Climate change clairvoyants are trying to scry the future in a pool of computer output. Much like other psychics, they ignore their failures and point with vindication to the (very) few predictions they get right.
Nostradamus, the famous prognosticator, was said to have received his visions of the future by scrying—staring into a pool of ink for hours on end. The climate science equivalent of a gazing pool is the computer climate model, huge collections of complicated computer code that supposedly crank out frightening visions of the future. Most of the discussion about climate change has centered on the global aspects of the anthropogenic global warming (AGW), but now a number of climate mystics are turning their modeling dark arts to doing regional predictions. Why? The better to frighten the public and elicit funding from government coffers. Unfortunately, as climate researchers struggling to sharpen their fuzzy picture of what the future holds one fact has been ignored—there is even more uncertainty in regional models than in the global ones.
Scrying is a form of divination, which involves prolonged gazing into a crystal, a pool of water, a black mirror, or similar surface, in order to obtain visions. Modern climate scientists have been peering at computer output for decades, in an attempt to divine Earth’s future climate, with almost as much success as medieval seers. Time after time, the computer climate models have come up short on predictive power, with many different models disagreeing with each other. Even so, it is modeling that supports the climate alarmists’ frantic warnings about a dystopian future caused by a warming climate. According to Richard A. Kerr, resident warm monger at the AAAS journal Science:
Climate researchers are quite comfortable with their projections for the world under a strengthening greenhouse, at least on the broadest scales. Relying heavily on climate modeling, they find that on average the globe will continue warming, more at high northern latitudes than elsewhere. Precipitation will tend to increase at high latitudes and decrease at low latitudes.
While this blind faith in climate modeling flies in the face of experience, the climate science community is pretty much tied to their computer predictions. Evidently believing that the best defense is a strong offense, the modelers are now upping the ante by shifting to regional models to provide more detailed predictions of the ravages of global warming. Switching from global models to models focusing on a single region creates a more detailed forecast, but it also “piles uncertainty on top of uncertainty,” says meteorologist David Battisti of UW Seattle.
In the news focus article “Vital Details of Global Warming Are Eluding Forecasters,” it is reported that regional modelers are “well into their first extensive comparison of global-regional model combinations to sort out the uncertainties.” Leading the new effort in the US is the North American Regional Climate Change Assessment Program (NARCCAP), a combined effort of NSF, EPA, DOE, NOAA and several others.
NARCCAP is an international program to produce high resolution climate change simulations in order to investigate uncertainties in regional scale projections of future climate and generate climate change scenarios for use in impacts research. NARCCAP modelers are running a set of regional climate models (RCMs) driven by a set of atmosphere-ocean general circulation models (AOGCMs) over a domain covering the conterminous United States and most of Canada. The reason this new effort is seen as important is because of the dismal history of regional models.
More than a decade ago, the U.S. government commissioned a report, Climate Change Impacts on the United States, which relied on the most rudimentary regional forecasting techniques (see “Dueling Models: Future U.S. Climate Uncertain”). A committee of experts divided the country into eight regions and then used two of their best global climate models to predict the climate of each region over the next century.
The two models were somewhat consistent in the far southwest, but elsewhere the predictions tended to disagree, sometimes dramatically. For example, corn crops in Kansas would either suffer severe droughts more frequently, as one model predicted, or enjoy even more moisture than it currently does, as the other indicated. No competent computer modeler would have been surprised that different models could yield widely divergent answers.
“For the most part, these sorts of models give a warming,” said modeler Filippo Giorgi at the time, “but they tend to give very different predictions, especially at the regional level, and there’s no way to say one should be believed over another.” Oh what to do? The Oracle at Delphi says one thing while the haruspices report the sheep entrails say the opposite. Call the Augur to break the tie!
These results proved unsatisfactory, even to the notoriously slipshod climate change prophets of the time, prompting greater reliance on more global models. In the 2009 study Global Climate Change Impacts in the United States, output from 15 global models were combined into single projections. It was assumed that local changes would be proportional to changes on the larger scales, guess work clocked by the imposing term “ statistical downscaling,” On top of that, they then adjusted the regional climate projections according to how well model simulations of the past matched actual climate data.
In other words, they took 15 sets of divergent and contradictory data, averaged it out and then “adjusted” it so it fit actual data from the past—just the thing to base you future economic and energy policy on (see “Climate Models Fail To Predict Past Catastrophes”). Still, there’s grant money in them models and a climate modeling gold-rush is on, according to Kerr’s article:
A rapidly growing community of regional modelers is turning out increasingly detailed projections of future climate, but many researchers, mostly outside the downscaling community, have serious reservations. “Many regional modelers don’t do an adequate job of quantifying issues of uncertainty,” says Bretherton, who is chairing a National Academy of Sciences study committee on a national strategy for advancing climate modeling. “We’re not confident predicting the very things people are most interested in being predicted,” such as changes in precipitation.
The problem with this approach starts with the global models themselves. Regional models must fill in the detail in the fuzzy picture of climate provided by global models, notes atmospheric scientist Edward Sarachik, professor emeritus at UW Seattle. Global models aren’t very good at painting regional pictures, he says, and if the fuzzy picture of the region is wrong, the details will be wrong as well.
A case in point is the way global models place the cooler waters of the tropical Pacific farther west than they are in reality. Temperature differences in the Pacific Ocean drive weather and climate shifts in regions halfway around the world. If the global models place cold water in the wrong place, the models drive climate change in the wrong regions. This is garbage in, garbage out elevated to dizzying heights.
It should be noted that all the recent results posted on the NARCCAP site were forced with the IPCC SRES A2 emissions scenario for the 21st century. According to the website, “the A2 scenario is at the higher end of the SRES emissions scenarios (but not the highest), and this was preferred because, from an impacts and adaptation point of view, if one can adapt to a larger climate change, then the smaller climate changes of the lower end scenarios can also be adapted to.”
Due to limited funding, the researchers chose to use only one emissions scenario, which was used for all simulations. Simulations were also produced for the recent past, in order to establish a baseline of current conditions. The RCMs were nested within the AOGCMs for the current period 1971-2000 and for the future period 2041-2070. All the RCMs were run at a spatial resolution of 50 km.
Moreover, the modeling runs omitted the coupled ocean model in order to save on computation. The atmospheric component of the AOGCM was run using observed sea surface temperatures and sea ice boundaries for the historical runs. Those same observations were combined with perturbations from the future AOGCM for the scenario run. In other words, they fixed the boundary conditions in their model by holding the contribution of the most important driver of climate, the ocean, constant. In terms of modeling verisimilitude this is a striking step backwards.
To summarize, government funded researchers started with one of the highest IPCC temperature estimates and used that to force both global and regional models. Bogus global models were used to drive unrealistic regional models. Unsurprisingly, the results varied widely. In the final analysis, these results were only useful in pointing out the deficiencies of the current crop of regional models.
“There are a lot of problems matching regional and global models,” says Gregory Tripoli, a meteorologist and modeler at the University of Wisconsin. Regional models cannot take long range interactions into account, effectively limiting them to being as inaccurate as the global models that feed them. Even the different philosophies involved in building global models vs regional models can lead to mismatches that create phantom atmospheric circulations, Tripoli says. “It’s not straightforward you’re going to get anything realistic.”
Yet, the extreme results generated by these studies will undoubtedly be picked up by climate change alarmists and eco-activists, used to bolster the flagging case for AGW. Karl Popper, the great philosopher of science, said that all scientific theories are wrong, some are just less wrong than others. When scientists say that their new models are giving better results than before, it does not mean that the new results are correct, just less wrong than the previous ones. Try explaining that to a news network airhead or a self-serving politician and you will get predictions of impending catastrophe reported as fact or government funding of favored projects.
So when you hear news that scientists predict a 30% to 50% decrease in the area suitable for production of premium Californian wine grapes, skiing in the Rockies will be curtailed or that your local river is going to dry up, take it with a grain of salt. It’s just the latest set of non-prediction predictions from the seers of climate science—climate change clairvoyants trying to scry the future in a pool of computer output. Much like other psychics, they ignore their failures and point with vindication to the (very) few predictions they get right. None the less, Nostradamus still has ardent followers, as does global warming.
Be safe, enjoy the interglacial and stay skeptical.