GPS snow sensing: results from the EarthScope Plate Boundary Observatory

Abstract

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.

Appendix

To avoid confusion with Fresnel zones expressions valid for space- and air-borne platforms, here we provide expressions for ground-based installations (Hristov 2000). Start with n = 1 indicating the first Fresnel zone (FFZ), λ for wavelength, h for antenna height, and e and a for satellite elevation angle and azimuth, respectively. Then, the FFZ dimensions are:

• d = nλ/2;

• R = h/tan(e) + (d/sin(e))/tan(e)

• b = (2 d h/sin(e) + (d/sin(e))²)^1/2

• a = b/sin(e)

Its perimeter can be discretized as function of the inner angle θ $\in$ [0, 2π]:

• x′ = a cos(θ) + R

• y′ = b sin(θ)

Finally, the semi-major axis is aligned with the satellite azimuth:

• x = sin(a) x′ − cos(a) y′

• y = sin(a) y′ + cos(a) x′