|From the WSJ response to "No Need to Panic..."|
There is a lot of interesting debate in the WSJ opinion pages regarding "climate change."
On January 27, 2012 the WSJ published an opinion piece "No Need to Panic About Global Warming." Needless to say it generated a lot of interest.
The main points of the article were
- CO2 is not a pollutant.
- The temperature of the planet hasn't changed significantly in 10 years.
- Why are significant changes in public policy based on these non-facts.
The article was authored by some sixteen or so different scientists - though none from the "Climate Research" area.
A huge attack followed with a slew of letters and comments decrying how wrong this analysis was, how the scientists lacked standing, and so forth.
All standard fare.
Recently a second opinion column appeared by these same scientists. This time answering the critics of their first article.
One of the most important comments was that regarding the standard IPCC climate modeling. The chart above (from the WSJ) shows the various IPCC predictions (starting in 1990) about the "surface global temperature." Each is significantly wrong and each significantly over-predicts a temperature increase that fails to materialize.
The article goes on to discuss the various political and policy science aspects of the arguments.
But the issue for this post is not "Climate Change." I mention this because it segues nicely into the real topic: predictability.
Many of you have no doubt heard of the "butterfly effect." The idea is that a butterfly can flap its wings in Peking and a day later you get rain instead of sunshine in Central Park (or a year later you get a hurricane that destroys New Orleans instead of a sunny day).
Now in point of fact it turns out that there may not really be such a thing as the butterfly effect.
And the reason is quite interesting.
The basic scenario of things like climate modeling implicitly include the following: I take a "snapshot" of the Earth in, say, 1950, and I run a simulation (A) of it forward to 2012 with man dumping CO2 into the atmosphere and I run simulation (B) of it forward without man I show that man's CO2 is warming the planet (or with or without our butterfly).
Simulation (A) shows one thing, (B) another.
The problem is that, on the quantum level (as well as at any level of any mathematical precision in the "simulation" of the climate) that even if I ran (A) or (B) through a second time I would not get the same result. (See this blog by Graham Morehead at Nature.)
The reason for this is that at the quantum level there is a lot of "noise" - heat transfer and other non-predictable quantum events - will not be the same - they cannot be. This is simulated (perhaps not intentionally) in various climate models by the precision of the calculations (imagine 3.14159.......234... in one simulaton and 3.14159......235... in another).
The difference between the 4 and the 5 in the two values, perhaps many decimal to the right, can play a significant role in the outcome down the line.
Well, you might say, the model of climate is a mathematical one and it should always give the same result, i.e., it must be precise.
Unfortunately you'd be wrong because of the quantum effects. The real "earth" is not "repeatable" in the same sense as a precise mathematical simulation. The quantum effects of everyday things add noise and noise changes the predictability of the model.
And climate models, which are all about heat, have to accurately portray randomness because, in fact, there is unpredictable quantum heat noise in the real world.
(What is heat, after all, but higher energy quantum activity; quantum in the unpredictable sense of not knowing what the vibrating atoms will exactly do. There are statistical means to talk about this but they are not exact in the predictive sense.)
So what's the upshot of all this?
For one thing, there cannot be a precise mathematical model climate because that would involve quantum thermodynamic "noise" which would make the model unpredictable because these quantum effects are unpredictable.
So even if you had a model if you ran it over and over your results would be different.
Nonsense you might say...
Well, try this simple experiment at home. Take a thermometer and measure the temperature in your living room at five different random points around the room. Chances are that these measurements will vary.
Because if the locations are in fact random some measurements will come out by, say a heating vent or window, others will not.
If someone else took five measurements at another random set of points at the same time they would likely get different results than you.
So even if you "averaged" these reading the results would be different.
The bottom line is that the mathematics and physics of temperature make modeling climate accurately impossible.
So of course the IPCC will be wrong - they have to be.