M-CaStLe generalizes local stencil-based causal discovery to the multivariate case and decomposes resulting graphs into reaction and spatial components for interpretation in space-time gridded data.
and Naveau, P.: Probabilities of Causation of Climate Changes
2 Pith papers cite this work. Polarity classification is still indexing.
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A non-stationary Markov process with bivariate extreme value theory attributes full heatwave time series over Europe to anthropogenic forcing via likelihood ratios between ERA5 and CMIP6 runs, finding strong evidence since the 1970s but no signal beyond mean temperature increase.
citing papers explorer
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M-CaStLe: Uncovering Local Causal Structures in Multivariate Space-Time Gridded Data
M-CaStLe generalizes local stencil-based causal discovery to the multivariate case and decomposes resulting graphs into reaction and spatial components for interpretation in space-time gridded data.
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Non-stationary time series attribution for heatwaves over Europe
A non-stationary Markov process with bivariate extreme value theory attributes full heatwave time series over Europe to anthropogenic forcing via likelihood ratios between ERA5 and CMIP6 runs, finding strong evidence since the 1970s but no signal beyond mean temperature increase.