elevation change is a direct measure of the imbalance between the atmospheric forcing and ice sheet dynamics. Hence, identified as an essential climate variable, SEC is derived from present and past ESA radar altimetry missions.
The era of ESA altimetry missions was initiated with ERS-1 in 1992, and data from ERS-2, Envisat and CryoSat-2 have contributed to an unbroken time series from then to present. At present we have two ESA missions contributing with data for the Greenland ice sheet; Cryosat-2 and Sentinel-3a/b ensuring the time series to be continued.
The nature of the radar measurements enables surface penetration in the interior parts of the Greenland ice sheet and the radar measures a reflecting surface within the upper 2 meters of the snow cover, rather than the snow-air interface.
As a by-product of the work on SEC products, also a Digital Elevation Model for Greenland (GrIS DEM) has been generated.
Ice Velocity (IV)
Glacier velocity and its spatial derivative strain rate (which is a measure of the ice deformation rate) are key variables for estimating e.g. ice discharge and mass balance and are essential input for glacier models that try to quantify ice dynamical processes. Changes in velocity and velocity gradients can point at changing boundary conditions. Remote sensing techniques that utilize SAR and optical satellite data are the only feasible manner to derive accurate surface velocities of the remote Greenland glaciers on a regular basis.
The ice velocity (IV) products generated in the Greenland Ice Sheet CCI are derived from both optical and SAR data using combinations of different techniques. Details of the methods are provided in the Algorithm Theoretical Basis Document (ATBD).
Ice velocity is provided as gridded velocity fields (maps) in NetCDF format with separate files for x and y velocity components (in m/yr). The velocity represents a mean velocity value over a time period ranging from the time span of the satellite repeat-cycle (between 1 to 46 days) to a full season or year for the ice sheet wide velocity maps.
Calving Front Location (CFL)
The Calving Front Location (CFL) of outlet glaciers from ice sheets is a basic parameter for ice dynamic modelling, computing mass fluxes and mapping glacier area change. From the ice velocity at the calving front and a time sequence of Calving Front Locations, the iceberg production rate can be computed, which is of relevance for estimating the export of ice mass to the ocean.
The CFL product is generated by a deep learning based model using optical satellite imagery (Sentinel-2). The digitized calving front is stored as vector lines in standard GeoJSON files. Additionally, metadata information on the sensor and processing steps are stored in corresponding attributes in the GeoJSON files. GeoJSON is an open standard format designed for representing simple geographical features (points, line strings, polygons, and collections), along with their non-spatial attributes.
Products by Science [&] Technology AS.
The CFL can also be derived by manual delineation using SAR and optical satellite data. The digitised calving front is stored as vector lines in standard GIS format. Additionally, metadata information on the sensor and processing steps are stored in the corresponding attribute table. In accordance with the URD, the vector files are provided in ESRI shape-file format. This product, generated by ENVEO, is currently not in production but it can still be downloaded from this website.
Grounding Line Location (GLL)
The grounding line location (GLL) marks the position of where a marine terminating glacier starts to float. Understanding the processes at the grounding line of outlet glaciers is important in order to predict the response of the ice to changing boundary conditions and to establish realistic future scenarios in response to climate change.
Remote sensing observations do not provide direct measurements of the grounding line position but can be used to detect the tidal flexure zone, using InSAR data, or spatial changes in texture and shading, using optical images, which are indicators of the transition from grounded to floating ice. Due to the plasticity of ice these indicators usually spread out over a zone upstream and downstream of the actual grounding line also called the grounding zone.
In the Greenland Ice Sheet CCI the grounding line location is derived from InSAR data by mapping the tidal flexure zone visible in interferograms. It is generated for selected glaciers with a floating ice tongue.
Gravimetric Mass Balance (GMB)
The Gravity Recovery and Climate Experiment (GRACE) twin satellites have been measuring changes in the Earth’s gravitational field between 2002 and 2017. Its follow-on mission GRACE-FO continues the time series since 2018. Time-variable gravity fields can be used to infer mass changes and mass redistributions in the Earth’s subsystems (e.g. the cryosphere). Mass variations of the Greenland Ice Sheet (GIS) can be measured with an accuracy of around 20 Gt/yr. In order to meet the IGOS (Integrated Global Observing Strategy) requirements as outlined in the GCOS-154 document SYSTEMATIC OBSERVATION REQUIREMENTS FOR SATELLITE-BASED DATA PRODUCTS FOR CLIMATE – 2011 Update: Supplemental details to the satellite-based component of the “Implementation Plan for the Global Observing System for Climate in Support of the UNFCCC (2010 Update)”, the Greenland Ice Sheet cci (GIS_cci) produces Gravimetric Mass Balance (GMB) products for the Greenland Ice Sheet from GRACE and GRACE-FO measurements. These products comprise monthly mass change time series for the entire GIS and different drainage basins as well as gridded mass change trends over different 5-year periods between.
GRACE/GRACE-FO data are available from different processing centres, including the Center for Space Research (CSR) at University of Texas, and the GeoForschungsZentrum (GFZ). Here, we use the CSR RL06 solution series (http://www2.csr.utexas.edu/grace/RL06.html), which includes spherical harmonic coefficients up to degree lmax=96.
Monthly spherical harmonic coefficients of changes in the Earth’s gravity field are available for the mission period. Different processing algorithms exist in order to derive the required information from the available data for the GIS. The round robin (RR) exercise carried out during the second phase of GIS_cci by TU Dresden has confirmed that the mass inversion and spherical harmonic filtering methods give comparable results. Therefore the GIS GMB setup is primarily based on the inversion method, method applied by DTU Space, where a direct estimate of mass changes are done in a direct least-squares generalized inverse processing. The choice of this method secures a consistency with the current Danish Polar Portal data (http://polarportal.dk), and a better and more explicit separation of Greenland mass changes from the mass changes from adjacent ice caps, especially northern Canadian ice caps in Ellesmere, Devon and Baffin Island. Details of the inversion method is outlined in the ATBD document. In addition, a second GMB product based on the regional integration approach using tailored sensitivity kernels is provided by TU Dresden.
As specified in the User Requirements Document (URD), user requirements for a gravimetric mass balance product (GMB) were found through a user survey for the Antarctic Ice Sheet cci (AIS_cci). The results were adopted for the GIS_cci.
Mass Flow rate and Ice Discharge (MFID)
The mass flow rate and ice discharge (MFID) product generated in the Greenland Ice Sheet CCI are derived from the CCI ice velocity (IV) product, the CCI surface elevation change (SEC) product, and ice thickness from BedMachine (v3). Details of the methods are provided in the Algorithm Theorotical Basis Document (ATBD) or in Mankoff /et al./ (2019).
MFID is provided as a time series CSV file where each column represents one sector from Zwally (2012) with units in Gt/yr. Additional files provide error estimates and coverage (a measure of gap-filling).
The product is generated by GEUS.
Supraglacial Lakes (SGL)
Supraglacial Lakes (SGL) are meltwater lakes that form in depressions at the surface of the ice sheet in the ablation zone. Supraglacial lakes are indicators of surface melt, and are a major component of routing and storage of meltwater at the ice sheet surface. These play an important role in the delivery of meltwater to the base of the ice sheet. The delivery of water to the base of glaciers and ice sheets has been observed to influence basal sliding on a range of spatio-temporal scales, as well as play a pivotal role in the seasonal evolution of the subglacial drainage system.
The SGLs are derived from Sentinel-2 optical data using an automated Normalised Difference Water Index (NDWI). These products are produced for selected regions of interest, and version 1.1 is for the Sermeq Kujalleq (Jakobshavn Isbrae) hydrological catchment, as defined by Mankoff et al. 2020. The lake outlines are stored as standard vectorised polygons, with additional metadata stored in the attribute table. The detected lakes are filtered according to maximum recorded surface area and a mask of SGL basins from DEM sink filling is applied to remove false positives.
The product is a R&D CCI+ activity and it is generated by Asiaq (Greenland).
