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Instrumental Record

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 (Scafetta, 2022b) 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
  2. N. Scafetta, "CMIP6 GCM ensemble members versus global surface temperatures", Climate Dynamics, vol. 60, pp. 3091-3120, 2022. http://dx.doi.org/10.1007/s00382-022-06493-w

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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A CERES of fortunate events…

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The CERES estimates of the top-of-atmosphere radiative fluxes are available from 2001 to the present. That is long enough to see that there has been a noticeable trend in the Earth’s Energy Imbalance (EEI), mostly driven by a reduction in the solar radiation reflected by the planet, while the outgoing long wave radiation does not appear to contribute much. But what can be causing this?

A paper last year (Goode et al., 2021) also reported on a two decade estimate of Earthshine measurements which appear to confirm a small decrease in albedo (and decrease in reflected short wave (SW) radiation). While the two measurements are subtly different due to the distinct geometries, they do show sufficient coherence to give us some confidence that they are real.

Comparison of CERES SWup trends (blue) with inferred changes in Earthshine (black).

Similarly, Loeb et al. (2021) show that the trends in the EEI derived from CERES match what you get from the changes in ocean heat content.

Satellite-derived trends in EEI compared to estimates from changes in ocean heat (updated by Schmidt et al, 2023).

A few people have started to interpret the dominance of the SW trends to imply that the overall trends in climate are not (despite copious evidence) being driven by the rise in greenhouse gases (for instance, the rather poorly argued and seemingly un-copyedited Dübal and Vahrenholt (2021)) but these simplistic interpretations are seriously confused.

We can explore the issues and pitfalls of this using the ‘simple model’ of the greenhouse effect we explored back in 2007. At that time, we said:

You should think of these kinds of exercises as simple flim-flam detectors – if someone tries to convince you that they can do a simple calculation and prove everyone else wrong, think about what the same calculation would be in this more straightforward system and see whether the idea holds up. If it does, it might work in the real world (no guarantee though) – but if it doesn’t, then it’s most probably garbage.

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References

  1. P.R. Goode, E. Pallé, A. Shoumko, S. Shoumko, P. Montañes‐Rodriguez, and S.E. Koonin, "Earth's Albedo 1998–2017 as Measured From Earthshine", Geophysical Research Letters, vol. 48, 2021. http://dx.doi.org/10.1029/2021GL094888
  2. N.G. Loeb, G.C. Johnson, T.J. Thorsen, J.M. Lyman, F.G. Rose, and S. Kato, "Satellite and Ocean Data Reveal Marked Increase in Earth’s Heating Rate", Geophysical Research Letters, vol. 48, 2021. http://dx.doi.org/10.1029/2021GL093047
  3. H. Dübal, and F. Vahrenholt, "Radiative Energy Flux Variation from 2001–2020", Atmosphere, vol. 12, pp. 1297, 2021. http://dx.doi.org/10.3390/atmos12101297

The CO2 problem in six easy steps (2022 Update)

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One of our most-read old posts is the step-by-step explanation for why increasing CO2 is a significant problem (The CO2 problem in 6 easy steps). However, that was written in 2007 – 15 years ago! While the basic steps and concepts have not changed, there’s 15 years of more data, updates in some of the details and concepts, and (it turns out) better graphics to accompany the text. And so, here is a mildly updated and referenced version that should be a little more useful.

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River Ice break-up trends 2022

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As in previous years, the spring break-up of river ice on the Tanana River at Nenana and the Yukon River at Dawson City in Canada (new! h/t Ed Wiebe), is a great opportunity to highlight phenology that indicates that the planet is in fact reacting to the ongoing global warming. As we’ve done in previous years, the Nenana dates can be plotted and show a clear trend towards earlier break-ups (by about 8 days/century over the whole record, or 13 days/century since 1975).

Nenana Ice Classic break up dates since 1917.

2022 was on trend, and in 2014, I noted that May 3rd was the most likely date given the trends until then.

Dawson City in the Yukon is about 250 miles east of Nenana which is close enough for the seasonal anomalies in climate to be quite highly correlated. So one might expect that the break-up dates would be similarly correlated… and indeed they are:

Break up dates at Nenana and Dawson City

The ice at Dawson breaks up on average 3.8 days later than the ice at Nenana (5.1 days this year), but the correlation between the two series is an impressive 0.82. There have been 15 times the ice went out within 24 hours of each other and in 1963 they broke up less than 3 minutes apart! The trends are likewise very similar 7.7±3.8 days/century for Nenana, compared to 6.5±3.1 days/century since 1917. This pretty much puts paid to the occasional claim of the urban heat island in Fairbanks affecting the water and causing the trend.

[Update: I misunderstood the Yukon river break up website, and erroneously stated that the break-up was on May 2nd. It was not. I’ll update this again when it has. Apologies.]

[Update II: The Yukon river ice broke up on May 7, and I’ve updated the graph and text.]

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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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

Another dot on the graphs (Part II)

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We have now updated the model-observations comparison page for the 2021 SAT and MSU TMT datasets. Mostly this is just ‘another dot on the graphs’ but we have made a couple of updates of note. First, we have updated the observational products to their latest versions (i.e. HadCRUT5, NOAA-STAR 4.1 etc.), though we are still using NOAA’s GlobalTemp v5 – the Interim version will be available later this year. Secondly, we have added a comparison of the observations to the new CMIP6 model ensemble.

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Another dot on the graph

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So last week was the annual release of the temperature records from NASA, NOAA and Berkeley Earth. The Copernicus ERA5 data was released a few days ago, and the HadCRUT data will follow soon. Unlike in years past, there is no longer any serious discrepancy between the records – which use multiple approaches for the ocean temperatures, the homogenization of the weather stations records, and interpolation.

Depending on the product, 2021 was either the 5th, 6th or 7th warmest year, but in all cases, it is part of the string of warm years (since 2015) that have all been more than 1ºC warmer than the late 19th C.

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