SNR-based GNSS reflectometry for coastal sea-level altimetry: results from the first IAG inter-comparison campaign
Journal article, 2020

Ground-based Global Navigation Satellite System Reflectometry (GNSS-R) is quickly maturing toward the objective of becoming a viable alternative for operational coastal sea-level (SL) altimetry in a geocentric reference frame. SL has immense societal implications related to climate change. Of particular interest is the exploitation of existing coastal GNSS sites for reflectometry by means of signal-to-noise ratio (SNR) observables. We report results from the first inter-comparison campaign on SNR-based GNSS-R. The goal was to cross-validate retrieval solutions from independent research groups under comparable conditions. This action was an initiative of the International Association of Geodesy working group 4.3.9 (2015–2019 term). Data collected at the Onsala Space Observatory for a 1-year period (2015–2016) were compared to a co-located tide gauge (TG). SNR data for the GPS L1-C/A signal were processed by four groups, in Sweden, Luxembourg/Brazil, Germany, and the UK. Semidiurnal tidal constituents showed good agreement between TG and all GNSS-R groups. SL variations at diurnal and longer periods were also well captured by all series. Most GNSS-R solutions exhibited spurious tones at integer fractions of one sidereal day, the satellite revisit time of the particular GNSS constellation employed (GPS). Band-pass filtering between 3 h and 30 h confirmed that the dominant tidal components were well captured by most GNSS-R solutions. Higher-frequency SL variations (periods < 3 h) are poorly represented by GNSS-R as a consequence of its low temporal resolution. The solution with the worst agreement neglects a correction associated with the rate of change in sea level and uses narrower satellite elevation ranges per retrieval. Overall, there was excellent agreement, with correlation coefficients exceeding 0.9 and RMSE smaller than 5 cm.

GPS

Altimetry

SNR

GNSS-R

Reflectometry

Sea level

GNSS

Author

F. Geremia-Nievinski

Universidade Federal do Rio Grande do Sul (UFRGS)

Thomas Hobiger

University of Stuttgart

Rüdiger Haas

Chalmers, Space, Earth and Environment, Onsala Space Observatory, Space Geodesy and Geodynamics

W. Liu

Shanghai Maritime University

Joakim Strandberg

Chalmers, Space, Earth and Environment, Onsala Space Observatory, Space Geodesy and Geodynamics

S. Tabibi

University of Luxembourg

S. Vey

German Research Centre for Geosciences (GFZ)

J Wickert

Technische Universität Berlin

German Research Centre for Geosciences (GFZ)

Simon D. P. Williams

National Oceanography Centre Southampton

Journal of Geodesy

0949-7714 (ISSN) 1432-1394 (eISSN)

Vol. 94 8 70

Subject Categories

Physical Geography

Climate Research

Signal Processing

DOI

10.1007/s00190-020-01387-3

More information

Latest update

8/17/2020