Can we measure snow depth with GPS receivers?

Abstract

Snow is an important component of the climate system and a critical storage component in the hydrologic cycle. However, in situ observations of snow distribution are sparse, and remotely sensed products are imprecise and only available at a coarse spatial scale. GPS geodesists have long recognized that snow can affect a GPS signal, but it has not been shown that a GPS receiver placed in a standard geodetic orientation can be used to measure snow depth. In this paper, it is shown that changes in snow depth can be clearly tracked in the corresponding multipath modulation of the GPS signal. Results for two spring 2009 snowstorms in Colorado show strong agreement between GPS snow depth estimates, field measurements, and nearby ultrasonic snow depth sensors. Because there are hundreds of geodetic GPS receivers operating in snowy regions of the U.S., it is possible that GPS receivers installed for plate deformation studies, surveying, and weather monitoring could be used to also estimate snow depth.

Assessment of modernized GPS L5 SNR for ground-based multipath reflectometry applications

“…Combining Eqs. (6) and (7) yields 4pk À1 sin e, which if it is taken as an independent variable for SNR observations, it produces a spectrum whose frequency domain is expressed in terms of reflector height, H (Larson et al, 2009). Least-squares spectral analysis (Wells et al, 1985), also known as the Lomb-Scargle periodogram, was applied to estimate the best-fitting sinusoid.…”

“…Although all GPS measurements are affected by multipath, SNR measurements are primarily used in this type of GPS-MR. SNR indicates the ratio of the signal power to the noise power (integrated over a given bandwidth) and has conventionally been used for comparing tracking channels. SNR is straightforward to analyze for the multipath signature as there is no need to account for ranging effects, such as ephemerides, atmospheric delays, clock errors, etc., parameters that normally need to be known precisely for carrier-phase and pseudorange measurements (Larson et al, 2009).…”

“…The authors found excellent agreement between the GPS and sensor estimates of soil moisture (correlations between 0.9 and 0.76) for non-snow and non-freezing conditions over a three-month period. Again using the L2C signal, Larson et al (2009) tracked the snow depth from two separate snow-storms in Marshall, Colorado; agreement with three nearby ultrasonic snow depth sensors was very good throughout the history of the storms.…”

“…There is a type of GPS-R that relies on the multipath reception of simultaneously and coherently recorded directly and reflected signals. It employs signal-to-noise ratio (SNR) measurements for retrieving environmental parameters such as soil moisture (Kavak et al, 1998;Larson et al, 2008;RodriguezAlvarez et al, 2011;Chew et al, 2014;Alonso-Arroyo et al, 2014), snow depth (Jacobson, 2008;Larson et al, 2009;Rodriguez-Alvarez et al, 2012;Nievinski and Larson, 2014d;Jin and Najibi, 2014), vegetation growth Rodriguez-Alvarez et al, 2011;Wan et al, 2014), and sea level variations (Anderson, 2000;Lö fgren et al, 2014). The technique samples the environment over a sizable area, e.g., $1000 m 2 in the vicinity of a 2-m tall GPS antenna.…”

Soil Moisture & Snow Properties Determination with GNSS in Alpine Environments: Challenges, Status, and Perspectives

“…Some important work has also been performed by the University of Colorado in the estimation of snow depth [19,109,110]. The various experiments were performed with geodetic receivers from the EarthScope network.…”