Comparison of different methods to account for the plasmaspheric electron content in GNSS-derived ionospheric altimeter corrections and their impact on sea level trend estimation

Abstract

Global ionospheric maps based on GNSS measurements are nowadays often used to correct satellite altimeter measurements when the instruments have only one frequency or measure over coasts and inland waters. If these corrections do not account for the free electron fraction over the altimeter satellites, this leads to systematic deviations in the range measurements and thus in the estimated sea level. This study compares and assesses different approaches to reduce GNSS-based corrections for the plasmaspheric electron content. It is shown that using a simple scaling with a constant factor of 0.881 gives the best results for the Jason-1 mission, while correcting with the commonly used model ratios leads to higher sea level trend artefacts and larger noise levels, especially for periods of lower solar activity. Using this approach, the sea level trend error for both Jason-1 and Sentinel-6A can be reduced to below 0.1 mm/year, with standard deviations of the differences from the dual-frequency altimeter corrections of 6.74 mm. A simple machine learning approach (boosted regression tree) is also investigated and shows promising results. However, due to the higher processing capacity requirements and the larger deviations from long-term trend, further improvements are recommended before such an approach can be used in routine processing of altimeter corrections.Graphical