Something I forgot to mention in my comments before: Peter Watson suggested to me it’s reasonably likely that estimates of climate sensitivity will be revised upwards for the next IPCC, as the latest generation of models are running hotter. (e.g. https://www.carbonbrief.org/guest-post-why-results-from-the-next-generation-of-climate-models-matter, https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2019GL085782 - “The range of ECS values across models has widened in CMIP6, particularly on the high end, and now includes nine models with values exceeding the CMIP5 maximum (Figure 1a). Specifically, the range has increased from 2.1–4.7 K in CMIP5 to 1.8–5.6 K in CMIP6.”) This could drive up the probability mass over 6 degrees in your model by quite a bit, so could be worth doing a sensitivity analysis on that.
Cloud formation was the biggest unknown feedback loop and efforts to model them more accurately has led to the increase in range. The effects only start at unprecedented levels of warming which is why observational data may not fit.
Peter here—so actually I’d say this isn’t clear now—here’s some recent work for example suggesting that estimates of future warming won’t change much compared to those from the previous set of models once recent observed warming is used as a constraint i.e. those newer models with higher sensitivity seem to warm too fast compared to observations e.g. https://advances.sciencemag.org/content/6/12/eaaz9549 . Well, the models are only one piece of evidence going into the overall estimate anyway. I don’t follow the literature on this closely enough to be confident about what the IPCC will actually conclude.
Something I forgot to mention in my comments before: Peter Watson suggested to me it’s reasonably likely that estimates of climate sensitivity will be revised upwards for the next IPCC, as the latest generation of models are running hotter. (e.g. https://www.carbonbrief.org/guest-post-why-results-from-the-next-generation-of-climate-models-matter, https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2019GL085782 - “The range of ECS values across models has widened in CMIP6, particularly on the high end, and now includes nine models with values exceeding the CMIP5 maximum (Figure 1a). Specifically, the range has increased from 2.1–4.7 K in CMIP5 to 1.8–5.6 K in CMIP6.”) This could drive up the probability mass over 6 degrees in your model by quite a bit, so could be worth doing a sensitivity analysis on that.
Ah, I didn’t know that, thanks, I haven’t followed the literature that closely over the last year. I’ll put that into the model.
On a side note, that does seem high, and doesn’t seem like it would fit with the observational data for the last 200 years very well.
Cloud formation was the biggest unknown feedback loop and efforts to model them more accurately has led to the increase in range. The effects only start at unprecedented levels of warming which is why observational data may not fit.
https://e360.yale.edu/features/why-clouds-are-the-key-to-new-troubling-projections-on-warming
right, that’s bad news.
Peter here—so actually I’d say this isn’t clear now—here’s some recent work for example suggesting that estimates of future warming won’t change much compared to those from the previous set of models once recent observed warming is used as a constraint i.e. those newer models with higher sensitivity seem to warm too fast compared to observations e.g. https://advances.sciencemag.org/content/6/12/eaaz9549 . Well, the models are only one piece of evidence going into the overall estimate anyway. I don’t follow the literature on this closely enough to be confident about what the IPCC will actually conclude.