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Blanusa, M.L., López-Zurita, C.J. & Rasp, S. Internal variability plays a dominant role in global climate projections of temperature and precipitation extremes. Clim Dyn (2023). https://doi.org/10.1007/s00382-023-06664-3
It’s a paper on the relative uncertainties in predictions (not projections as the title suggests as it treats scenarios as an uncertainty) of extreme events arising from: internal variability, model uncertainty and scenario uncertainty. The extreme events are once in a decade daily precip or Tmax values and they are asking about the predictability of the exact number of events over a particular time window. Unsurprisingly, internal variability is a large component of this mix in the near future. For precip it remains a large component in many regions out to the end of the century. The intro says “If internal variability makes up a large fraction of the total variability, even a significant model improvement would only lead to a minor reduction in total uncertainty”. As internal variability constitutes a large fraction of the variability, they conclude that there is less to be gained from reducing model uncertainty and that ensembles are important. I agree with the latter claim.
I have one major overarching criticism, but upfront I’ll say this is a well written paper, clearly expressed and illustrated and it looks like a good deal of thought went into assessing sensitivity to various choices made, at least within the boundaries set by the original question.
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