Unique insights into firn structure across western Greenland’s percolation zone from hyperspectral images of shallow firn cores

Abstract

The physical structure of the firn column directly influences the transport and storage of infiltrating water generated by surface melt in ice sheet accumulation zones. Firn density is relatively easy to measure in field or laboratory settings and provides porosity-based estimates of the meltwater storage capacity but does not describe meltwater movement through open pore space. Pore structure controls meltwater flow and is better characterized by microstructural parameters, such as grain size. Firn grain size is therefore a state variable that needs to be accurately modeled or measured to quantify meltwater transport and storage in the firn column. Manually or digitally measuring grain size from firn samples can be tedious, time consuming, and subjective. Here, we characterize firn structure from 14 firn cores spanning approximately 1000 km across western Greenland’s percolation zone. We scanned the top 10 m of each core with a near infrared hyperspectral imager (NIR-HSI; 900-1700 nm) mounted on a linear translation stage. Leveraging the relationship between ice grain size and near infrared absorption, we invert measured reflectance to retrieve an effective grain radius, resulting in a high-resolution (~ 0.4 mm) grain size map of the firn core. We compare the retrievals against traditional grain size measurements from 7 of the cores. Additionally, the hyperspectral firn core grain size maps allow for quickly retrieving vertical ice layer distributions within the firn column and identifying regions that have been previously wetted that are not readily apparent by visual inspection. We use our unique dataset to examine correlations between grain size, infiltration ice content, and measured firn density to determine whether microstructural information can be extracted from firn density measurements. While cores provide a snapshot of firn conditions at the time of collection, we show that hyperspectral imaging of firn cores can reveal a detailed hydrologic history of the firn column and provide validation data for modeling future meltwater percolation.