Spatio-temporal influence of tundra snow properties on Ku-band (17.2 GHz) backscatter

King, Joshua; Kelly, Richard; Kasurak, A.; Duguay, Claude R.; Gunn, Grant E.; Rutter, Nick; Watts, Tom; Derksen, Chris

doi:10.3189/2015jog14j020

Cited by 44 publications

(37 citation statements)

References 34 publications

(57 reference statements)

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“…1; Derksen et al, 2009). As depth hoar and wind slab have strongly diverging microwave scattering properties (Hall et al, 1991), the relative proportion of each strongly influences Ku-band radar backscatter (Yueh et al, 2009;King et al, 2015King et al, , 2018. Knowledge of how layers vary within Arctic snowpacks is therefore critical to the assessment of uncertainty in radar-based retrievals of snow water equivalent (SWE) and forward models of snow radiative transfer.…”

Section: Introductionmentioning

confidence: 99%

Effect of snow microstructure variability on Ku-band radar snow water equivalent retrievals

Rutter

Sandells²,

Derksen

et al. 2019

The Cryosphere

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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.

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Section: Introductionmentioning

confidence: 99%

Effect of snow microstructure variability on Ku-band radar snow water equivalent retrievals

Rutter

Sandells²,

Derksen

et al. 2019

The Cryosphere

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“…The yearly average air temperature is −6.5 • C, and it receives about 201 cm of snowfall annually [45]. The study site is located at approximately 58.7299 • N, 93.8203 • W and 29 m a.s.l., near the tree line on organic soils over permafrost [9,46]. The radar observations were made of a black spruce forest and taiga snow environment from an elevated platform; the trees ranged in height to a maximum of about 15 m.…”

Section: Study Location and Site Descriptionmentioning

confidence: 99%

“…This study also demonstrates the use of these frequencies in a forest canopy application, and the use of the Freeman-Durden three-component decomposition on scatterometer observations in a terrestrial snow accumulation environment. of radar response [7][8][9][10]. Synthetic aperture radar (SAR) imaging can provide wintertime landscape observations at spatial resolutions <100 m, which makes it an attractive technique for snow mapping.Current methods for estimating the SWE at Ku-and X-band frequencies focus on moderate-to-shallow snow and include that proposed by [7] for the CoReH20 mission and that proposed by [11], which uses an interferometric approach; other recent work has been done by [12][13][14].…”

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Observations of a Coniferous Forest at 9.6 and 17.2 GHz: Implications for SWE Retrievals

Thompson

Kelly

2018

Remote Sensing

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UWScat, a ground-based Ku-and X-band scatterometer, was used to compare forested and non-forested landscapes in a terrestrial snow accumulation environment as part of the NASA SnowEx17 field campaign. Field observations from Trail Valley Creek, Northwest Territories; Tobermory, Ontario; and the Canadian Snow and Ice Experiment (CASIX) campaign in Churchill, Manitoba, were also included. Limited sensitivity to snow was observed at 9.6 GHz, while the forest canopy attenuated the signal from sub-canopy snow at 17.2 GHz. Forested landscapes were distinguishable using the volume scattering component of the Freeman-Durden three-component decomposition model by applying a threshold in which values ≥50% indicated forested landscape. It is suggested that the volume scattering component of the decomposition can be used in current snow water equivalent (SWE) retrieval algorithms in place of the forest cover fraction (FF), which is an optical surrogate for microwave scattering and relies on ancillary data. The performance of the volume scattering component of the decomposition was similar to that of FF when used in a retrieval scheme. The primary benefit of this method is that it provides a current, real-time estimate of the forest state, it automatically accounts for the incidence angle and canopy structure, and it provides coincident information on the forest canopy without the use of ancillary data or modeling, which is especially important in remote regions. Additionally, it enables the estimation of forest canopy transmissivity without ancillary data. This study also demonstrates the use of these frequencies in a forest canopy application, and the use of the Freeman-Durden three-component decomposition on scatterometer observations in a terrestrial snow accumulation environment. of radar response [7][8][9][10]. Synthetic aperture radar (SAR) imaging can provide wintertime landscape observations at spatial resolutions <100 m, which makes it an attractive technique for snow mapping.Current methods for estimating the SWE at Ku-and X-band frequencies focus on moderate-to-shallow snow and include that proposed by [7] for the CoReH20 mission and that proposed by [11], which uses an interferometric approach; other recent work has been done by [12][13][14]. However, these studies have excluded forested regions and, therefore, have neglected the sub-canopy SWE. This is unsurprising, because forested regions are among the most challenging environments for remote sensing of snow [15]. Of particular relevance in Canada, the boreal forest, dominated by coniferous species and situated in the circumpolar northern high latitudes, covers 270 million ha, or about 30% of the landscape [16]. Globally, boreal forest covers 1.1 billion ha and is the Earth's largest terrestrial ecosystem [15]. Given the northern locale and the intersection of the boreal zone with snow-covered landscapes [17], it is important that the estimation of the SWE accounts for forest attenuation of the snow backscatter signal.Recent studies on SWE retrieval from borea...

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“…The system is composed of two separated parabolic antennas with a size of around 33 cm that provide co-and cross-polarization modes for a total weight of less than 5 kg. Currently, Ku-band is employed for measuring oceanic surface wind, ice sheet, and snow-pack, from spaceborne-borne Ku-band scatterometers (e.g., SASS (14.6 GHz), NSCAT (14.0 GHz), and Seawind (13.4 GHz)) and ground based SAR [14,15]. A Ku-band satellite mission, called Cold Regions Hydrology High-resolution Observatory (CoRe-H 2 O), was proposed to ESA for spatially improving the observations of snow and ice in climate research [16], without success.…”

Section: Introductionmentioning

confidence: 99%

An Analysis of Ku-Band Profiling Radar Observations of Boreal Forest

et al. 2017

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Radar sensors have the potential to retrieve vertical forest structure measurements thanks to their capability to penetrate into the foliage. However, studies are needed in order to understand better the interaction of radar beams with the canopy. The most commonly used radar technique for estimating forest parameters operates from spacecraft at different wavelength (X-, C-, and L-band). In order to assist in the interpretation of satellite data for forest applications, and as a possible complementary technique to Lidar (Light detection and ranging), the Finnish Geospatial Research Institute has developed the first helicopter-borne profiling radar system operating in Ku-band, called Tomoradar, which is able to provide a vertical canopy profile. The study focuses on the analyses of Ku-band profiling radar waveforms and the backscatter signal of boreal forest, supported by simultaneously acquired Lidar measurements, in order to detect ground and canopy profiles and quantify the ground echo ratio under different canopy coverage and the backscatter signal variation through the vegetation. The Tomoradar data was acquired simultaneously with a lightweight Velodyne VLP-16 Lidar system in October 2016 over a boreal forest located in Evo in southern Finland. Additionally, highly accurate Riegl VQ-480 Lidar data, acquired in 2014, was used as a ground reference for both lightweight systems. We analysed the co-and cross-polarized (HH and HV) Tomoradar backscatter signals of a 600 m long profile. It is found that the Ku-band Tomoradar penetrates the canopy to a similar extent as the Velodyne Lidar, i.e., the distribution of backscatter signals through the vegetation follows the vegetation density. Moreover, the ground backscatter signal strength and ground echo ratio depend strongly on the presence of gaps in the canopy. By comparing the elevation of the corresponding canopy and ground Tomoradar signal peaks with the Velodyne Lidar data, the Tomoradar ground elevation accuracy is on average −0.03 m and −0.20 m for the cross-and co-polarization, respectively, whereas the bias of the canopy elevation is, on average, −0.58 m and 1.35 m for the cross-and co-polarization, respectively. With respect to the ground height data derived from the Lidar measurements of 2014, the Tomoradar ground profile reveals, on average, higher accuracy (i.e., 0.00 m (σ = 0.41 m) and 0.04 m (σ = 0.37 m) for the co-and cross-polarizations, respectively) than the Velodyne system (−0.37 m with σ = 0.25 m).

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Spatio-temporal influence of tundra snow properties on Ku-band (17.2 GHz) backscatter

Cited by 44 publications

References 34 publications

Effect of snow microstructure variability on Ku-band radar snow water equivalent retrievals

Effect of snow microstructure variability on Ku-band radar snow water equivalent retrievals

Observations of a Coniferous Forest at 9.6 and 17.2 GHz: Implications for SWE Retrievals

An Analysis of Ku-Band Profiling Radar Observations of Boreal Forest

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