Nate Silver, holism, and all the news that’s fit to print.

Nate Silver has been in the news quite a bit of late. Chances are good you know who he is, but if you don’t you should. Here’s a bio on this very special 34-year-old. He’s best known for his political polls, which you can find at FiveThirtyEight.com. But he got his start by developing a highly-respected system for predicting the development and performance of baseball players. This week a lot of publicity for his forthcoming book The Signal and the Noise The Signal and the Noise: Why Most Predictions Fail – But Some Don’t (New York: Penguin, 2012, publication date: September 27, 2012) has added to the buzz.

The buzz is especially loud in our part of the blogosphere because of his rather favorable assessment of weather predictions in his book. You can find a substantial bit of his thinking in a recent New York Times article, which is excellent not withstanding the rather unfortunate title The Weatherman is Not a Moron. Here’s a snippet: “Why are weather forecasters succeeding when other predictors fail? It’s because long ago they came to accept the imperfections in their knowledge. That helped them understand that even the most sophisticated computers, combing through seemingly limitless data, are painfully ill equipped to predict something as dynamic as weather all by themselves. So as fields like economics began relying more on Big Data, meteorologists recognized that data on its own isn’t [sic] enough.”

The blogosphere has made much of meteorologists’ desirable attribute of humility. But the part of the article that really matters is this part… “The holy grail of meteorology, scientists realized, was dynamic weather prediction – programs that simulate the physical systems that produce clouds and cold fronts, windy days in Chicago and the morning fog over San Francisco as they occur. Theoretically, the laws that govern the physics of the weather are fairly simple. In 1814, the French mathematician Pierre-Simon Laplace postulated that the movement of every particle in the universe should be predictable as long as meteorologists could know the position of all those particles and how fast they are moving. Unfortunately, the number of molecules in the earth’s atmosphere is perhaps on the order of 100 tredecillion, which is a 1 followed by 44 zeros. To make perfect weather predictions, we would not only have to account for all of those molecules, but we would also need to solve equations for all 100 tredecillion of them at once.

The most intuitive way to simplify the problem was to break the atmosphere down into a finite series of boxes, or what meteorologists variously refer to as a matrix, a lattice or a grid. The earliest credible attempt at this, according to Loft, was made in 1916 by an English physicist named Lewis Fry Richardson, who wanted to determine the weather over northern Germany on May 20, 1910. This was not technically a prediction, because the date was some six years in the past, but Richardson treated it that way, and he had a lot of data: a series of observations of temperature, barometric pressures and wind speeds that had been gathered by the German government. And as a pacifist serving a volunteer ambulance unit in northern France, he also had a lot of time on his hands. So Richardson broke Germany down into a series of two-dimensional boxes, each measuring three degrees of latitude by three degrees of longitude. Then he went to work trying to solve the equations that governed the weather in each square and how they might affect weather in the adjacent ones…”

Silver hints at what all meteorologists know…there are five equations governing atmospheric dynamics or weather, and they must be solved or satisfied simultaneously, everywhere, or we have no solutions at all.

If the human race is to make its way successively over the coming decades, we have to do something similar with our simultaneous problems of extracting food, energy, and water resources from the Earth, protecting the environment and ecosystems, and building resilience to natural hazards,…and dealing effectively with each other. We must solve these problems together or not at all.

Recent stories from Silver’s employer, The New York Times, show we’re not developing such solutions. Let’s start with Mark Hertsgaard’s article entitled Harvesting a Climate Disaster. He covers Tuesday’s visit to Capitol Hill by farmers, demanding that Congress pass a farm bill. He suggests that the farmers’ current problems stem in part from this summer’s drought. He points out that this drought may in part stem from global warming, and that the bill does nothing to address farming’s giant carbon footprint which amounts to perhaps one-third of global emissions.

So here we have in one compact policy discussion a clear nexus of resource, environmental protection, and hazard policies.

Mr. Hertsgaard points out that the farm bill in question by no means takes such a holistic perspective.

Step back, and we find even greater dysfunction. “All the news that’s fit to print” focuses largely on the dreadful dust-ups in the Middle East over a preview of a film viewed as anti-Islamic – the rioting and the terrorist actions and killing occurring under cover of those riots. These horrors have completely overshadowed what farmers had hoped would be yesterday’s paramount concern.

And some in this country has seized on those tragic events to seek political advantage.

As a society, we’re some ways from matching the rigor of meteorologists, and solving all our problems simultaneously. The political/social problems are far more daunting than those pesky Navier-Stokes equations that do the accounting on Mr. Silver’s 100 tredecillion particles.

But nature is a stern taskmaster, accepting nothing less.

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After a bit of reflection…a postscript. Before we weathermen go too far down the road congratulating ourselves, and patting ourselves on the back for either our predictive skills or our humility, we might do well to reflect on how we’re coming with our predictions of climate change… and our discussions on it.

Just thinking holistically.

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