The conventional wisdom in meteorology has been that certain factors such as the complete oceanic state and the exact concentrations of greenhouse gases are of minor importance for a normal weather forecast. Moreover, whereas sea surface temperatures (SST) are important, the deep sea temperatures are believed to have little impact for predictions for the next few days. The reason is that the ocean reacts slowly to changes in the atmosphere (has much higher inertia and much higher heat capacity). Hence, the most important information needed for such a weather forecast is the atmospheric initial conditions, a description of what the atmosphere and the SST look like when the weather model starts computing the weather evolution.
If we want to make predictions over longer periods, such as the subsequent months, then the effects of boundary conditions become more important than the atmospheric initial conditions (due to internal chaos and the lack of predictability from the initial state). The oceans, which provide part of the boundary conditions for the atmosphere, also have sufficient time to change appreciably, and the change in the oceanic state must be taken into account. Such long forecasts are often referred to as seasonal forecasting. Seasonal forecasts are often made with coupled ocean-atmoaphere models (more like climate models), as opposed to atmosphere-only models for ordinary weather forecasts. Until now, it has been assumed that factors such as greenhouse gas concentrations play a minor role for the skill of the seasonal forecasts. However, a new study by Doblas-Reyes and co-authors at the European Centre for Medium-Range Weather Forecasts (ECMWF) – the ‘European weather centre’ – suggests that by updating the greenhouse conditions with the observed annual mean values, the skill of the seasonal forecasts improve noticeably.
The implications of these findings are quite subtle, but important: we are already feeling the climatic effects of rising greenhouse gas concentrations. These findings also open for more practical use of our knowlegde about climate change: by taking these trends (i.e. extra information) into account, we improve our ability to make predictions seasons ahead. This is also something that has been observed, e.g. in Norway, where the climatic trends result in more warm than cold seasons.
Doblas-Reyes, F.J., R. Hagedorn, T.N. Palmer and J.-J. Morcrette:
Impact of increasing greenhouse gas concentrations in seasonal ensemble forecasts.
ECMWF Tech. Mem. #476, October 2005