Bayesian spatial extreme value analysis to assess the changing risk of concurrent high temperatures across large portions of European cropland

Benjamin Adam Shaby, Brian J. Reich

Research output: Contribution to journalArticle

23 Scopus citations

Abstract

There is strong evidence that extremely high temperatures are detrimental to the yield and quality of many economically and socially critical crops. Fortunately, the most deleterious conditions for agriculture occur rarely. We wish to assess the risk of the catastrophic scenario in which large areas of croplands experience extreme heat stress during the same growing season. Applying a hierarchical Bayesian spatial extreme value model that allows the distribution of extreme temperatures to change in time both marginally and in spatial coherence, we examine whether the risk of widespread extremely high temperatures across agricultural land in Europe has increased over the last century.

Original languageEnglish (US)
Pages (from-to)638-648
Number of pages11
JournalEnvironmetrics
Volume23
Issue number8
DOIs
StatePublished - Dec 1 2012

All Science Journal Classification (ASJC) codes

  • Ecological Modeling
  • Statistics and Probability

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