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Upward-looking L-band FMCW radar for snow cover monitoring.

Okorn R, Brunnhofer G, Platzer T, Heilig A, Schmid L, Mitterer C, Schweizer J, Eisen O - Cold Reg Sci Technol (2014)

Bottom Line: The phase information significantly improved the detectability of the temporal evolution of the snow surface reflection.Results were compared with independently measured snow height from a laser snow-depth sensor and results derived from an upward-looking impulse radar system (upGPR).The semi-automated tracking used the phase information and had an accuracy of about 6 to 8 cm for dry-snow conditions, similar to the accuracy of the upGPR, compared to measurements from the laser snow-depth sensor.

View Article: PubMed Central - PubMed

Affiliation: FH JOANNEUM, Department of Electronic Engineering, Kapfenberg, Austria.

ABSTRACT
Forecasting snow avalanche danger in mountainous regions is of major importance for the protection of infrastructure in avalanche run-out zones. Inexpensive measurement devices capable of measuring snow height and layer properties in avalanche starting zones may help to improve the quality of risk assessment. We present a low-cost L-band frequency modulated continuous wave radar system (FMCW) in upward-looking configuration. To monitor the snowpack evolution, the radar system was deployed in fall and subsequently was covered by snowfalls. During two winter seasons we recorded reflections from the overlying snowpack. The influence of reflection magnitude and phase to the measured frequency spectra, as well as the influence of signal processing were investigated. We present a method to extract the phase of the reflection coefficients from the phase response of the frequency spectra and their integration into the presentation of the measurement data. The phase information significantly improved the detectability of the temporal evolution of the snow surface reflection. We developed an automated and a semi-automated snow surface tracking algorithm. Results were compared with independently measured snow height from a laser snow-depth sensor and results derived from an upward-looking impulse radar system (upGPR). The semi-automated tracking used the phase information and had an accuracy of about 6 to 8 cm for dry-snow conditions, similar to the accuracy of the upGPR, compared to measurements from the laser snow-depth sensor. The percolation of water was observable in the radargrams. Results suggest that the upward-looking FMCW system may be a valuable alternative to conventional snow-depth sensors for locations, where fixed installations above ground are not feasible.

No MeSH data available.


(a) Radargram for the period when the snowpack became wet for the season 2011–2012 (lower antenna position), with decreased color saturation. Same representation as in Fig. 7. (b) Air (red) and snow surface temperature (blue) for the same period. (c) Detail showing a period with melt-freeze cycles (daily from 21 to 29 March) and water percolation down to a snow height of 2 m at 23–24 March and 28–29 March 2012.
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f0050: (a) Radargram for the period when the snowpack became wet for the season 2011–2012 (lower antenna position), with decreased color saturation. Same representation as in Fig. 7. (b) Air (red) and snow surface temperature (blue) for the same period. (c) Detail showing a period with melt-freeze cycles (daily from 21 to 29 March) and water percolation down to a snow height of 2 m at 23–24 March and 28–29 March 2012.

Mentions: The bulk permittivity of the snowpack highly depends on the liquid water content (θW). Consequently, presence of water alters the position and magnitude of reflections. In addition, assuming a constant wave velocity is no longer valid since water significantly decreases the wave speed. As a consequence, snow height was overestimated as soon as considerable parts of the snowpack became wet (Fig. 9). Similar to Gubler (1997), we could qualitatively identify periods of wetting and refreezing. Decreasing the color saturation in Fig. 8 allowed us to detect periods and parts of the snow cover with presence of liquid water (Fig. 10a). A first distinct warming at the beginning of March wetted the snow surface, so that the surface temperature occasionally reached 0 °C (Fig. 10b). A distinct cooling followed this first warm period and consequently the water refroze forming a melt-freeze crust. From late March until the beginning of April several such cycles produced water at the snow surface (Fig. 10c). It appears that the meltwater percolated down to a snow height of 2 m or 17.5 ns (~ 0.3 m beneath the surface) and subsequently formed a thick melt-freeze crust within the snowpack. The next period with high air temperatures (last week of April) again, produced considerable water at the snow surface, which first was blocked by the thick melt-freeze crust and probably drained to the bottom of the snowpack within the first days of May 2012. It was, however, very difficult to determine the exact date because the processing to identify and calibrate the record for the reflection originating from the board covering the upFMCW was difficult for the period around 1 May.


Upward-looking L-band FMCW radar for snow cover monitoring.

Okorn R, Brunnhofer G, Platzer T, Heilig A, Schmid L, Mitterer C, Schweizer J, Eisen O - Cold Reg Sci Technol (2014)

(a) Radargram for the period when the snowpack became wet for the season 2011–2012 (lower antenna position), with decreased color saturation. Same representation as in Fig. 7. (b) Air (red) and snow surface temperature (blue) for the same period. (c) Detail showing a period with melt-freeze cycles (daily from 21 to 29 March) and water percolation down to a snow height of 2 m at 23–24 March and 28–29 March 2012.
© Copyright Policy - CC BY
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4045589&req=5

f0050: (a) Radargram for the period when the snowpack became wet for the season 2011–2012 (lower antenna position), with decreased color saturation. Same representation as in Fig. 7. (b) Air (red) and snow surface temperature (blue) for the same period. (c) Detail showing a period with melt-freeze cycles (daily from 21 to 29 March) and water percolation down to a snow height of 2 m at 23–24 March and 28–29 March 2012.
Mentions: The bulk permittivity of the snowpack highly depends on the liquid water content (θW). Consequently, presence of water alters the position and magnitude of reflections. In addition, assuming a constant wave velocity is no longer valid since water significantly decreases the wave speed. As a consequence, snow height was overestimated as soon as considerable parts of the snowpack became wet (Fig. 9). Similar to Gubler (1997), we could qualitatively identify periods of wetting and refreezing. Decreasing the color saturation in Fig. 8 allowed us to detect periods and parts of the snow cover with presence of liquid water (Fig. 10a). A first distinct warming at the beginning of March wetted the snow surface, so that the surface temperature occasionally reached 0 °C (Fig. 10b). A distinct cooling followed this first warm period and consequently the water refroze forming a melt-freeze crust. From late March until the beginning of April several such cycles produced water at the snow surface (Fig. 10c). It appears that the meltwater percolated down to a snow height of 2 m or 17.5 ns (~ 0.3 m beneath the surface) and subsequently formed a thick melt-freeze crust within the snowpack. The next period with high air temperatures (last week of April) again, produced considerable water at the snow surface, which first was blocked by the thick melt-freeze crust and probably drained to the bottom of the snowpack within the first days of May 2012. It was, however, very difficult to determine the exact date because the processing to identify and calibrate the record for the reflection originating from the board covering the upFMCW was difficult for the period around 1 May.

Bottom Line: The phase information significantly improved the detectability of the temporal evolution of the snow surface reflection.Results were compared with independently measured snow height from a laser snow-depth sensor and results derived from an upward-looking impulse radar system (upGPR).The semi-automated tracking used the phase information and had an accuracy of about 6 to 8 cm for dry-snow conditions, similar to the accuracy of the upGPR, compared to measurements from the laser snow-depth sensor.

View Article: PubMed Central - PubMed

Affiliation: FH JOANNEUM, Department of Electronic Engineering, Kapfenberg, Austria.

ABSTRACT
Forecasting snow avalanche danger in mountainous regions is of major importance for the protection of infrastructure in avalanche run-out zones. Inexpensive measurement devices capable of measuring snow height and layer properties in avalanche starting zones may help to improve the quality of risk assessment. We present a low-cost L-band frequency modulated continuous wave radar system (FMCW) in upward-looking configuration. To monitor the snowpack evolution, the radar system was deployed in fall and subsequently was covered by snowfalls. During two winter seasons we recorded reflections from the overlying snowpack. The influence of reflection magnitude and phase to the measured frequency spectra, as well as the influence of signal processing were investigated. We present a method to extract the phase of the reflection coefficients from the phase response of the frequency spectra and their integration into the presentation of the measurement data. The phase information significantly improved the detectability of the temporal evolution of the snow surface reflection. We developed an automated and a semi-automated snow surface tracking algorithm. Results were compared with independently measured snow height from a laser snow-depth sensor and results derived from an upward-looking impulse radar system (upGPR). The semi-automated tracking used the phase information and had an accuracy of about 6 to 8 cm for dry-snow conditions, similar to the accuracy of the upGPR, compared to measurements from the laser snow-depth sensor. The percolation of water was observable in the radargrams. Results suggest that the upward-looking FMCW system may be a valuable alternative to conventional snow-depth sensors for locations, where fixed installations above ground are not feasible.

No MeSH data available.