1.27.2011

Histories of Numerical Climate Models

Meteorology Project, 
Institute for Advanced Study, Princeton, 1952. 
Left to right: Jule Charney, MANIAC I, Norman Phillips, 
Glenn Lewis, N. Gilbarg, George Platzman.
I was recently doing some background reading on the history of general circulation models (GCMS) for a paper and thought I'd share two of the nice histories I found.  The first is one that I've shared with many colleagues, both for information and for inspiration:

General Circulation Models of Climate
ABSTRACT: The climate system is too complex for the human brain to grasp with simple insight. No scientist managed to devise a page of equations that explained the global atmosphere's operations. With the coming of digital computers in the 1950s, a small American team set out to model the atmosphere as an array of thousands of numbers. The work spread during the 1960s as computer modelers began to make decent short-range predictions of regional weather. Modeling long-term climate change for the entire planet, however, was held back by lack of computer power, ignorance of key processes such as cloud formation, inability to calculate the crucial ocean circulation, and insufficient data on the world's actual climate. By the mid 1970s, enough had been done to overcome these deficiencies so that Syukuro Manabe could make a quite convincing calculation. He reported that the Earth's average temperature should rise a few degrees if the level of carbon dioxide gas in the atmosphere doubled. This was confirmed in the following decade by increasingly realistic models. Skeptics dismissed them all, pointing to dubious technical features and the failure of models to match some kinds of data. By the late 1990s these problems were largely resolved, and most experts found the predictions of overall global warming plausible. Yet modelers could not be sure that the real climate, with features their equations still failed to represent, would not produce some big surprise.
And here is one of my favorite passages about the birth of the enterprise:
In 1922, the British mathematician and physicist Lewis Fry Richardson published a more complete numerical system for weather prediction. His idea was to divide up a territory into a grid of cells, each with its own set of numbers describing its air pressure, temperature, and the like, as measured at a given hour. He would then solve the equations that told how air behaved (using a method that mathematicians called finite difference solutions of differential equations). He could calculate wind speed and direction, for example, from the difference in pressure between two adjacent cells. These techniques were basically what computer modelers would eventually employ. Richardson used simplified versions of Bjerknes's "primitive equations," reducing the necessary arithmetic computations to a level where working out solutions by hand seemed feasible. Even so, "the scheme is complicated," he admitted, "because the atmosphere itself is complicated."  
The number of required computations was so great that Richardson scarcely hoped his idea could lead to practical weather forecasting. Even if someone assembled a "forecast-factory" employing tens of thousands of clerks with mechanical calculators, he doubted they would be able to compute weather faster than it actually happens. But if he could make a model of a typical weather pattern, it could show meteorologists how the weather worked. 
So Richardson attempted to compute how the weather over Western Europe had developed during a single eight-hour period, starting with the data for a day when scientists had coordinated balloon-launchings to measure the atmosphere simultaneously at various levels. The effort cost him six weeks of pencil-work Perhaps never has such a large and significant set of calculations been carried out under more arduous conditions: a convinced pacifist, Richardson had volunteered to serve as an ambulance-driver on the Western Front. He did his arithmetic as a relief from the surroundings of battle chaos and dreadful wounds.
The work ended in complete failure. At the center of Richardson's simulacrum of Europe, the computed barometric pressure climbed far above anything ever observed in the real world. "Perhaps some day in the dim future it will be possible to advance the calculations faster than the weather advances," he wrote wistfully. "But that is a dream." Taking the warning to heart, meteorologists gave up any hope of numerical modeling.

I also found this chapter in a Google-book from a decade ago which had a very nice introduction to some of the early experiments and technical innovations.  It's slightly more technical, but extremely succinct. Less history but maybe more science.

1.02.2011

Temperature and aggression

Sometimes we don't take time to think about simple "obvious" things or to seriously consider older bodies of research.  Here's a gem from 1986 that I found recently.

Ambient Temperature and Horn Honking: A Field Study of the Heat/Aggression Relationship
Environment and Behavior, March 1986
Douglas T. Kenrick and Steven W. MacFarlane
Abstract
Using a method developed in previous field studies of aggression, this study examined the influence of ambient temperature on responses to a car stopped at a green light. To investigate alternative models of the effects of high temperature on interpersonal hostility, the study was conducted during the spring and summer in Phoenix, Arizona, and included a range on the temperature humidity discomfort index up to 116 degrees F. Results indicated a direct linear increase in horn honking with increasing temperature. Stronger results were obtained by examining only those subjects who had their windows rolled down (and presumably did not have air conditioners operating).
[As someone who spends the entire day in front of a computer screen, I am jealous of people who do this kind of research:]

[and the results:]

This relatively older literature on temperature and aggression is reviewed here.  It seems to be something that psychologists studied for a while, but hasn't been discussed at all in the highly technical discussions of climate change impacts.  Perhaps it could add something to the recent controversy over the idea that temperature changes can lead to conflict? In my reading of the recent literature, I don't think this mechanism was ever discussed. Somehow we manage to miss simple and "obvious" mechanisms when we think about complex global processes.

(A similar case is the effect of temperature on productivity, which again should be "obvious"...)