Testing for Collective Statistical Significance in Climate Change Detection Studies

  • Radan HuthEmail author
  • Martin Dubrovský
Conference paper
Part of the Advances in Science, Technology & Innovation book series (ASTI)


We examined several approaches to detecting statistical significance of trends defined on a grid, that is, on a regional scale. To this end, we introduced a novel simple procedure of significance testing based on counting signs of local trends (sign test), and comparing it with four other approaches to testing collective significance of trends (counting, extended Kendall, Walker, and FDR tests). Synthetic data were used to construct the null distributions of trend statistics and determine critical values of the tests. The application of the five tests to real datasets reveals that outcomes of the tests may differ even though trends are locally significant at the majority of the grid points.


Climate change Significance testing Collective statistical significance Temperature Trend detection 



This study was supported by the Czech Science Foundation, project 16-04676S.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Physical Geography and GeoecologyCharles UniversityPragueCzech Republic
  2. 2.Institute of Atmospheric PhysicsCzech Academy of SciencesPragueCzech Republic

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