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The Scafetta Saga

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It has taken 17 months to get a comment published pointing out the obvious errors in the Scafetta (2022) paper in GRL.

Back in March 2022, Nicola Scafetta published a short paper in Geophysical Research Letters (GRL) purporting to show through ‘advanced’ means that ‘all models with ECS > 3.0°C overestimate the observed global surface warming’ (as defined by ERA5). We (me, Gareth Jones and John Kennedy) wrote a note up within a couple of days pointing out how wrongheaded the reasoning was and how the results did not stand up to scrutiny.

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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

Area-based global hydro-climatological indicators

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The World Meteorological Organisation (WMO) Global Climate Observing System (GCOS) and Copernicus Climate Change Services (C3S) both provide sets of global climate statistics to summarise the state of Earth’s climate. They are indeed valuable indicators for the global or regional mean temperature, greenhouse gas concentrations, both ice volume and area, ocean heat, acidification, and the global sea level.

Still, I find it surprising that the set does not include any statistics on the global hydrological cycle, relevant to rainfall patterns and droughts. Two obvious global hydro-climatological indicators are the total mass of water falling on Earth’s surface each day P and the fraction of Earth’s surface area on which it falls Ap.  

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Turning a new page[s]

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The world is full of climate dashboards (and dashboards of dashboards), and so you might imagine that all datasets and comparisons are instantly available in whatever graphical form you like. Unfortunately, we often want graphics to emphasize a particular point or comparison, and generic graphs from the producers of the data often don’t have the same goal in mind. Dashboards that allow for more flexibility (like WoodForTrees) are useful, but aren’t as visually appealing as they could be. Thus, I find myself creating bespoke graphics of climate and climate model data all the time.

Some of these are maintained on the Climate model-observations comparison page but many of the graphs that I make (often to make a point on twitter) aren’t saved there and often their provenance is a bit obscure. Given that twitter will not last forever (though it might be around for slightly longer than a head of lettuce), it’s probably useful to have a spot to upload these graphics to, along with some explanation, to serve as a reference.

I have therefore created a couple of ‘pages’ (in wordpress speak) with fixed URLs where I will be curating relevant graphics I make (and findable at the bottom of the page under “DATA AND GRAPHICS”). The first is focused on the surface temperature records. I often update relevant graphics associated with this in early January (when we get another dot on the graphs), but there are associated graphs that I’ve made that don’t make it into those updates, so this is a place for them too. This includes the impacts of ENSO, comparisons across different platforms, or the impact of homogenization.

Comparison of four instrumental records which all coherently show warming since 1880.

The second page is bit more eclectic. These are graphs that are relevant to some trope or talking point that often pops up, and my graphs are an attempt to provide context (usually), or to debunk it entirely. This is where you’ll find maps of where the climate is warming faster than the global average, time-series of river ice break-up dates, and an example of sensible scaling of CO2 changes and temperature.

Map showing all the areas where trends from 1971-2022 are greater than the global mean trend. Almost all of the northern hemisphere landmass, and much of the SH land too.

To start with, I’m just going to upload some graphs I’ve made recently (with any updates that are needed), and I’ll add content as I make something new. If there are any other ideas (that aren’t too involved!), I’ll be happy to look at adding those too. Let me know if this is useful.

The summary for policymakers of the Intergovernmental Panel on Climate Change sixth assessment reports synthesis

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The summary for policymakers of the Intergovernmental Panel on Climate Change (IPCC) sixth synthesis report was released on March 20th (available online as a PDF). There is a recording of the IPCC Press Conference – Climate Change 2023: Synthesis Report for those who are interested in watching an awkward release of the report.

It strikes me that the IPCC perhaps assumes that everyone is climate literate and are up to speed on climate change. While many journalists clearly got the message, expressed through news reports though e.g. the Guardian and Washington Post, I doubt that relevant leaders were swayed. One problem may be that journalists do not carry as much weight as scientists. 

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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

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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Watching the detections

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The detection and the attribution of climate change are based on fundamentally different frameworks and shouldn’t be conflated.

We read about and use the phrase ‘detection and attribution’ of climate change so often that it seems like it’s just one word ‘detectionandattribution’ and that might lead some to think that it is just one concept. But it’s not.

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Digital Twinge

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A couple of weeks ago the EU announced that they were funding a project called DestinE (Destination Earth) to build ‘digital twins’ of the Earth System to support policy making and rapid reaction to weather and climate events.

While the term ‘digitial twin’ has a long history in the engineering world, it’s only recently been applied to Earth System Modeling, and is intended (I surmise, as does Bryan Lawrence) to denote something more than the modeling of either weather or climate that we’ve been doing for years. But what exactly? And is it an achievable goal or just a rebranding effort of things that are happening anyway?

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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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