Quantifying the accuracy of snow water equivalent estimates using broadband radar signal phase

Abstract:

Radar wave velocity in dry snow depends solely on density. Consequently, ground-based pulsed systems can be used to accurately measure snow depth and snow water equivalent (SWE) using signal travel-time, along with manual depth-probing for signal velocity calibration. Travel-time measurements require a large bandwidth pulse not possible in airborne/space-borne platforms. In addition, radar backscatter from snow cover is sensitive to grain size and to a lesser extent roughness of layers at current/proposed satellite-based frequencies (~ 8 – 18 GHz), complicating inversion for SWE. Therefore, accurate retrievals of SWE still require local calibration due to this sensitivity to microstructure and layering. Conversely, satellite radar interferometry, which senses the difference in signal phase between acquisitions, has shown a potential relationship with SWE at lower frequencies (~ 1 – 5 GHz) because the phase of the snow-refracted signal is sensitive to depth and dielectric properties of the snowpack, as opposed to its microstructure and stratigraphy. We have constructed a lab-based, experimental test bed to quantify the change in radar phase over a wide range of frequencies for varying depths of dry quartz sand, a material dielectrically similar to dry snow. We use a laboratory grade Vector Network Analyzer (0.01 – 25.6 GHz) and a pair of antennae mounted on a trolley over the test bed to measure amplitude and phase repeatedly/accurately at many frequencies. Using ground-based LiDAR instrumentation, we collect a coordinated high-resolution digital surface model (DSM) of the test bed and subsequent depth surfaces with which to compare the radar record of changes in phase. Our plans to transition this methodology to a field deployment during winter 2014-2015 using precision pan/tilt instrumentation will also be presented, as well as applications to airborne and space-borne platforms toward the estimation of SWE at high spatial resolution (on the order of meters) over large regions (> 100 square kilometers).