GPS snow sensing: results from the EarthScope Plate Boundary Observatory
- 1.2k Downloads
Accurate measurements of snowpack are needed both by scientists to model climate and by water supply managers to predict/mitigate drought and flood conditions. Existing in situ snow sensors/networks lack the necessary spatial and temporal sensitivity. Satellite measurements currently assess snow cover rather than snow depth. Existing GPS networks are a potential source of new snow data for climate scientists and water managers which complements existing snow sensors. Geodetic-quality GPS networks often provide signal-to-noise ratio data that are sensitive to snow depth at scales of ~1,000 m2, a much larger area than for other in situ sensors. However, snow depth can only be estimated at GPS sites when the modulation frequency of multipath signals can be resolved. We use data from the EarthScope Plate Boundary Observatory to examine the potential for snow sensing in GPS networks. Examples are shown for successful and unsuccessful snow retrieval sites. In particular, GPS sites in forested regions typically cannot be used for snow sensing. Multiple-year time series of snow depth are estimated from GPS sites in the Rocky Mountains. Peak snow depths ranged from 0.4 to 1.2 m. Comparisons with independent sensors show strong correlations between the GPS snow depth estimates and the timing of snowstorms in the region.
KeywordsGPS Reflections Multipath Snow
This research was supported by NSF EAR 0948957, NSF AGS 0935725, and a CU interdisciplinary seed grant. Mr. Nievinski has been supported by a Capes/Fulbright Graduate Student and a NASA Earth System Science Research Fellowship. Dr. Larson used a Dean’s Faculty Fellowship in 2011 to write the manuscript. All RINEX files used in this study are freely available from UNAVCO. The authors thank Mark Williams, Eric Small, Valery Zavorotny, and Ethan Gutmann for many valuable discussions. Personnel at UNAVCO routinely provided information and support for this project. Some of this material is based on data, equipment, and engineering services provided by the Plate Boundary Observatory operated by UNAVCO for EarthScope (http://www.earthscope.org) and supported by the National Science Foundation (EAR-0350028 and EAR-0732947). We thank PBO for providing the photographs and Google Earth for satellite images. SNOTEL data shown in this paper were retrieved from http://www.wcc.nrcs.usda.gov/nwcc.
- Bilich A, Larson KM (2007) Mapping the GPS multipath environment using the signal-to-noise ratio (SNR). Radio Sci 42:RS6003. doi: 10.1029/2007RS003652
- Bilich A, Axelrad P, Larson KM (2007) Scientific utility of the signal-to-noise ratio (SNR) reported by geodetic GPS receivers. Proceedings of the 20th international technical meeting of the satellite division of the institute of navigation (ION GNSS 2007), Fort Worth, TX, Sep 2007, pp 1999–2010Google Scholar
- Erickson T, Williams MW, Winstral A (2005) Persistence of topographic controls on the spatial distribution of snow depth in rugged mountain terrain, Colorado, USA. Water Resour Res 41(4):W04014. doi: 10.1029/2003WR002973
- ESA (2008) CoReH2o—COld REgions hydrology high-resolution observatory, ESA SP-1313/3 candidate earth explorer core missions—report for assessmentGoogle Scholar
- Gutmann E, Larson KM, Williams M, Nievinski FG, Zavorotny V (2011) Snow measurement by GPS interferometric reflectometry: an evaluation at Niwot Ridge, Colorado. Hydrol Process. doi: 10.1002/hyp.8329
- Hristov HD (2000) Fresnel zones in wireless links, zone plate lenses and antennas. Artech House. ISBN 9780890068496, pp 323Google Scholar
- Joseph A (2010) What is the difference between SNR and C/N0? InsideGNSS, Nov/Dec 2010, pp 20–25Google Scholar
- Kind RJ (1981) Snow drifting. In: Gray D, Male D (eds) Handbook of snow: principles, processes, management and use. Elsevier, New York, pp 338–359Google Scholar
- Press F, Teukolsky S, Vetterling W, Flannery B (1996) Numerical recipes in Fortran 90: the Art of parallel scientific computing, 2nd edn. Cambridge University Press, CambridgeGoogle Scholar
- Woo KT (1999) Optimum semi-codeless carrier phase tracking of L2. In: Proceedings of the 12th international technical meeting of the satellite division of the institute of navigation, Nashville, TN., Sep 14–17, 1999Google Scholar