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.
Where is the story hère though? So they looked retroactively and found some models in the past that fitted with current observations even though they had no clue that China would become such a powerful force in terms of CO2 emissions?
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.
Whether or not China emitted lots of CO2 doesn't matter here. The old studies didn't predict how much CO2 the world would emit. They predicted how much the planet would warm, for various amounts of CO2 emissions. It turned out they were correct about that.
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.
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.
> even though they had no clue that China would become such a powerful force in terms of CO2 emissions
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?
Your comment contains hypotheticals ("run random models and wait long enough you will always be able to find at least one model that predicted the current observations") that are NOT what the present study did.
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.
> they had no clue that China would become such a powerful force in terms of CO2 emissions?
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?
They compared both temperature over time and temperature vs forcing. The latter test factors out the "quantity of emissions" which as you say are much harder to predict (geopolitical), so just measures the quality of the climate modelling.
while I generally agree with your comment, I don't think it is necessary you'd actually have to know about China, you just need to know the general growth trends and if emissions seem to correlate with it, whether that meant cocentrated manufacturing in China or distributed around the world, or even concentrated somewhere else seems like a "detail"
> Anyone involved with forecasting will know what I mean.
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.
Yeah, this is like the stories about the guy who correctly predicted the winner of the Presidential election decades in advance (Bloom County said Trump would win back in the 1980s was it), or did well on some stock investments that did well based on events they didn't actually predict.
>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.
It does seem like survivorship bias could be a factor. The article talks about how some of the old models were off until they "corrected" them. All right, and did they apply the same scrutiny to the apparently "correct" ones? "All of the models predicted this (except for the ones that didn't.)
The only correction I see referenced was the amount of CO2 produced by people after the papers were written. Annual CO2 emissions from human industry is an input to the model, rather than the model itself, but it does affect the result and can only be estimated when the models were published. Seems pretty reasonable to me. Unless I overlooked other changes.
I’m confused as hell to be honest. A few years ago they said there was a global warming pause.[1]. They seemed so sure it was happening that Nature devoted a whole issue to it.
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?
There were dozens and dozens of "climate models" which predicted everything from global cooling to a fiery wasteland and everything in between. Of course you could go back and find a model that "predicted" correctly because every possibility was predicted.
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.
Those predictions were based upon projections that we would not address the growing levels of smog and other particulates, and the cooling effect from those would be larger than the warming effect from greenhouse gases.
We did address smog. Without growing smog, those models predicted warming.
I never doubted our capability to predict short term (10s of years) temperature change from CO2 levels.
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?
I find it absolutely disastrous that we spend more time talking about the environmental impacts of humans, than we do about the inevitability that one of the Sun's CMEs completely decimates our power grid and can cause warming of several orders of magnitude higher than the human footprint.
This reminds me of the models I made a few years ago to predict where a Frisbee will land after you throw it. I made about 14 different models, some of them correctly predict where the Frisbee will land. That's right, I have a model that can tell you where the Frisbee you are about to throw will land, it correctly predicts Frisbee throws.
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.
Some time ago, I got curious about the sources of data in the period where humans were measuring temperature using thermometers. When we talk about predictions from fifty years ago matching today (also I read the linked article and I didn't really see proof that a model that was specified at that time being explicitly benchmarked), it matters how the distribution of sources of surface temperature data varied since then.
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.
What about the person who believes in anthropogenic climate change but doesn’t believe that humans will ever be able (or have ever been able) to cooperate to the extent that is necessary to prevent it, and questions whether required technological advances will ever be made?
Not sure about ordering people like this, but to your underlying point: I would say that the evidence for Earth not being flat is directly and immediately observable in everyday life. Climate change evidence on the other hand, one has to either put in some effort in the form of research/reading, or, place trust in an authority or peers.
Since you've clearly got it all figured out, Tell me, how are we going to address China's runaway coal plant development? Bangladesh's rampant deforestation?
Are you so bold as to say that you know what's best for the people in those countries?
[+] [-] svara|6 years ago|reply
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.
[+] [-] vmchale|6 years ago|reply
[+] [-] ekianjo|6 years ago|reply
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.
[+] [-] DennisP|6 years ago|reply
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.
[+] [-] starpilot|6 years ago|reply
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.
[+] [-] namirez|6 years ago|reply
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...
[+] [-] mturmon|6 years ago|reply
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.
[+] [-] daenz|6 years ago|reply
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.
[+] [-] svara|6 years ago|reply
There would actually be substance to your comment if you could point us to the models the authors didn't consider.
[+] [-] ajross|6 years ago|reply
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?
[+] [-] moultano|6 years ago|reply
[+] [-] keithnz|6 years ago|reply
[+] [-] unknown|6 years ago|reply
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[+] [-] Lutger|6 years ago|reply
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.
[+] [-] chrisbrandow|6 years ago|reply
[+] [-] unknown|6 years ago|reply
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[+] [-] droithomme|6 years ago|reply
[+] [-] jml7c5|6 years ago|reply
>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.
[+] [-] jml7c5|6 years ago|reply
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...
[+] [-] aidenn0|6 years ago|reply
> Note to reader: I was going to use Arctic sea ice in 2100 as an example, but there probably won’t be any lol
[+] [-] jml7c5|6 years ago|reply
[+] [-] starpilot|6 years ago|reply
[+] [-] chrisbrandow|6 years ago|reply
[+] [-] henrifdrake|6 years ago|reply
[+] [-] refurb|6 years ago|reply
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...
[+] [-] s1k3b8|6 years ago|reply
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.
[+] [-] unknown|6 years ago|reply
[deleted]
[+] [-] yters|6 years ago|reply
[+] [-] tzs|6 years ago|reply
We did address smog. Without growing smog, those models predicted warming.
[+] [-] chrisbrandow|6 years ago|reply
[+] [-] acje|6 years ago|reply
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?
[+] [-] ev0lv|6 years ago|reply
[+] [-] ltbarcly3|6 years ago|reply
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.
[+] [-] metasj|6 years ago|reply
[+] [-] nanis|6 years ago|reply
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...
[+] [-] Paraesthetic|6 years ago|reply
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[+] [-] tamaharbor|6 years ago|reply
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[+] [-] woodandsteel|6 years ago|reply
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[+] [-] triceratops|6 years ago|reply
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[+] [-] nickysielicki|6 years ago|reply
Asking for a friend...
[+] [-] onhn|6 years ago|reply
[+] [-] bagacrap|6 years ago|reply
[+] [-] jakeogh|6 years ago|reply
[+] [-] duckMuppet|6 years ago|reply
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[+] [-] huffmsa|6 years ago|reply
Since you've clearly got it all figured out, Tell me, how are we going to address China's runaway coal plant development? Bangladesh's rampant deforestation?
Are you so bold as to say that you know what's best for the people in those countries?
[+] [-] phkahler|6 years ago|reply
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[+] [-] RickJWagner|6 years ago|reply
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[+] [-] garchee|6 years ago|reply