Estimating snow accumulation and ablation with L-band interferometric synthetic aperture radar (InSAR)

• Published in: The cryosphere 2023-05, Vol.17 (5), p.1997-2019
• Main Authors: Tarricone, Jack, Webb, Ryan W, Marshall, Hans-Peter, Nolin, Anne W, Meyer, Franz J
• Format: Article
• Language: English
• Subjects: Ablation; Accumulation; Artificial satellites in remote sensing; Atmospheric correction; Dielectric properties; Equivalence; Estimates; Ground penetrating radar; Indian space program; Interferometric synthetic aperture radar; Interferometry; Mountains; Radar; Radar data; Remote sensing; SAR (radar); Snow; Snow accumulation; Snow cover; Snow depth; Snow-water equivalent; Snowpack; Space research; Synthetic aperture radar; Synthetic aperture radar interferometry; Time series; Topography; Tracking; Water resources; Weather stations
• ISSN: 1994-0424; 1994-0416; 1994-0424; 1994-0416
• DOI: 10.5194/tc-17-1997-2023

Snow is a critical water resource for the western United States and many regions across the globe. However, our ability to accurately measure and monitor changes in snow mass from satellite remote sensing, specifically its water equivalent, remains a challenge. To confront these challenges, NASA initiated the SnowEx program, a multiyear effort to address knowledge gaps in snow remote sensing. During SnowEx 2020, the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) team acquired an L-band interferometric synthetic aperture radar (InSAR) data time series to evaluate the capabilities and limitations of repeat-pass L-band InSAR for tracking changes in snow water equivalent (SWE). The goal was to develop a more comprehensive understanding of where and when L-band InSAR can provide SWE change estimates, allowing the snow community to leverage the upcoming NASA–ISRO (NASA–Indian Space Research Organization) SAR (NISAR) mission. Our study analyzed three InSAR image pairs from the Jemez Mountains, NM, between 12 and 26 February 2020. We developed a snow-focused multi-sensor method that uses UAVSAR InSAR data synergistically with optical fractional snow-covered area (fSCA) information. Combining these two remote sensing datasets allows for atmospheric correction and delineation of snow-covered pixels within the radar swath. For all InSAR pairs, we converted phase change values to SWE change estimates between the three acquisition dates. We then evaluated InSAR-derived retrievals using a combination of fSCA, snow pits, meteorological station data, in situ snow depth sensors, and ground-penetrating radar (GPR). The results of this study show that repeat-pass L-band InSAR is effective for estimating both snow accumulation and ablation with the proper measurement timing, reference phase, and snowpack conditions.