This $411,096 federal Project Grant award was provided by the National Science Foundation's Polar Programs (CFDA 47.078) to The Leland Stanford Junior University (Stanford University). The project aims to utilize machine learning and physics-based models to map and understand how surface meltwater on the Greenland ice sheet reaches the bedrock, which can impact ice sheet dynamics and response to climate change. Key products and services to be delivered include: Development of open-source deep...
This $191,725 National Science Foundation Project Grant supports research at Lehigh University to develop artificial intelligence solutions for navigating and analyzing big data from polar ice sheets. Funded through the NSF's Computer and Information Science and Engineering program, the one-year award will investigate deep learning and hybrid machine learning approaches to automatically mine and understand heterogeneous datasets collected by the Center for Remote Sensing of Ice Sheets....
This $127,350 project grant from the National Science Foundation Division of Polar Programs, under the Polar Programs federal grant program (CFDA 47.078), will support collaborative research to improve modeling of terminus ablation for Greenland's outlet glaciers. The researchers will use machine learning to analyze glaciological observations and better understand the variables influencing the ice-ocean boundary. They will develop an equation to represent ice-ocean interactions in an ice sheet...
The National Science Foundation awarded a $269,223 Project Grant to the University of Texas at Austin from the Polar Programs federal grant program (CFDA 47.078) to support research titled "Collaborative Research: Machine-Enabled Modeling of Terminus Ablation for Greenland's Outlet Glaciers." The research aims to improve projections of sea-level rise from Greenland through developing physics-based modeling of ice-ocean interactions at outlet glaciers using machine learning analysis...
This $325,213 Project Grant awarded by the National Science Foundation's (NSF) Division of Polar Programs (CFDA 47.078) to The Trustees of Columbia University in the City of New York will investigate the role of meltwater in governing the geophysical properties of deforming icy systems. The project aims to create new flow laws that explicitly incorporate the effects of meltwater on ice flow, which is a key factor in modeling glacial mass loss and sea level rise. The research will employ...
The National Science Foundation awarded a $2.8 million project grant under the Geosciences program (CFDA 47.050) to Virginia Polytechnic Institute and State University for the period of October 1, 2022 to December 31, 2026. The project aims to map changes in Greenland resulting from ice thinning and explore emerging landslide and hazard risks. Researchers will integrate local observations from Greenlandic communities with remote sensing data to understand how hazards evolve over time. Advanced...
This $1,263,530 National Science Foundation award through the Mathematical and Physical Sciences program (CFDA 47.049) will fund research into the dynamics of melting ice. New York University will investigate ice melting through laboratory experiments, numerical simulations, mathematical modeling, and analysis. Researchers will study melting in idealized settings and increasingly complex situations involving changing geometry, temperature, and salinity. Experiments will precisely measure...
This Project Grant award of $317,795 from the National Science Foundation Division of Polar Programs (CFDA 47.078) supports research by the Colorado School of Mines to disentangle the internal and basal processes that influence ice sheet flow and contribute to sea-level rise. The project combines satellite remote sensing data with ice-penetrating radar observations to partition the contributions of internal and basal friction within the ice sheet. Key efforts include developing open-source...
This National Science Foundation (NSF) Polar Programs (CFDA 47.078) Project Grant awarded to Morgan State University for $157,585 from December 1, 2024 to March 31, 2027 supports collaborative research to disentangle the impacts of runoff and ocean terminus dynamics on the flow velocity of fast-flowing outlet glaciers. The research aims to improve understanding of how liquid water input and ocean processes affect ice flow speed, which is essential for forecasting future ice loss and sea level...
This Project Grant award from the National Science Foundation's Polar Programs (CFDA 47.078) will fund a $408,486 study at the University of Washington to conduct a large-scale assessment of iceberg mélange (a mixture of sea ice and icebergs) and its impacts on glacier retreat in Greenland. The 3-year project will utilize satellite data to map the location and timing of mélange formation and breakup around the Greenland ice sheet, and then compare this to measurements of changing glacier...
This $191,868 National Science Foundation project grant supports research to understand surface-to-bed meltwater pathways across the Greenland Ice Sheet. Funded through the Polar Programs grant program (CFDA 47.078), the award will utilize machine learning and physics-based models to map cracks and draining lakes on the ice sheet from satellite imagery. Researchers at the University of Kansas Center for Research will develop open-source artificial intelligence codes to automatically detect ice sheet surface features at scale. This will generate continent-wide databases of surface features for mechanistic modeling of conditions creating new surface-to-bed pathways and their impact on ice sheet dynamics. Additionally, the project aims to foster US-UK collaboration and establish a mentoring program for underrepresented doctoral students in cryospheric sciences. The research products will provide insight into ice sheet response to climate change by better elucidating evolving hydrology and meltwater drainage roles in dynamic responses.