Estimating Vertical Land Motion and Residual Altimeter Systematic Errors Using a Kalman‐Based Approach

Abstract

AbstractVertical land motion (VLM) is the connection between absolute sea‐level (ASL) from a satellite altimeter (ALT) and relative sea‐level from a tide gauge (TG). VLM is often sparsely observed yet is required for understanding sea‐level rise. Many studies have sought to exploit ALT and TG data to infer VLM, yet regionally correlated systematic errors in altimetry have not been considered. We have developed a Kalman filtering and smoothing framework to simultaneously estimate location‐specific VLM and residual mission‐specific systematic errors in a geocentric reference frame. We used ALT minus TG, ALT crossovers and global positioning system (GPS) bedrock height observations in a multi‐stage solution approach that gradually separated time‐variable parameter estimates in an ill‐posed problem. We evaluated the performance of the method using the Jason‐series along‐track data in the Baltic Sea, where glacial isostatic adjustment is the dominant driver of VLM. We estimated local VLM variability at TGs of up to ∼4.5 mm/yr which is not evident in spatially interpolated GPS velocities. The estimated regional altimeter errors are significant and within the range of ∼±0.5–2.5 mm/yr. Our approach improves agreement between ASL estimates from ALT and TG records, provides a ∼20% decrease in root mean squared error of latitudinal ASL variability at TGs, and a reduction of the ASL rate from altimetry by ∼0.3 mm/yr across the region. This method advances the ALT‐TG approach to determining VLM at TG locations and systematic errors of altimetry, which is broadly applicable to other regional‐ and global‐scale studies.