Comparison of techniques for detection of discontinuities in temperature series

By Jean-François Ducré-Robitaille, L. Vincent, G. Boulet. 2003

207 citations recorded by the source corpus.

Subfields: Environmental Engineering, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/06ba00e028b09618615c12a0049f154ab7cc2d8b

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In Environmental Engineering

In Global and Planetary Change

Citations in the corpus

Detection of Undocumented Changepoints Using Multiple Test Statistics and Composite Reference Series. (2005, unknown): “Rather than compare, for example, the percentage of simulated changepoints that are identified by various tests (see Ducré-Robitaille et al. 2003 for a recent comparison of eight methods), this comparison was undertaken to ascertain whether multiple tests can be combined to improve overall…”
Homogenization of Temperature Series via Pairwise Comparisons (2009, methodology): “3s, which is below the sensitivity of most tests for undocumented changepoints (DeGaetano 2006; Ducré-Robitaille et al. 2003).”
Efficiency evaluation for detecting inhomogeneities by objective homogenisation methods (2011, methodology): “…(MLR, Vincent 1998), Penalised Maximal t test (PMT, Wang et al. 2007), Standard Normal Homogeneity Test for shifts only (SNH, Alexandersson 1986), Standard Normal Homogeneity Test for shifts and trends (SNHT, Alexandersson and Moberg 1997), t test (tts, Ducré-Robitaille et al. 2003), C-M and MASH.”
Benchmarking homogenization algorithms for monthly data (2012, unknown): “To stimulate the development of homogenization methods, the Hungarian Meteorological Service started a series of “Seminars for homogenization” in 1996 (HMS, 1996; WMO, 1999, 2004, 2006, 2011; OMSZ, 2001). A review on existing homogenization methods and national approaches for creating homogenized da”
A Survey of Methods for Time Series Change Point Detection (2016, unknown): “Climate analysis, monitoring, and predictionmethods that utilize change point detection have become increasingly important over the last few decades due to the possible occurrence of climate change and the increase in greenhouse gases in the atmosphere [24,32,51].”
Changepoint Detection in Periodic and Autocorrelated Time Series (2007, background): “and Ducré-Robitaille et al. (2003) (among others).”
A Review and Comparison of Changepoint Detection Techniques for Climate Data (2007, background): “…climatologists Easterling and Peterson (1995) conducted the first major attempt, although their introduced statistic did not always produce a clear conclusion More recent review attempts have been made by Peterson et al. (1998), Ducré-Robitaille et al. (2003), Rodionov (2004), and DeGaetano (2006).”
Comparison of homogeneity tests for temperature using a simulation study (2016, methodology): “Comparison of the observed results with the literature Ducre-Robitaille et al. (2003) concluded that SNHT no trend, MLR and Bayesian with reference produce the best solutions for the identification of homogeneous series.”
Ecological thresholds and regime shifts: approaches to identification. (2009, methodology): “The most commonly investigated regime shift hypothesis is a step change in mean level using parametric [40, 42, 43] or non-parametric [44] methods.”
A Method of Homogenizing the Extremes and Mean of Daily Temperature Measurements (2006, methodology): “1a. Previous studies on the homogenization of daily climate data While the methods used to homogenize annual and monthly data are well established (e.g. Peterson et al. 1998; Ducre-Robitaille et al. 2003)) relatively few methods exist to homogenize daily data.”