Even 50-year-old climate models correctly predicted global warming
sciencemag.org
sciencemag.org
Unfortunately, arguing about this might just reinforce the mistaken view that there are different valid "sides" to this.
[1] https://en.m.wikipedia.org/wiki/Svante_Arrhenius#Greenhouse_...
Edit: That doesn't detract from the article's more subtle point about the precision of climate models in the past, I was reacting to the comments here viewing this in the light of a fictive controversy.
If you run random models and wait long enough you will always be able to find at least one model that predicted the current observations. That does NOT mean the models were right, it means that you are basically ignoring all the other models that made bad predictions. So in order to make a headline out of this you would need to make a extensive review of all the models we had back then and found out HOW MANY were actually not bad.
Would not make that much of a headline because you would find most models were bad. Anyone involved with forecasting will know what I mean.
As someone who's written basic fluid dynamics codes, I'm blown away by the complexity of climate models. The errors I ran into in debugging my relatively straightforward codes were incredibly subtle. Like pressures, velocities still "looking right" but still being wrong, due to numerical viscosity and other artifacts of the inexact solutions to Navier-Stokes. This is for flow in a box in a steady state. For an entire planetary atmosphere at a time scale of decades, I can't even imagine how they can track down every error without duct taping "corrections" (overfitting) on everything.
But also yes, it's complex, that's why independent groups dedicate huge amounts of time researching and building them and then models are compared against each other.
Not in the slightest. For example, the output of a numerically unstable [1] algorithm, run on 64-bit floats, can diverge arbitrarily from the output of the same algorithm run on real numbers with infinite precision (which computers can't do). Often this will lead to obviously wrong outputs, but not always. There are numerically-stable versions of most of the workhorse linear algebra algorithms, but (1) sometimes it's possible to use a faster, numerically unstable algorithm, and this is a matter of judgment that can be mistaken and (2) it's easy to introduce numerical instability via subtle bugs, or even via the exact arithmetic steps you use to calculate a result (in particular, trying to add or subtract two numbers of very different orders of magnitude is a big no-no).
Numerical instability leads to obvious, wildly inconsistent errors. It isn’t subtle. Literally no climate simulations are going off the rails because of these kinds of first-year grad-student code problems.
Much more work in this direction is needed.
This cannot possibly be correct; it's the same reasoning as the argument "Either the sun will rise tomorrow or it won't. These two possibilities exhaust the entire space. Therefore, the odds of the sun rising tomorrow are 50%, one in two." The premises are completely correct -- and unrelated to the conclusion.
Amazingly, the author at one point says:
"In proper science, the different theories are bloodily competing with each other."
as a contrast to climate science, where supposedly these models are just peacefully cooperating to raise more funds. Anyone who has been in the middle of a conference where people with competing models are comparing results (to each other and to observations) knows how off-base this is.
Can you elaborate your point of view a little more?
P.S. Read the paper here: https://pubs.giss.nasa.gov/abs/ha08910q.html
As noted in TFA, they looked at 17 forecasts from 14 models and found that the temperature predictions of 10 of them were consistent with what has happened in the meantime. And if you adjust for forcing (CO2, methane) then the predictions improve further.
Pardon a little pedantry:
>> The researchers compared annual average surface temperatures across the globe to the surface temperatures predicted in 17 forecasts. Those predictions were drawn from 14 separate computer models released between 1970 and 2001. In some cases, the studies and their computer codes were so old that the team had to extract data published in papers, using special software to gauge the exact numbers represented by points on a printed graph.
They compared annual average surface temperatures across the globe to 17 forecasts, from 14 separate models.
But....how many models did they look at, before choosing those particular 14 models?
TFA doesn't say.
Articles written in this style provide rich fodder for conspiracy theorists, particularly because there is no shortage of examples in the past where authoritative, trustworthy organizations have gotten caught in lies. Rare is the climate change article I've read that can't easily have similar holes poked in it.
What's the real truth here? Based on the literal content of this article, no one knows. It is speculation vs speculation.
I've said it before, and I will say it again: if your persuasion tactics aren't working, it might be worth considering whether you should change your tactics.
What GP wants is transparency around how many possible models were there over the last decades from which they chose the 14. This gives the reader a better understanding of whether 14 is a lot or a little. It is a fair point IMO regardless of their overall stance on the issue.
Secondly, the forecast models evaluated in the study are from the likes of James Hansen, William Nordhaus, and the IPCC (in other words, authoritative sources). So at the very least this adds weight to the hypothesis that the models published by the IPCC are accurate and methodologically sound. Sure, there is some probability that the models and reality corresponded by random chance, but that probability is made ever more diminishingly small as evidence accumulates.
So, I don’t think any of the comments in this thread that accuse the authors of retrospective cherry-picking of climate models are anything but embarrassing examples of pseudo-intellectual contrarianism and/or confusion over basic statistics.
The models considered by the study, their predictions, and the methodology used are all located here and were easily found after 30s of digging: https://github.com/hausfath/OldModels
In many of these cases, it's clear that the commenters have done no background reading, and have no climate science background. Their comments thus consist of simple armchair speculation (your "lowest of the low-hanging fruit").
In these comments, I have found people with strong opinions on the lack of seriousness of climate science, who have no idea we have gravimetric measurements of ice sheet mass. This is a dataset going back almost 20 years that has revolutionized geoscience. HN commenters have expressed strong opinions about melting ice, with no knowledge of this data and what it means.
I have found people who think that climate science consists of having a stable of models each with a host of knobs, and the research method is to turn the knobs or choose new models until the results look dramatic enough to publish.
The gap between the firmness of these claims and the knowledge to back it up just boggles the mind.
The most basic step people could take to fix this is to read the executive summary of the IPCC AR5 report, or (even better/easier) the executive summary of the NCA (https://science2017.globalchange.gov). This report was specifically written by people who really know this stuff, for people like us.
There's no indication that the authors are cherry-picking their models but the comments above are assuming this (without reading the original paper to get a sense of the care of the analysis). It's really easy to find supposed gotchas in this way - basically any analytic step can be questioned.
If you live in the Bay Area, AGU is next week at Moscone Center. It's the biggest one-stop-shop in the world for geoscience research. Maybe it's worth paying a one-day admission fee to see some of this in person?
--> It's a word coined by pg that's sort of a term-of-art for the depressing tendency of the top HN comment to be something which pooh-poohs the company/topic/idea in the submission, doesn't add anything to the discussion, but (crucially) is worded convincingly enough to not just end up on the bottom of the thread.
--> e.g. "Lol that suckz because Google can steal ur passwerdz!" would not end up at the top of the thread. We wouldn't be terribly worried if someone actually said "Wait, I just audited NativeClient and it turns out you can achieve arbitrary code execution. Maybe you should avoid this software." The danger zone is comments which sound like the second but, on reflection, only tell you about as much as the first.
I love the first reply:
"Ironically the concept of a "middlebrow dismissal" seems to me to enable what it condemns--e.g. HN'ers can now just post "hey that's a middlebrow dismissal" instead of a detailed statement of why a particular response falls short. Basically I think pg made it worse by giving it a catchy name."
- something which pooh-poohs the company/topic/idea in the submission [Invalid]
- doesn't add anything to the discussion [Invalid]
- We wouldn't be terribly worried if someone actually said "Wait, I just audited NativeClient and it turns out you can achieve arbitrary code execution. Maybe you should avoid this software." [If you'd have read more closely, and less tribally, perhaps you might have noticed something along these lines]
> There's no indication that the authors are cherry-picking their models
My comment wasn't that they are cherry picking their models, it was that it is (as worded) not entirely clear that they are not. I also explained why this is may be harmful.
> but the comments above are assuming this
Mine weren't assuming anything.
> basically any analytic step can be questioned
Perhaps. But survivorship bias isn't a conspiracy theory.
> If you live in the Bay Area, AGU is next week at Moscone Center. It's the biggest one-stop-shop in the world for geoscience research. Maybe it's worth paying a one-day admission fee to see some of this in person?
I'm satisfied enough with the science to support doing something about climate change. My interest in this conversation is the apparent unwillingness of similarly minded people to consider weaknesses in their persuasion campaign. How do you foresee getting past the current impasse we find ourselves in?
Why don't you demolish me with your science and facts? Does that question even register?
Would you like to try? The authors of the paper seem unwilling, perhaps you'd like to give it a shot.
It says something.
> They looked at 17 forecasts drawn from 14 models.
It does not say this. What you have written is your uncritical interpretation, what I wrote is a literal quotation, which allows for (satisfies) the conspiratorial possibility that I raised.
> You are the one who implicitly believes they are lying about that
You are speculating. Speculation is fine, but it's best to realize (and state explicitly) when you're doing it.
Know how I know you're speculating? Because while you only believe you can read my mind, I can actually do it, and I do not "believe they are lying". I was only pointing out that as written, they could be lying.
And I even told you the reason why I wrote that comment: "Articles written in this style provide rich fodder for conspiracy theorists..."
If you truly want to change minds, you might want to learn how the minds you want to change work. Go spend some serious time in conspiracy forums, I suspect you might learn something useful.
And rather than largely ignoring the actual words of someone who's trying to help out your cause, treating them as an enemy rather than someone who may have some insight you lack, it might be helpful to keep a more open mind. Perhaps if those with knowledge severely lacking in the mainstream discourse weren't rate limited, some here may find some new ideas to consider.
"You looked at 1000 models, but what about the 1000 models that scientists made and didn't publish. You didn't look at those!"
People can always suggest more tests you need to do or poke holes in any analysis. That doesn't mean you just stop ding the work.
Overall it is impressive that different models made over 30 years can predict fairly accurate results. In my opinion that shows that the underlying physics of the models is correct and makes me trust the models even more.
Undoubtedly some would, but are you willing to consider the possibility that the number/percentage of people that would do so might be altered by the language used in articles on climate science?
> People can always suggest more tests you need to do or poke holes in any analysis.
Some analyses are easier to poke holes in than others. If this article was tightened up in the manner I describe, excluding the possibility of survivorship bias, then an entirely new approach to denial would be required. As written, survivorship bias is a very real possibility.
Wikipedia says: "Survivorship bias or survival bias is the logical error of concentrating on the people or things that made it past some selection process and overlooking those that did not, typically because of their lack of visibility. This can lead to false conclusions in several different ways. It is a form of selection bias."
Survivorship bias is a real phenomenon, not a conspiracy theory. It is neither illogical or unscientific to consider the possibility that is might be in play behind the scenes here, and the article as written makes no attempt to rule it out.
> Overall it is impressive that different models made over 30 years can predict fairly accurate results. In my opinion that shows that the underlying physics of the models is correct and makes me trust the models even more.
I suspect this is because your mind does not consider it a possibility that the models discussed do not result from survivorship bias. A conspiratorial mind however, would most likely strongly consider that a possibility, and therefore compute a completely different level of trust.
Imagine for a moment how the human mind works when reading something. Typically, if the mind is primed with preexisting beliefs, it is going to be actively searching (interpreting) for confirmation of those beliefs, and this behavior will likely be stronger if the topic happens to be one associated with one's identity. So, your mind processes an article such as this optimistically (uncritically), whereas a "denier" or "conspiracy theorist" is going to read it pessimistically (critically).
https://en.wikipedia.org/wiki/Confirmation_bias#Biased_inter...
https://www.verywellmind.com/what-is-a-confirmation-bias-279...
Here is another interesting example. See this reddit thread on the article: https://www.reddit.com/r/science/comments/e63ic5/of_17_clima...
The top comment is: (/u/aClimateScientist) "Hi all, I'm a coauthor of this paper (Henri Drake) and happy to answer questions."
Someone asks the question: "How did you account for survivorship bias of models? IOW how did you select the 17? I mean if I asked 1,000 psychics to predict GDP growth, I could probably find 10-20 who were pretty close and say that that proves they're clairvoyant."
As of when I'm writing this, neither /u/aClimateScientist nor /u/avogadros_number (the article submitter, who seems to have considerable background in climate science) have addressed this question.
(Or, same thread: a moderator [Removed] comment.)
My question to you is: do you think it is possible that the manner in which your mind evaluates this particular situation (an unanswered question, in a thread with 29 total comments) may differ from how the mind of a "denier" or "conspiracy theorist" might evaluate the situation, and how that evaluation may in turn be used (or not) to tune your respective mental models and subconscious heuristics?
A followup question is: do you believe this perspective is irrelevant (has no bearing on) the climate change dilemma?
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I sometimes wonder if the climate change dilemma was reproduced in a sim-style video game, would the human mind be less resistant to recognizing and reacting to the behavior of their adversary? If the adversary is a machine rather than a human, might the tribalism component of subconscious decision making decrease? This is one of those things that seems so obvious, I wonder if there might be some studies on it.
As shocked as people here are at the continued existence of "deniers" (or more accurately, their mental models of deniers), I am similarly shocked at the psychological unwillingness of intelligent people to acknowledge certain unfortunate realities. It's kind of comically/tragically ironic if you think about it.
With that being said, I doubt that survivorship bias is strong enough to explain their combined result of 10/17 models being significant.
> “We conducted a literature search to identify papers published prior to the early-1990s that include climate model outputs containing both a time-series of projected future GMST (with a minimum of two points in time) and future forcings (including both a publication date and future projected atmospheric CO2 concentrations, at a minimum). Eleven papers with fourteen distinct projections were identified that fit these criteria.
This brings to mind the old joke: "I used to smoke weed. I still do, but I used to, too."
Specifically, the phrase "were identified that fit these criteria" sets off my skepticism spider senses. Kind of like the popular "97% of scientists..." meme, that doesn't quite hold water when you dig under the covers.
To be clear, I'm not saying deceit is taking place, I am simply saying that I am skeptical.
I wasn't able to find any details on the specifics of the literature search, such that the search could be reproduced. Any idea if that was included in the study and I somehow overlooked it?
The motive here is the "trust climate scientists now because they've been right about everything all along" narrative. There's no other reason for it.
I think you're making the same mistake that you're attributing to the story. It really doesn't matter what China does per se. The global energy consumption, roughly, follows a log-linear trend. If the energy comes from fossil fuels, the CO2 emissions would also follow the same trend [1]. It doesn't matter whether it's China or someone else; the CO2 emission would go up if we don't innovate and rely on fossil fuels.
As an analogy, think about the Moore's law. Does it matter whether the chip is made by Intel or AMD?
[1] https://commons.wikimedia.org/wiki/File:Global_co2_emissions...
Rising prosperity comes with rising energy consumption. If China didn't export so much it wouldn't be able to import the fuel that it used. Its dramatic rise was definitely not a given.
Of course it's a model. Please look up the Kardashev scale and correlations that people have developed based on it [1]. The energy output is not necessarily coupled with the CO2 emission unless we burn fossil fuels to generate power.
[1] https://en.wikipedia.org/wiki/Kardashev_scale#Current_status...
Why would the models care? In fact world GDP growth has been right on trend since the 60's. It's true that it's concentrated in areas we didn't expect, but that's always true. China did much better than expected, the Americas were right on curve, Europe a little worse and eastern europe in particular fell off a cliff. So what?
Those models surely predicted aggregate carbon output pretty well. Are you saying they didn't?
There would actually be substance to your comment if you could point us to the models the authors didn't consider.
>We gathered all the climate models published between 1970 and the mid-2000s that gave projections of both future warming and future concentrations of CO2 and other climate forcings – from Manabe (1970) and Mitchell (1970) through to CMIP3 in IPCC 2007.
If you're a cynic or suspicious: "projections of future warming" means they intentionally excluded studies that projected cooling.
Otherwise: it could have been written as "projections of future temperature", but they came across no studies that projected cooling.
This really makes me wish for open access journals, as most of the questions in this thread could be answered if it was possible for anyone to look at the paper.
Rasool and Schneider 1971 [1] https://pdfs.semanticscholar.org/4db2/1045b17ebcdd6a8c6adeb1...
Earl Barrett 1971 https://www.sciencedirect.com/science/article/abs/pii/003809...
Hamilton and Seliga 1972 https://www.igsoc.org/journal/14/72/igs_journal_vol14_issue0...
Chylek and Coakley 1974 https://science.sciencemag.org/content/183/4120/75
Bryson and Dittberner 1976 https://journals.ametsoc.org/doi/pdf/10.1175/1520-0469%28197...
Sean Twomey 1977 https://journals.ametsoc.org/doi/pdf/10.1175/1520-0469%28197...
[1] edit: Schneider later retracted findings
I share your wish for open access journals.
Among the models this study looked at was Hansen's. That's the NASA scientist who testified about global warming to Congress in 1988. It'd be quite a coincidence if there were lots of models with a wide variety of predictions, and the one model that was presented to Congress just happened by chance to be one of the few that got it right.
But if you can actually show that there were in fact a bunch of models by scientists of similar stature, which made really different predictions and were left out of this study, then that would be interesting.
There are people downthread who are arguing that because numerical instability bugs exist and climate models are complicated, climate models can’t be trusted. Literally any flimsy pretext is used to dismiss work that people don’t like.
This conversation is dominated by people who have just enough knowledge to defend their pre-conceptions, but no more.
Your claim that "The old studies didn't predict how much CO2 the world would emit" is directly contradicted on the first page. The paper begins by pointing out that "model projections rely on...accurate assumptions around future emissions of CO2". In fact, one of the criteria the authors used for choosing a model to include was that it came with a time-series prediction of "future projected atmospheric CO2 concentrations".
With that restriction, the authors found 11 papers containing a total of 14 models. Unless the authors of this paper left out other predictions from the original papers, the only papers included in the study that "predicted how much the planet would warm, for various amounts of CO2 emissions" were Hansen's, and the other 9 papers included in this study only made one prediction for both emissions and temperature.
This paper also points out that Hansen's 1988 "most plausible" model, which you described as "the one model that was presented to Congress", was not accurate under the usual definition of accurate: "H88's “most plausible” scenario B overestimated warming experienced subsequent to publication by around 54%."
Then how does this paper lead to the headline that "Even 50-year-old climate models correctly predicted global warming"?
What the authors of this paper have done is to compare errors in the models' predictions of CO2 emissions to errors in the models' predictions of temperature. In other words, the models were wrong about both, but in the same direction. They overestimated both future emissions and future temperature.
Even so, the claim that the models were accurate is a linguistic trick. The table on line 326 shows what the authors are calling skill score: "A skill score of one represents perfect agreement between a model projection and observations."
Not a single model has a "skill score" of one, or for which one is within the uncertainty. In fact, all of the models are wrong in the same direction, even after this paper has attempted to correct for their incorrect assumptions about future CO2 emissions.
The linguistic trick is that this error is not, according to the authors, "statistically significant". But that's a tremendous abuse of the phrase. The authors are effectively saying: "The null hypothesis is that the models are right, and we've failed to disprove it." They've assumed the conclusion.
I suspect that this paper is being promoted for political, not scientific, correctness.
1: A PDF of this paper can be found at https://pubs.giss.nasa.gov/docs/tbp/inp_Hausfather_ha08910q....
But here is Hansen's original 1988 paper: https://pubs.giss.nasa.gov/abs/ha02700w.html
From the abstract: "We make a 100-year control run and perform experiments for three scenarios of atmospheric composition. These experiments begin in 1958 and include measured or estimated changes in atmospheric CO2, CH4, H2O, chlorofluorocarbons (CFCs) and stratospheric aerosols for the period from 1958 to the present. Scenario A assumes continued exponential trace gas growth, scenario B assumes a reduced linear linear growth of trace gases, and scenario C assumes a rapid curtailment of trace gas emissions such that the net climate forcing ceases to increase after the year 2000."
Note the word "assumes." There's no attempt to really model what humanity would choose to emit. None of these assumptions exactly match what happened with CO2 and other greenhouse gases, so of course none of them exactly match the temperature either. But adjusted for actual greenhouse emissions, they come remarkably close.
Were they completely accurate in that way? Certainly not. People knew a lot less back then. It took a while to nail down things like the effect of water vapor, which is a greenhouse gas but also makes clouds that reflect sunlight away. But they were close enough to make good policy decisions, and if we'd paid attention, we'd be much better off today.
Incidentally, the case for global warming doesn't depend on models. There have been warming events before, and there's enough evidence in geological history to tell us what's going to happen. Hansen's book has details.
Take a look at the table I mentioned (line 326), in particular "ΔT / ΔF skill". That's the change in temperature over the change in forcing (ie, CO2 etc). Hausfather et al call it "implied TCR". In (overly) simple terms, it's the predicted increase in temperature per unit of CO2 emitted.
Look at the numbers: 0.51, 0.41, 0.63, 0.42, 0.83, etc. The best is 0.87. The average was 0.69.
The authors attempted to adjust for actual CO2 emissions and found that, after the correction, the models were predicting 40%-90% of the observations, with an average score around 70%.
Is that "remarkably close"?
Well, we might disagree about the meaning of that term. But there's another observation that we should agree on. Note what the authors say after that table:
> The average of the median skill scores across all the model projections evaluated is 0.69 for the temperature vs time metric.
> Using the implied TCR metric, the average projection skill of the models was also 0.69.
In other words, the models are, on average, as accurate with or without the correction. Adjusting for actual greenhouse emissions doesn't make the models more accurate (nor less).
I'm not involved with forecasting, but am generally very skeptical of people 'debunking' climate science in non-scientific forums such as these. Can you back up your claim that these people haven't done their job properly? Have you read the article and their methodology? It seems to be behind a paywall unfortunately so I can't assess your claim right now.
Since you didn't point out any specific flaw in the study, but mentioned merely general biases which any scientist is aware of, suggesting they apply to the article but not really pointing out how, I really can't take this criticism of a peer reviewed article seriously.
EDIT:
Here is some of the code used in the paper: https://github.com/hausfath/OldModels
Here is a blog post on the paper, written by one of the authors: http://www.realclimate.org/index.php/archives/2019/12/how-go...
EDIT AGAIN:
The "supporting information" .docx at the bottom of this page has a lot more detail, for those (like me) who can't get past the paywall ( :-/ ): https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2019...
> Note to reader: I was going to use Arctic sea ice in 2100 as an example, but there probably won’t be any lol
Life thrived
The Sahara desert was a grassland 5000-10000 years
Life thrived.
Perhaps not as many of us. But that's part of the problem isn't it? Too many humans, chopping down forests, over fishing, sucking melted dinosaurs out of the earth.
Instead of making an argument justifying genocide, perhaps we should instead take action against climate change before it becomes a problem? Or would you prefer the next war to be fought over water instead of oil?
I kinda question that the living quality and wealth of the survivors ends up better in your scenario...
The question is whether we will. Civilization is a fragile thing.
Honest question.
Then they came back and said “actually it never happened”.[2]
Shouldn’t it be pretty straightforward to tell whether there was warming or not?
[1] https://www.nature.com/collections/sthnxgntvp
[2] https://insideclimatenews.org/news/18122018/global-warming-h...
There was never some broadly held idea that warming dynamics had paused.
I’d say a full issue Nature dedicated to exploring why there was a pause, suggests it was a broadly held idea.
That said, if there was no consensus, why is that? Why do some scientists believe there was a pause, while others disagree? Isn’t figuring out whether warning was happening pretty straightforward?
Not exactly. There are two ways that it can be ambiguous:
1. We don't measure the entire earth to measure its temperature, and combining the sensor readings from various sources to get a calibrated total energy content can be difficult.
2. It is difficult to take a time series, and with a short history, decide whether something is a significant deviation from the trend or just random variation. Humans instinctively underestimate how often a random sequence of coin flips will have consecutive strings of heads of a given length, and the same tendency causes us to see a "pause" as a deviation from the trend, when it's really just random variation causing a bunch of consecutive heads.
If there can be disagreement over something as basic as "are temperatures actually going up", then that throws all of climatology into doubt. Global temperature is the question that motivates this field, yet you're arguing here that whether it was going up or stable was merely an "idea" rather than a matter of measuring physical reality. It is absurd that such a basic question is actually a matter of dispute at this point: reading thermometers and averaging them just isn't that difficult compared to what other scientific fields routinely accomplish.
There's also an interesting social viewpoint on display: you claim the "climate science community" is a completely separate group from "skeptics" and they only "had" to spend time answering the "question" of a pause due to "beating the drum".
Are there no climate scientists skeptical of beliefs in their own field, like there are in every other field of science? If not, why not? Why are people asking obvious questions like "why does it seem temperatures stopped rising" seen as nuisance outsiders rather than fellow scientists seeking the truth? From an outsider's perspective this looks a lot like groupthink.
There was never some broadly held idea that warming dynamics had paused.
This is not true, as refurb already showed. To spell it out, his [2] link starts by saying: "The United Nations panel of climate science experts mentioned it in a 2013 report, scientists have published more than 200 papers analyzing it, and climate deniers said it was proof that climate change didn't exist, but in reality the global warming pause or hiatus never occurred."
Over 200 papers published analysing a pause is clear evidence that this was a broadly held idea.
There seems to be a problematic tendency in climatology to try and retroactively rewrite history. Prior disputes or false predictions are recast as "scientists didn't actually believe that" or "scientists weren't actually wrong after all" using dubious, Orwellian style practices. Even temperature records themselves are constantly being rewritten: basic questions like "what was the temperature on date X at location Y" had different answers in the past to what they do now.
As another example, elsewhere in this thread [1] the author of the paper we're discussing claims he couldn't find any papers that predicted global cooling. Predictions of a new ice age were widely covered in the media and discussed in the literature in the 1970s. There were global conferences and scientific summits held about it. Embarrassingly, some random Hacker News commentator was able to produce a list of six such papers within an hour of that post being made.
What is wrong with climatology? Other fields like physics or medicine don't have problems dealing with their past history of wrong experiments, theories or measurements.
That's like dozens and dozens of "stock price models" predicting FB stock to go up, down and stay the same. Of course one is guaranteed to be correct.
What is "scientific" about this? It's simply people who want to prove something and then narrowly searching for the data to prove that point and ignoring everything else.
This is so disappointing coming from something calling itself a sciencemag.
I'm sorry you feel that way. Would be interested to find which parts you felt was "nonsensical and intellectually dishonest" so I expand on it and clarify it for you. Hard to respond to an ad hominem.
> This is not at all what this paper did, nor what any remotely credible scientific study ever does.
It's exactly what it did. How about this. If a "anticlimatemag" opposed to the climate change agenda had an article titled "Even 50-year-old climate models were wrong about global warming", would you be defending it as vigorously?
>There were dozens and dozens of "climate models" which predicted everything from global cooling to a fiery wasteland and everything in between. > What is "scientific" about this? It's simply people who want to prove something and then narrowly searching for the data to prove that point and ignoring everything else.
The paper clearly states their methodology, which included a literature review to find all published climate models that produce a numeric forecast for future average temperatures. I quoted the relevant section in a different comment. If they missed or ignored dozens and dozens of other published climate models, then find them and show us. Otherwise, you're explicitly accusing the authors and publishers of peer-reviewed science of committing research malpractice.
>Of course you could go back and find a model that "predicted" correctly because every possibility was predicted.
The output of a climate model (in this context) is an expected value (i.e. a single real number) of the global mean temperature at time t (in years). It is true that if the support of a random variable is the real numbers, then every outcome in (-inf, +inf) is weighted by some probability density (and yet any particular outcome in the set of reals occurs with zero probability!). But it is decidely untrue that the model predictions analyzed by this study (or produced by climate scientists in the time period considered by the study) contained the set of all possible outcomes. It data evaluated is one temperature value per model per year are published right here--take a look: https://github.com/hausfath/OldModels/tree/master/references
>That's like dozens and dozens of "stock price models" predicting FB stock to go up, down and stay the same. Of course one is guaranteed to be correct.
Effectively the same fallacy as above, but with a discrete number of outcomes. The point of probabilistic forecasts is not to be correct (this goes against the definition), it's to estimate the likelihood that a certain outcome will occur in the future given information known up until the current time (ideally--but not necessarily--so that some rational decision can be made). Laypeople often incorrectly redefine prediction to meaning the black-or-white selection of a particular future outcome. I could go on, but I suggest you read this masterpiece instead: https://fivethirtyeight.com/features/the-media-has-a-probabi... (or Thinking, Fast and Slow for the human psychology lens on this problem of misunderstanding the nature of uncertainty).
>If a "anticlimatemag" opposed to the climate change agenda had an article titled "Even 50-year-old climate models were wrong about global warming", would you be defending it as vigorously?
Um, no? I do not and will not defend blatantly false anti-science regardless of the source or agenda. That is extra true of anti-science that supports an avoidable existential threat to half of all species, countless current and future human lives (especially in the developing world, who bear most of the costs while contributing a negligible amount to the problem), and perhaps to civilization and the era of an inhabitable Earth itself.
But as the essential quote goes, "All models are wrong, but some are useful". It's always possible for disingenous headlines like the hypothetical Climate models are useful because they enable us to (quite accurately, it turns out) estimate risks to our single most precious resource, which then allows us to take rational action to minimize that risk (and other models, e.g. those produced by environmental economists, suggest ways to balance the costs of mitigative action).
Your comments, on the other hand, are not useful (so far...).
Also: as has been pointed out, in TFA and elsewhere in this thread, the authors of the linked study did not cherry-pick the models.
How else would you do this?
We did address smog. Without growing smog, those models predicted warming.
I'm also 100% sure we aren't capable of predicting the consequences of these temperature changes, because they are going to be complex. This will be an interesting ride and the train has left the station. We may want to find more diverse controls than just the CO2 emissions. How about manipulating not just land but also the oceans to run more efficient photosynthesis? Dangerous perhaps?
Here is how it works: You input all the factors of your Frisbee throw. Then you throw the Frisbee, and that's it! Well, I guess there is one more step, since all 14 models make wrong predictions about where the Frisbee will land. But you can just go back and adjust the models and input better data after you already know where the Frisbee actually ended up, and then some of them correctly predicted where it will land!
Don't down-vote me, this is definitely what the phrase 'correctly predicted' means, and I'm not being misleading at all.
I haven't been motivated enough to do another one of these animations, but this video[1] shows locations of all temperature stations in GHCNv3[2] (I see that GHCNv4[3] is out). Notice how where humans measure temperature depends so much on what living conditions humans seek or find acceptable. I find this visualization interesting in terms of the number of modeling questions it poses. If you are interested, it shouldn't take much to replicate something similar with current hardware/software.
As another note, it makes little sense to say model predictions are not statistically significantly different from each other. What is the population from which these models are being drawn? What is the measure of variability among models? The article[4] is behind a paywall, so I can't see what they did.
[1]: https://www.youtube.com/watch?v=h95uvT67bNg
[2]: https://www.ncdc.noaa.gov/data-access/land-based-station-dat...
[3]: https://www.ncdc.noaa.gov/data-access/land-based-station-dat...
[4]: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2019...
[0] https://www.cnbc.com/2019/09/07/bill-gates-funded-solar-geoe...
More at 11.
I know of at least a few cases, where skeptics have changed their minds due to new evidence (Richard Muller [0] comes to mind). I'm curious if there are any instances of reputable scientists with sufficient training in the relevant fields, who went from true believers to significant skepticism of anthropogenic influence.
[0] https://www.nytimes.com/2012/07/30/opinion/the-conversion-of...
Even 20k years is miniscule.
Like I said, not a smoking gun; just a clue that it's worth digging into. And from a Bayesian perspective, one must ask: what are the odds that that rising temperature would happen to correlate with CO2, for entirely unrelated reasons? https://www.youtube.com/watch?v=Sme8WQ4Wb5w
Don't get me wrong, I find Greta-style alarmism and claims of "extinction" to be counter-productive. But given how difficult it is to get nerds to agree on anything, the fact that there are so few credible scientists on the other side of the issue gives me pause. Pure groupthink? Maybe. Hardly unprecedented. But we've been examining the data and improving the models for decades (including from those with a strong financial incentive to debunk AGW), and yet the scientific consensus continues trending in one direction. Skepticism is a good thing, but the evidence for AGW can't merely be handwaved away by causal narrative.
I know that alarmism is the best way to get attention, but its also the best way for me to think you're a zealot who should be ignored.
https://fee.org/articles/the-myth-that-the-polar-bear-popula...
It's very easy to find a model that predicts this retrospectively. It's also completely worthless. Predicting the future is much harder.
That's my main beef with climate science: not only do they do this kind of hand picking retroactively and claim they're able to "predict", they also sometimes go back and _tweak the input data_ to fit the models better, or make it up entirely where coverage is inadequate. This is not how science is done in any other field. This also doesn't feel like it's being treated as an existential threat would be treated, in terms of scientific rigor. I understand it's a very complex problem, sure, but that doesn't give you a license to take arbitrary liberties with scientific method or ground truth data.
But now, as you can already see proliferating in the comments to this piece, the new acceptable contrarian take on climate change is that of course its happening, but since life thrived on the planet during other climactic conditions there's nothing to worry about.
The message is the same as it's always been: trying to do anything in response is foolish, and we should all continue to just focus on making as much money as possible.
But the real issue with climate change is and has always been that it will socially and politically de-stabilize the planet, because quite a few people live in places that will become less livable in the near future, and those people will want to go somewhere else.
Those people will have a quite strong claim on land and resources in wealthy countries that emitted most of the pollution and have lots of mostly empty and more habitable land. This will cause global conflict on a scale beyond any that exists in living memory.
Yes, "life" will survive. Our societies in their current configurations will not, and decisions we make now will determine how messy or violent (or not) that transition will be.
Pedantic retorts about geological time should embarrass you in the face of the leaders of the tech industry evidently using their immense wealth to prepare for social collapse[1].
And although these people are clearly willing to spend money to prep for climate change, I still can't get a single one of the recruiters who cold-call or email me about HOT NEW SILICON VALLEY OPPORTUNITIES to find me a single credible company working on anything climate or energy adjacent. I can just hear their jaws slackening every time I bring it up.
1. https://www.theguardian.com/news/2018/feb/15/why-silicon-val...