About

Eric Rignot is the Donald Bren Professor of Earth System Science at the University of California, Irvine, where he also serves as Chair of the Department. He is a member of the National Academy of Sciences and has been with UCI since 2007. Prior to joining UCI, he worked at NASA's Jet Propulsion Laboratory (JPL), where he continues to serve as a Senior Research Scientist. Eric holds a Ph.D. in Electrical Engineering from the University of Southern California and is an engineer from Ecole Centrale Paris, France. He is an expert on polar ice sheets and the effects of global climate change on the cryosphere. His research integrates satellite and airborne remote sensing data, field oceanographic surveys, and computer modeling using tools such as the JPL/UCI Ice Sheet System Model (ISSM) and the MIT general circulation model (MITgcm) to study glacier dynamics along the coasts of Antarctica, Greenland, Alaska, and Patagonia. His work has documented the acceleration of ice loss in these regions due to climate change and highlighted the critical role of ice-ocean interactions in driving glacier systems out of balance more rapidly than previously understood.

Research topics

• Geology
• Geomorphology
• Oceanography
• Climatology
• Physical geography
• Geography

Selected publications

• Data from: Seawater intrusions control the retreat of Thwaites Glacier, West Antarctica

  Zenodo (CERN European Organization for Nuclear Research) · 2026-02-26

  datasetOpen access

  README The content of this repository is from: Seawater intrusions control the retreat of Thwaites Glacier, West Antarctica (under review). Description of the data and file structure File description: runme.m: MATLAB script to reproduce results presented in the manuscript. Notably, the sensitivity simulations discussed in the paper are initialized and run in step 16. Thwaites.mat: All data associated with the ice sheet model initial state is included in Thwaites.mat, after spin-up (step 11 in readme.m). The file contains a MATLAB ‘model’ object. Usage notice: In MATLAB, the model can be loaded and displayed by running load(‘Thwaites.mat’), which will load in the model variable ‘md’. Of particular interest will be the following data contained in md: md.mesh (mesh information), md.geometry (initial ice sheet geometry, ice shelf geometry, and bed topography), and md.mask (ice mask and grounded ice mask). Note that all fields are defined on the mesh nodes, and one can plot a given field in MATLAB using the ISSM tool ‘plotmodel’. Ice sheet modeling results and initial states are compatible with the open source, NASA funded Ice-sheet and Sea-level System Model (ISSM, Larour et al. 2012), which is freely available for download on Github. In addition, the data files provided in the publication are available as *.mat files, which are compatible with MATLAB but can be accessed using most scripting languages.

  PublisherDOI

• Brief communication: Updated grounding line mapping in the Amundsen Sea Embayment, Antarctica, from one day repeat Sentinel-1 SAR data

  ˜The œcryosphere · 2026-03-16 · 1 citations

  articleOpen access

  Abstract. Knowledge of Antarctic glacier grounding lines, which mark the transition between grounded and floating ice, is a vital parameter in determining the stability of major ice shelves and hence the ice sheet. Rapid grounding line retreat and associated mass loss has been documented at numerous Antarctic glaciers, particularly in the Amundsen Sea Embayment. However, few comprehensive grounding line mappings exist, particularly from recent years. Here, we utilize a unique record of Sentinel-1 Synthetic Aperture Radar 1 d repeat-pass imagery to generate a comprehensive retrieval of grounding line location in the Amundsen Sea Embayment in 2025 and evaluate recent changes.

  PublisherDOI

• Thirty years of glacier grounding line retreat in Antarctica

  Proceedings of the National Academy of Sciences · 2026-03-02 · 2 citations

  articleOpen access1st authorCorresponding

  The Grounding Line (GL)—the transition from ice grounded on the continent and ice afloat in the ocean—is a sensitive indicator of glacier stability and mass balance. Using differential synthetic aperture radar interferometry from ERS-1/2, Sentinel-1, RADARSAT-1/2, RADARSAT Constellation Mission, ALOS PALSAR-2, COSMO-SkyMed, and ICEYE, we assemble a continental scale record of grounding line migration from 1992 to 2025. Over 77 ± 10% of Antarctic coastal length, we detect no GL migration. Retreat is concentrated in i) the Antarctic Peninsula–2 to 18 km along Larsen A-B and 2 to 6 km along parts of George VI; ii) Wilkes and George V lands–6 to 10 km on Denman, Totten, Moscow, Frost, Holmes, Mertz, Ninnis, and Cook, and 26 km on Vanderford; and iii) West Antarctica–5 to 7-km on Ferrigno, Fox, and Venable, with extreme retreat in the Amundsen and Getz sectors (Pine Island 33 km, Thwaites 26 km, Haynes 20 km, Pope 23 km, Smith 42 km, Kohler 12 km, East Getz 9 km toward Berry 18 km, Hull 14 km, and Land 5 km). The ice sheet lost 12,820 ± 1,873 km 2 of grounded ice in 1996–2025, or 442 ± 64 km 2 /y, with 62% from West Antarctica and 28% from East Antarctica. Retreat clusters in areas where bathymetry channelizes warm Circumpolar Deep Water toward deep grounding zones where beds are retrograde, except in the northeastern Antarctic Peninsula. The results provide a harmonized benchmark for ice grounding zone-based ice sheet models and identifies gateways where future retreat is likely to accelerate.

  PublisherDOI

• Machine-learned global glacier ice volumes

  2026-03-13

  articleOpen accessCorresponding

  Knowledge of glacier ice volumes is crucial for constraining future sea level rise, evaluating freshwater resources, and assessing impacts on societies, from regional to global. Yet, significant uncertainties persist in both regional estimates of total glacier ice volume and in distributed ice thickness for individual glaciers. Here, we present the results from IceBoost v2.0, a machine learning system able to model the ice thickness of individual glaciers, trained on 7 million ice thickness measurements and informed by physical and geometrical predictors. Globally, we find a total glacier volume of (149 ± 38) × 103 km3 and sea level equivalent of 323 ± 91 mm, both well within existing estimates. We examine major glaciated regions and compare the results with other models. Confidence in our solution is highest at higher latitudes, where abundant training data adequately sample the feature space. Over steep and mountainous terrain, small glaciers, and under-represented lower-latitude regions, confidence is lower. IceBoost v2.0 demonstrates strong generalization at ice sheet margins. On the Geikie Plateau, East Greenland, we find nearly twice as much ice compared to BedMachine v3, highlighting the method's potential to refine the bed topography in parts of the ice sheets. The quality of the modeled ice thickness depends on the accuracy of the training data, the digital elevation model, ice velocity fields, and glacier geometries, including nunataks. We present the released dataset of ice thickness and associated uncertainty for all glaciers within the Randolph Glacier Inventory version 6 and 7, totaling half a million maps. This may be useful for modeling glacier dynamics, future evolution and sea-level rise, informing the design of glaciological surveys, field campaigns, as well as guiding policies on freshwater management.

  PublisherDOI

• On the Correction of the Penetration-Related Elevation Bias in Harmony Cross-Track InSAR Products of Ice Sheets and Glaciers

  elib (German Aerospace Center) · 2026-06-01

  other
  Publisher

• Data from: Seawater intrusions control the retreat of Thwaites Glacier, West Antarctica

  Open MIND · 2026-02-26

  dataset

  README The content of this repository is from: Seawater intrusions control the retreat of Thwaites Glacier, West Antarctica (under review). Description of the data and file structure File description: runme.m: MATLAB script to reproduce results presented in the manuscript. Notably, the sensitivity simulations discussed in the paper are initialized and run in step 16. Thwaites.mat: All data associated with the ice sheet model initial state is included in Thwaites.mat, after spin-up (step 11 in readme.m). The file contains a MATLAB ‘model’ object. Usage notice: In MATLAB, the model can be loaded and displayed by running load(‘Thwaites.mat’), which will load in the model variable ‘md’. Of particular interest will be the following data contained in md: md.mesh (mesh information), md.geometry (initial ice sheet geometry, ice shelf geometry, and bed topography), and md.mask (ice mask and grounded ice mask). Note that all fields are defined on the mesh nodes, and one can plot a given field in MATLAB using the ISSM tool ‘plotmodel’. Ice sheet modeling results and initial states are compatible with the open source, NASA funded Ice-sheet and Sea-level System Model (ISSM, Larour et al. 2012), which is freely available for download on Github. In addition, the data files provided in the publication are available as *.mat files, which are compatible with MATLAB but can be accessed using most scripting languages.

  DOI

• Observation and Coordination Needs for Current, Near‐Future, and Next Generation Earth‐Observing SAR Systems

  Earth and Space Science · 2026-05-01

  articleOpen access

  Abstract This paper summarizes an evaluation by experts of how coordination of Earth‐observing Synthetic Aperture Radar (SAR) missions among the world's space agencies could advance toward game‐changing scientific discoveries and fully realizing SAR's practical capability to address many issues facing society. We consider key science disciplines for which spaceborne SAR sensors are routinely used, with an emphasis on SAR imaging instruments. We outline the current state of the science and identify critical information gaps for 10 disciplines: Ice Sheets and Glaciers, Solid Earth Science, Hazards, Forests and Biomass, Wetlands, Agriculture and Crop Monitoring, Soil Moisture, Sea Ice, Permafrost, and Oceans. We provide recommendations on how these gaps can be addressed by coordination of missions currently operating or in development, then look forward to the next decade during which as‐yet‐unplanned coordinated SAR constellations could be game‐changing. We identify synergies and conflicts between the optimal SAR configurations required for individual disciplines to achieve transformational science advancement. Finally, we provide summary recommendations for beneficial coordination that consider SAR‐enabled Earth science studies both as a whole and within the context of multiple individual disciplines that have benefited from a common observational strategy. Overall, there are clear benefits that can be derived from coordinated utilization of spaceborne SAR assets based on their individual capabilities and availability, and through coordinated and shared data and observation strategies.

  PublisherDOI

• Bedmap3 updated ice bed, surface and thickness gridded datasets for Antarctica

  Scientific Data · 2025-03-10 · 47 citations

  articleOpen access

  We present Bedmap3, the latest suite of gridded products describing surface elevation, ice-thickness and the seafloor and subglacial bed elevation of the Antarctic south of 60 °S. Bedmap3 incorporates and adds to all post-1950s datasets previously used for Bedmap2, including 84 new aero-geophysical surveys by 15 data providers, an additional 52 million data points and 1.9 million line-kilometres of measurement. These efforts have filled notable gaps including in major mountain ranges and the deep interior of East Antarctica, along West Antarctic coastlines and on the Antarctic Peninsula. Our new Bedmap3/RINGS grounding line similarly consolidates multiple recent mappings into a single, spatially coherent feature. Combined with updated maps of surface topography, ice shelf thickness, rock outcrops and bathymetry, Bedmap3 reveals in much greater detail the subglacial landscape and distribution of Antarctica's ice, providing new opportunities to interpret continental-scale landscape evolution and to model the past and future evolution of the Antarctic ice sheets.

  PublisherOA PDFDOI

• Bathymetry of the Antarctic continental shelf and ice shelf cavities from circumpolar gravity anomalies and other data

  Scientific Reports · 2025-01-07 · 13 citations

  articleOpen access

  Bathymetry critically influences the intrusion of warm Circumpolar Deep Water onto the continental shelf and under ice shelf cavities in Antarctica, thereby forcing ice melting, grounding line retreat, and sea level rise. We present a novel and comprehensive bathymetry of Antarctica that includes all ice shelf cavities and previously unmeasured continental shelf areas. The new bathymetry is based on a 3D inversion of a circumpolar compilation of gravity anomalies constrained by measurements from the International Bathymetric Chart of the Southern Ocean, BedMachine Antarctica, and discrete seafloor measurements from seismic and ocean robotic probes. Previously unknown troughs with thicker ice shelf cavities are revealed in many parts of Antarctica, especially East Antarctica. The greater depths of troughs on the continental shelf and ice shelf cavities imply that many glaciers are more vulnerable to ocean subsurface warming than previously thought, which may increase the projections of sea level rise from Antarctica.

  PublisherOA PDFDOI

• A call for integrated and cooperative global sharing of China’s Earth observation data

  Nature Geoscience · 2025-10-30 · 2 citations

  article
  PublisherDOI

Recent grants

• Three-dimensional Stokes grounding line dynamics with the open community JPL/UCI Ice Sheet System Model (ISSM).

  NSF · $275k · 2011–2014

Frequent coauthors

• J. Mouginot

  Institut polytechnique de Grenoble

  634 shared

• Mathieu Morlighem

  340 shared

• Romain Millan

  Université Grenoble Alpes

  235 shared

• B. Scheuchl

  196 shared

• Hélène Seroussi

  Dartmouth College

  180 shared

• I. Velicogna

  161 shared

• Eric Larour

  150 shared

• M. R. van den Broeke

  Utrecht University

  125 shared

Labs

• Rignot Research GroupPI

Education

• PhD, Electrical Engineering

  University of Southern California

• Master, Electrical Engineering

  University of Southern California

• Master, Aerospace Engineering

  University of Southern California

• Master, Air Espace

  Ecole centrale de Paris