Sensitivity of GNSS-Derived Estimates of Terrestrial Water Storage to Assumed Earth Structure

• Main Authors: Swarr, Matthew Jacob, Martens, Hilary Rose, Fu, Yuning
• Format: Other/Unknown Material
• Language: unknown
• Published: Authorea, Inc. 2023
• Subjects: Greenland; Ice Sheet
• Online Access: http://dx.doi.org/10.22541/essoar.169651354.42556413/v1

Geodetic methods can monitor changes in terrestrial water storage (TWS) across large regions in near real-time. Here, we investigate the effect of assumed Earth structure on TWS estimates derived from Global Navigation Satellite System (GNSS) displacement time series. Through a series of synthetic tests, we systematically explore how the spatial wavelength of water load affects the error of TWS estimates. Large loads (e.g., >1000 km) are well recovered regardless of the assumed Earth model. For small loads (e.g., <10 km), however, errors can exceed 75% when an incorrect model for the Earth is chosen. As a case study, we consider the sensitivity of seasonal TWS estimates within mountainous watersheds of the western U.S., finding estimates that differ by over 13% for a collection of common global and regional structural models. Errors in the recovered water load generally scale with the total weight of the load; thus, long-term changes in storage can produce significant uplift (subsidence) enhancing errors. We demonstrate that regions experiencing systematic and large-scale variations in water storage, such as the Greenland ice sheet, exhibit significant differences in predicted displacement (over 20 mm) depending on the choice of Earth model. Since the discrepancies exceed GNSS observational precision, an appropriate Earth model must be adopted when inverting GNSS observations for mass changes in these regions. Furthermore, regions with large-scale mass changes that can be quantified using independent data (e.g., altimetry, gravity) present opportunities to use geodetic observations to refine structural deficiencies of seismologically derived models for the Earth’s interior structure.