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13 - Field Significance

Published online by Cambridge University Press:  03 February 2022

Timothy DelSole
Affiliation:
George Mason University, Virginia
Michael Tippett
Affiliation:
Columbia University, New York
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Summary

Field significance is concerned with testing a large number of hypothesis simultaneously. Previous chapters have discussed methods for testing one hypothesis, such as whether one variable is correlated with one other variable. Field significance is concerned with whether one variable is related to a random vector. In climate applications, a characteristic feature of field significance problems is that the variables in the random vector correspond to quantities at different geographic locations. As such, neighboring variables are correlated and therefore exhibit spatial dependence. This spatial dependence needs to be taken into account when testing hypotheses. This chapter introduces the concept of field significance and explains three hypothesis test procedures: a Monte Carlo method proposed by Livezey and Chen (1983) and an associated permutation test, a regression method proposed by DelSole and Yang (2011), and a procedure to control the false discovery rate, proposed in a general context by Benjamini and Hockberg (1995) and applied to field significance problems by Ventura et al. (2004) and Wilks (2006).

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Publisher: Cambridge University Press
Print publication year: 2022

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  • Field Significance
  • Timothy DelSole, George Mason University, Virginia, Michael Tippett, Columbia University, New York
  • Book: Statistical Methods for Climate Scientists
  • Online publication: 03 February 2022
  • Chapter DOI: https://doi.org/10.1017/9781108659055.014
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  • Field Significance
  • Timothy DelSole, George Mason University, Virginia, Michael Tippett, Columbia University, New York
  • Book: Statistical Methods for Climate Scientists
  • Online publication: 03 February 2022
  • Chapter DOI: https://doi.org/10.1017/9781108659055.014
Available formats
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Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Field Significance
  • Timothy DelSole, George Mason University, Virginia, Michael Tippett, Columbia University, New York
  • Book: Statistical Methods for Climate Scientists
  • Online publication: 03 February 2022
  • Chapter DOI: https://doi.org/10.1017/9781108659055.014
Available formats
×