News and Events
New Cryosphere paper exploring the uncertainty in continental Antarctic Ice Sheet projections  more >>
We investigate how regional warming has expanded water-filled crevasse ponds in the shear margins of Jakobshavn Isbræ and impacted ice flow.  more >>
The SHMIP results feature the two subglacial hydrology models implemented in ISSM.  more >>
New Cryosphere paper assesses the importance of sub-element parameterization of basal melt to capture grounding line motion  more >>


to the Ice Sheet System Model (ISSM) website. ISSM is the result of a collaboration between the Jet Propulsion Laboratory and University of California at Irvine. Its purpose is to tackle the challenge of modeling the evolution of the polar ice caps in Greenland and Antarctica.
ISSM is open source and is funded by the NASA Cryosphere, IceBridge Research and MAP (Modeling Analysis and Prediction) programs, JPL R&TD (Research, Technology and Development) and the National Science Foundation.
As synthesized in the last Intergovernmental Panel on Climate Change (IPCC) Assessment Report AR5, "significant uncertainties remain, particularly related to the magnitude and rate of the ice-sheet contribution for the 21st century and beyond".
To address this problem, large scale ice flow models are necessary that can accurately model the evolution of Greenland and Antarctica in a warming climate. In order to achieve this goal, and improve projections of future sea level rise, ISSM relies on state of the art technologies. These include:
  • Finite Element Modeling, which allows for the use of unstructured meshes to reach high resolutions in areas where ice flow dynamics is critical.
  • Higher-order ice dynamics: instead of relying on the Shallow Ice Approximation (SIA), ISSM includes a suite of model of increasing complexity, including Full-Stokes.
  • Parallel technologies, using state of the art clusters such as the NASA Advanced Supercomputing Pleiades cluster. This allows ISSM to run bigger models, with a faster turn around.
  • Anisotropic mesh refinement, which allows ISSM to zoom in on areas of interest, while saving computational resources by using coarse meshes where ice flow is stagnant.
  • Data assimilation using inverse methods to infer unknown parameters from observations, using either variational data assimilation or using automatic differentiation.
  • Sensitivity analysis tools, based on the Dakota toolkit from Sandia National Laboratories. This suite of tools allows ISSM to constrain projections of future sea level rise, and to assess the reliability of such projections.

Capability Support

Capability Support Contacts
Stress balance ISSM team
Thermal Seroussi
Mass transport ISSM team
Transient ISSM team
Static inversions (friction, B) ISSM team
Mesh generation Morlighem
Grounding line (hydrostatic) ISSM team
Python Interface De Fleurian
UQ (dakota) Schlegel
Balance velocities Morlighem
Calving Morlighem
Damage Borstad
Rifts Larour
Hydrology De Fleurian (DC) & Sommers (SHAKTI)
Grounding line (FS, contact) Seroussi
Mass Conservation Morlighem
Adaptive Mesh Refinement dos Santos
GIA Caron
Crustal displacement Adhikari
MITgcm coupling Seroussi
Automatic Differentiation Larour & Morlighem
Sea level Larour & Adhikari
Production (fully Supported)
Development (not fully supported)
Experimental (not supported)