Skip to Main content Skip to Navigation
Journal articles

A new segmentation method for the homogenisation of GNSS-derived IWV time-series

Abstract : Homogenization is an important and crucial step to improve the usage of observational data for climate analysis. This work is motivated by the analysis of long series of GNSS Integrated Water Vapour (IWV) data which have not yet been used in this context. This paper proposes a novel segmentation method that integrates a periodic bias and a heterogeneous, monthly varying, variance. The method consists in estimating first the variance using a robust estimator and then estimating the segmentation and periodic bias iteratively. This strategy allows for the use of the dynamic programming algorithm that remains the most efficient exact algorithm to estimate the change-point positions. The statistical performance of the method is assessed through numerical experiments. An application to a real data set of 120 global GNSS stations is presented. The method is implemented in the R package GNSSseg that will be available on the CRAN.
Complete list of metadata

Cited literature [45 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-02957051
Contributor : Olivier Bock <>
Submitted on : Sunday, October 4, 2020 - 2:42:44 PM
Last modification on : Friday, April 16, 2021 - 3:31:31 AM
Long-term archiving on: : Tuesday, January 5, 2021 - 6:12:06 PM

File

2005.04683.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-02957051, version 1
  • ARXIV : 2005.04683

Citation

Annarosa Quarello, Olivier Bock, Emilie Lebarbier. A new segmentation method for the homogenisation of GNSS-derived IWV time-series. Journal of the Royal Statistical Society: Series C Applied Statistics, Wiley, In press. ⟨hal-02957051⟩

Share

Metrics

Record views

96

Files downloads

87