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Serious mistakes found in recent paper by Connolly et al.

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Guest post by Mark Richardson who is a Research Scientist in the Aerosol and Clouds Group at NASA’s Jet Propulsion Laboratory, California Institute of Technology. All opinions expressed are his own and do not in any way represent those of NASA, JPL or Caltech.

Should scientists choose to believe provably false things? Even though that would mean more inclusive debates with a wider range of opinions, our recent paper Richardson & Benestad (2022) argues no: “instead of repeating errors, they should be acknowledged and corrected so that the debate can focus on areas of legitimate scientific uncertainty”. We were responding to Connolly et al., who suggested that maybe the Sun caused “most” of the warming in “recent decades” based on a simple maths mistake. 

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References

  1. M.T. Richardson, and R.E. Benestad, "Erroneous use of Statistics behind Claims of a Major Solar Role in Recent Warming", Research in Astronomy and Astrophysics, vol. 22, pp. 125008, 2022. http://dx.doi.org/10.1088/1674-4527/ac981c

Scafetta comes back for more

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A new paper from Scafetta and it’s almost as bad as the last one.

Back in March, we outlined how a model-observations comparison paper in GRL by Nicola Scafetta (Scafetta, 2022a) got wrong basically everything that one could get wrong (the uncertainty in the observations, the internal variability in the models, the statistical basis for comparisons – the lot!). Now he’s back with a new paper in a different journal that could be seen as trying to patch the holes in the first one, but while he makes some progress, he now adds some new errors while attempting CPR on his original conclusions.

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References

  1. N. Scafetta, "Advanced Testing of Low, Medium, and High ECS CMIP6 GCM Simulations Versus ERA5‐T2m", Geophysical Research Letters, vol. 49, 2022. http://dx.doi.org/10.1029/2022GL097716

New misguided interpretations of the greenhouse effect from William Kininmonth

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I have a feeling that we are seeing the start of a new wave of climate change denial and misrepresentation of science. At the same time, CEOs of gas and oil companies express optimism for further exploitation of fossil energy in the wake of Russia’s invasion of Ukraine, at least here in Norway.

Another clue is William Kininmonth’s ‘rethink’ on the greenhouse effect for The Global Warming Policy Foundation. He made some rather strange claims, such as that the Intergovernmental Panel on Climate  Change (IPCC) allegedly should have forgotten that the earth is a sphere because “most absorption of solar radiation takes place over the tropics, while there is excess emission of longwave radiation to space over higher latitudes”. 

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The modern demarcation problem

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Defining (and enforcing) a clear line between information and mis-information is impossible, but that doesn’t mean misinformation doesn’t exist or that there is nothing to be done to combat it.

I found myself caught in an ‘interesting’ set of exchanges on twitter a few weeks ago (I won’t link to it to spare you the tedium, but you could probably find it if you look hard enough). The nominal issue was whether deplatforming known bull******s was useful at stemming the spread of misinformation (specifically with respect to discussions around COVID). There is evidence that this does in fact work to some extent, but the twitter thread quickly turned to the question of who decides what is misinformation in the first place, and then descended into a free-for-all where just the very mention that misinformation existed or that the scientific method provided a ratchet to detect it, was met with knee-jerk references to the Nazi’s and the inquisition. So far, so usual, right?

While the specific thread was not particularly edifying, and I’ll grant that my tweets were not perfectly pitched for the specific audience, this is a very modern example of the classic Demarcation Problem (Stanford Encyclopedia of Philosophy) in the philosophy of science.

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Issues and Errors in a new Scafetta paper

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Earlier this week, a new paper appeared in GRL by Nicola Scafetta (Scafetta, 2022) which purported to conclude that the CMIP6 models with medium or high climate sensitivity (higher than 3ºC) were not consistent with recent historical temperature changes. Since there have been a number of papers already on this topic, notably Tokarska et al (2020), which did not come to such a conclusion, it is worthwhile to investigate where Scafetta’s result comes from. Unfortunately, it appears to emerge from a mis-appreciation of what is in the CMIP6 archive, an inappropriate statistical test, and a total neglect of observational uncertainty and internal variability.

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References

  1. N. Scafetta, "Advanced Testing of Low, Medium, and High ECS CMIP6 GCM Simulations Versus ERA5‐T2m", Geophysical Research Letters, vol. 49, 2022. http://dx.doi.org/10.1029/2022GL097716
  2. K.B. Tokarska, M.B. Stolpe, S. Sippel, E.M. Fischer, C.J. Smith, F. Lehner, and R. Knutti, "Past warming trend constrains future warming in CMIP6 models", Science Advances, vol. 6, 2020. http://dx.doi.org/10.1126/sciadv.aaz9549

The Future of Climate Modeling?

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There was an interesting workshop last week focused on the Future of Climate Modelling. It was run by the World Climate Research Program (WCRP) Core Project on Earth System Modelling and Observations (ESMO) which is part of a bewildering alphabet soup of various advisory committees that exist for mostly unclear historical reasons. This one actually does something useful – namely it helps organize the CMIP activities that many modeling groups contribute to (which inform the assessment reports like IPCC and various national Climate Assessments). They had a wide variety of people and perspectives to discuss the changing landscape of climate modeling and what people want from these models. You won’t agree with everything, but it was informative.

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“Don’t Look Up”

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The highlight of the movie season for climate science has clearly been the release on Dec 24th 2021 of “Don’t Look Up”. While nominally about a different kind of disaster – the discovery of a comet heading to Earth on a collision course – the skewering of our current science-policy dysfunction transcends the specifics and makes a powerful metaphor for climate change, and even the ongoing COVID-19 pandemic.

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BAU wow wow

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How should we discuss scenarios of future emissions? What is the range of scenarios we should explore? These are constant issues in climate modeling and policy discussions, and need to be reassessed every few years as knowledge improves.

I discussed some of this in a post on worst case scenarios a few months ago, but the issue has gained more prominence with a commentary by Zeke Hausfather and Glen Peters in Nature this week (which itself partially derives from ongoing twitter arguments which I won’t link to because there are only so many rabbit holes that you want to fall into).

My brief response to this is here though:

Mike Mann has a short discussion on this as well. But there are many different perspectives around – ranging from the merely posturing to the credible and constructive. The bigger questions are certainly worth discussing, but if the upshot of the current focus is that we just stop using the term ‘business-as-usual’ (as was suggested in the last IPCC report), then that is fine with me, but just not very substantive.

References

  1. Z. Hausfather, and G.P. Peters, "Emissions – the ‘business as usual’ story is misleading", Nature, vol. 577, pp. 618-620, 2020. http://dx.doi.org/10.1038/d41586-020-00177-3

Update day 2020!

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Following more than a decade of tradition (at least), I’ve now updated the model-observation comparison page to include observed data through to the end of 2019.

As we discussed a couple of weeks ago, 2019 was the second warmest year in the surface datasets (with the exception of HadCRUT4), and 1st, 2nd or 3rd in satellite datasets (depending on which one). Since this year was slightly above the linear trends up to 2018, it slightly increases the trends up to 2019. There is an increasing difference in trend among the surface datasets because of the polar region treatment. A slightly longer trend period additionally reduces the uncertainty in the linear trend in the climate models.

To summarize, the 1981 prediction from Hansen et al (1981) continues to underpredict the temperature trends due to an underestimate of the transient climate response. The projections in Hansen et al. (1988) bracket the actual changes, with the slight overestimate in scenario B due to the excessive anticipated growth rate of CFCs and CH4 which did not materialize. The CMIP3 simulations continue to be spot on (remarkably), with the trend in the multi-model ensemble mean effectively indistinguishable from the trends in the observations. Note that this doesn’t mean that CMIP3 ensemble means are perfect – far from it. For Arctic trends (incl. sea ice) they grossly underestimated the changes, and overestimated them in the tropics.

CMIP3 for the win!

The CMIP5 ensemble mean global surface temperature trends slightly overestimate the observed trend, mainly because of a short-term overestimate of solar and volcanic forcings that was built into the design of the simulations around 2009/2010 (see Schmidt et al (2014). This is also apparent in the MSU TMT trends, where the observed trends (which themselves have a large spread) are at the edge of the modeled histogram.

A number of people have remarked over time on the reduction of the spread in the model projections in CMIP5 compared to CMIP3 (by about 20%). This is due to a wider spread in forcings used in CMIP3 – models varied enormously on whether they included aerosol indirect effects, ozone depletion and what kind of land surface forcing they had. In CMIP5, most of these elements had been standardized. This reduced the spread, but at the cost of underestimating the uncertainty in the forcings. In CMIP6, there will be a more controlled exploration of the forcing uncertainty (but given the greater spread of the climate sensitivities, it might be a minor issue).

Over the years, the model-observations comparison page is regularly in the top ten of viewed pages on RealClimate, and so obviously fills a need. And so we’ll continue to keep it updated, and perhaps expand it over time. Please leave suggestions for changes in the comments below.

References

  1. J. Hansen, D. Johnson, A. Lacis, S. Lebedeff, P. Lee, D. Rind, and G. Russell, "Climate Impact of Increasing Atmospheric Carbon Dioxide", Science, vol. 213, pp. 957-966, 1981. http://dx.doi.org/10.1126/science.213.4511.957
  2. J. Hansen, I. Fung, A. Lacis, D. Rind, S. Lebedeff, R. Ruedy, G. Russell, and P. Stone, "Global climate changes as forecast by Goddard Institute for Space Studies three-dimensional model", Journal of Geophysical Research, vol. 93, pp. 9341, 1988. http://dx.doi.org/10.1029/JD093iD08p09341
  3. G.A. Schmidt, D.T. Shindell, and K. Tsigaridis, "Reconciling warming trends", Nature Geoscience, vol. 7, pp. 158-160, 2014. http://dx.doi.org/10.1038/ngeo2105