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Statistical methods are proposed to select homogeneous locations whenanalyzing spatial block maxima data, such as in extreme event attributionstudies. The methods are based on classical hypothesis testing using Wald-typetest statistics, with critical values obtained from suitable parametricbootstrap procedures and corrected for multiplicity. A large-scale Monte Carlosimulation study finds that the methods are able to accurately identifyhomogeneous locations, and that pooling the selected locations improves theaccuracy of subsequent statistical analyses. The approach is illustrated with acase study on precipitation extremes in Western Europe. The methods areimplemented in an R package that allows easy application in future extremeevent attribution studies.

Regional Pooling in Extreme Event Attribution Studies: an Approach Based on Multiple Statistical Testing