Comparison of techniques for detection of discontinuities in temperature series.
Abstract
Abstract Several techniques for the detection of discontinuities in temperature series are evaluated. Eight homogenization techniques were compared using simulated datasets reproducing a vast range of possible situations. The simulated data represent homogeneous series and series having one or more steps. Although the majority of the techniques considered in this study perform very well, two methods seem to work slightly better than the others: the standard normal homogeneity test without trend, and the multiple linear regression technique. Both methods are distinctive because of their sensitivity concerning homogeneous series and their ability to detect one or several steps properly within an inhomogeneous series. Copyright © 2003 Environment Canada. Published by John Wiley & Sons, Ltd.
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Of the nine shifts not identified, six had a magnitude of less than 0.3σ.
“Of the nine shifts not identified, six had a magnitude of less than 0.3s, which is below the sensitivity of most tests for undocumented changepoints (DeGaetano 2006;Ducre ´-Robitaille et al. 2003).”
From Homogenization of Temperature Series via Pairwise Comparisons (2009) · cites this paper as Ducre ´-Robitaille et al. 2003
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References 11 · Cited by 182
- Authors
- Ducré‐Robitaille, J., Vincent, L. A., & Boulet, G.
- Affiliations
- Environment and Climate Change Canada (CA)
- ORCID
- Vincent, Lucie A.
- Venue
- International Journal of Climatology
- Publisher
- Wiley
- Published
- 2003-07
- Volume
- 23
- Issue
- 9
- Pages
- 1087-1101
- ISSN
- 0899-8418 (ISSN-L)
- 1097-0088
- OpenAlex
- W2085187101
- Cited by
- 182
- References
- 11
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 8 · 2023: 5 · 2022: 6 · 2021: 13 · 2020: 10 · 2019: 8 · 2018: 11 · 2017: 6 · 2016: 11 · 2015: 7 · 2014: 13 · 2013: 14 · 2012: 23
- FWCI
- 3.89
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Climatology (publishedVersion)
- Funders
- Direction des changements climatiques, Ministère de l'Environnement du Québec
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
- Physical Sciences › Environmental Science › Environmental Engineering › Urban Heat Island Mitigation
- Physical Sciences › Environmental Science › Global and Planetary Change › Hydrology and Drought Analysis
- Keywords
- temperature time series, discontinuity detection, homogenization, Standard Normal Homogeneity Test, multiple linear regression, step detection, simulated data, climate data quality
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