Michael Bond at NewScientist (14 March 2015) reports (paywall) on the numerical models used by the UK Meteorology Office via an interview with head of the Numerical Methods division, Ken Mylne. I found this part of the Q&A interesting for reasons having nothing to do with the weather:
From 2011, the Met Office started presenting rain forecasts using probabilities. Was that controversial?
We’d been debating it for a long time. The Americans have been putting out probability of precipitation forecasts for many years, and it’s quite accepted there. The argument in favour is that often you cannot – for good scientific reasons – say definitely that it will or will not be raining. So you are giving people much better information if you tell them the probability of rainfall. While we recognise that some people find probabilities difficult to understand, lots of people do understand them and make better decisions as a result.
I’m located in Minnesota and have been for a long time, and I cannot remember when the local weather stations did not offer probabilities of precipitation in their forecasts. Mr. Mylne suggests that a portion of the population may not understand probabilities, and therefore they had not offered those estimates in the interests of not confusing the audience.
My thought is this: if your expectations of an audience is low, that’s where they’ll perform. If you want to see improvement, expectations must be set higher. Any teacher, I’m sure, will tell you that. Statistics and probability can certainly become frustrating subjects once you get beyond the basics, but basics is really all we present for the weather forecasts – so present it and let the audience know they can learn the basics if they are interested.
Nowadays, you can get in as deep as you like in any subject, as the Web lets experts freely share their knowledge with anyone. Ever wonder why? They often have problems of their own that they hope someone else may have an answer.
