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Comparison of Statistically Optimal Approaches to Detecting Anthropogenic Climate Change

Comparison of Statistically Optimal Approaches to Detecting Anthropogenic Climate Change 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Climate American Meteorological Society

Comparison of Statistically Optimal Approaches to Detecting Anthropogenic Climate Change

Journal of Climate , Volume 10 (5) – Sep 18, 1995

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Publisher
American Meteorological Society
Copyright
Copyright © 1995 American Meteorological Society
ISSN
1520-0442
DOI
10.1175/1520-0442(1997)010<1125:COSOAT>2.0.CO;2
Publisher site
See Article on Publisher Site

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.

Journal

Journal of ClimateAmerican Meteorological Society

Published: Sep 18, 1995

There are no references for this article.