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Clauser-ology: Cloudy with a chance of meatballs

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John Clauser’s theory of climate explained.

Some of you will have heard of John Clauser because he was an awardee of the 2022 Nobel Prize in Physics for his role in the experimental verification of quantum entanglement. Some of you will have heard of him because the first thing that he did after winning the Nobel was join a climate denial organization and make some rather odd claims about climate science. And some of you will never have heard of him (in which case, feel free to skip this post!).

At no point in his long and, by all accounts, successful, career has he ever published a paper on climate[1]. He has not penned an article, nor even a blog post or a tweet on the topic, and so any scientific basis for his opinions (if any) has been opaque… until recently. In the last few months he has given two interviews in which he goes into to detail about what he describes as a ‘missing element’ in climate science and what he imagines the consequences are for climate change. The first interview was for the Epoch Times (a far right-wing newspaper and media organization affiliated with Falun Gong). The second was a podcast with the somewhat troubled Chris Smith, an Australian journalist. (The material is somewhat similar in each). And more comprehensively, it was repeated in a recent video lecture as well.

And what is this supposed ‘missing element’? Clouds.

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2022 updates to the temperature records

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Another January, another annual data point.

As in years past, the annual rollout of the GISTEMP, NOAA, HadCRUT and Berkeley Earth analyses of the surface temperature record have brought forth many stories about the long term trends and specific events of 2022 – mostly focused on the impacts of the (ongoing) La Niña event and the litany of weather extremes (UK and elsewhere having record years, intense rainfall and flooding, Hurricane Ian, etc. etc.).

But there are a few things that don’t get covered much in the mainstream stories, and so we can dig into them a bit here.

What influence does ENSO really have?

It’s well known (among readers here, I assume), that ENSO influences the interannual variability of the climate system and the annual mean temperatures. El Niño events enhance global warming (as in 1998, 2010, 2016 etc.) and La Niña events (2011, 2018, 2021, 2022 etc.) impart a slight cooling.

GISTEMP anomalies (w.r.t. late 19th C) coded for ENSO state in the early spring.

Consequently, a line drawn from an El Niño year to a subsequent La Niña year will almost always show a cooling – a fact well known to the climate disinformers (though they are not so quick to show the uncertainties in such cherry picks!). For instance, the trends from 2016 to 2022 are -0.12±0.37ºC/dec but with such large uncertainties, the calculation is meaningless. Far more predictive are the long term trends which are consistently (now) above 0.2ºC/dec (and with much smaller uncertainties ±0.02ºC/dec for the last 40 years).

It’s worth exploring quantitatively what the impact is, and this is something I’ve been looking at for a while. It’s easy enough correlate the detrended annual anomalies with the ENSO index (maximum correlation is for the early spring values), and then use that regression to estimate the specific impact for any year, and to estimate an ENSO-corrected time series.

Correlation of detrended annual anomalies and spring ENSO indexGISTEMP and and ENSO-corrected version of the time series
a) Correlation between an ENSO index (in Feb/Mar) and the detrended annual anomaly. b) An ENSO-corrected version of the GISTEMP record.

The surface temperature records are becoming more coherent

Back in 2013/2014, the differences between the surface indices (HadCRUT3, NOAA v3 and GISTEMP v3) contributed to the initial confusion related to the ‘pause’, which was seemingly evident in HadCRUT3, but not so much in the other records (see this discussion from 2015). Since then all of the series have adopted improved SST homogenization, and HadCRUT5 adopted a similar interpolation across the pole as was used in the GISTEMP products. From next month onwards, NOAA will move to v5.1 which will now incorporate Arctic buoy data (a great innovation) and also provide a spatially complete record. The consequence is that the surface instrument records will be far more coherent than they have ever been. Some differences remain pre-WW2 (lots of SST inhomogeneities to deal with) and in the 19th C (where data sparsity is a real challenge).

Four surface-station based estimate of global warming since 1880.

The structural uncertainty in satellite records is large

While the surface-based records are becoming more consistent, the various satellite records are as far apart as ever. The differences between the RSS and UAH TLT records are much larger than the spread in the surface records (indeed, they span those trends), making any claims of greater precision somewhat dubious. Similarly, the difference in the versions of the AIRS records (v6 vs. v7) of ground temperature anomalies produce quite distinct trends (in the case of AIRS v6, Nov 2022 was exceptionally cold, which was not seen in other records).

1979 trends in surface and satellite records showing a coherent warming in all records, but substantial differences between AIRS and MSU TLT versions.
Differences between surface, MSU TLT and AIRS ground temperature records.

When will we reach 1.5ºC above the pre-industrial?

This was a very common question in the press interviews this week. It has a few distinct components – what is the ‘pre-industrial’ period that’s being referenced, what is the uncertainty in that baseline, and what are the differences in the long term records since then?

The latest IPCC report discusses this issue in some depth, but the basic notion is that since the impacts that are expected at 1.5ºC are derived in large part from the CMIP model simulations that have a nominal baseline of ~1850, ‘pre-industrial’ temperatures are usually assumed to be some kind of mid-19th Century average. This isn’t a universally accepted notion – Hawkins et al (2017) for instance, suggest we should use a baseline from the 18th Century – but it is one that easier to operationalise.

The baseline of 1880-1900 can be calculated for all the long temperature series, and with respect to that 2022 (or the last five years) is between 1.1 and 1.3ºC warmer (with Berkeley Earth showing the most warming). For the series that go back to 1850, the difference between 1850-1900 and 1880-1900 is 0.01 to 0.03ºC, so probably negligible for this purpose.

Linear trends since 1996 are robustly just over 0.2ºC/decade in all series, so that suggests between one and two decades are required to have the mean climate exceed 1.5ºC, that is around 2032 to 2042. The first specific year that breaches this threshold will come earlier and will likely be associated with a big El Niño. Assuming something like 2016 (a +0.11ºC effect), that implies you might see the excedence some 5 years earlier – say 2027 to 2037 (depending a little on the time-series you are following).

2023 is starting the year with a mild La Niña, which is being forecast to switch to neutral conditions by mid-year. Should we see signs of an El Niño developing towards the end of the year, that will heavily favor 2024 to be a new record, though not one that is likely to exceed 1.5ºC however you calculate it.

[Aside: In contrast to my reasoning here, the last decadal outlook from the the UK MetOffice/WMO suggested that 2024 has a 50-50 chance of exceeding 1.5ºC, some 5 or so years early than I’d suggest, and that an individual year might reach 1.7ºC above the PI in the next five years! I don’t know why this is different – it could be a larger variance associated with ENSO in their models, it could be a higher present day baseline (but I don’t think so), or a faster warming rate than the linear trend (which could relate to stronger forcings, or higher effective sensitivity). Any insight on this would be welcome!]

References

  1. E. Hawkins, P. Ortega, E. Suckling, A. Schurer, G. Hegerl, P. Jones, M. Joshi, T.J. Osborn, V. Masson-Delmotte, J. Mignot, P. Thorne, and G.J. van Oldenborgh, "Estimating Changes in Global Temperature since the Preindustrial Period", Bulletin of the American Meteorological Society, vol. 98, pp. 1841-1856, 2017. http://dx.doi.org/10.1175/BAMS-D-16-0007.1

A Nobel pursuit

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Klaus Hasselmann and Suki Manabe

Last week, the Nobel physics prize was (half) awarded to Suki Manabe and Klaus Hasselmann for their work on climate prediction and the detection and attribution of climate change. This came as quite a surprise to the climate community – though it was welcomed warmly. We’ve discussed the early climate model predictions a lot (including some from Manabe and his colleagues), and we’ve discussed detection and attribution of climate change as well, though with less explicit discussion of Hasselmann’s contribution. Needless to say these are big topics which have had many inputs from many scientists over the years.

But RC has a more attuned audience to these topics than most, and so it might be fun to dive into the details of their early work to see what has stood the test of time and what has not, and how that differs (if it does) from their colleagues and rivals at the time.

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The IPCC Sixth Assessment Report

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Climate scientists are inordinately excited by the release of a new IPCC report (truth be told, that’s a bit odd – It’s a bit like bringing your end-of-(seven)-year project home and waiting anxiously to see how well it will be received). So, in an uncharacteristically enthusiastic burst of effort, we have a whole suite of posts on the report for you to read.

If/when we add some more commentary as we digest the details and we see how the report is being discussed, we’ll link it from here. Feel free to discuss general issues with the report in the comments here, and feel free to suggest further deep dives we might pursue.

2020 Hindsight

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Yesterday was the day that NASA, NOAA, the Hadley Centre and Berkeley Earth delivered their final assessments for temperatures in Dec 2020, and thus their annual summaries. The headline results have received a fair bit of attention in the media (NYT, WaPo, BBC, The Guardian etc.) and the conclusion that 2020 was pretty much tied with 2016 for the warmest year in the instrumental record is robust.

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Flyer tipping

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You would be forgiven for not paying attention to the usual suspects of climate denial right now, but they are trying to keep busy anyway.

Last week (January 8), Roy Spencer [Update Jan 13: now deleted] posted a series of Climate Change “flyers” on his personal blog that purported to be organised by David Legates (NOAA, detailed to Office of Science and Technology Policy (OSTP), nominally on leave from (and soon to return to) U. Delaware). Each was a rather garishly colored rehash of standard climate denial talking points, but featuring the OSTP official logo, and claiming to be copyrighted by OSTP (a legal impossibility). Note that if this was an official US Govt. work, they could not copyright them, but if it wasn’t, they could not legally use the OSTP logo to indicate that it was.

Dubious use of an official government logo…

The reaction to this definitive refutation of mainstream science (ha!) was… silence. Spencer’s post was reblogged at WUWT but again, nothing happened [Update Jan 13: Also now deleted]. . Many of the authors of the pieces themselves – many of whom are active on social media – didn’t bother to tweet or post about them. Odd.

The whole thing seems to be Legates trying to get a pet project out into the world before the new administration comes in, but without bothering with all that messy peer-review, official permission, proper channels or, you know, actual science. Almost certainly this is also a violation of the Data Quality Act, something Patrick Michaels (one of the flyer authors) was quite exercised about in his effort. Consistency is also apparently optional.

Anyway, a couple of days ago (Jan 10), they were also posted on Willie Soon’s new website where they were noticed on twitter, and today there have been some media eyebrows raised.

Is there a there there?

The flyers themselves are remarkably thin on valid argumentation. Will Happer’s discussion of Radiative Transfer is mostly textbook stuff except for the last paragraph where he simply asserts that a radiative forcing of 3 W/m2 can’t possibly matter. That’s kind of the key issue, which he totally elides.

Christopher Essex purports to discuss climate models, without ever showing anything from a climate model. He seems to be arguing against some Aristotelian concept of climate models that never has to be bothered with actually looking at the real world (for instance). Weird, and totally pointless.

Spencer makes the remarkable assertion that climate has changed for natural reasons in the past (I’m shocked, shocked!), and ignores how attribution actually works (I’m not at all shocked).

The Connollys and Willie Soon’s flyer purports to talk about sun-climate connections, but they spend most of their effort talking about Milankovitch forcing before pivoting to imagining a universe where the temperatures have not in fact been steadily climbing but where they could conceivably have a higher correlation to out-of-date and unsupported reconstructions of solar activity. In so doing, they even have the chutzpah to cite a paper of mine. Meh.

Etc. If there is a demand in the comments, I could expand on the others, but for now, I think you get the idea.

Why should anyone care?

Great question! I don’t think anyone should. But this whole effort is emblematic of how far the climate question has moved. With a new US administration poised to act on climate across a whole series of fronts, this feeble throwback (were they released on a Thursday?), serves to underline how out-of-touch these old school deniers and their talking points really are. This is perhaps the last weak ‘hurrah’ of a bankrupt cause.

Good riddance to bad rubbish.

Update (4pm, Jan 12): that was quick:

Somebody read the comments…

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This post is just to highlight an interesting paper that’s just been published that analyzed the comment threads here and at WUWT.

In it, the authors analyze how the commenters interact, argue and attempt to persuade, mostly, to be fair, unsuccessfully. It may be that seeing how academics analyse the arguments, some commenters might want to modify their approach… who knows?

The comment threads they looked at (I think) are from five posts from Feb to April 2019, including The best case for worst case scenarios, Nenana Ice Classic 2019, First successful model simulation of the past 3 million years and a couple of open threads.

References

  1. C.W. van Eck, B.C. Mulder, and A. Dewulf, "Online Climate Change Polarization: Interactional Framing Analysis of Climate Change Blog Comments", Science Communication, vol. 42, pp. 454-480, 2020. http://dx.doi.org/10.1177/1075547020942228

One more data point

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The climate summaries for 2019 are all now out. None of this will be a surprise to anyone who’s been paying attention, but the results are stark.

  • 2019 was the second warmest year (in analyses from GISTEMP, NOAA NCEI, ERA5, JRA55, Berkeley Earth and Cowtan & Way, RSS TLT), it was third warmest in the standard HadCRUT4 product and in the UAH TLT. It was the warmest year in the AIRS Ts product.
  • For ocean heat content, it was the warmest year, though in terms of just the sea surface temperature (HadSST3), it was the third warmest.
  • The top 5 years in all surface temperature series, are the last five years. [Update: this isn’t true for the MSU TLT data which have 2010 (RSS) and 1998 (UAH) still in the mix].
  • The decade was the first with temperatures more than 1ºC above the late 19th C in almost all products.

This year there are two new additions to the discussion, notably the ERA5 Reanalyses product (1979-2019) which is independent of the surface weather stations, and the AIRS Ts product (2003-2019) which again, is totally independent of the surface data. Remarkably, they line up almost exactly. [Update: the ERA5 system assimilates the SYNOP reports from weather stations, which is not independent of the source data for the surface temperature products. However, the interpolation is based on the model physics and many other sources of observed data.]

The two MSU lowermost troposphere products are distinct from the surface record (showing notably more warming in the 1998, 2010 El Niño years – though it wasn’t as clear in 2016), but with similar trends. The biggest outlier is (as usual) the UAH record, indicating that the structural uncertainty in the MSU TLT trends remains significant.

One of the most interesting comparisons this year has been the coherence of the AIRS results which come from an IR sensor on board EOS Aqua and which has been producing surface temperature estimates from 2003 onwards. The rate and patterns of warming of this and GISTEMP for the overlap period are remarkably close, and where they differ, suggest potential issues in the weather station network.

The trends over that period in the global mean are very close (0.24ºC/dec vs. 0.25ºC/dec), with AIRS showing slightly more warming in the Arctic. Interestingly, AIRS 2019 slightly beats 2016 in their ranking.

I will be updating the model/observation comparisons over the next few days.

Just the facts?

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In the wake of the appalling mass shootings last weekend, Neil DeGrasse Tyson (the pre-eminent scientist/communicator in the US) tweeted some facts that were, let’s just say, not well received (and for which he kind of apologised). At least one of the facts he tweeted about was incorrect (deaths by medical errors are far smaller). However, even if it had been correct, the overall response would have been the same, because the reaction was not driven by the specifics of what was said, but rather by the implied message of the context in which it was said. This is a key feature (or bug) of communications in a politicized environment, and one that continues to trip up people who are experienced enough to know better.

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Koonin’s case for yet another review of climate science

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We watch long YouTube videos so you don’t have to.

In the seemingly endless deliberations on whether there should be a ‘red team’ exercise to review various climate science reports, Scott Waldman reported last week that the original architect of the idea, Steve Koonin, had given a talk on touching on the topic at Purdue University in Indiana last month. Since the talk is online, I thought it might be worth a viewing.

[Spoiler alert. It wasn’t].

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