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

2. Locate instrumentation-related signals…

3. And get rid of them!

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

5. Metal reflector experiment

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

10. 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)

11. In-situ Density and Wetness

12. In-situ Reflectivity

13. Radar Snow Water Equivalent Estimates

14. 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

16. Snowpit comparison, SLF, Feb 19, 2004

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

18. 3-layer model – complicated for thin layers

19. Depths of major reflections automatically picked

20. Comparison of FMCW radar and SnowMicroPen

23. Chuckchi Sea, Barrow March, 2006 300 meter profile on 1 st year sea ice 601 MagnaProbe measurements >3000 FMCW radar snow depths

24. 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

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

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

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

28. Comparing point depths to radar measurements

29. 1.7 km profile,  x=10 cm,  z=1.5 cm

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

33. 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