At present, the greenland ICE sheet is undergoing rapid changes, losing mass to the ocean at an increasing rate. Various techniques have been used to document these changes, including radar/laser…

This is a $461,480 grant awarded by the National Aeronautics and Space Administration (NASA) to the University of California, Irvine (UC Irvine) on June 2, 2018. The grant supports research to better quantify the uncertainty and model the runoff production from surface melt, which is a key component of the mass loss of the Greenland ice sheet. The research will leverage data from automated weather stations, snow pits, and ice cores to evaluate the ability of regional atmospheric climate models and global climate models to accurately represent runoff. No set-aside designation was indicated. UC Irvine is a major public research university that has received numerous federal grants and contracts for research and development work across various agencies, including the Department of Defense, Department of Energy, and Department of the Navy. The State of California Controller's Office serves as the parent organization for UC Irvine and has also secured federal grants and contracts to provide technical support, product development, and financial assistance for students.

At present, the greenland ICE sheet is undergoing rapid changes, losing mass to the ocean at an increasing rate. Various techniques have been used to document these changes, including radar/laser altimetry, time-variable gravity, and mass budget combining ICE discharge with surface mass balance (SMB) reconstructions from regional atmospheric climate models (RCM). This proposal addresses the largest remaining uncertainty in ICE sheet mass balance which is the runoff production from surface melt. While snowfall accumulation from RCM and MERRA2/geos-5 global climate model (GCM) has been evaluated in detail from a network of automated weather stations (AWS), snow PIT and ICE core data, runoff is known with a default uncertainty of 20% due to a lack of in-situ data for evaluation. As runoff will remain a dominant component of the mass loss for decades to centuries to come, IT is imperative to better quantify its uncertainty and document the RCM/GCM ability to model IT.