Using Simulated Clusters to Analyze and Develop Snow Radar Products in Grand Mesa, Colorado

Abstract

Obtaining timely basin-scale winter and early spring characteristics of snowpack in the Western United States are important for modeling water availability during the melt season, especially with increased warming due to anthropogenic climate change. Using an ultra-wideband (UWB) frequency modulated continuous wavelength (FM-CW) airborne radar sensor (2-18 GHz), we are able to map snow depth to an accuracy of 3 cm or less on a basin scale. The assessment of snow depth from processed radar data requires careful quality control, with precision of the assessment directly related to the time committed to the quality control effort. Given the inherent snow depth variability within a radar footprint (approximately 7m by 70m), a level of precision exceeding the inherent snow depth variability would needlessly delay the preparation of our snow depth data product. To quantify what level of precision is needed, we aggregated in situ snow depth measurements into clusters of similar dimensions to a radar footprint. We also examined how forest canopyand topology changes snow depth variability within a radar footprint, which parameters such as elevation, canopy heights or tree canopy cover drive snow depth variability, and whether these parameters are apparent in radar-derived measurements. We used in situ and radar measurements from Grand Mesa, Colorado, an extensively studied site for snowpack monitoring. We measure that snow depths in a 7 m by 70 m area can vary anywhere between 5% to 30% of the average snow depth of the footprint. Radar-derived snow depths were measured to be within these levels on variability (17% to 20%). Elevation is noted to be the primary driver of snow depth variability in Grand Mesa, followed by canopy heights and tree canopy cover from a randomforest regression. Despite limited availability of flight paths to analyze, this study showed good agreements of radar-derived snow depths to aggregated in situ snow depth variability.