Comparison of Snow Data Assimilation System with GPS reflectometry snow depth in the Western United States

In this study, we compare gridded snow depth estimates from the Snow Data Assimilation System (SNODAS) with snow depth observations derived from GPS interferometric reflectometry (GPS-IR) from roughly 100 Plate Boundary Observatory sites in the Western United States spanning four water-years (2010–2013). Data from these sites are not assimilated by SNODAS; thus, GPS-IR measurements provide an independent data set to evaluate SNODAS. Our results indicate that at 80% of the sites, SNODAS and GPS-IR snow depth agree to better than 15-cm root mean square error, with correlation coefficients greater than 0.6. Significant differences are found between GPS-IR and SNODAS for sites that are distant from other point measurements, are located in complex terrain or are in areas with strong vegetation heterogeneities. GPS-IR estimates of snow depth are shown to provide useful error characterization of SNODAS products across much of the Western United States and may have potential as an additional data assimilation source that could help improve SNODAS estimates. © 2014 The Authors. Hydrological Processes published by John Wiley & Sons Ltd.

[1]  T. Stansell,et al.  The New L 2 Civil Signal , 2001 .

[2]  Chris Derksen,et al.  Estimating Snow Water Equivalent Using Snow Depth Data and Climate Classes , 2010 .

[3]  Michael Lehning,et al.  Spatial and temporal variability of snow depth and ablation rates in a small mountain catchment , 2010 .

[4]  Eric E. Small,et al.  Modeling bulk density and snow water equivalent using daily snow depth observations , 2013 .

[5]  Richard D. Fontana,et al.  The New L2 Civil Signal , 2001 .

[6]  F. Nievinski,et al.  GPS snow sensing: results from the EarthScope Plate Boundary Observatory , 2012, GPS Solutions.

[7]  J. Wickham,et al.  Completion of the 2001 National Land Cover Database for the conterminous United States , 2007 .

[8]  A. Barrett,et al.  National Operational Hydrologic Remote Sensing Center SNOw Data Assimilation System (SNODAS) Products at NSIDC , 2003 .

[9]  Felipe G. Nievinski,et al.  Inverse Modeling of GPS Multipath for Snow Depth Estimation—Part II: Application and Validation , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[10]  M. Clark,et al.  Characteristics of the western United States snowpack from snowpack telemetry (SNOTEL) data , 1999 .

[11]  F. Nievinski,et al.  Can we measure snow depth with GPS receivers? , 2009 .

[12]  J. Eischeid,et al.  Precipitation Fluctuations over Northern Hemisphere Land Areas Since the Mid-19th Century , 1987, Science.

[13]  Don Cline,et al.  Noaa’s National Snow Analyses , 2005 .

[14]  Balaji Rajagopalan,et al.  Seasonality of precipitation along a meridian in the western U , 1995 .

[15]  K. Verdin,et al.  Evaluation of SNODAS snow depth and snow water equivalent estimates for the Colorado Rocky Mountains, USA , 2011 .

[16]  Michael J. Oimoen,et al.  The National Elevation Dataset , 2002 .

[17]  Kelly Elder,et al.  Spatial Snow Modeling of Wind-Redistributed Snow Using Terrain-Based Parameters , 2002 .

[18]  Hosni Ghedira,et al.  Application of Satellite Microwave Images in Estimating Snow Water Equivalent1 , 2008 .

[19]  Manfred Ehlers,et al.  Photogrammetric Engineering and Remote Sensing , 2007 .

[20]  E. Small,et al.  Snow depth, density, and SWE estimates derived from GPS reflection data: Validation in the western U. S. , 2014 .

[21]  Martyn P. Clark,et al.  STEP WISE, MULTIPLE OBJECTIVE CALIBRATION OF A HYDROLOGIC MODEL FOR A SNOWMELT DOMINATED BASIN 1 , 2006 .

[22]  F. Nievinski,et al.  Snow measurement by GPS interferometric reflectometry: an evaluation at Niwot Ridge, Colorado , 2012 .

[23]  M. Clark,et al.  Seasonal Cycle Shifts in Hydroclimatology over the Western United States , 2003 .

[24]  Günter Blöschl,et al.  Potential of time‐lapse photography of snow for hydrological purposes at the small catchment scale , 2012 .

[25]  Kelly Elder,et al.  A Distributed Snow-Evolution Modeling System (SnowModel) , 2004 .

[26]  Balaji Rajagopalan,et al.  Inference and uncertainty of snow depth spatial distribution at the kilometre scale in the Colorado Rocky Mountains: the effects of sample size, random sampling, predictor quality, and validation procedures , 2014 .