Climate History: Cato Boffins Discovered “Anti-information”
By Patrick J. Michaels and Paul C. “Chip” Knappenberger
While doing some historical studies in preparation for an article in Cato’s Regulation magazine, we found that we once discovered the information equivalent of antimatter, namely, “anti-information”.
This breakthrough came when we were reviewing the first “National Assessment” of climate change impacts in the United States in the 21st century, published by the U.S. Global Change Research Program (USGCRP) in 2000. The Assessments are mandated by the Global Change Research Act of 1990. According to that law, they are, among other things, for “the Environmental Protection Agency for use in the formulation of a coordinated national policy on global climate change…”
One cannot project future climate without some type of model for what it will be. In this case, the USGCRP examined a suite of nine climate models and selected two for the Assessment. One was the Canadian Climate Model, which forecast the most extreme warming for the 21st century of all models, and the other was from the Hadley Center at the U.K Met Office, which predicted the greatest changes in precipitation.
We thought this odd and were told by the USGCRP that they wanted to examine the plausible limits of climate change. Fair enough, we said, but we also noted that there was no test of whether the models could simulate even of the most rudimentary climate behavior in past (20th) century.
So, we tested them on ten-year running means of annual temperature over the lower 48 states.
One standard method used to determine the utility of a model is to compare the “residuals”, or the differences between what is predicted and what is observed, to the original data. Specifically, if the variability of the residuals is less than that of the raw data, then the model has explained a portion of the behavior of the raw data and the model can continue to be tested and entertained.
A model can’t do worse than explaining nothing, right?
Not these models! The differences between their predictions and the observed temperatures were significantly greater (by a factor of two) than what one would get just applying random numbers.
Ponder this: Suppose there is a multiple choice test, asking for the correct temperature forecast for 100 temperature observations, and there were four choices. Using random numbers, you would average one-in-four correct, or 25%. But the models in the National Assessment somehow could only get 12.5%!
“No information”—a random number simulation—yields 25% correct in this example, which means that anything less is anti-information. It seems impossible, but it happened.
We informed the USGCRP of this problem when we discovered it, and they wrote back that we were right, and then they went on to publish their Assessment, undisturbed that they were basing it models that had just done the impossible.
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Weather forecasts for tomorrow are fairly accurate, for the day after that less so and for the third day; you’re looking at a little better than evens. Does that behaviour sound familiar? A whole branch of Mathematics, called rather fittingly Chaos Theory, grew out of that sort of ‘spiralling unpredictably out of control’ behaviour exhibited by one of the first attempts to simulate the weather on a computer.
http://thepointman.wordpress.com/2011/01/21/the-seductiveness-of-models/
Pointman
This is funny.
Models that predict two times worse that plotting random numbers?
It’s like a nonsense that is twice more gibberish than an utter gobbledygook.
Or an idiocy that is twice more stupid than being brain-dead.
Anti models actually sound useful – you could use anti-models to eliminate ranges of values from the probable path of future climate. Who knows, after AR5, by inverting the model projections, eliminating values which the models predict, we might actually have a prediction landscape which yields useful insights into future climate.
😉
” …… model can continue to be tested and entertained.”
Do models eat popcorn while being entertained?
(Sorry, couldn’t resist.)
Yeah, its just like climate sensitivity less than 1.5degrees C being ‘ruled out’ in IPCC AR4. Yet that is what the temperatures are doing.
Most times a climate alarmist says something is ‘very unlikely’, ruled out, ‘can’t happen’, ‘is not in the consensus’, one can take it for granted that it is more likely to be true and correct, because anything that is true but against alarmism is specifically targeted by an army of researchers to try and be countered by ‘pal review’.
No, weather forecasts are NOT accurate today, a little less tomorrow and so on.
After having lived in the High Rockies for three years I have found that the typical weather forecast for today is 5-10 degrees off of low and high. It may have predicted snow for today and none, or with a prediction of no snow we get eight inches.
The 15 day forecast is so horrendous that I emailed the weather channel help and comment desk where I was informed that it is their “best guess” for those days. Rhe 15 day forecast is accurate ZERO percent of the time and I said so while asking why do you even bother with the 15 day. No response.
So, I cant get an accurate prediction now for later today….EVER, and people mean to tell me to within hundredths of a degree the temperature 100 years from now?
This is so beyond absurd I havent any expression for it.
gaelan, weather forecasts in most areas are getting very accurate. Obviously there are some locations that either are too chaotic for the models to work with, or the sensors feeding the data into them are not properly situated or calibrated.
Just a few years ago, weather forecasting was primarily a manual task. A meteorologist examined the “current” weather conditions and, based on training and experience, decided what the likely future weather would be.
There was a situation in Calgary (similar location relative to the Rockies to Denver) a few years back where the Environment Canada forecaster, NOT a Calgarian, had an almost perfect record for forecasting… for over a year the vast majority of his forecasts were just about as wrong as could be. In the last few years, especially since they’ve installed Doppler (Canada took its time getting this tech deployed), the forecasts for one, two, even three days are quite accurate, and even the 10 days are closer than they ever used to be.
However, no matter how good a meteorological model is, it is still dependent upon the input (current conditions, usually from automated sensors), and the fundamental assumptions (such as typical airflow through the region, what kind of real temperatures are likely to occur from an incoming pressure system, etc.) As these assumptions are tuned the models improve.
Obviously, “climate models”, developed by people who think they’re several rungs up the evolutionary ladder from mere “weathermen”, don’t care about anything other than unproven assumptions, like GHGs and other trivial phenomena. This is why they’re wrong, and always will be until the basic assumptions are moved closer to reality. Personally I don’t foresee that happening any time soon.
Whether weather forecasts are accurate only for 10 minutes out or 10 hours or 10 days, we’re still talking an incredibly brief amount of time relative to years, decades, and centuries… which is why I 100% agree with this:
(the only expression I can think of is ‘hubris’)
These guys cheat more than my golf buddies.It was never about the climate . It was never about the environment. It was never about conservation or pollution. It’s about the destruction of capitalism and control over the human race. Unlike my golf buddies these people are evil.
[Anti-information] in science smells as sweetly as falsification!
Are we done, is the hypothesis falsified, is not all else to follow mere ADHOCKERY shoring up a failed argument?
Darn the typo; it should be Anti-information. But like a cat’s hairball, they’ll retch warmism up again and again until it is swallowed by the gullable.
If they show persistent anti-skill, they are the first climate models that are useful (We know that what they predict will NOT happen.)
This all sounds like a Terry Pratchett novel (see Pyramids and the predictive robot in there) or Larry Niven (Ringworld; the girl with the genetic predisposition to be lucky.)
gaelan clark says:
May 23, 2013 at 3:52 am
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In Florida they are always correct but not very accurate.
Here we understand it’ll be warm and muggy and ‘it might rain’.
We get pop-up thunderstorms and lots of lightning.
It’s not easy living with a governor of a regional climate system.
h/t to w.
cn
btw …. Do climate governors include such things as arctic winds and heavy rain cycles or are they considered something else?
gaelan clark says:
May 23, 2013 at 3:52 am
“No, weather forecasts are NOT accurate today, a little less tomorrow and so on.”
That would depend on where you are forecasting. For instance, on the SW Gulf coast of Florida you can forecast that from now through Sep day time highs will be around 92 with a 30% chance of thunderstorms. Any fronts or disturbances that come our way are easy to see making it easy to predict what changes they will bring. Life is so much easier in warm weather.
This is one of the funniest posts I’ve seen in a long time. It reminds me of “the Andy letter”.
http://www.cartalk.com/content/andy-scale-0
The sad thing is, people are trying to set public policy on this comedy, which is not funny at all.
-BillR
It strikes me that if a model consistently does worse than randomness, then it is predicting against the hypothesis. For example it is showing CO2 warming when CO2 actually causes cooling. This means these model show what will more likely not happen than happen.
Doug Huffman says:
May 23, 2013 at 4:26 am
[Anti-information] in science smells as sweetly as falsification!
Are we done, is the hypothesis falsified, is not all else to follow mere ADHOCKERY shoring up a failed argument?
———————————
Nice term. Would that be a verb?
Ad Hockery: An argument which attempts to shore up a failed argument.
or
Would that be Post Hockery since it’s to sustain a falsified argument?
cn
Yes, but remember that we are regularly told that their predictions get better the further out in time they are applied!
gaelan clark says:May 23, 2013 at 3:52 am
I agree with your synopsis of the precision of weather prediction. I live in the Rockies and have heard that meteorologists train in Colorado because weather systems are formed and redirected by the mountains, making it one of the most difficult areas to forecast. There is a saying here, “if you don’t like the weather, wait ten minutes…”
Even though these models apparently are pretty good at predicting what will not happen, the EPA is going to set policy based on these models as if they predict what will happen. Is this Alice in Wonderland now?
It’s obvious why the prediction was so far off, they intentionally DESIGNED the data to make a point, it was just the wrong point. I can’t figure out if if the climate scientists are really stupid enough not to understand that predicting something means one day it can be proven false, or if they are just overcome with religious zeal and believe all the crap they print.
This may be related to the Gore Effect – an anti-dis-information phenomenon.
Mike jarosz says:
May 23, 2013 at 4:11 am
These guys cheat more than my golf buddies.It was never about the climate . It was never about the environment. It was never about conservation or pollution. It’s about the destruction of capitalism and control over the human race. Unlike my golf buddies these people are evil.
——————————————–
True but if you remind your buddy he took a drop on the 3rd hole and actually got a 6 he will correct his score.
A warmists golfer will declare, after the fact, there was an ant hill down by the lake where his ball was and he was allowed a free drop. He says he got a 5 on the 3rd hole so his score will stand. If you ask him to show you where he dropped he says go find it yourself.
I’m sure I wouldn’t want to play golf with an alarmist.
cn
Maybe they would have been more accurate using log(2) / log(√2) = 2 expressed as a Brownian motion fractal 🙂
William C Rostron says:
May 23, 2013 at 4:55 am
It reminds me of “the Andy letter”.
http://www.cartalk.com/content/andy-scale-0
================
Well worth the read. Answers the age old question: Do two people that know nothing about a subject know even less than one person that knows nothing about a subject?
In this case we have two climate models that know nothing about the future. The question is: Do they know even less about the future than one model, a random number generator, that knows nothing about the future? Apparently they only know 1/2 as much about the future as a model that knows nothing.
This points to real progress in climate forecasting. Climate Science has finally found a way to predict what will not happen in the future. Thus, we can apply the Sherlock Holmes method to climate forecasting. With enough climate models predicting what will not happen in the future, whatever they are not predicting, no matter how unbelievable, must be the truth.
@gaelan clark: Not to worry. In ten or twenty years you’ll have learned that every drainage in a mountain range has its own weather and you’ll be able to formulate your own 24-hour forecast to a reasonable degree of accuracy. Or, just wait five minutes and it’ll change anyway.