Matthew Sturm


DOI bib
Effect of snow microstructure variability on Ku-band radar snow water equivalent retrievals
Nick Rutter, Melody Sandells, Chris Derksen, Joshua King, Peter Toose, Leanne Wake, Tom Watts, Richard Essery, Alexandre Roy, A. Royer, Philip Marsh, C. F. Larsen, Matthew Sturm
The Cryosphere, Volume 13, Issue 11

Abstract. Spatial variability in snowpack properties negatively impacts our capacity to make direct measurements of snow water equivalent (SWE) using satellites. A comprehensive data set of snow microstructure (94 profiles at 36 sites) and snow layer thickness (9000 vertical profiles across nine trenches) collected over two winters at Trail Valley Creek, NWT, Canada, was applied in synthetic radiative transfer experiments. This allowed for robust assessment of the impact of estimation accuracy of unknown snow microstructural characteristics on the viability of SWE retrievals. Depth hoar layer thickness varied over the shortest horizontal distances, controlled by subnivean vegetation and topography, while variability in total snowpack thickness approximated that of wind slab layers. Mean horizontal correlation lengths of layer thickness were less than a metre for all layers. Depth hoar was consistently ∼30 % of total depth, and with increasing total depth the proportion of wind slab increased at the expense of the decreasing surface snow layer. Distinct differences were evident between distributions of layer properties; a single median value represented density and specific surface area (SSA) of each layer well. Spatial variability in microstructure of depth hoar layers dominated SWE retrieval errors. A depth hoar SSA estimate of around 7 % under the median value was needed to accurately retrieve SWE. In shallow snowpacks <0.6 m, depth hoar SSA estimates of ±5 %–10 % around the optimal retrieval SSA allowed SWE retrievals within a tolerance of ±30 mm. Where snowpacks were deeper than ∼30 cm, accurate values of representative SSA for depth hoar became critical as retrieval errors were exceeded if the median depth hoar SSA was applied.


DOI bib
The influence of snow microstructure on dual-frequency radar measurements in a tundra environment
Joshua King, Chris Derksen, Peter Toose, Alexandre Langlois, C. F. Larsen, Juha Lemmetyinen, P. Marsh, Benoît Montpetit, Alexandre Roy, Nick Rutter, Matthew Sturm
Remote Sensing of Environment, Volume 215

Abstract Recent advancement in the understanding of snow-microwave interactions has helped to isolate the considerable potential for radar-based retrieval of snow water equivalent (SWE). There are however, few datasets available to address spatial uncertainties, such as the influence of snow microstructure, at scales relevant to space-borne application. In this study we introduce measurements from SnowSAR, an airborne, dual-frequency (9.6 and 17.2 GHz) synthetic aperture radar (SAR), to evaluate high resolution (10 m) backscatter within a snow-covered tundra basin. Coincident in situ surveys at two sites characterize a generally thin snowpack (50 cm) interspersed with deeper drift features. Structure of the snowpack is found to be predominantly wind slab (65%) with smaller proportions of depth hoar underlain (35%). Objective estimates of snow microstructure (exponential correlation length; lex), show the slab layers to be 2.8 times smaller than the basal depth hoar. In situ measurements are used to parametrize the Microwave Emission Model of Layered Snowpacks (MEMLS3&a) and compare against collocated SnowSAR backscatter. The evaluation shows a scaling factor (ϕ) between 1.37 and 1.08, when applied to input of lex, minimizes MEMLS root mean squared error to