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Bayesian spatial extreme value analysis to assess the changing risk of concurrent high temperatures across large portions of European cropland
Author(s) -
Shaby Benjamin A.,
Reich Brian J.
Publication year - 2012
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/env.2178
Subject(s) - extreme value theory , agriculture , bayesian probability , environmental science , spatial coherence , spatial distribution , climate change , bayesian inference , physical geography , econometrics , climatology , geography , coherence (philosophical gambling strategy) , statistics , mathematics , ecology , geology , archaeology , biology
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. Copyright © 2012 John Wiley & Sons, Ltd.