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.