The research at U.P.S. is paying off. Last year, it cut 28 million miles from truck routes — saving roughly three million gallons of fuel — in good part by mapping routes that minimize left turns.
Incredible – something that seems obvious in retrospect, but in practice hard to implement. Interestingly, it wouldn’t work in the UK, since you have to stop at red lights whichever direction you’re turning.
Also, a couple of good passages from the book on weather I’m reading:
When sunlight hits the atmosphere, the light waves are scattered in different directions by dust particles and air molecules. The shorter violet and blue waves are scattered more effectively than the orange and red ones. The effect is similar to what happens when ripples in water encounter a swimmer: small ripples are deflected while large waves continue past the obstacle undisturbed.
A mixture of violet, blue, green, and tiny amounts of the other colours is scattered across the sky. The combination of these colours is blue. The exact shade of blue will vary according to the amount of dust and water vapour in the air. Water droplets and dust particles enhance scattering, increasing the amount of green and yellow and turning the sky a paler blue.
This is why the summer skies of densely populated European countries seem paler than those of vast, sparsely populated areas such as Australia and Africa.
This is one of the clearest, most concise explanations of ‘why is the sky blue’ that I’ve seen yet. Not only does it explain the science in full, not only does it give a very visual and accurate analogy with the swimmer, but it also explores the consequences of the explanation in a way that will be immediately familiar. This is in stark contrast to the ‘explanation’ proffered by the Guardian, ‘A daytime sky is blue because molecules in the air scatter blue light from the sun more than they scatter red light,’ which explains nothing.
Meteorologists distinguish between skill and no-skill forecasting methods. If we consider rainfall prediction, two basic no-skill methods appear to give impressive results. The first is the persistence method, which is simply forecasting tomorrow’s rain to be the same as today’s. In middle latitudes, this typically gives results of about 70% accuracy, but of course fails to predict changes.
The other no-skill method, the climatological method, uses long-term averages. If, for example, the statistics for a particular location show that during January there is an average of 10 rainy days, then we would forecast rain every third day. Our forecasting accuracy would again be about 70% for many middle-latitude locations.
These methods take no account of the actual weather. For a forecasting technique to demonstrate skill, it must be more accurate than these no-skill approaches.
For some reason, it pleases me to know that you can reach a 70% accuracy in weather forecast simply by saying ‘tomorrow is going to be the same as today’. It makes me understand how priests and shamans could get away with their predictions.