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The official website of the Nobel Prize - NobelPrize.org The Nobel Prize rewards science, humanism and peace efforts. This is one of the central concepts in the will of Alfred Nobel, and it also permeates the outreach activities that have been developed for...

John Clarke, my previous advisor and co-author from UC Berkeley, just won the Nobel Prize in Physics! John is not only brilliant, he is also super kind and nice. It makes me very happy that someone like John, driven by genuine curiosity, not status, won this incredibly prestigious award. Congrats!

Yes, that's right.

The median is biased... Before using statistics, you should make sure the sample is representative. Yes? We finally have a new paper out which looks at this question for scenarios assessed in the IPCC Sixth Assessment Report...

And @glenpeters.bsky.social provides a good summary here: www.linkedin.com/pulse/median...

A popular version of the paper can also be found here: cicero.oslo.no/en/articles/...
@cicero.oslo.no

Different 1.5°C pathways come with different trade-offs, costs and benefits. The IPCC should focus more on identifying robust scenario relationships, while also conveying what we don’t know, and where there is disagreement in the scenarios literature.

The purpose of scenario analysis is not to provide precise estimates of isolated scenario outcomes, but to show the implications of choices and trade-offs. Different models provide different views. Statistical values from an arbitrary sample does little to convey this.

Where does that leave us? The use of individual scenario variable statistics may not be the best way to reflect the findings contained within the scenarios literature, which is what the IPCC is ultimately meant to assess.

Had the number of scenarios from different models or studies in the IPCC scenarios database been different, headline IPCC mitigation findings could have been different. Statistical findings are, not surprisingly, impacted by the distribution of models and studies.

It is partly because the dominant model, REMIND, is responsible for a very large share (42%) of the 1.5°C scenarios – much larger than the dominant study, ENGAGE (26%). But also because many scenario outcomes are strongly model dependent – models have distinct “fingerprints”.

It is the model with the most scenarios that has the largest influence on most 1.5°C scenario findings. Individual studies have mostly only a small or negligible impact. Why is this?

Median 2050 coal and gas reductions change from 95% to 83% and from 43% to 29%. The median net-zero GHG year shifts from 2098 to 2086 when removing just one model, from 2098 to 2084 when removing just one study, and to after 2100 when removing several others.

Median global GHG reductions by 2030 — a widely recognized target, used in the Sharm el-Sheikh Implementation Plan — changes from 43% to 50% (relative to 2019) when only a single model is excluded. This is despite more than 50 models submitting scenarios to the IPCC database.

Influence of individual models and studies on quantitative mitigation findings in the IPCC Sixth Assessment Report - Nature Communications The paper analyses the impact of the uneven representation of models and studies on key mitigation findings in the IPCC Sixth Assessment Report. It finds that the model with the most scenarios has a considerable influence on several findings.

New paper with @glenpeters.bsky.social in Nature Communications today. We show how models and studies with a lot of scenarios in the IPCC scenarios database have a large impact on key findings, including emissions reductions, net-zero GHG year, and coal, gas, and oil consistent with 1.5°C.