C51B-0708
Extending the Record of Greenland Ice Sheet Subsurface Meltwater: Exploring New Applications of Satellite Remote Sensing Data
Friday, 18 December 2015
Poster Hall (Moscone South)
Margeaux Carter, New Mexico Institute of Mining and Technology, Earth and Environmental Sciences, Socorro, NM, United States, David B Reusch, New Mexico Institute of Mining and Technology, Department of Earth and Environmental Science, Socorro, NM, United States and Christopher Charles Karmosky, University of Tennessee Martin, Department of Agriculture, Geosciences and Natural Resources, Martin, TN, United States
Abstract:
The discovery of pervasive year-round englacial meltwater in southeastern Greenland by Forster et. al (2012) in the form of a Perennial Firn Aquifer (PFA) with an estimated 140+/120 GT of water (pre-2011 melt season) has significantly changed the understanding of meltwater retention, energy balance models and Greenland hydrology. Prior to this, englacial meltwater was not considered a significant portion of the water budget in Greenland. The cryosphere and hydrology communities are currently observing and studying PFAs through data obtained from the NASA ICEBridge Program. Due to environmental and time constraints, data is limited to a few months each year beginning in 2010. This leaves a significant need to explore new methods of monitoring PFAs both throughout the year and across time in order to improve the understanding of PFA formation and hydrologic consequences. Both passive microwave and infrared radiation have been used to monitor surface melt via satellite remote sensing, are recorded regularly over Greenland, and are available from 1979. While infrared data are confined to the surface, microwaves have been noted to penetrate past the ice sheet surface and return a subsurface melt signal. A combination of microwave and infrared reflectance signals has the potential to identify subsurface meltwater distinct from surface melt throughout the year. This method of identifying englacial meltwater will be compared to recognized data sets, and correlated to meteorological requirements to determine accuracy. If this method proves effective, it could significantly extend the record of PFA location and physical and temporal extent so that hydrologic and climatic results can be better analyzed.