The National Science Foundation Division of Polar Programs awarded the University of Pennsylvania $153,965 on October 1, 2025, under the Polar Programs assistance listing (CFDA 47.078) to support collaborative research with UK partners funded jointly by NSF and the UK's Natural Environment Research Council.
The award funds development of machine-learning and physics-based models to understand how surface meltwater on the Greenland Ice Sheet reaches the bed and affects ice sheet movement. The research team will use deep learning algorithms to identify cracks and draining lakes in satellite imagery, then apply mathematical models to understand crack formation and its impact on ice dynamics. The project emphasizes open-source artificial intelligence code development and supports US-UK collaboration alongside training for students and junior scientists.
The University of Pennsylvania is the recipient, with place of performance in Philadelphia, Pennsylvania. The period of performance runs from October 1, 2025, through January 31, 2027. The funding mechanism is a project grant with $153,965 obligated. Under the NSF/GEO-NERC lead agency agreement, NSF funds the proportion of the budget supporting US-based investigators while NERC funds the UK portion through a single joint peer-reviewed proposal process.