It's worth keeping in mind that the modeled data lines up with reality because it's supposed to. That's how you calibrate your model, by making sure it fits reality.
The real trick is to see how well your model extrapolates from the data you have out into the future. As in, if you feed it data up to, say, 1990, will it correctly spit out 2015 temperatures that fit the reality of 2015, or will it spit out crazy 2015 predictions like the models that were built in 1990 did. And, the bigger question: How will its predictions for 2040 (given 2015 data) match up to the reality over the next 25 years.
We seem to be getting a lot better at the modeling side. That's a good thing, since the first couple decades of watching people panicking and fighting each other over whatever scary results came out of the first generation climate models wasn't any fun to watch.
"The real trick is to see how well your model extrapolates from the data you have out into the future."
That is the most common way to show the modeller is not shamelessly overfitting.:-| Another way, though, is less common but not vanishingly uncommon: the model may be so much simpler than the data it fits that overfitting is not a plausible explanation. (Roughly there are too many bits of entropy in the match to the data to have been packed into the model no matter how careless or dishonest you might have been about overfitting.) E.g., quantum mechanics is fundamentally pretty simple --- I can't quantify it exactly, but I think 5 pages of LaTeX output, in a sort of telegraphic elevator pitch cheat sheet style, would suffice to explain it to 1903 Einstein or Planck well enough that they could quickly figure out how to do calculations. Indeed, one page might suffice. And there are only a few adjustable parameters (particle/nucleus masses, Planck's constant, and less than a dozen others). And it matches sizable tables of spectroscopic data to more than six significant figures. (Though admittedly I dunno whether the non-hydrogen calculations would have been practical in 1903.) For the usual information-theoretical reasons, overfitting is not a real possibility: even if you don't check QM with spectroscopic measurements on previously unstudied substances, you can be pretty sure that QM is a good model. (Of course you still have to worry about it potentially breaking down in areas you haven't investigated yet, but at least it impressively captures regularities in the area you have investigated.)
I agree, but I have to say their imagination on what other things might be causing warming is not very robust.
For just one example, there are at least two major effects of burning:
1. Release of chemicals into the atmosphere (ex: carbon dioxide)
2. Directly heating the atmosphere
There are literally billions of air conditioners, heaters, cars, factories, etc that all generate heat. The effect of these billions of heaters throughout the world definitely increases global temperatures. After all, this effect is a reason why cities are warmer than their surrounding rural areas (1). This is relevant because direct heating should be temporary while greenhouse gas increases are cumulative.
Honest question - has anyone calculated the effect of the direct heating on the atmosphere from the billions of heaters we use vs greenhouse gas increase?
It's not my field, but I'd be very surprised if models were not also calibrated by extrapolating earlier known years and comparing to later known years.
You can really only judge models on days that was not yet available when they were created.
The shape of the curve is driven by the independent variable (CO2 concentration, volcanic activity, etc). The magnitude needs to get adjusted so that it doesn't produce inconsistent results when extrapolated backwards in time. Which is the problem with explaining the recent spike in temperature as anything other than CO2 concentration. Most of the other variables like solar flux are relatively steady so that if you increase their climate forcing effect you get a really bad fit in the 1900s which is non-physical.
There's also additional data like satellite measurements of the broadening of the absorption lines of CO2 and H2O in the IR blackbody spectra that the Earth radiates and the measurement of the shortfall of outgoing radiation in the radiation budget which are consistent with GHG effects and independently confirm these models.
Exactly. When modeling most data, you would hold back a validation set, but that doesn't really work as well in this situation. The only thing holding back the validation set is time.
The thing is, it's not just the temperature measurements fitting the greenhouse gases. It's also all the biological and physical evidence. Bird migrations, plant species ranges, glacier and ice cap shrinkage and growth, permafrost melting, polar vortices occurring, etc.,etc.,etc. Screw the models: look at the reality.
There's a lovely book called The Limits to Growth published in 1972, through the years authors have updated their book and their models (there's more than 20). It turned out that business-as-usual model extrapolated very well from '70s to '00s. So, even them modelling was fairly good.
> if you feed it data up to, say, 1990, will it correctly spit out 2015 temperatures that fit the reality of 2015, or will it spit out crazy 2015 predictions like the models that were built in 1990 did
Yeah, so they pick models until they find one that fits both 1990 and 2015? That would be using the test data to train the model - like the Baidu approach.
I have absolutely no knowledge about this field, but from what I understand people who study the Sun wouldn't agree as much with the numbers about the suns temperature.
This visualization is a multivariate linear regression with time trending variables...lol the entire thing is garbage, I could get a better R^2 than the 7 or so variables they used if instead I used variables to explain climate change like: number of gay marriages in the world, murders, abortions, etc...I don't recommend this, I'm just saying trended data can "say" anything
This repeats some buried comments but I think it's worthwhile: I'm not a climate scientist, but in my experience the absolute most reliable, most time-efficient way to learn about climate change is the IPCC reports. I wonder if there is anything written in any other field that compares:
Specifically, if you are short on time, read the 'Summaries for Policymakers', written at the level and attention spans of non-technical politicians. They are quite readable and as I wrote in another post, if they can understand it, so can you. :) (The longer reports are fascinating, if you have an interest in science and want to get lost in something.)
As I understand it the reports are prepared by a global team of hundreds of scientists, and reviewed by thousands more.[1] (Seriously, has anything like that existed in any other field?) They are meant to cover the breath of climate science and the reports also are meticulous about the language of probabilities.
Spend a little time reading them and it will save you the time of reading 99% of what's written elsewhere, and you'll be much better informed.
---
EDIT:
[1] Review process: http://www.ipcc.ch/activities/activities.shtml (scroll down to "The AR5 Writing and Review Process") -- for example, one report had over 50,000 comments on two drafts from >600 experts.
---
EDIT 2: Website interface help.
Can you believe this needs to be written, and for HN readers? I had JavaScript off which makes the site usable (if not pretty). With JavaScript on, apparantly the UX concept is 'Easter eggs':
There are 4 images arranged horizontally at the top; these are report covers (with text too small to read even if you knew they were clickable). If you click a report cover then the section beneath it changes to display a description of and links to that report.
All that work making the reports accessible to the world, hamstrung by web design.
A couple years back I read the IPCC reports trying to find out if global warming was real or not. I noticed the Vostok ice core data in the earlier reports showed the temperature rose first and then the CO2 rose. Likewise, the temperature fell first and then the CO2 fell later on. They fixed this little inconvenient data problem in the later reports.
Helpful when reading this thread to keep in mind Michael Mann's six stages of climate change denial:
1. CO2 is not actually increasing.
2. Even if it is, the increase has no impact on the climate since there is no convincing evidence of warming.
3. Even if there is warming, it is due to natural causes.
4. Even if the warming cannot be explained by natural causes, the human impact is small, and the impact of continued greenhouse gas emissions will be minor.
5. Even if the current and future projected human effects on Earth's climate are not negligible, the changes are generally going to be good for us.
6. Whether or not the changes are going to be good for us, humans are very adept at adapting to changes; besides, it’s too late to do anything about it, and/or a technological fix is bound to come along when we really need it.
Interesting note from the l0phet article the other day regarding how fire codes and regulation in cities didn't come about even after great disaster swept the city.
Wysopal offered this grim precedent: Cities were once
vulnerable to disastrous fires, which raged through dense
clusters of mostly wooden buildings. It took a giant fire
in Chicago to spur government officials into serious
reforms, including limits on new wooden structures, a
more robust water supply for suppressing blazes and an
overhaul to the city’s fire department.
“The market didn’t solve the problem of cities burning
down,” Wysopal said, predicting that Internet security
may require a historic disaster to force change. “It
seems to me that the market isn’t really going to solve
this one on its own.”
But here’s a frightening fact: The push to create tough
new fire-safety standards did not start after the Great
Chicago Fire in 1871, which killed hundreds of people and
left 100,000 homeless. It took a second fire, nearly
three years later in 1874, to get officials in Chicago to
finally make real changes.
Though I wouldn't accept #5 and #6 exactly as phrased, it does seem like positive effects ought to be balanced against the negative, and the uncertainty of future technological developments ought to inform our current decision of how much to spend addressing climate change.
The first four stages have always baffled me. Anyone who knows basic chemistry understands how carbon dioxide interacts with infrared radiation. Combine that with the fact that human activity is releasing tens of billions of tons of CO2 every year, which does not magically disappear. In fact, it's quite measurable.
The climate is complex, but the basic facts of the situation are incredibly simple and unavoidable. And yet, people have still tried.
I don't think the general population is thinking about it that much. To me, the main denial seems to be a dislike and/or distrust of the people advocating the AGW theory.
For example, having Al Gore as a prominent figure of the AGW theory movement for a number of years is enough to make them suspicious. They see him fly in private jets, own multiple humongous homes, make investments that will pay off if things like carbon credits become mainstream, release a movie 9 months after Katrina that promised more and more severe hurricanes that never materialized, etc, etc. He might not be a duck but he sure seems to quack a lot.
The other main denial seems to be things like, "It's cold today - in your face global warming".
I think Michael Mann is giving people far too much credit.
Please don't take this as a denial of climate change, it is an honest question. How do scientists learn the levels of ozone, aerosols, green house gases, and the other data points going so far back at a global scale? Is the data from before the latter half of the 20th century spotty? If so, why is it considered good enough to use in a context of scientific research where quality and correctness of data is paramount?
It's important to note that history didn't begin in 1880, and that some effects lag their cause. Forests, along with oceanic flora, normally sequester Carbon from CO2 and return O2 to the atmosphere. However, this effect only takes place when the forests are actually there.
I don't have any religion, one way or another, about climate change and its causes, but I think we won't learn anything from media propaganda like this. It doesn't even bring up the possibility of albedo playing a role in climate change?
While forests represent a sizable reservoir of fixed carbon, the amount of carbon they fix in any given year is actually not huge (trees grow slowly). It would not nearly be enough to offset our current rate of burning of fossil fuels, for instance.
I didn't read the whole paper (where that graph came from), so my apologies if i am misstating anything. It appears that the paper is focused mostly on the forests in Eastern Canada. At first glance, I'd find the slope on that graph (last 500 years) very hard to believe if it were for all of planet earth.
Does it bother anyone else that only the Global temperate has its axis labelled?
What is the orbital wobble measuring?
What is the volcano line measuring?
Is that decreased forests or decreased land use?
Should be be using more aerosols?
Is that meant to be suns temperature or sun activity, or sun colour?
I realise that the actual data is from reliable carefully measured models but it makes this illustration so pointless.
In climate 130 years is not a long time. I wish these articles showed graphs with historical data that go back thousands of years so that I could see how, in a historical context, greenhouse emissions are affecting the world. I've only ever seen data from the 1900's, and it looks pretty hockey stick, but would be interesting to see fluctuations with the ice age(s) and local highs included.
Edit: historical data is of course not available, but approximations must exist?
This graphic really just plays into the hands of climate change deniers. No labelled axis, a timeline of only 100 years (you could also argue the dinosaurs caused global warming), and the quite proud declaration at the end the argument is really "no contest" under the assumption that correlation == causation. I could also make a graph that shows the increase in global temperature correlating with the rise in the Latino population, could I then declare it a "no contest"?
This article only serves to stroke the ego of people who already believe that CO2 emissions cause global warming. It does nothing for people who already deny it.
Evidence, no matter how strong doesn't serve to change the nature of a man. People would rather bend the logic and the evidence to fit their convenient perception of reality.
Which brings me to the question: "What can change a nature of a man?" Imminent danger? If an assailant had a gun pointed at your head, it'd be impossible to deny. How can this evidence about global warming be presented so that it can't be denied?
Not trying to argue against manmade climate change here, but the conclusion is inconsistent with the stated point/headline.
The main question is whether or not humans are the primary driving factor in the changes observed. Graphs show lack of correlation with various manmade causes and some natural causes, but then the conclusion is reached with the graph of "the influence of greenhouse gas emissions." In other words, the "nail in the coffin" evidence is simply showing the effects of the problem graphed against the problem itself; it doesn't prove one way or another whether the cause of the rise in greenhouse gasses is manmade.
Downvote as you will, but that doesn't seem like science to me; it feels like proving a point by simply restating the point.
Since I seem to be repeating myself all over this thread:
It is basic physics (the optics of IR and visible light and thermodynamics) that trace amounts of CO2 and methane can significantly warm the atmosphere.
We know physics pretty damn well, and if you do not accept this, there is no conversation.
Sure, one should look at the data to see to what extent this is happening and there are all kinds of questions one can ask. But all this talk of "correlation is not causation" is nonsense.
> "No, it really is greenhouse gasses." .. "See for yourself."
Being patronising has such a great track record in turning hearts and minds, I'm glad they didn't stoop to such decadent clap track as "engaging with opposing arguments".
is it y=f(x) or y=x(f)? aka is is warmer because of the higher greenhouse gases or is there more greenhouse gases because of the warmer climate (that could have been caused by things like leaving an ice age and approaching a warm period in Earth's life)
Just to clarify, i support green technology and I think this is definitely the way to go but I don't like the unjustified crusade using proofs that can be ripped apart in minutes.
There's also confounding variables to take into account. One of those might not be driving the other.
Many commenters above are speaking about how hard it is to eject someone out of a bias, but I don't know why they're doing this. They're lamenting the inefficacy of logic to convince people while not applying it in this very case. The graph just shows a correlation.
It's really depression to see such a large aggregation of smart people applying their abilities to nitpicking details of global warming instead of coming up with solutions.
Very cool visualization and great way to display it.
As someone who refuses to trust authority and wants to understand things for myself before making a decision, global warming is very frustrating because nobody will answer my questions without personal attacks or appeals to authority. I don't have an agenda either way, I just have a very inquisitive mind. Have any of you felt the same?
Some of the questions I have that never seem to get an adequate answer:
1) How are the models validated? Is it like backtesting a trading strategy? Come up with a hypothesis that seems to fit historical data, then let it run with actual data, and see how accurate it is? If so, how have the models held up?
2) How do they account for confounding factors and how do they separate causal correlations from mere correlations?
For example, at 95% of fires firemen were present. Firemen and fires are strongly correlated. But nobody would say firemen are the cause of fires.
Cholesterol was thought to be a causal factor for heart problems because it is strongly correlated but they later found it is not a causal factor. Something else causes the heart disease and cholesterol raises when heart disease is present. They can use it as a predictor of heart disease but it is now understood that cholesterol doesn't actually cause the problem.
3) It seems to me that for a model to be trusted it must have predictive capability, and it must fit a physical model of our current understanding. How do the various models hold up with these criteria? It seems like climate is still a very complex field that we don't fully understand.
My only problem is that the planet is over 4 billion years old and as this shows, we've been collecting climate data for a little over 100 years. The natural skeptic in me isn't ok with establishing a trend based on 1/40,000,000 of the available data, the sample size is simply too small. Am I completely off-base with this?
On my MacBook Pro using Chrome, it was even worse. Impossible to read at least tells me that something is wrong, but using the trackpad to scroll through the options in a natural flicking way actually skips over multiple entries at a time with only the barest flicker to indicate that it happened. I got almost to the end before I realized I had only seen about one third of the information they were trying to present.
I have nothing against clever visualizations like this, but god damn it web designers, stop co-opting standard UI interactions to make it happen. There is no reason to hijack window scrolling here. None. All you accomplished by doing this was make it harder to figure out how to read the thing, and break it badly for a lot of people. What's wrong with buttons? You can even look for swipes on touchscreen devices. That's pretty standard! But quit stealing the scrollers!
Same here. I can't seem to get it to scroll and show headers at the same time. I tried scrolling really slowly and it still stops showing headers after third graph. For a venue as big as Bloomberg you'd expect them to test it thoroughly before publishing.
[+] [-] jasonkester|10 years ago|reply
It's worth keeping in mind that the modeled data lines up with reality because it's supposed to. That's how you calibrate your model, by making sure it fits reality.
The real trick is to see how well your model extrapolates from the data you have out into the future. As in, if you feed it data up to, say, 1990, will it correctly spit out 2015 temperatures that fit the reality of 2015, or will it spit out crazy 2015 predictions like the models that were built in 1990 did. And, the bigger question: How will its predictions for 2040 (given 2015 data) match up to the reality over the next 25 years.
We seem to be getting a lot better at the modeling side. That's a good thing, since the first couple decades of watching people panicking and fighting each other over whatever scary results came out of the first generation climate models wasn't any fun to watch.
[+] [-] wnewman|10 years ago|reply
That is the most common way to show the modeller is not shamelessly overfitting.:-| Another way, though, is less common but not vanishingly uncommon: the model may be so much simpler than the data it fits that overfitting is not a plausible explanation. (Roughly there are too many bits of entropy in the match to the data to have been packed into the model no matter how careless or dishonest you might have been about overfitting.) E.g., quantum mechanics is fundamentally pretty simple --- I can't quantify it exactly, but I think 5 pages of LaTeX output, in a sort of telegraphic elevator pitch cheat sheet style, would suffice to explain it to 1903 Einstein or Planck well enough that they could quickly figure out how to do calculations. Indeed, one page might suffice. And there are only a few adjustable parameters (particle/nucleus masses, Planck's constant, and less than a dozen others). And it matches sizable tables of spectroscopic data to more than six significant figures. (Though admittedly I dunno whether the non-hydrogen calculations would have been practical in 1903.) For the usual information-theoretical reasons, overfitting is not a real possibility: even if you don't check QM with spectroscopic measurements on previously unstudied substances, you can be pretty sure that QM is a good model. (Of course you still have to worry about it potentially breaking down in areas you haven't investigated yet, but at least it impressively captures regularities in the area you have investigated.)
[+] [-] guelo|10 years ago|reply
[+] [-] 300bps|10 years ago|reply
I agree, but I have to say their imagination on what other things might be causing warming is not very robust. For just one example, there are at least two major effects of burning:
1. Release of chemicals into the atmosphere (ex: carbon dioxide)
2. Directly heating the atmosphere
There are literally billions of air conditioners, heaters, cars, factories, etc that all generate heat. The effect of these billions of heaters throughout the world definitely increases global temperatures. After all, this effect is a reason why cities are warmer than their surrounding rural areas (1). This is relevant because direct heating should be temporary while greenhouse gas increases are cumulative.
Honest question - has anyone calculated the effect of the direct heating on the atmosphere from the billions of heaters we use vs greenhouse gas increase?
----
(1) http://www.smithsonianmag.com/science-nature/city-hotter-cou...
[+] [-] reitzensteinm|10 years ago|reply
You can really only judge models on days that was not yet available when they were created.
[+] [-] lamontcg|10 years ago|reply
There's also additional data like satellite measurements of the broadening of the absorption lines of CO2 and H2O in the IR blackbody spectra that the Earth radiates and the measurement of the shortfall of outgoing radiation in the radiation budget which are consistent with GHG effects and independently confirm these models.
[+] [-] tosseraccount|10 years ago|reply
[+] [-] croddin|10 years ago|reply
[+] [-] MaysonL|10 years ago|reply
[+] [-] birdsbolt|10 years ago|reply
[+] [-] dj_doh|10 years ago|reply
[+] [-] visarga|10 years ago|reply
Yeah, so they pick models until they find one that fits both 1990 and 2015? That would be using the test data to train the model - like the Baidu approach.
[+] [-] ThomPete|10 years ago|reply
I will see if I can find the numbers.
[+] [-] omalleyt|10 years ago|reply
[+] [-] hackuser|10 years ago|reply
http://www.ipcc.ch/
Specifically, if you are short on time, read the 'Summaries for Policymakers', written at the level and attention spans of non-technical politicians. They are quite readable and as I wrote in another post, if they can understand it, so can you. :) (The longer reports are fascinating, if you have an interest in science and want to get lost in something.)
As I understand it the reports are prepared by a global team of hundreds of scientists, and reviewed by thousands more.[1] (Seriously, has anything like that existed in any other field?) They are meant to cover the breath of climate science and the reports also are meticulous about the language of probabilities.
Spend a little time reading them and it will save you the time of reading 99% of what's written elsewhere, and you'll be much better informed.
---
EDIT:
[1] Review process: http://www.ipcc.ch/activities/activities.shtml (scroll down to "The AR5 Writing and Review Process") -- for example, one report had over 50,000 comments on two drafts from >600 experts.
---
EDIT 2: Website interface help.
Can you believe this needs to be written, and for HN readers? I had JavaScript off which makes the site usable (if not pretty). With JavaScript on, apparantly the UX concept is 'Easter eggs':
There are 4 images arranged horizontally at the top; these are report covers (with text too small to read even if you knew they were clickable). If you click a report cover then the section beneath it changes to display a description of and links to that report.
All that work making the reports accessible to the world, hamstrung by web design.
[+] [-] narrator|10 years ago|reply
[+] [-] tosseraccount|10 years ago|reply
The best way to evaluate science is to look at the raw data and the scientist's original paper.
[+] [-] unknown|10 years ago|reply
[deleted]
[+] [-] themgt|10 years ago|reply
1. CO2 is not actually increasing.
2. Even if it is, the increase has no impact on the climate since there is no convincing evidence of warming.
3. Even if there is warming, it is due to natural causes.
4. Even if the warming cannot be explained by natural causes, the human impact is small, and the impact of continued greenhouse gas emissions will be minor.
5. Even if the current and future projected human effects on Earth's climate are not negligible, the changes are generally going to be good for us.
6. Whether or not the changes are going to be good for us, humans are very adept at adapting to changes; besides, it’s too late to do anything about it, and/or a technological fix is bound to come along when we really need it.
[+] [-] nosuchthing|10 years ago|reply
[+] [-] bjt|10 years ago|reply
Does that make me a climate change denier?
[+] [-] TillE|10 years ago|reply
The climate is complex, but the basic facts of the situation are incredibly simple and unavoidable. And yet, people have still tried.
[+] [-] 300bps|10 years ago|reply
For example, having Al Gore as a prominent figure of the AGW theory movement for a number of years is enough to make them suspicious. They see him fly in private jets, own multiple humongous homes, make investments that will pay off if things like carbon credits become mainstream, release a movie 9 months after Katrina that promised more and more severe hurricanes that never materialized, etc, etc. He might not be a duck but he sure seems to quack a lot.
The other main denial seems to be things like, "It's cold today - in your face global warming".
I think Michael Mann is giving people far too much credit.
[+] [-] wtbob|10 years ago|reply
[1] http://www.steynonline.com/6565/the-lonesomest-mann-in-town
[+] [-] ryanobjc|10 years ago|reply
[+] [-] macinjosh|10 years ago|reply
[+] [-] mangeletti|10 years ago|reply
It's important to note that history didn't begin in 1880, and that some effects lag their cause. Forests, along with oceanic flora, normally sequester Carbon from CO2 and return O2 to the atmosphere. However, this effect only takes place when the forests are actually there.
I don't have any religion, one way or another, about climate change and its causes, but I think we won't learn anything from media propaganda like this. It doesn't even bring up the possibility of albedo playing a role in climate change?
[+] [-] snowwrestler|10 years ago|reply
[+] [-] munificent|10 years ago|reply
Isn't that exactly what the "So If It's Not Nature, Is It Deforestation?" slide is about?
[+] [-] bharath28|10 years ago|reply
[+] [-] antidaily|10 years ago|reply
[+] [-] posnet|10 years ago|reply
What is the orbital wobble measuring? What is the volcano line measuring? Is that decreased forests or decreased land use? Should be be using more aerosols? Is that meant to be suns temperature or sun activity, or sun colour?
I realise that the actual data is from reliable carefully measured models but it makes this illustration so pointless.
[+] [-] nixy|10 years ago|reply
Edit: historical data is of course not available, but approximations must exist?
[+] [-] rza|10 years ago|reply
[+] [-] crimsonalucard|10 years ago|reply
Evidence, no matter how strong doesn't serve to change the nature of a man. People would rather bend the logic and the evidence to fit their convenient perception of reality.
Which brings me to the question: "What can change a nature of a man?" Imminent danger? If an assailant had a gun pointed at your head, it'd be impossible to deny. How can this evidence about global warming be presented so that it can't be denied?
[+] [-] curiousgeorgio|10 years ago|reply
The main question is whether or not humans are the primary driving factor in the changes observed. Graphs show lack of correlation with various manmade causes and some natural causes, but then the conclusion is reached with the graph of "the influence of greenhouse gas emissions." In other words, the "nail in the coffin" evidence is simply showing the effects of the problem graphed against the problem itself; it doesn't prove one way or another whether the cause of the rise in greenhouse gasses is manmade.
Downvote as you will, but that doesn't seem like science to me; it feels like proving a point by simply restating the point.
[+] [-] drjesusphd|10 years ago|reply
It is basic physics (the optics of IR and visible light and thermodynamics) that trace amounts of CO2 and methane can significantly warm the atmosphere.
We know physics pretty damn well, and if you do not accept this, there is no conversation.
Sure, one should look at the data to see to what extent this is happening and there are all kinds of questions one can ask. But all this talk of "correlation is not causation" is nonsense.
[+] [-] mseebach|10 years ago|reply
Being patronising has such a great track record in turning hearts and minds, I'm glad they didn't stoop to such decadent clap track as "engaging with opposing arguments".
[+] [-] gtrubetskoy|10 years ago|reply
As if it's not enough that the air in major cities and vast parts of entire countries is literally toxic.
[+] [-] istvan__|10 years ago|reply
is it y=f(x) or y=x(f)? aka is is warmer because of the higher greenhouse gases or is there more greenhouse gases because of the warmer climate (that could have been caused by things like leaving an ice age and approaching a warm period in Earth's life)
Just to clarify, i support green technology and I think this is definitely the way to go but I don't like the unjustified crusade using proofs that can be ripped apart in minutes.
[+] [-] skylan_q|10 years ago|reply
Many commenters above are speaking about how hard it is to eject someone out of a bias, but I don't know why they're doing this. They're lamenting the inefficacy of logic to convince people while not applying it in this very case. The graph just shows a correlation.
http://www.tylervigen.com/spurious-correlations
[+] [-] vlasev|10 years ago|reply
[+] [-] beatpanda|10 years ago|reply
[+] [-] bcheung|10 years ago|reply
As someone who refuses to trust authority and wants to understand things for myself before making a decision, global warming is very frustrating because nobody will answer my questions without personal attacks or appeals to authority. I don't have an agenda either way, I just have a very inquisitive mind. Have any of you felt the same?
Some of the questions I have that never seem to get an adequate answer:
1) How are the models validated? Is it like backtesting a trading strategy? Come up with a hypothesis that seems to fit historical data, then let it run with actual data, and see how accurate it is? If so, how have the models held up?
2) How do they account for confounding factors and how do they separate causal correlations from mere correlations?
For example, at 95% of fires firemen were present. Firemen and fires are strongly correlated. But nobody would say firemen are the cause of fires.
Cholesterol was thought to be a causal factor for heart problems because it is strongly correlated but they later found it is not a causal factor. Something else causes the heart disease and cholesterol raises when heart disease is present. They can use it as a predictor of heart disease but it is now understood that cholesterol doesn't actually cause the problem.
3) It seems to me that for a model to be trusted it must have predictive capability, and it must fit a physical model of our current understanding. How do the various models hold up with these criteria? It seems like climate is still a very complex field that we don't fully understand.
[+] [-] thadd|10 years ago|reply
[+] [-] lordnacho|10 years ago|reply
He says the predictions were generally pretty good, maybe IPCC was a bit on the high side compared to what happened.
[+] [-] Sapient|10 years ago|reply
[+] [-] mikeash|10 years ago|reply
I have nothing against clever visualizations like this, but god damn it web designers, stop co-opting standard UI interactions to make it happen. There is no reason to hijack window scrolling here. None. All you accomplished by doing this was make it harder to figure out how to read the thing, and break it badly for a lot of people. What's wrong with buttons? You can even look for swipes on touchscreen devices. That's pretty standard! But quit stealing the scrollers!
[+] [-] elorant|10 years ago|reply
[+] [-] zdw|10 years ago|reply