Guest essay by Eric Worrall
The UK MET is celebrating that their new £97 million computer can now create slightly better 12 month predictions than tossing a coin.
The Met Office has shown it can predict the weather one year in advance with its new £97 million supercomputer.
Scientists believe they can now forecast with some accuracy the North Atlantic Oscillation (NAO) weather phenomenon in the Atlantic Ocean which largely governs the British winter.
The phenomenon forms because of low-pressure over Iceland and high pressure over the Azores in the Atlantic.
A large pressure difference brings increased westerly winds, cool summers and mild, rainy winters. In contrast when the difference is small there are fewer winds and Britain shivers in a big freeze during the winter months.
It was previously thought that the NAO was a chaotic system which could not be predicted but the Met Office has used a technique called ‘hindcasting’ to check whether their new supercomputer could have predicted past winters.
After looking back at weather data going back to 1981, they discovered that they could largely predict what the winter weather would have done for the past 35 years, a year in advance, with 62 per cent accuracy.
The abstract of the study;
Skilful predictions of the winter North Atlantic Oscillation one year ahead
The winter North Atlantic Oscillation is the primary mode of atmospheric variability in the North Atlantic region and has a profound influence on European and North American winter climate. Until recently, seasonal variability of the North Atlantic Oscillation was thought to be largely driven by chaotic and inherently unpredictable processes. However, latest generation seasonal forecasting systems have demonstrated significant skill in predicting the North Atlantic Oscillation when initialized a month before the onset of winter. Here we extend skilful dynamical model predictions to more than a year ahead. The skill increases greatly with ensemble size due to a spuriously small signal-to-noise ratio in the model, and consequently larger ensembles are projected to further increase the skill in predicting the North Atlantic Oscillation. We identify two sources of skill for second-winter forecasts of the North Atlantic Oscillation: climate variability in the tropical Pacific region and predictable effects of solar forcing on the stratospheric polar vortex strength. We also identify model biases in Arctic sea ice that, if reduced, may further increase skill. Our results open possibilities for a range of new climate services, including for the transport, energy, water management and insurance sectors.
Read more (paywalled): http://www.nature.com/ngeo/journal/vaop/ncurrent/full/ngeo2824.html
It will be fascinating to see whether the new forecast system delivers. A lot of models which can hindcast successfully don’t survive contact with reality.
Imagine building a model for predicting lottery wins. With enough effort your model could be coerced into accurately hindcasting past lottery results. But it is very unlikely your lottery model would be able to predict future draws. Fitting a model to a limited data set is often not the same thing as accurately modelling the physics behind the data.