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  Comparison of statistically optimal approaches to detecting anthropogenic climate change

Hegerl, G. C., & North, G. R. (1997). Comparison of statistically optimal approaches to detecting anthropogenic climate change. Journal of Climate, 10, 1125-1133. doi:10.1175/1520-0442(1997)010<1125:COSOAT>2.0.CO;2.

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JoC-1997-Hegerl.pdf (Publisher version), 146KB
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 Creators:
Hegerl, Gabriele C.1, Author
North, Gerald R.2, Author
Affiliations:
1MPI for Meteorology, Max Planck Society, Bundesstraße 53, 20146 Hamburg, DE, ou_913545              
2Climate Research Program, College of Geosciences and Mariteme Studies, Texas A&M University, College Station, TX 77843-3150, USA, ou_persistent22              

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Free keywords: anthropogenic effect; climate change; method comparison; statistical analysis
 Abstract: Three statistically optimal approaches, which have been proposed for detecting anthropogenic climate change, are intercompared. It is shown that the core of all three methods is identical. However, the different approaches help to better understand the properties of the optimal detection. Also, the analysis allows us to examine the problems in implementing these optimal techniques in a common framework. An overview of practical considerations necessary for applying such an optimal method for detection is given. Recent applications show that optimal methods present some basis for optimism toward progressively more significant detection of forced climate change. However, it is essential that good hypothesized signals and good information on climate variability be obtained since erroneous variability, especially on the timescale of decades to centuries, can lead to erroneous conclusions.

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Language(s): eng - English
 Dates: 1997
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Degree: -

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Title: Journal of Climate
  Other : J. Clim.
Source Genre: Journal
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Publ. Info: Boston, MA : American Meteorological Society
Pages: - Volume / Issue: 10 Sequence Number: - Start / End Page: 1125 - 1133 Identifier: ISSN: 0894-8755
CoNE: https://pure.mpg.de/cone/journals/resource/954925559525

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Title: Report / Max-Planck-Institut für Meteorologie
  Other : MPI Report
Source Genre: Series
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Publ. Info: Hamburg : Max-Planck-Institut für Meteorologie
Pages: - Volume / Issue: 167 Sequence Number: - Start / End Page: - Identifier: ISSN: 0937-1060
CoNE: https://pure.mpg.de/cone/journals/resource/0937-1060