River forecaster Tom Pagano, late of Portland, Ore., and Australia, is on the road working on a book about river forecasting, so naturally he’s ended up in Thailand. In a post today, he talks about a language dilemma forecasters face:
A phrase like the “worst case scenario” is a double-edged sword. This is the kind of information that decision-makers crave and request from forecasters. But what is the chance of this worst case scenario happening? 1 in 3? 1 in 10? 1 in 100? History is filled with examples of where the actual outcome was above the worst case scenario and decisionmakers ended being very resentful of this. Of course, forecasters could instead conjure up a wildly high scenario (e.g. take the above map and multiply it by 3), but this leads to wasteful overplanning and its own form of resentment.
(Tom was one of the water-climate scientist characters in my book, The Tree Rings’ Tale, which you should head to your local bookstore to buy in time for that smart young person on your holiday shopping list.)
Excellent point. That’s why insurance is so useful. People will pay for coverage against the worst case but not the WORST case. No such discipline with politicians using other people’s money!
The definition problem is even worse than stated. A hundred year flood plain may be only separated from a normal heavy rain year by a few inches. Once you put in standard error, they are not different. So, for instance, insurance that requires protection against a hundred year flood may really lead to expensive upgrades that are seldom needed.
You have to define terms consistently, their error bars consistently, and the regulations about the terms consistently.
Just a few thoughts.