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Bayesian uncertainty quantification of internal climate variability
Dimensionality reduction techniques are powerful for extracting modes of climate variability from observational data sets and climate model output. Over the past decades, multiple studies have shown that dominant climate patterns can be identified, and that climate evolution can be approximately linearized in such subspaces.Vincent Verjans, Markus Donat
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The physics of climate variability and climate change
Reviews of Modern Physics, 2020Michael Ghil, Valerio Lucarini
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Internal wave-driven mixing: governing processes and consequences for climate
Nature Reviews Earth & Environment, 2020Caitlin B Whalen +2 more
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The internal variability of the climatic system
2017K. Ya. Kondratyev, A. P. Cracknell
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Climate change impacts on wind power generation
Nature Reviews Earth & Environment, 2020Sara C Pryor +2 more
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