The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Accounting for Autocorrelation in Detecting Mean Shifts in Climate Data Series Using the Penalized Maximal t or F Test
Abstract
This study proposes an empirical approach to account for lag-1 autocorrelation in detecting mean shifts in time series of white or red (first-order autoregressive) Gaussian noise using the penalized maximal t test or the penalized maximal F test. This empirical approach is embedded in a stepwise testing algorithm, so that the new algorithms can be used to detect single or multiple changepoints in a time series. The detection power of the new algorithms is analyzed through Monte Carlo simulations. It has been shown that the new algorithms work very well and fast in detecting single or multiple changepoints. Examples of their application to real climate data series (surface pressure and wind speed) are presented. An open-source software package (in R and FORTRAN) for implementing the algorithms, along with a user manual, has been developed and made available online free of charge.
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Citations
Cites
Statistical Analysis in Climate Research
Lund, R. B., von Storch, H., & Zwiers, F. W. (2000) · Journal of the American Statistical Association · doi:10.2307/2669798 · Cited by 2,741
Statistical Analysis in Climate Research
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A homogeneity test applied to precipitation data.
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HISTALP—historical instrumental climatological surface time series of the Greater Alpine Region
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Homogeneity adjustments ofin situ atmospheric climate data: a review
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A Review and Comparison of Changepoint Detection Techniques for Climate Data
Reeves, J., Chen, J., Wang, X. L., Lund, R., & Lu, Q. Q. (2007) · Journal of Applied Meteorology and Climatology · doi:10.1175/jam2493.1 · Cited by 638 · cited 1×
“There have also emerged several studies that review and compare different methods for testing artificial shifts (e.g., Easterling and Peterson 1995; Peterson et al. 1998; DeGaetano 2006; Reeves et al. 2007).”
ResultSelf-citationWang, X. L., & Swail, V. R. (2001) · Journal of Climate · doi:10.1175/1520-0442(2001)014<2204:coewhi>2.0.co;2 · Cited by 552
Self-citationA new method for detecting undocumented discontinuities in climatological time series
Easterling, D. R., & Peterson, T. C. (1995) · International Journal of Climatology · doi:10.1002/joc.3370150403 · Cited by 419
Penalized Maximal t Test for Detecting Undocumented Mean Change in Climate Data Series
Wang, X. L., Wen, Q. H., & Wu, Y. (2007) · Journal of Applied Meteorology and Climatology · doi:10.1175/jam2504.1 · Cited by 368
Self-citationPenalized Maximal F Test for Detecting Undocumented Mean Shift without Trend Change
Wang, X. L. (2008) · Journal of Atmospheric and Oceanic Technology · doi:10.1175/2007jtecha982.1 · Cited by 339
Self-citation
Cited by
Donat, M. G., Peterson, T. C., Brunet, M., King, A. D., Almazroui, M., Kolli, R. K., Boucherf, D., Al‐Mulla, A. Y., Nour, A. Y., Aly, A. A., et al. (2014) · International Journal of Climatology · doi:10.1002/joc.3707 · Cited by 391
Vincent, L. A., Wang, X. L., Milewska, E. J., Wan, H., Yang, F., & Swail, V. (2012) · Journal of Geophysical Research: Atmospheres · doi:10.1029/2012jd017859 · Cited by 372
Self-citationBenchmarking homogenization algorithms for monthly data
Venema, V. K. C., Mestre, O., Aguilar, E., Auer, I., Guijarro, J. A., Domonkos, P., Vertacnik, G., Szentimrey, T., Stepanek, P., Zahradnicek, P., et al. (2012) · Climate of the Past · doi:10.5194/cp-8-89-2012 · Cited by 368
New Techniques for the Detection and Adjustment of Shifts in Daily Precipitation Data Series
Wang, X. L., Chen, H., Wu, Y., Feng, Y., & Pu, Q. (2010) · Journal of Applied Meteorology and Climatology · doi:10.1175/2010jamc2376.1 · Cited by 321
Self-citationExposure, instrumentation, and observing practice effects on land temperature measurements
Trewin, B. (2010) · WIREs Climate Change · doi:10.1002/wcc.46 · Cited by 153
Metadata
- Authors
- Wang, X. L.
- Venue
- Journal of Applied Meteorology and Climatology
- Publisher
- American Meteorological Society
- Published
- 2008-09-01
- Volume
- 47
- Issue
- 9
- Pages
- 2423-2444
- ISSN
- 1558-8424 (ISSN-L)
- 1558-8432
- OpenAlex
- W1998197711
- Cited by
- 427
- References
- 20
- FWCI
- 12.74
- Type
- journal article
- Language
- en
- Open access
- closed
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- Wang, X. L. (2008). Accounting for Autocorrelation in Detecting Mean Shifts in Climate Data Series Using the Penalized Maximal t or F Test. Journal of Applied Meteorology and Climatology. https://doi.org/10.1175/2008jamc1741.1
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