In Denierland I compiled a list of predictions of the disappearance of Arctic sea ice. You won’t have seen this unless you delved into the notes and references for Chapter 4. With the passage of a couple of years I thought it was about time to resurrect the list, search for any more predictions and to check whether any predictions have been falsified in the intervening year (the last update before publication was 2019 for predictions and 2020 for results). I’ve only managed to find two more recent predictions that were bold enough to put a date on things, both made in 2020.
Two predictions are at risk of being falsified in the coming September: Tim Flannery’s of 2007 (and that is giving him a lot of leeway) and James Anderson of Harvard’s.
The following explanatory text comes from Denierland:
Several of these predictions (and both those dating from before 2005) were sourced from ClimateChangePredictions.org. The rest have come from news searches on the internet. In some cases I have had to use a tad of judgement in giving the date for the loss of ice, when statements like “in the next two decades” are used. An asterisk in the “Ice Will Be Gone By” column indicates that a form of words allowing some wriggle-room was used: “could be gone by…” etc.
“The study analyzed recent results from 40 of the latest climate computer models and involved 21 research institutes from around the world.”
The following paragraphs are repeated verbatim from Denierland; I would have put things a little differently if writing them today, but I didn’t want to edit them:
What is the point of all this? Not to prove that making predictions is hard, especially about the future. Instead, I want to highlight that predictions are actually very easy to make, and for some reason, predictions made by scientists have a certain currency beyond the SWAG of a typical human on the street. Learned folks have credentials, and their predictions are to be respected, or at least used to generate clicks on the internet. Strangely when predictions expire, the scientists who made them are not called back to ask why. Indeed when predictions expire, some regulars just make a new prediction a few years down the road.
“How does one prepare their children for the extintction [sic] event we are witnessing? How long before it impacts us all to the point where it is a matter of survival? Is it best to be ignorant at this point and not tell them that [they] will not see their adulthood?”
The3Js, in a comment beneath the 2013 article at Arctic News.
Well, The3Js’ children are now 7 years (2022 update: 9 years) older, so it looks as if climate change might not preclude them reaching adulthood after all. The following is from a BBC article in 2012:
Professor Peter Wadhams, from Cambridge University, told BBC News: “A number of scientists who have actually been working with sea ice measurement had predicted some years ago that the retreat would accelerate and that the summer Arctic would become ice-free by 2015 or 2016.
“I was one of those scientists – and of course bore my share of ridicule for daring to make such an alarmist prediction.”
But Prof Wadhams said the prediction was now coming true, and the ice had become so thin that it would inevitably disappear.
Turns out that the good professor was wrong, but his credentials meant that he could keep giving alarming predictions over and over (see the table above). Only one that I can find has yet to expire, from two years after the above quote, pushing the ice-free date back to this year, 2020. (Oops, looks like that was a fail too.)
I found the following quote in one of the cited articles, and found it so remarkable that I reproduce it here.
“Sometime in the 2030s or 2040s time frame, at least for a few days, you won’t have ice out there in the dead of summer,” said Dr John Walsh, chief scientist of the International Arctic Research Centre.
From the 2016 Guardian article in the table above.
To use the phrase “dead of summer” is amazing, simply because the summer is the only time there is visible life in the high Arctic.
Finally, here is the latest update on sea ice minima, as of September last year:
If we extrapolate the line beyond the range of the data (usual caveats apply), it hits 0 in about 60 years. For reasons that will not be gone into here, “ice-free” generally means when there is less than 1 million square km of ice left. So that would be in about 40 years. The scatter around the line of course means that, ceteris paribus, we might hit an ice-free weekend one day in September in about 25 years.
Featured image: The most recent Arctic sea ice minimum extent, 22 September 2021, from NASA worldview terra/aqua and JAXA’s AMSR-2 instrument.
With apologies for the formatting of the table, which is left-aligned in preview, but centred when published. I would have liked to colour the rows for expired predictions in pink, but couldn’t see how.
Some of the links might be dead now. I checked them in 2020, when only one failed – this is marked as such in square brackets.
If anyone knows of any other predictions, let me know and I will update the table accordingly.
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Prof Peter Wadhams seems to be a sucker for punishment.
Jit, you probably want predictions from credentialled experts only but I can’t resist supplying some from Roger Hallam, XR’s former thinker-in-residence.
During a talk he gave at King’s College London in April 2018, he showed a 2014 graph of Arctic sea-ice volume and said the following (a full transcript from 20m20s to 22m20s of the video linked below; I have emboldened Hallam’s own sea-ice predictions):
I’m going to stick my neck out and say this, objectively, is the most important graph in the world, probably the most important graph in the history of humanity. It shows what’s happening to the ice. In 30 years it’s gone from what you might call fully-full cover to 25% cover. [Er, it’s a graph of volume, not area.] So the idea is that it’s going to hit zero in the next few years.
Now, if I was, like, a 13-year-old science student, I’d be able to work that out, I think. It doesn’t take a lot of thinking about, does it? I don’t know. I’m really hoping someone’s going to prove me wrong but I’m sort of looking at this, OK? It’s like there’s a little bit of noise in the system but ice melts when it’s warm and 25% still to go. And you follow the graph down and if you’re a very clever mathematician you can work out whether it’s going to be 2019, 2020 or 2022. But let’s say for the sake of argument that it’s going to be ice-free by, what, 2024? Give or take. Which isn’t all that far off.
So, what does that mean? Well, if you see the full graph – you can see the ones in January, it’s all over the Internet, so presumably from all these ice institutes – the rest of the ice is going to be gone within ten years after that.
If you do listen to some of the major professors and supposed intellectuals of the world and you ask them when the ice is gone, they say like 2030 or 2050. I don’t quite know why. Ha! Or is that a deeply psychological issue? I had a woman last week said 2030. Anyway, it’s not! It’s going to be 2022. Because we can all just just look at the graph. It’s a basic physical system. Not complicated.
The whole talk is worth a watch. It is packed full of nonsense. Wrong arithmetic, wrong history, wrong chemistry, wrong analogies (some of them about the Holocaust)… The whole thing is just extraordinarily stupid. The man is an idiot – and yet he has been extraordinarily influential in the last few years. (I think XR was more his idea than Bradbrook’s or Barda’s or Bramwell’s.)
Hallam’s KCL talk:
The 2014 PIOMAS graph that Hallam (ab)used:
Thanks for providing this update. Presumably the ice physicists are using more complex models than a linear extrapolation to make their predictions. And I would assume that their models would be largely driven by modelled predictions of arctic air and sea temperatures. So if future air and sea temperatures were overestimated, which is quite likely, then their modelled ice cover predictions would be off.
I am a fan of simple linear models like yours. But it strikes me from your graph that it might be worth fitting a polynomial to the data. The catastrophists like to assume positive feedbacks causing “tipping points” but your data might indicate negative feedbacks as the curve seems to be flattening. In other words it could be more difficult to melt the last remaining ice than is commonly assumed.
It’s good to see the claims listed like that. The key point – and you make it – is that claims of environmental breakdown are all too common, and are loudly trumpeted when made, especially in the MSM usual suspects. However, when the claimed outcomes fail to come to pass, there never seems to be any sort of reckoning or publicity regarding that fact.
When I worked in commerce and industry, regular PCRs (post-completion reviews) were undertaken for investment projects that had gone ahead in earlier months and years. The investment would have been procured on the basis of claims made in advancing regarding the outcome of the investment, whether that investment was a business purchase, extension, refurbishment, or whatever, and it was always based on an anticipated profit and rate of return. The project would be re-visited later to see if the claimed returns had been realised. If they had, then all well and good. If not, why not? Lessons could be learned from either outcome, as to mistakes to avoid in future and investments that were worth making.
Given how much is at stake (whether in terms of claimed climate crises or just the huge financial sums that are supposed to be spent and sacrifices made to lifestyles), one might have thought that each claim of imminent catastrophe should be subjected to a “PCR” with a view to learning lessons. Save at places like this, it doesn’t seem to happen, least of all in the MSM.
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But Mark predictions made by academics have little real value. Usually what is lost isn’t monetary, it is reputational and prestige for the predictor and the institution or organisation they represent. That is (or should be) worth didally-squat in the world of commerce.
If in the real world commercial decisions are based on academic work, then it is those decisions, and not necessarily the academic results, that require review of the type you suggest. At stake would be whether or not the predictor would be heeded in future or be given financial support in future.
Your 7.49 p.m. brought back memories of several nerve-wreaking boardroom meetings I had when, long ago, I worked for an oil company as an in house, semi-tamed academic. Commonly I had helped make predictions that had been tested by the drill. You always kept your workings (= justifications).
Vinny, I will be pleased to add Mr. Hallam’s guess to the list when I have a mo. I hope it is easy to figure out how to insert a row. But does he predict 2022, or 2024? I suppose “2022-2024” would be a fair interpretation.
And perhaps you could explain to me how that linear fit minimises the squared errors, since for the first half of the time the line is firmly north of the data. (It’s not fair for me to ask you this, since it’s not your figure!)
potentilla, I agree that even the linear fit might be a pessimistic prediction. A reasonable default as a sceptic is “as before, so later,” inasmuch as I have an allergy to speculative swerves in graphs such as are presented for things like sea ice (Vinny’s Hallam example above), sea level rise, or temperature.
Of course putting my line violates the laws of linear regression because the data is very red. So perhaps a better prediction for this year’s minimum is… last year’s minimum.
There is reason to suppose that there might be positive feedback within a northern summer, but equally there is reason to suppose there might be negative feedback between years, a sort of “reset” in the winter. It is certainly not clear to me whether any summer will ever have the gumption to melt all the floating ice present in March.
Mark/Alan, I think civilisation ought to be able to rely on scientists to give impartial answers. Unfortunately wherever you look there is evidence that scientists often come to the wrong conclusion: the true conclusion is usually the least exciting. I have always believed that science will prevail, but I have become increasingly disillusioned about the objectivity of the “typical” scientist.
Of course there must be no comeback for making an erroneous prediction. Mistakes are natural. The question is rather whether we ought to place any weight at all on a subsequent prediction. If your theory makes predictions which are falsified, you had better revisit your theory. Unfortunately revisiting the theory for Arctic sea ice merely means pushing the date of disappearance on a few years.
By the way, the median of the predictions was 16 years in advance of the date made, and the average about 19 years ahead. Is this the sweet spot between “falsified too quickly” and “too far away to stimulate dramatic action”?
I leave the reader to be the judge.
[Median and mean calculated by taking the mid-point of a prediction’s range as the predicted date when a single year was not given.]
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JIT, thanks for digging into the Arctic ice issue. My own tracking of this noted that climatologists define the annual minimum as the September monthly average extent, rather than a single day, which can reverse itself a day or two later. One of the difficulties measuring anything in the Arctic domaine. Though your intuition is correct: Any one-day shortage of Arctic ice would receive the full media amplification and triple alarms. There is also an association of Arctic ice watchers who predict each year what they expect to be the upcoming minimum as defined above.
Last September, the picture looked like this:
Detailed analysis here:
The Sea Ice Prediction Network is here: https://www.arcus.org/sipn/sea-ice-outlook/2021/september
Their submitted forecasts date from June to September 2021, and those results are here compared to the actual SII Sept. 2021 average Arctic ice extent.
Vinny – thanks for the Hallam link “talk he gave at King’s College London”
I tried to watch the whole thing, but gave up at 30mts into his rambling lecture.
how this guy thinks he can educate anybody with this is beyond me.
Ron, thanks for the links. I have edited your comment slightly to make the first image appear.
I always use area rather than extent because I don’t really understand what extent is telling me. My figure does show the average value for September, but it’s area, not extent. [To the uninitiated: the difference between extent and area in September has gone down over the satellite era, from about 2.5 million square km to about 1.5 million square km. I don’t know why.]
Of course, if a sceptic was to have been asked to predict what climatologists would themselves have predicted for sea-ice minimum last year, they would probably have gone “lower than the actual.” Which is precisely what happened, as your second figure shows us. In fact, none of the methods had the true value within the two central quartiles, even when initiated in late August or early September, i.e. within the very month whose value they were tasked with predicting.
[True value: 4.95 million square km. Image from arcus.org. The four blocks represent models initiated in the four months from June.]
Jit, there is this discussion of sea ice area and extent.
The threshold commonly used by organisations making estimates of sea-ice extent is 15% of sea-ice concentration. The National Snow and Ice Data Centre (NSIDC), for example, uses 15% for their Sea Ice Index, an index on which most sea-ice statistics quoted in the media are based on! Why 15%? Well, estimates of sea-ice extent in the past using this 15% threshold have been found to match well with other forms of observations, e.g. airborne measurements from planes.”
The use of sea-ice area (rather than extent) might seem more intuitive and precise for understanding the long-term evolution of sea ice in polar regions and its relationship with other climatic variables. This is why climate modellers often prefer to use it. However, modellers have an unfair advantage: the climate simulations they use provide clearly-defined grid cells and sea-ice concentration.
When monitoring sea ice by satellite, the ocean is not divided into clearly-defined grid cells and it is not always straightforward to discriminate between open ocean and sea ice! Read more in this previous post about these issues. This is why sea-ice extent is often preferred in the satellite community.”
I would add that MASIE (Multi-sensor Arctic Sea Ice Extent) is based on 4km2 cells with a 40% ice coverage, compared to SII with 16 km2 cells and 15% coverage.
Sorry, my last sentence is poorly stated. MASIE cells are 4km by 4km, SII cells are 16km by 16km.
Also a memory fail. SII cells are actually 25km by 25km. See
“No Sign of the BBC’s Alarmist Climate ‘Tipping Points’ in the Arctic”
“The BBC’s green activist-in-residence Justin Rowlatt was in fine form on Monday, kicking off his week-long Radio 4 ‘end is nigh’ climate catastrophe promotions. “We are running faster than ever towards a climate abyss,” he reported, and the Arctic is currently warming faster than the rest of the planet. Sporting the latest fashion accessory for every climate catastrophist – the ‘tipping point’ – he went to report that Arctic warming leads to stalled weather patterns, leading to more “heat domes”, deep freezes and torrential downpours. All of this is said to be “predicted” to become increasingly common and more extreme….”.
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Well, the northern summer duly ended. The cat thinks it’s now too cold, and I’m inclined to agree.
Arctic sea ice did not disappear this year, thus falsifying two learned predictions that it would. The first was by Tim Flannery, made in 2007:
The expiry of Flannery’s prediction in 2022 was giving him a lot of leeway – he said 5-15 years, which gave a date range of 2012-2022.
The second expired prediction was James Anderson’s.
The links to the predictions in the table in the main article are still live, if anyone wants to check my homework.
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Another one for Jit’s List: