Applying advanced materials characterization techniques for an enhanced understanding of firn and snow properties

Abstract

Understanding snow microstructure and stratigraphy is critical for enhancing modeling efforts and instrument validation for the polar regions and seasonal snow. Controlled laboratory experiments help with these efforts and are essential for enhanced comprehension of polar firn densification, snow metamorphism, avalanche mechanics, snow hydrology, and radiative transfer properties. This dissertation aims to characterize snow and ice as they relate to the mechanical and sintering properties of simulated firn subject to trace amounts of sulfuric acid (H 2SO 4). Studies were also developed to characterize faceted snow crystallographic orientation using electron backscatter diffraction (EBSD) and understand the observed reflectance of remote sensing instruments related to mapping changing snow microstructure. To investigate the effects of soluble impurities, 50 ppm H 2SO 4 and impurity-free ice grains were developed to simulate polar firn and then subjected to a series of unconfined uniaxial compression to monitor the effect in mechanical strength at different temperatures and strain rates. Meanwhile, the role of sintering is less defined for ice grains that contain impurities. Two experiments were developed to quantify sintering rates with H 2SO 4. One experiment tracked the changes in microstructure at isothermal conditions using X-ray computed microtomography over 264 days. A second experiment used angle of repose tests to characterize the subsecond sintering between H 2SO 4 and impurity-free ice grains. In addition, it is well known that snow has constantly changing microstructure once deposited during precipitation events. These changes have an immediate impact on the crystallographic and optical properties. Faceted snow crystals, collected from the field and artificially grown, were analyzed using EBSD to map vapor-deposited growth along the three ice (Ih) crystallographic planes. Moreover, validation of remote sensing techniques such as near-infrared hyperspectral imaging (NIR-HSI) and lidar is essential for accurate field measurements. In the laboratory, an intercomparison test was conducted for NIR-HSI and lidar to analyze bidirectional reflectance returns, mapping the effective grain size of snow under different microstructural conditions and during melt/freeze events and surface hoar growth.