Risky business: Coping with chaos in weather forecasts

 作者:殳焰劁     |      日期:2019-03-15 06:03:01
By Michael Bond How do you forecast the weather? We set up a model to represent the current state of the atmosphere based on many observations. From that, the model projects forward in time and calculates how the atmosphere may evolve. The outcome of the forecast is very sensitive to small errors in the initial state, so we run what we call an ensemble forecast. Instead of just running the model once, we make a series of small changes to the initial state and re-run the model a large number of times to get a set of forecasts. On some days the model runs may be similar, which gives us a high level of confidence in the forecast; on other days, the model runs can differ radically so we have to be more cautious. How certain can you be about forecasts? The level of confidence varies from day to day and from forecast to forecast. In some circumstances you can get big differences between the forecasts in the ensemble. The biggest uncertainties are often around big storms and the dramatic weather everyone cares about, because the atmosphere has to be in a sensitive, unstable state to generate that high-impact weather. The chaotic nature of the atmospheric system does impose fundamental limits on predictability. In terms of day-to-day weather, that limit is typically between 10 days and two weeks using probabilistic forecasts. “Often you cannot – for good scientific reasons – say definitely that it will or will not be raining” Can you give an example of how forecasting influences behaviour? In December 2013,