Researchers have published the world’s first corrected and downscaled dataset designed to measure the concrete impacts of climate tipping points at +2 °C.
Assessing what would result from the collapse of the southern Atlantic rollover circulation (AMOC) or the decline of the Amazon forest requires both accurate and fine simulations. General circulation patterns remain too coarse and biased for impact studies. A team led by Philipp Hess and Niklas Boers presents ClimTip-GML, a global 0.25° resolution dataset that fills this gap.
It covers eight key variables from three climate models (CESM1-CAM5, HadGEM3-GC31-MM and MPI-ESM1-2-HR), on one-century simulations: pre-industrial and historical conditions, then a warming of +2 °C with or without change of the AMOC or Amazon. Generative models, trained on reanalysis, correct biases and increase resolution by keeping physical coherence in space, time and between variables.
According to the authors, biases are significantly reduced and small-scale variability better restored, without altering the long-term response to forcings and shifts. More directly feed into adaptation and mitigation policies.
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