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  How to determine the statistical significance of trends in seasonal records: Application to Antarctic temperatures

Bunde, A., Ludescher, J., Schellnhuber, H. J. (2021 online): How to determine the statistical significance of trends in seasonal records: Application to Antarctic temperatures. - Climate Dynamics.

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Item Permalink: https://publications.pik-potsdam.de/pubman/item/item_26043 Version Permalink: https://publications.pik-potsdam.de/pubman/item/item_26043_1
Genre: Journal Article

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 Creators:
Bunde, Armin1, Author
Ludescher, Josef2, Author              
Schellnhuber, Hans Joachim2, Author              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: We consider trends in the m seasonal subrecords of a record. To determine the statistical significance of the m trends, one usually determines the p value of each season either numerically or analytically and compares it with a significance level α~. We show in great detail for short- and long-term persistent records that this procedure, which is standard in climate science, is inadequate since it produces too many false positives (false discoveries). We specify, on the basis of the family wise error rate and by adapting ideas from multiple testing correction approaches, how the procedure must be changed to obtain more suitable significance criteria for the m trends. Our analysis is valid for data with all kinds of persistence. Specifically for long-term persistent data, we derive simple analytical expressions for the quantities of interest, which allow to determine easily the statistical significance of a trend in a seasonal record. As an application, we focus on 17 Antarctic station data. We show that only four trends in the seasonal temperature data are outside the bounds of natural variability, in marked contrast to earlier conclusions.

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Language(s): eng - English
 Dates: 2021-09-122021-10-05
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: MDB-ID: No data to archive
PIKDOMAIN: RD1 - Earth System Analysis
Organisational keyword: RD1 - Earth System Analysis
PIKDOMAIN: Director Emeritus / Executive Staff / Science & Society
Organisational keyword: Director Emeritus Schellnhuber
Regional keyword: Arctic & Antarctica
Model / method: Quantitative Methods
OATYPE: Hybrid - DEAL Springer Nature
 Degree: -

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Title: Climate Dynamics
Source Genre: Journal, SCI, Scopus, p3
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Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals77
Publisher: Springer