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A novel probabilistic forecast system predicting anomalously warm 2018-2022 reinforcing the long-term global warming trend ArchiMer
Sevellec, Florian; Drijfhout, Sybren S..
In a changing climate, there is an ever-increasing societal demand for accurate and reliable interannual predictions. Accurate and reliable interannual predictions of global temperatures are key for determining the regional climate change impacts that scale with global temperature, such as precipitation extremes, severe droughts, or intense hurricane activity, for instance. However, the chaotic nature of the climate system limits prediction accuracy on such timescales. Here we develop a novel method to predict global-mean surface air temperature and sea surface temperature, based on transfer operators, which allows, by-design, probabilistic forecasts. The prediction accuracy is equivalent to operational forecasts and its reliability is high. The post-1998...
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Ano: 2018 URL: https://archimer.ifremer.fr/doc/00454/56545/58254.pdf
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