Advances in artificial intelligence (AI) never cease to impress, and the weather is no exception. Recently, Google’s AI subsidiary DeepMind demonstrated that its weather forecasting system is more accurate than any other to date.
DeepMind: AI to improve the reliability of weather predictions
For the past few years, DeepMind has been working to develop an AI-powered tool capable of outperforming traditional weather forecasting models. Called GraphCast, this tool has proved its ability to anticipate with unprecedented accuracy the scale of the storms and hurricanes that have hit the Atlantic coasts in recent weeks.
However, DeepMind is not looking to completely replace traditional methods. Rather, the aim is to provide experts with an additional tool to refine their predictions and thus avoid as far as possible the dramatic consequences that unexpected weather can bring.
More reliable forecasts thanks to deep learning
The use of convolutional neural networks
This tool is based on deep learning algorithms, and more specifically on convolutional neural networks (CNN). These networks enable AI to processhuge volumes of data, making it particularly well-suited to improving the quality of weather forecasts. More specifically, this AI is able to take into account data emitted by :
- Weather satellites;
- Speed cameras;
- Ground stations;
- Marine buoys.
By exploiting these multiple sources, artificial intelligence can identify trends and patterns still invisible to the human eye, enabling it to considerably refine the reliability of weather predictions.
Machine learning to counter human error
Machine learning can also be used to correct any human errors in forecasts. Indeed, even if they have access to the same data as AI, meteorologists are faced with a complex task that requires them to take into account a large number of variables. So there’s always room for error. Thanks to its continuous learning process, AI can quickly detect these errors and adjust forecasts in real time to make them more reliable.
The benefits of better weather forecasting
An AI capable of pushing the limits of weather forecasting would have many advantages, including:
- Economy: to avoid as far as possible the negative impact of unexpected weather on agriculture, tourism and transport;
- Safety: anticipate dangerous climatic phenomena for the population and put in place appropriate protection systems;
- Environment: monitor long-term climate trends and adapt environmental policies accordingly.
With tools like GraphCast, we’re well on the way to gaining a better understanding of our environment and considerably improving our ability to anticipate weather fluctuations.
DeepMind’s artificial intelligence represents a quantum leap in weather forecasting. By exploiting deep learning and convolutional neural networks, we can considerably increase the reliability of our predictions. Whether it’s to support economic decision-making, protect populations from climatic hazards or monitor climate change, this AI paves the way for a safer, more controlled future in meteorology.
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