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Randall Ray Bonnell

Publications and source records attributed to Randall Ray Bonnell.

3 recordsLinked to original sources

Evaluating snow depth measurements from ground-penetrating radar and airborne lidar in boreal forest and tundra environments during the NASA SnowEx 2023 campaign

Snow is a vital component of high-latitude terrestrial systems, but environmental factors (e.g., permafrost) and complex vegetation challenge the accurate measurement of key snowpack properties. We evaluated local-scale ground-penetrating radar (GPR) and large-scale airborne lidar retrievals of snow depth collected during the NASA SnowEx 2023 campaign in tundra and boreal forest environments in Alaska along 44 short (3–12 m) transects. Compared to in situ observations, we identified modest biases for GPR snow depths (bias <0.03 m in tundra, +0.06 m in boreal forests) and larger biases for lidar snow depths in the boreal forests (–0.16 m). At the Upper Kuparuk-Toolik tundra site, lidar snow depths exhibited a small bias (–0.02 m), whereas the bias was much larger at the Arctic Coastal Plain tundra site (+0.19 m). For most sites, biases were primarily related to sub-snow vegetation, tussocks, and seasonally dynamic ground. However, we identified vertical alignment issues with the Arctic Coastal Plain lidar snow depth dataset that likely contributed to the higher bias. The complex ground surface and sub-snow vegetation in these environments present a challenge to established snow depth measurement methods, which needs to be considered when evaluating novel remote sensing approaches.

Alaska

Sentinel-1 SAR estimates of snowmelt onset coincide with SNOTEL soil moisture pulses across the western U.S.

While there have been recent advancements in synthetic aperture radar (SAR)-based snow water equivalent (SWE) retrievals, obtaining accurate estimates of SWE requires knowledge of the amount of liquid water content (LWC) in the snowpack given its strong impact on radar velocity. Recent studies have utilised Sentinel-1 SAR to identify snowmelt runoff onset in complex, high-elevation terrain based on a seasonal minimum backscatter time-series; however, detailed investigations into the snowpack state before and after snowmelt runoff onset are lacking. In this study, we integrated repeat field measurements at five sites, SNOw TELemetry (SNOTEL) station data ( n = 260) from across the Western United States, and paired Sentinel-1 SAR estimates of snowmelt runoff onset to (1) assess the snowpack state prior to and after Sentinel-1 SAR-derived runoff onset estimates, and (2) evaluate Sentinel-1 SAR estimates of runoff onset with SNOTEL-derived estimates of melt output via soil moisture ‘pulses’. We found that on the date of minimum backscatter, the snowpack was isothermal at three of the five field sites, and snow pit-measured LWC was increasing at all field sites relative to previous survey dates. SNOTEL soil moisture pulses preceded Sentinel-1 SAR estimates of snowmelt runoff onset by a median of 3 days (standard deviation = ±25.3 days) and post-dated peak SWE by a median of 3 days (standard deviation = ±18.2 days). Snow density and the number of positive degree days on soil moisture pulse date increased with latitude and longitude and decreased with elevation. Although satellite-based estimates of snowmelt runoff onset provide a promising approach for improving spaceborne retrievals of SWE, local climatological conditions exert significant influence on meltwater runoff onset signal clarity for both in situ and satellite-based estimates.

western United States