Along with the usual blather I hear on right-wing talk shows, there's a fresh falsity being spread over the airwaves: computer climate models are unsophisticated attempts to mirror changes in the Earth's weather and shouldn't be trusted.
This isn't true. So don't believe global warming skeptics like George Taylor, who isn't Oregon's state climatologist but likes to pretend that he is.
I heard Taylor spout his uninformed criticisms of climate models on KPAM's Victoria Taft show. Since those models show both that global climate change is going to be an increasingly serious problem, and that humans are responsible for a large share of the rise in carbon dioxide that is helping to drive global warming, ExxonMobil supported pseudo-scientists like Taylor try to discredit the models.
Recently Taft echoed the unscientific party line, claiming that the models don't include basic factors that affect the climate. Such as, Taft said, "the sun." I suspect she meant to say sunspots, or some other subtlety of solar radiation, but that wasn't what came over my car radio. I remember hearing: "Gosh, those models don't even include the sun. How crazy is that?"
Well, not crazy at all. Because Taft and Taylor don't know what they're talking about. Here's the graphical bottom line that proves them wrong, courtesy of the Woods Hole Research Center, along with a couple of paragraphs of Woods Hole commentary.
Look, read, and believe in the models. (As noted in the commentary, "forcing" means an influence on global temperature; "anthropogenic" means human-caused.)
For example, recorded global temperature change can be compared with computer models that predict temperature change under different "forcing" scenarios, (with "forcings" signifying external influences on the solar radiative budget of the planet - greenhouse gases, aerosols, increased solar radiation, and other agents). Fig. 2 above compares observed temperature anomalies from the historic mean (red line) with the results of computer models that attempt to predict temperature based on the interactions of other environmental influences (gray line).
The top two charts in the figure illustrate that models using natural and anthropogenic influences alone [(a) Natural Forcing Only & (b) Anthropogenic Forcing Only] fail to match the observed record of temperature anomalies since 1866. But the combination of natural and anthropogenic models [(c) Natural + Anthropogenic Forcing] produces a close match to the measured data. This is seen as a clear "thumbprint" of human impacts on climate change.
These graphs also are in Alan J. Thorpe's informative (and readable) paper, "Climate Change Prediction: A challenging scientific problem." Thorpe starts out by saying:
Predictions of future climate change, based on numerical global climate models, are the critical outputs of climate science. Whilst much has been written about the details of the predictions themselves, skepticism about the prediction models is rife and this is why this paper is devoted to de-mystifying the prediction methodology…There is little doubt that a lack of knowledge about how climate change is predicted and the associated uncertainties are amongst the main reasons for ill-informed comment on climate change.
And he concludes with:
So why do commentators imagine that top scientists are deluded about anthropogenic climate change? The stakes are high and rarely are scientists under such scrutiny. Scientists are appalled that they could be suspected of distorting the evidence to enhance their reputations or funding opportunities. Of course scientific hypotheses and analysis can be refuted by later discoveries but this is not the same as complicity. The fact that everyone experiences weather and climate may explain why nonscientists feel confident in attempting to refute the scientific evidence.
The complexity of the climate system and its many interacting and compensating physical processes means that simple arguments that gloss over this complexity have to be approached with a significant degree of scepticism. A common method of arguing starts by identifying a single cause or physical process that either has not been included or has been included in an imperfect way, into climate models. But the climate changes because of a multiplicity of interacting processes and any one process alone cannot be the whole story.
The search for the one and only cause of climate change is doomed to failure. Climate modellers attempt to include in the models all the processes that are even remotely likely to have a detectable effect – any newly discovered process will quickly find itself incorporated into the models!
So be highly skeptical of global climate change skeptics. Thorpe says that the models they dismiss with off-hand comments ("doesn't even include the sun!") have about three-quarters of a million lines of computer code.
Compare that with the miniscule iota of sense made by global warming deniers such as George Taylor and Victoria Taft. Believe the models, not them.