The DTC Ice Sheets Project is part of the European Space Agency’s Digital Twin Earth (DTE) initiative, developed under the Lead Digital Twin Components (DTC) Development Actions for the Ice Sheets.
Our goal is to design, implement, and validate a pre-operational digital twin of the Greenland and Antarctic ice sheets and ice shelves (DTC-IS). By integrating Earth Observation (EO) data with advanced computational models, the aim of the DTC-IS is to fully represent the ice sheets system and address issues related to hydrology, ice shelf and ice sheet stability, ice sheet mass balance, and climatology.
The Greenland and Antarctic ice sheets are essential to the Earth system, storing vast freshwater reserves and driving sea level, ocean, and climate dynamics. Their evolution, through ice flow, surface melting, calving, and basal melting, affects ecosystems, coastal regions, and global climate. Through modular, interactive tools and stakeholder-driven use cases, the DTC-IS provides a near-real-time, science-based platform for exploring the state of the ice sheets and for performing “what-if” scenarios, supporting research, and decision-making and policies.
For an interactive introduction to the project’s themes and objectives, explore our DEA story, or continue reading to learn about the datasets, modules, and use cases that make up the DTC-IS system.
EO and Complementary Datasets
Our work builds on a broad range of Earth Observation (EO) datasets, which form a central foundation for modelling, analysis, and validation within the DTC Ice Sheets system. In addition to EO data, the digital twin also integrates complementary datasets, including numerical model outputs and other data sources that support data-driven modelling and system development within DTC-IS.
Below, you can explore key datasets and precursor projects that underpin the digital twin component.
Surface elevation change
Description
Radar altimetry–derived surface elevation change rates, providing a consistent multi-mission climate data record from 1992 to present.
Spatio-temporal coverage
Gridded 5 km monthly products, updated tri-monthly
Precursor projects
Supraglacial lake maps
Description
Optical satellite imagery–derived maps of supraglacial lakes on the Greenland ice sheet.
Spatio-temporal coverage
Seasonal to annual spatial products
Precursor projects
Surface elevation change
Description
Satellite radar altimetry-derived surface elevation change measurements using swath processing techniques.
Spatio-temporal coverage
Gridded 2 km monthly products updated monthly
Precursor projects
Ice sheet topography
Description
Stereoscopic imagery measurements providing a high resolution digital elevation map of Antarctica.
Spatio-temporal coverage
Gridded product
Precursor projects
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Calving front
Description
Time evolving Antarctic calving fronts derived from satellite altimetry measurements.
Spatio-temporal coverage
Gridded and vector monthly to annual products
Precursor projects
Ice velocity
Description
Sentinel-1 derived ice velocity data over Greenland and Antarctica.
Spatio-temporal coverage
Gridded monthly and yearly products
Precursor projects
Ice shelf basal melt rate
Description
Basal melt rates derived from satellite altimetry measurements.
Spatio-temporal coverage
Gridded product
Precursor projects
Surface melt maps
Description
Surface melt maps using passive microwave radiometry data.
Spatio-temporal coverage
Gridded daily product
Precursor projects
Sea ice
Description
Sea ice maps for both sea concentration and edge using satellite passive microwave temperature.
Spatio-temporal coverage
Gridded monthly product
Precursor projects
Ice shelf mass balance components
Description
Constituent components of ice shelf mass balance for the Antarctic ice shelves.
Spatio-temporal coverage
Annual time series
Precursor projects
Atmospheric variability
Description
Southern hemisphere annular mode index calculated from the mean sea level pressure between approximately 40°S and 65°S.
Spatio-temporal coverage
Monthly time series
Precursor projects
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Ocean moorings
Description
Time series of ocean temperature, salinity, and current velocity from moored instruments.
Spatio-temporal coverage
Time series
Precursor projects
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Subglacial lake flux
Description
Radar altimetry–derived maps and time series of Antarctic subglacial lake activity.
Spatio-temporal coverage
Monthly time series
Precursor projects
Regional climate models
Description
Numerical regional climate model data supporting EO datasets and data-driven modelling within the DTC-IS framework.
Spatio-temporal coverage
Gridded monthly products
Precursor projects
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Ocean reanalysis
Description
Global ocean reanalysis products supporting ice–ocean interaction studies.
Spatio-temporal coverage
Gridded monthly products
Precursor projects
Atmospheric reanalysis
Description
Global atmospheric and land-surface reanalysis supporting ice–atmosphere interaction studies.
Spatio-temporal coverage
Gridded hourly to monthly products
Precursor projects
Our Modules
Our system is built from a set of functional modules, each tackling specific tasks to help us understand and predict ice-sheet behaviour. Some modules address ice-sheet processes directly, while others provide more general-purpose data and analysis capabilities.
Select a module below to explore its functionality, input and output specifications, and role within our digital twin component.
Ice Sheet-Specific Modules
Ice Sheet Mass Balance
Sea-Level Response EMulator (SELREM)
Damage Forecasting
Generic Modules
Gaussian Random Field (GRF)
Functional Time Series/Extremes
Super Resolution Modelling
Spatiotemporal Insights
Covariate Analyser
Change Detection
Our Use Cases
The DTC will address four specific use cases:
- 🔋 Hydropower (led by Lancaster University) – Predict climatically driven changes to freshwater flux from the Greenland Ice Sheet into the proglacial environment.
- 🌊 EU Sea Level Response Fingerprint(led by Technical University of Denmark) – Simulate and predict the impact of melting ice sheets on sea levels within the EU.
- ❄️ State and Fate of Antarctic Ice Shelves (led by University of Edinburgh) – Provide up-to-date reconstruction of Antarctic Ice Shelves and their interactions with the ice sheet, atmosphere, and ocean, and forecast their evolution.
- 🌍 Enhanced Surface Climate (led by Katholike Universiteit Leuven) – Leverage super-resolution modeling techniques to enhance the monitoring and prediction of surface climate conditions over Greenland and Antarctica.
Contact
For more information about the DTC Ice Sheets project, please contact the Project Science Lead, Sebastian B. Simonsen, or the Project Manager, Kirsty Wilson.