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Hacker News has climate change "denialists" because climate models are terrible at predicting global temperature[1][2]. Once scientists gain the ability to make

by crassus 13y ago

Hacker News has climate change "denialists" because climate models are terrible at predicting global temperature[1][2]. Once scientists gain the ability to make accurate predictions, more logic-minded hackers will go along. Hackers like predictive models with a good track record, a la Nate Silver. They dislike emotional bullying. [1] http://wattsupwiththat.com/2013/10/14/90-climate-model-projectons-versus-reality/ http://wattsupwiththat.com/2013/10/14/90-climate-model-proje... [2] http://www.economist.com/news/science-and-technology/21574461-climate-may-be-heating-up-less-response-greenhouse-gas-emissions http://www.economist.com/news/science-and-technology/2157446...

timr 13y ago
It's quite clear that "hackers" don't understand enough about the research to make informed criticisms. Cherry picking two measurements of temperature data does not make for a convincing rebuttal against the overwhelming independent lines of evidence summarized in (among other places), the IPCC reports.
- crassus 13y ago
  Ah yes. I need to listen to authority and ignore the fact that observed data are falling out the bottom side of their models' 95% confidence intervals. This is how science is done in the modern age.
  - timr 13y ago
    Prove your claim. Cite something other than a picture you found on a blog.
    - sien 13y ago
      This is from another blog, but the figures are from draft versions of the latest IPCC report: http://climateaudit.org/2013/10/08/fixing-the-facts-2/ http://climateaudit.org/2013/10/08/fixing-the-facts-2/ The figure that was removed shows that measured temperatures are falling outside a 95% confidence interval from the multi-model mean. This does not mean the climate will not warm, that C02 is not the major factor (or at least a major factor), but it does mean the models that are used for 100 year projections have failed after after 15 years and are running too hot. It should be cause for celebration. The highest warming scenarios are considerably less likely. This also does not mean that an emissions tax and spending on R&D on low emissions energy sources is unwise. But it should be factored into cost benefit analysis of climate change response. Ultimately response to climate change is a public policy problem and is not just based on scientific data and projections. Really, the response boils down to one question, how much is each of us willing to pay per year to respond? $10, $100, $1000, $10000?
      - timr 13y ago
        Ok, so you're citing three pictures on a blog. I guess I'm supposed to be 300% more convinced? But seriously: you're cherry picking one set of mean global temperature data, to dispute one graph in one IPCC report, for one line of evidence (of many). And your argument isn't rigorous or statistical -- some guy hand-drew some lines over the graphs, and asserts that it doesn't fit the data, even though the observed data lands pretty cleanly in the range of the models. And even if the models are off here, it doesn't invalidate the hypothesis of AGW. You can't win, even if you make a good argument here. The reason nobody but climate denialists read these arguments is because they're pedantic and facile, not because there's a vast scientific conspiracy against you.
- guscost 13y ago
  Argumentum ad verecundiam.
  - saraid216 13y ago
    Not actually a fallacy, even the informal kind, despite the Latin name.
mattdmrs 13y ago
One can argue that science will always have a hard time constructing an accurate model for predicting weather, because of its inherent humongous complexity and nonlinear behavior: > [...] we provide a number of illustrative examples and highlight key mechanisms that give rise to nonlinear behavior, address scale and methodological issues, suggest a robust alternative to prediction that is based on using integrated assessments within the framework of vulnerability studies and, lastly, recommend a number of research priorities and the establishment of education programs in Earth Systems Science. http://link.springer.com/article/10.1023/B:CLIM.0000037493.89489.3f http://link.springer.com/article/10.1023/B:CLIM.0000037493.8...
dmpk2k 13y ago
Nate Silver comes out very clearly in support of climate change theory in his The Signal and The Noise, and elucidates why, although he goes carefully through the problems and limitations with many climate models. Criticising models is not the same as claiming that anthropogenic global warming is false. Indeed, Nate Silver makes the point that climatologists are their own greatest critics -- they collectively know the limits of their models better than almost everyone else. So I'm not really sure why he's in your comment. If you've read what he writes, then you'll need to be building counterarguments to much of what he wrote on the topic; "models have problems" is just part of it.
snowwrestler 13y ago
Climate models are not intended to precisely predict global temperature on short time scales, so the fact that they cannot does not disprove their accuracy or utility. Furthermore, global climate models are tools for a particular kind of research, not the basis for the theory of global warming--which predates electronic computers by about 40 years. Evolutionary theory cannot reliably predict complex outcomes either. For example, despite the relative biological simplicity of a flu virus, scientists struggle to predict the strain(s) that will be most virulent each year. But I never see posts on HN holding this failure up as proof that evolution is not believable.

by crassus 13y ago

timr 13y ago

It's quite clear that "hackers" don't understand enough about the research to make informed criticisms. Cherry picking two measurements of temperature data does not make for a convincing rebuttal against the overwhelming independent lines of evidence summarized in (among other places), the IPCC reports.

crassus 13y ago
Ah yes. I need to listen to authority and ignore the fact that observed data are falling out the bottom side of their models' 95% confidence intervals. This is how science is done in the modern age.
- timr 13y ago
  Prove your claim. Cite something other than a picture you found on a blog.
  - sien 13y ago
    This is from another blog, but the figures are from draft versions of the latest IPCC report: http://climateaudit.org/2013/10/08/fixing-the-facts-2/ http://climateaudit.org/2013/10/08/fixing-the-facts-2/ The figure that was removed shows that measured temperatures are falling outside a 95% confidence interval from the multi-model mean. This does not mean the climate will not warm, that C02 is not the major factor (or at least a major factor), but it does mean the models that are used for 100 year projections have failed after after 15 years and are running too hot. It should be cause for celebration. The highest warming scenarios are considerably less likely. This also does not mean that an emissions tax and spending on R&D on low emissions energy sources is unwise. But it should be factored into cost benefit analysis of climate change response. Ultimately response to climate change is a public policy problem and is not just based on scientific data and projections. Really, the response boils down to one question, how much is each of us willing to pay per year to respond? $10, $100, $1000, $10000?
    - timr 13y ago
      Ok, so you're citing three pictures on a blog. I guess I'm supposed to be 300% more convinced? But seriously: you're cherry picking one set of mean global temperature data, to dispute one graph in one IPCC report, for one line of evidence (of many). And your argument isn't rigorous or statistical -- some guy hand-drew some lines over the graphs, and asserts that it doesn't fit the data, even though the observed data lands pretty cleanly in the range of the models. And even if the models are off here, it doesn't invalidate the hypothesis of AGW. You can't win, even if you make a good argument here. The reason nobody but climate denialists read these arguments is because they're pedantic and facile, not because there's a vast scientific conspiracy against you.
guscost 13y ago
Argumentum ad verecundiam.
- saraid216 13y ago
  Not actually a fallacy, even the informal kind, despite the Latin name.

mattdmrs 13y ago

One can argue that science will always have a hard time constructing an accurate model for predicting weather, because of its inherent humongous complexity and nonlinear behavior: > [...] we provide a number of illustrative examples and highlight key mechanisms that give rise to nonlinear behavior, address scale and methodological issues, suggest a robust alternative to prediction that is based on using integrated assessments within the framework of vulnerability studies and, lastly, recommend a number of research priorities and the establishment of education programs in Earth Systems Science. http://link.springer.com/article/10.1023/B:CLIM.0000037493.89489.3f http://link.springer.com/article/10.1023/B:CLIM.0000037493.8...

dmpk2k 13y ago

Nate Silver comes out very clearly in support of climate change theory in his The Signal and The Noise, and elucidates why, although he goes carefully through the problems and limitations with many climate models. Criticising models is not the same as claiming that anthropogenic global warming is false. Indeed, Nate Silver makes the point that climatologists are their own greatest critics -- they collectively know the limits of their models better than almost everyone else. So I'm not really sure why he's in your comment. If you've read what he writes, then you'll need to be building counterarguments to much of what he wrote on the topic; "models have problems" is just part of it.

snowwrestler 13y ago

Climate models are not intended to precisely predict global temperature on short time scales, so the fact that they cannot does not disprove their accuracy or utility. Furthermore, global climate models are tools for a particular kind of research, not the basis for the theory of global warming--which predates electronic computers by about 40 years. Evolutionary theory cannot reliably predict complex outcomes either. For example, despite the relative biological simplicity of a flu virus, scientists struggle to predict the strain(s) that will be most virulent each year. But I never see posts on HN holding this failure up as proof that evolution is not believable.