Estimation of the Vertical Land Motion from GNSS Time Series and Application in Quantifying Sea-Level Rise
Document Type
Book Chapter
Department or Administrative Unit
Geological Sciences
Publication Date
2020
Abstract
Sea-level rise observed at tide gauges must be corrected for vertical land motion, observed with GNSS, to obtain the absolute sea-level rise with respect to the centre of the Earth. Both the sea-level and vertical position time series contain temporal correlated noise that need to be taken into account to obtain the most accurate rate estimates and to ensure realistic uncertainties. Satellite altimetry directly observes absolute sea-level rise but these time series also exhibit colored noise. In this chapter we present noise models for these geodetic time series such as the commonly used first order Auto Regressive (AR), the General Gauss Markov (GGM) and the ARFIMA model. The theory is applied to GNSS and tide gauge data from the Pacific Northwest coast.
Recommended Citation
Montillet, J.-P., Bos, M. S., Melbourne, T. I., Williams, S. D. P., Fernandes, R. M. S., & Szeliga, W. M. (2019). Estimation of the Vertical Land Motion from GNSS Time Series and Application in Quantifying Sea-Level Rise. In J.P. Montillet & M. Bos (Eds.), Geodetic Time Series Analysis in Earth Sciences (pp. 317–344). Springer. https://doi.org/10.1007/978-3-030-21718-1_11
Rights
© Springer Nature Switzerland AG 2020
Comments
This book chapter was originally published in Geodetic Time Series Analysis in Earth Sciences. The full-text article from the publisher can be found here.
Due to copyright restrictions, this article is not available for free download from ScholarWorks @ CWU.