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Attributing the probability of South African weather extremes to anthropogenic greenhouse gas emissions: Spatial characteristics
Author(s) -
Angélil Oliver,
Stone Dáithí A.,
Pall Pardeep
Publication year - 2014
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1002/2014gl059760
Subject(s) - climate extremes , environmental science , precipitation , greenhouse gas , climatology , spatial ecology , climate model , climate change , atmospheric sciences , magnitude (astronomy) , spatial variability , meteorology , geography , geology , statistics , mathematics , ecology , oceanography , physics , astronomy , biology
Recent studies have examined the role of anthropogenic emissions in the probability of extreme weather events. These studies examine an event aggregated over a spatial domain, but the dependence on domain definition is unknown. Here we investigate this dependence for the frequency of daily weather extremes across South Africa using a climate model run under both a real‐world and a nongreenhouse gas world scenario. Attributable changes in extremely hot and cold days are dominated by large‐scale spatial structures, with sharp gradients at the 100 km scale arising for hot events because of the large magnitude of changes. The attributable probabilities of heavy precipitation events are spatially heterogeneous down to the 100 km resolution of the climate model. Therefore, while estimates of attributable probability for temperature events may often be considered valid within smaller and neighboring spatial domains, it appears that estimates for heavy daily precipitation events may be sensitive to the definition of the event.