Weather: A theory to explain everything

Extremes of weather always seem to catch us unprepared. It may be that the cost of total preparedness would be prohibitive, but the statistics of bad weather also suggest a psychological explanation.

I have a theory that may explain everything. I may be wrong about this, but it seems to me that our reactions to everything - from hosepipe bans to the wrong type of snow, from flooding in Cornwall to the highest temperatures in 120 years in the Scottish highlands - all conform to the same psycho- statistical pattern.

We live, for the most part, in a neatly ordered world: a world of binomial distributions and bell curves where variable phenomena behave in a respectable way. We are used to meeting people of average height, average weight and average intelligence. And it doesn't matter much whether the average we are talking about is the mean, the mode or the median, because they all more of less coincide. We develop a feeling for what is the normal distribution, and anything within a couple of standard deviations from the mean does not take us unduly by surprise. We can even cope with well- behaved skew distributions such as, for example, the number of children people have. The mean is about two-and-a-half, the mode (the most common figure) is zero, and the median (the figure in the middle, if we arrange the sample in order) is probably one. But the distribution tails off quickly after about five children, and the number with a huge family - say more than a dozen - is very small indeed.

If you look at the daily temperatures or the hours of sunshine, or even wind-speeds during the month of November, you also get well-behaved statistics. Now look at the figures for daily rainfall at Heathrow in the table below:

In six of the past seven years for which we have complete data, there were 94 days with no rain, or only a trace of rain; 36 days with between 0 and 1mm of rain, 8 days with 1-2mm, then a gradual tailing off until we record only one day (out of 180) with 8-9mm. But it's the behaviour of the tail after that which is surprising. The wettest November days produced the following figures in millimetres of rain: 9.4, 10.1, 10.4, 13.4, 13.6, 14.8, 15.6, 16.7, 19.1, 19.9.

Those two days with more than 19mm of rain may be compared with suddenly meeting two men twelve feet tall with 30 children each.

Psychologically, such a badly behaved distribution is difficult enough to cope with, but economically it is an ever greater problem. If our drains can cope with anything up to 10mm of rain a day, that will cover 95 per cent of all November days (and November is as rainy a month as any). A small improvement in design might boost the capacity to 11 or 12mm, but that would only increase efficiency by 1 per cent - on our figures, only two days' flooding would be saved out of 180.

To cope with the full recorded range, including those two 19mm days, you would need almost to double the drains' capacity. It is more cost- effective to suffer the floods.