£1.2bn to create ‘world’s most advanced’ supecomputer dedicated to weather and climate 

A £1.2bn government supercomputer investment will enable weather forecasters to provide a much greater degree of local accuracy.

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.

Business and Energy Secretary and COP26 President Alok Sharma said: “Over the last 30 years, new technologies have meant more accurate weather forecasting, with storms being predicted up to 5 days in advance. “Come rain or shine, our significant investment for a new supercomputer will further speed up weather predictions, helping people be more prepared for weather disruption from planning travel journeys to deploying flood defences. “The new supercomputer will also strengthen the UK’s supercomputing and data technology capabilities, driving forward innovation and growing world-class skills across supercomputing, data science, machine learning and artificial intelligence.” Professor Penny Endersby, Met Office Chief Executive said: “This investment will ultimately provide earlier more accurate warning of severe weather, the information needed to build a more resilient world in a changing climate and help support the transition to a low carbon economy across the UK. “It will help the UK to continue to lead the field in weather and climate science and services, working collaboratively to ensure that the benefits of our work help government, the public and industry make better decisions to stay safe and thrive.” Chair of the Science Review Group Professor Ted Shepherd said: “The agreement to upgrade the Met Office high performance computer is welcome news. The improved processing power will deliver a step-change in weather forecasting and climate modelling capability for the UK, such as the further development of the Earth Systems Model, which involves collaboration with the many UKRI-NERC funded research centres. “Improved daily to seasonal forecasts and longer-term climate projections will equip society with a greater ability to proactively protect itself against the adverse impacts of climate change.” Currently, the Met Office’s 14 computers are all housed in the UK although overseas options are being explored in order to reduce carbon energy dependency.