America loves its models
reality: i respect it too much to believe in it.
-Jean Baudrillard
In my most recent post, I discussed the problematic nature of scientific consensus in response to a comment on a previous blog from my friend, Jake. The dubious nature of the scientific consensus that confirms the dangerous potential of anthropogenic global warming is only partially responsible for my skepticism on this topic. Today I will discuss the equally dubious behavior of scientifically modeling immature sciences.
In Jake’s original comment he says, “So do you believe that the wealth of researchers who do believe (or at least purport to believe) that human action has had a significant impact is literally nothing more than a conspiracy and the studies and models are contrived?” My answer to this question is to say, “how does America like it’s models?” Why fake of course. What good is a model, if it hasn’t been photoshopped, doctored up, and air-brushed to appeal to the baser emotions of humankind…fear, lust, greed. In fact, it is no surprise that the oh-so-fashionable art of creating scientific models has mirrored the modeling industry’s advance of oh-so-fashionable art.
As one who has spent much time studying artifice and sophistry, it is an affront to those of us who love words to see engineers use their numbers and equations to endeavor to tell stories. By any aesthetic standards, the stories that come out of the models designed by clever engineers are not good stories. If you apply scientific standards to the same stories, they just get worse.
For example, one might create a model that harvests historical temperature data, and spin a fabulous yarn about how the planet is getting hotter. Oh yeah, and did I mention that in this story that we are all doomed! Ha, Ha, Ha! (evil laugh). Then some hero comes along, named Anthony Watts, with a report that he produced about how the data was collected.
How to not measure temperature
In his report, Is the U.S. Surface Temperature Record Reliable?, Watts disrupts the narrative being presented by our wily, anonymous narrator.
According to Watts:
The reliability of data used to document temperature trends is of great importance in this debate. We can’t know for sure if global warming is a problem if we can’t trust the data.
and
In fact, we found that 89 percent of the stations – nearly 9 of every 10 – fail to meet the National Weather Service’s own siting requirements that stations must be 30 meters (about 100 feet) or more away from an artificial heating or radiating/reflecting heat source.
The conclusion is inescapable: The U.S. temperature record is unreliable.
Like your average supermodel, the mathematic supermodels of global warming are enhanced with perfectly manufactured pieces of silicon. These microchip implants have given the average scientist a new-found self-confidence. Unlike supermodels, I like my scientists to have enough self-confidence to doubt themselves.
Here is an article for further reading on the subject of problematic modeling.
Therefore thou hast forsaken thy people the house of Jacob, because they be replenished from the east, and are soothsayers like the Philistines
-Isaiah 2:6
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America does like its models. We also like our myths as well. My favorite myth is that of the outsider. The presidential candidate, who spent their life running with Washington now has to show they are not from Washington. A true outsider, someone like Lincoln who was self-taught, would never have a chance.
Harrison’s last blog post..Not Simply Nocturnal Emissions
Witty answer, but do you have a direct answer to the question posed? Both posts respond with witty observations, but you avoid the question. Does it boil down to liberal political conspiracy or is there something to the trend?
Otherwise, I think that the point of this post breaks down when one realizes that you are talking about two different types of models. One type is created as an ideal, perhaps we could term this a “prescriptive model.” This is the type that is airbrushed, idealized, etc. However, descriptive models are used to approximate the real world (with admittedly limited information, yet the best available information). The goals are different for these different models, and you are critiquing the latter as if it were the former.
You are absolutely correct that models are imperfect approximations of the world. That is precisely why we call them that: MODELS. I never claimed that my third grade diorama, or one might say, model, of the solar system approached some real replica of the actual solar system. However, given my skill and knowledge as well as the information available to me as a third grade student, my clay and paper replica was perhaps the best model allowed under my expertise, available materials, and knowledge of the subject. It was nonetheless imperfect.
In evaluating any model of any system, one must always take into account first and foremost the assumptions of the model, for there are always essential assumptions on which the predictions will vitally hinge (a point well summarized in the second source on our post, Leland Teschler’s editorial). One must also consider the data on which the model is based, and the quality of said data, as well as the actual structure of the model. The Watts data is certainly relevant in this vein, but people are also drawing very preliminary conclusions. It does not follow from his data that the U.S. temperature data is unreliable. This would have to be demonstrated by showing that now-compromised sensors have deviated from non-compromised sensors, which could be done fairly simply with (uh oh, here it goes) a regression model comparing the temperature data against Watts’s ratings. One other consideration is that human modification of the earth’s surface itself actually changes the reflective value of the surface. Would these encroachments that Watts talks about then provide some sort of approximation of this effect (albeit an overestimation?). I bring up these counterpoints because I think it is too quick (and perhaps politically motivated) to say that it logically follows that surface data should be thrown out. What about trends using only the sensors that have not been compromised?
There are certainly limitations to weather models as there are to economic models, but those that are constructed without obvious biases also give us the best possible predictions of the system, given available knowledge. To say that modeling itself is an all around fruitless endeavor is over-reaching, and perhaps ends the discipline of economics, as well as many others. I would hate to tell Brent that.
-Jacob