Attributes of Several Methods for Detecting Discontinuities in Mean Temperature Series

By Arthur Degaetano. 2006

83 citations recorded by the source corpus.

Subfields: Environmental Engineering, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/40784d9c0093169efd503fe60edbeac5bb642778

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Engineering

1. Xiaolan L. Wang
2. M. Menne
3. C. Naomie Williams
4. J. Kennedy
5. Ceylan Yozgatlıgil
6. P. Della-Marta
7. Peter G. Jones
8. C. Morice

In Global and Planetary Change

1. Xiaolan L. Wang
2. P. Domonkos
3. M. Menne
4. C. Naomie Williams
5. Yuehua Wu
6. C. Morice
7. D. Parker
8. Ceylan Yozgatlıgil

Citations in the corpus

• Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 data set (2012, background): “…distribution with a standard deviation of sH = 0.4 C. Recent studies of homogenization uncertainty report broadly similar magnitudes of homogenization uncertainty [DeGaetano, 2006; Menne and Williams, 2009; Menne et al., 2009] and so the model of sH = 0.4 C is maintained in CRUTEM4 and HadCRUT4.”
• Penalized Maximal F Test for Detecting Undocumented Mean Shift without Trend Change (2008, background): “The effects of artificial shifts (nonclimatic sudden changes) on the results of climate analysis, especially of historical climate trend assessment, have been illustrated in many studies, for example in Wang (2006), Hanesiak and Wang (2005), Vincent et al. (2002), and Easterling and Peterson (1995),”
• 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).”
• Homogenization of Temperature Series via Pairwise Comparisons (2009, methodology): “Given that preserving local trends (i.e., trend inhomogeneities) can often result in undesirable adjusted series, the pairwise algorithm was modified to employ the more commonly used M3 adjustment for all step changes (DeGaetano 2006).”
• A note on the use of the standard normal homogeneity test to detect inhomogeneities in climatic time series (2011, background): “DeGaetano (2006) found, in his analysis of break detection methods, a similar behaviour of SNHT in the case of false detected breaks (using 1000 homogeneous series).”
• Penalized Maximal t Test for Detecting Undocumented Mean Change in Climate Data Series (2007, methodology): “DeGaetano (2006) also compared several methods for detecting discontinuities in mean temperature series.”
• Comparison of homogeneity tests for temperature using a simulation study (2016, background): “INTERNATIONAL JOURNAL OF CLIMATOLOGY Int. J. Climatol. 36: 62–81 (2016) Published online 8 April 2015 in Wiley Online Library (wileyonlinelibrary.”
• EXACT ASYMPTOTIC DISTRIBUTION OF CHANGE-POINT MLE FOR CHANGE IN THE MEAN OF GAUSSIAN SEQUENCES (2010, background): “…Perreault et al. (2000a, 2000b) for application in hydrology; Jarušková (1996) for applications in meteorology; Fealy and Sweeney (2005) and DeGaetano (2006) for applications in climatology; Kaplan and Shishkin (2000) and Lebarbier (2005) for applications in signal processing; Andrews and…”
• Accounting for Autocorrelation in Detecting Mean Shifts in Climate Data Series Using the Penalized Maximal t or F Test (2008, methodology): “…effort has been devoted to detecting and adjusting for artificial shifts in climate data series (e.g., Vincent et al. 2002; Menne and Williams 2005; DeGaetano 2006; Wang 2006; Wan et al. 2007; among others), and several statistical methods have been proposed for detecting “undocumented shifts”…”
• Efficiency evaluation for detecting inhomogeneities by objective homogenisation methods (2011, background): “Although there have been some comparative examinations aiming to reveal the capability of detecting IHs by OHOMs (Buishand 1982; Easterling and Peterson 1995; Lanzante 1996; Ducre-Robitaille et al. 2003; Syrakova 2003; Drogue et al. 2005; Menne and Williams 2005; DeGaetano 2006; Domonkos 2006a; Ge”
• Pairwise homogeneity assessment of HadISD (2014, methodology): “PHA was developed as DeGaetano(2006) andReeves et al.”