1 Evaluation of radar measurements Hans-Peter Marshall, Boise State University and CRREL Snow Characterization Workshop, April 13-15, 2009

Locate instrumentation-related signals…

And get rid of them!

Locate causes of major reflections Metal reflectors placed at known depths, to determine cause of reflections in original signal

Metal reflector experiment

Accuracy of using mean dielectric properties to estimate velocity: < 2%

Comparing FMCW signal to in-situ electrical measurements radar => in-situ dielectric properties (Finish snowfork) [e.g. Harper and Bradford, 03] In-situ properties => physical properties (e.g. Sihvola et al, 1985; Schneebeli et al, 1998; Matzler, 1996)

In-situ Density and Wetness

In-situ Reflectivity

Radar Snow Water Equivalent Estimates

Comparison of radar with SMP at Swiss Federal Institute for Snow and Avalanche Research => Small diameter rod driven through snow at constant velocity, pressure measured at tip  250 measurements/mm  Measures rupture force of grain bonds SnowMicroPenetrometer

Snowpit comparison, SLF, Feb 19, 2004

Multi-Layer Model (e.g. Ulaby et al, 1981)

3-layer model – complicated for thin layers

Depths of major reflections automatically picked

Comparison of FMCW radar and SnowMicroPen

Chuckchi Sea, Barrow March, meter profile on 1 st year sea ice 601 MagnaProbe measurements >3000 FMCW radar snow depths

Static comparison 1) Expected error = velocity uncertainty (1.5 cm) + radar resolution (1.5 cm) + difference in horizontal support (2cm) = 5cm 2) Mean values within 1.5 cm

Density/Velocity distribution from SWE cores +/- 5% uncertainty in depth estimate due to density variability

FMCW radar profile Mean measured density used to estimate depth from radar TWT

FMCW radar / Magnaprobe comparison 1)Similar variability, good agreement 2)Differences mainly due to different support and coregistering of measurements

Comparing point depths to radar measurements

1.7 km profile,  x=10 cm,  z=1.5 cm

Conclusions - limitations Signal attenuated in very wet snow Magnitude information from reflections difficult to interpret for thin layers No mechanical / microstructural information

Conclusions - advantages Rapid (50 Hz) estimates of snow depth, SWE, major stratigraphic boundaries Basin-scale areas can be covered Slab geometry can be measured Simulate active microwave remote sensors