Improving GNSS-R sea level determination through inverse modeling of SNR data
Artikel i vetenskaplig tidskrift, 2016
This paper presents a new method for retrieving sea surface heights from Global Navigation Satellite Systems reflectometry (GNSS-R) data by inverse modeling of SNR observations from a single geodetic receiver. The method relies on a B-spline representation of the temporal sea level variations in order to account for its continuity. The corresponding B-spline coefficients are determined through a nonlinear least squares fit to the SNR data, and a consistent choice of model parameters enables the combination of multiple GNSS in a single inversion process. This leads to a clear increase in precision of the sea level retrievals which can be attributed to a better spatial and temporal sampling of the reflecting surface. Tests with data from two different coastal GNSS sites and comparison with colocated tide gauges show a significant increase in precision when compared to previously used methods, reaching standard deviations of 1.4 cm at Onsala, Sweden, and 3.1 cm at Spring Bay, Tasmania.
Sea level
Tide gauge
GNSS-R
Inverse modeling