Snow is an important component of the climate system and a critical storage component in the hydrologic cycle. However,in situobservations 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.

For the last decade, it has been known that reflected GPS signals observed with specialized instruments could be used to measure sea level. In this letter, data from an existing geodetic-quality GPS site near Kachemak Bay, Alaska, are analyzed for a one-year time period. Daily sea-level variations are more than 7 m. Tidal coefficients have been estimated and compared with coefficients estimated from records from a traditional tide gauge at Seldovia Harbor, ~ 30 km away. The GPS and Seldovia estimates of M₂ and S₂ coefficients agree to better than 2%; much of this residual can be attributed to true differences in the tide over 30 km as it propagates up Kachemak Bay. For daily mean sea levels the agreement is 2.3 cm. Because a standard geodetic GPS receiver/antenna is used, this GPS instrument can measure long-term sea-level changes in a stable terrestrial reference frame.

Snowpacks provide reservoirs of freshwater. The amount stored and how fast it is released by melting are vital information for both scientists and water supply managers. GPS multipath reflectometry (GPS-MR) is a new technique that can be used to measure snow depth. Signal-to-noise ratio data collected by GPS instruments exhibit peaks and troughs as coherent direct and reflected signals go in and out of phase. These interference fringes are used to retrieve the unknown land surface characteristics. In this two-part contribution, a forward/inverse approach is offered for GPS-MR of snow depth. Part I starts with the physically based forward model utilized to simulate the coupling of the surface and antenna responses. A statistically rigorous inverse model is presented and employed to retrieve parameter corrections responsible for observation residuals. The unknown snow characteristics are parameterized, the observation/parameter sensitivity is illustrated, the inversion performance is assessed in terms of its precision and its accuracy, and the dependence of model results on the satellite direction is quantified. The latter serves to indicate the sensing footprint of the reflection.