£1.2bn to create ‘world’s most advanced’ supecomputer dedicated to weather and climate
Kevin O'Sullivan, February 17, 2020 3 min read
The new programme of investment will help the Met Office provide forecasts down to the street-by-level over the next 10 years. Measures announced yesterday by the UK government are in response to Storms Ciara and Dennis, which have caused severe localised flooding. It is hoped over the next decade the Met Office’s data model of the Earth’s surface – called the ‘Digital Twin’ – will allow it much greater accuracy. To create this simulated picture, the world is divided into grid squares which allow a supercomputer to model the impact of weather. As technology has improved these squares have become smaller allowing for much more localised forecasting. At the moment the squares are 10km across, globally, with the UK’s more detailed at 1.5km. The investment should allow the Met Office’s model to improve to a degree of 100metre accuracy, meaning street level, which will facilitate a much faster environmental response to major weather events and to help mitigate the effects of climate change. Technology has enabled forecasters improve long range predictions with five-day forecasts now as accurate as a one-day forecast 40 years ago, equating to a day per decade improvement. Data from this new supercomputer – expected to be the world’s most advanced dedicated to weather and climate – will be used to help more accurately predict storms, select the most suitable locations for flood defences and predict changes to the global climate. The new supercomputer, to be managed by the Met Office, will also be used to help ensure communities can be better prepared for weather disruption, including through:
- More sophisticated rainfall predictions, helping the Environment Agency rapidly deploy mobile flood defences
- Better forecasting at airports so they can plan for potential disruption
- More detailed information for the energy sector to help them mitigate against potential energy blackouts and surges.