Retrieval of Spatial and Temporal Variability in Snowpack Depth over Glaciers in Svalbard Using GPR and Spaceborne POLSAR Measurements

The highly dynamic nature of snow requires frequent observations to study its various properties. Keeping this in mind, the present investigation presents results from the analysis of fully polarimetric synthetic aperture radar (POLSAR) parameters for the development of a snow depth (SD) inversion model for SD retrieval. Snow depth retrieved using ground penetrating radar (GPR) at 500 MHz over Austre Grønfjordbreen in the Svalbard region was used to understand the behaviour of certain polarimetric parameters. A significant correlation was found between field-measured SD and POLSAR parameters, namely coherence and normalized volume scattering power (R2 = 0.84 and R2 = 0.73, respectively.) Using the POLSAR scattering powers obtained from the six-component model-based decomposition (6SD), the heterogeneity and anisotropic behaviour in the firn areas are also explained. Further, based on the analyses shown in this work, a polarimetric parameter-based SD inversion algorithm have been proposed and validated. The univariate model with co-polarization coherence has the highest correlation (R2 = 0.84, Root Mean Square Error (RMSE) = 0.18). We have even tested several multivariate models for the same, to conclude that a combination of coherence, normalized volume and double-bounce scattering have a high correlation with SD (R2 = 0.84, RMSE = 0.18). Additionally, temporal and spatial variability in SD was also observed from three polarimetric SAR images acquired between 4 April 2015 and 15 May 2015 over the Western Nordenskiöld Land region. Increase in snow depth corresponding to snow precipitation events were also detected using the POLSAR data.

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Temporal and spatial variability in surface roughness and accumulation rate around 88° S from repeat airborne geophysical surveys

10.5194/tc-2020-51 ◽

2020 ◽

Author(s):

Michael Studinger ◽

Brooke C. Medley ◽

Kelly M. Brunt ◽

Kimberly A. Casey ◽

Nathan T. Kurtz ◽

...

Keyword(s):

Surface Roughness ◽

Accumulation Rate ◽

Snow Accumulation ◽

Small Scale ◽

Spatial And Temporal Variability ◽

Temporal And Spatial Variability ◽

Geophysical Surveys ◽

Slope Wind ◽

Temporal And Spatial ◽

Airborne Geophysical Data

Abstract. We use repeat high-resolution airborne geophysical data consisting of laser altimetry, snow and Ku-band radar and optical imagery acquired in 2014, 2016 and 2017 to analyze the spatial and temporal variability in surface roughness, slope, wind deposition, and snow accumulation at 88° S as this is a bias validation site for ICESat-2 and may be a potential validation site for CryoSat-2. We find significant small–scale variability (

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An Optical Method to Characterize Streamer Variability and Streamer-to-Flame Transition for Radio-Frequency Corona Discharges

Applied Sciences ◽

10.3390/app10072275 ◽

2020 ◽

Vol 10 (7) ◽

pp. 2275 ◽

Cited By ~ 2

Author(s):

Valentino Cruccolini ◽

Carlo N. Grimaldi ◽

Gabriele Discepoli ◽

Federico Ricci ◽

Luca Petrucci ◽

...

Keyword(s):

Radio Frequency ◽

Corona Discharge ◽

High Speed ◽

Original Method ◽

Spatial And Temporal Variability ◽

Optical Analysis ◽

Temporal And Spatial Variability ◽

Stable Operating ◽

Temporal And Spatial ◽

The Moment

In recent years, radio-frequency corona ignition gained increasing interest from the engine research community because of its capability to extend the engine stable operating range in terms of lean and EGR dilution. The corona discharge generates streamers coming from a star-shaped electrode, generally consisting of four or five tips. The temporal and spatial variability of such streamers in length, orientation, and branching can be factors that affect the combustion onset and, therefore, engine cycle-to-cycle variability. Generally, the latter is reduced with respect to a conventional spark igniter at the same air–fuel ratio, but still present. In this work, analysis on the corona discharge and on the subsequent combustion onset was carried out in an optically accessible engine by means of the detection, via high-speed camera, of the natural luminosity of streamers and flames. A method to characterize spatial and temporal variability in motored conditions is firstly presented. A statistical analysis of the streamer behavior was performed, by separately analyzing the streamers generated by each tip of the star-shaped electrode. Finally, an original method aimed at determining the moment of the first flame appearance, caused by the combustion onset, is presented. The outcome of this work can be used to improve the knowledge on corona discharge, in particular on the stochastic behavior that characterizes the streamers. The presented optical analysis can also be adapted to other volumetric, single- or multi-point ignition systems.

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Density of Seasonal Snow in the Mountainous Environment of Five Slovak Ski Centers

Water ◽

10.3390/w12123563 ◽

2020 ◽

Vol 12 (12) ◽

pp. 3563

Author(s):

Michal Mikloš ◽

Jaroslav Skvarenina ◽

Martin Jančo ◽

Jana Skvareninova

Keyword(s):

Spatial Variability ◽

Snow Depth ◽

Winter Season ◽

Seasonal Development ◽

Snow Density ◽

Temporal And Spatial Variability ◽

Development Processes ◽

Temporal And Spatial ◽

Natural Snow ◽

Snowpack Properties

Climate change affects snowpack properties indirectly through the greater need for artificial snow production for ski centers. The seasonal snowpacks at five ski centers in Central Slovakia were examined over the course of three winter seasons to identify and compare the seasonal development and inter-seasonal and spatial variability of depth average snow density of ski piste snow and uncompacted natural snow. The spatial variability in the ski piste snow density was analyzed in relation to the snow depth and snow lances at the Košútka ski center using GIS. A special snow tube for high-density snowpack sampling was developed (named the MM snow tube) and tested against the commonly used VS-43 snow tube. Measurements showed that the MM snow tube was constructed appropriately and had comparable precision. Significant differences in mean snow density were identified for the studied snow types. The similar rates of increase for the densities of the ski piste snow and uncompacted natural snow suggested that the key density differences stem from the artificial (machine-made) versus natural snow versus processes after and not densification due to snow grooming machines and skiers, which was relevant only for ski piste snow. The ski piste snow density increased on slope with decreasing snow depth (18 kg/m³ per each 10 cm), while snow depth decreased 2 cm per each meter from the center of snow lances. Mean three seasons maximal measured density of ski piste snow was 917 ± 58 kg/m³ the density of ice. This study increases the understanding of the snowpack development processes in a manipulated mountainous environment through examinations of temporal and spatial variability in snow densities and an investigation into the development of natural and ski piste snow densities over the winter season.

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