[1] http://wattsupwiththat.com/2013/10/14/90-climate-model-proje...
[2] http://www.economist.com/news/science-and-technology/2157446...
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.
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.
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?
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.
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.
> [...] 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.0000037493.8...