The Met Office Space Weather Operations Centre (MOSWOC) celebrates ten years of operations this week, looking back on a decade of forecasting potential impacts from the Sun.

Since becoming fully operational in 2014, MOSWOC has forecasted and monitored thousands of space weather events, helping key industries take steps to manage the risks posed by our dynamic Sun.

One of just a handful of 24/7 space weather forecasting centres in the world, MOSWOC is constantly monitoring the Sun for space weather activity, including solar flares, solar radiation storms, and coronal mass ejections which lead to geomagnetic storms here on Earth.

Since its creation, MOSWOC has issued over 1000 warnings for space weather, helping to provide satellite operators and other critical infrastructure providers with advanced notice so they can consider necessary actions to minimise any impacts on the public.

A new independent report released this week suggests that the Met Office’s space weather capability will be worth over £800million to the UK over the next decade.

In addition to operational forecasting, MOSWOC plays an active role in the international scientific community for the advancement of space weather sciences, helping to develop global monitoring and forecasting capability and advance scientific understanding.

Met Office Space Weather Manager Simon Machin said: “We’re proud to have been at the forefront of space weather forecasting over the last ten years.

“While many people will know about space weather from being responsible for the beautiful auroral displays we sometimes see, our forecasts have helped satellite operators and key infrastructure to mitigate impacts from severe space weather events and will continue to do so in the future.

“The next decade will encapsulate huge leaps forward for global space weather forecasting, with a number of projects set to enhance international capability, including the launch of the European Space Agency Vigil mission, which will provide a side-on view of the Sun to enhance forecast accuracy.”

Find out more about space weather forecasting at the Met Office.

Reporting on progress of the Met Office and Alan Turing Institute AI for Numerical Weather Prediction project. 

The UK’s weather is notoriously changeable, prompting everything from casual conversation amongst friends to vital decision-making by Government and industry that affects our lives and livelihoods.  

Behind the scenes, there is a paradigm shift underway in how we’ll get our daily dose of meteorological information. Artificial intelligence (AI), and more precisely machine learning (ML), is making significant strides in weather prediction, and the UK is at the forefront of this exciting development. 

A powerful partnership 

A key factor in this progress is the collaboration between the Met Office and the Alan Turing Institute which is helping maintain the UK’s position at the cutting-edge of weather prediction and deploying AI for public good.  

The benefits are mutual. Met Office experts have been able to provide crucial training in meteorology and the metrics used to evaluate weather models, while researchers from the Turing have shared their expertise in AI model design and optimisations for scaling-up on cloud platforms.  

This partnership has galvanised a new cross-disciplinary team and the exchange of knowledge and skills is accelerating innovation and driving forward the field of weather prediction. 

Progress report 

So, what have we achieved so far? It’s early days but the results are already promising.  

We have developed a machine learning model for weather prediction: “FastNet”, showcasing the potential of this technology to visualise complex weather patterns on a planetary scale.  

FastNet, and other AI models like it, represent the next step in the evolution of weather prediction, showing the UK’s commitment to embrace new technologies to remain at the cutting-edge of weather forecasting.  

We’re really pleased to see that for some metrics the FastNet model’s performance is comparable to that of the Met Office’s Global Numerical Weather Prediction (NWP) system, an international gold standard in weather forecasting 

This is a significant milestone, demonstrating that AI is not just a theoretical concept but a practical tool with the potential to match and even exceed the capabilities of traditional methods.   Drawing together AI and traditional physics-based models for weather prediction offers the chance to magnify the strengths of both approaches with models that are fast, accurate, explainable and trustworthy.

A frame from an animation comparing ERA5 (a reanalysis which uses a blend of observations and numerical weather prediction model to produce the best estimate of historical reality) with a prediction from the FastNet machine learning model.

Behind the scenes, a large-scale effort is underway to build a robust data infrastructure that can seamlessly integrate multiple data sources into the AI model. This may not be the most glamorous aspect of the project, but it’s a critical step laying the foundations for continued sustainable development and ensuring that the AI model has access to the most comprehensive and up-to-date information possible. 

The word FastNet will be familiar to many as one of the 31 sea areas covered by the Shipping Forecast: a nod to the Met Office’s founder, Vice-Admiral Robert FitzRoy, the first professional weather forecaster, who established the Shipping Forecast. 

The future of UK weather forecasting 

The ultimate goal of this collaboration is to operationalise the FastNet model so that the Met Office can use the optimal blend of physics-based and ML-based modelling for UK weather prediction. This means that AI could be used alongside physics-based models and play an important role in delivering the daily forecasts that we all rely on. We believe that using AI alongside physics-based numerical models provides the most robust way forward in a changing climate. 

The next few months should deliver some important advances in FastNet. Building on initial success with FastNet in global predictions, the partnership will next develop high-resolution regional forecasts for the UK using AI methods.  

By ingesting past UK weather forecasts into the FastNet training process, we will further train and refine it to produce detailed regional UK weather forecasts for potential operational use.  

For example, this will include: 

• The use of multi-resolution input data Traditional weather and climate models often operate close to the limits of the available computational resources, pushing supercomputers to the max, and so compromises need to be made: either reducing some of the complexity associated with the equations for physical processes, or by reducing the spatial and temporal resolution. Global weather models are designed to maximise spatial coverage, but some important small-scale physical processes may not be well represented, notably, convective processes and orographic processes (hills and mountains) that are nevertheless important drivers of localised, high-impact weather events. Limited-area models such as the Met Office’s UK weather model which uses a 1.5km grid is capable of resolving many of these important processes (see image below) but are too expensive to run over a larger area (for example, over the whole of Europe). AI models, such as FastNet now offer the possibility of combining the benefits of large-scale global NWP and high-resolution limited area models within the same model.  
• Representing uncertainty through the use of ensembles  
  The Met Office aims to migrate weather forecasts to ensemble mode, where multiple possible future realities are produced to create an ensemble of outcomes that allows us to assess the range of impending weather. AI is particularly attractive in this context as it offers the possibility of producing vast numbers of possible forecasts with relatively little computational cost – a potential major benefit of AI for weather forecasting. Together the Alan Turing Institute and Met Office will explore how we can produce rapid, cost effective and optimised ensemble weather forecasts. The ensemble produced needs to accurately represent the real weather by being skilful and reliable; so that when we say there is a 90% chance of rain, it really does rain 9 times in 10! 

Comparison of output from the Met Office’s Global Model (left) and UKV (right) for precipitation (top) and 10m wind speed (bottom) during Storm Kathleen on the 6 April 2024.
The high-resolution 1.5km grid-spacing used in the UKV model can capture high-intensity convective events (b) and the influence of small-scale topographic features including abrupt mountains and coastlines (b and d), whereas the model with the coarser grid (a and c) cannot thereby limiting its effectiveness to inform detailed mitigation plans for industries including wind generation and agriculture.

Looking to the future, we do not anticipate the need for well-established physics-based simulation approaches to end any time soon.  

Instead, we envisage the approaches running alongside and complementing one another maximising their combined strengths to provide accurate, fast, reliable, and trustworthy forecasts for the UK.  

For example, physics-based models provide the critical physical-process based insight needed to understand performance and build trust in weather prediction. They are also important when considering events that are outside the data that has been used to train AI models, and they provide the training data used to create AI models (new, recalibrated datasets will be needed as our climate changes).  

Complementing this, AI models are accurate, skilful and astonishingly fast (in some cases, tens of thousands of times faster than traditional methods). This speed delivers numerous benefits including more timely, accurate weather prediction at a significantly lower computation cost. 

A bright forecast 

The potential of AI in weather prediction is immense. By harnessing the power of data science and machine learning, we’re on the path to a future that draws together the strengths of both physics-based and data-driven modelling so that weather forecasts are faster, more accurate, detailed, and personalised than ever before.  

The collaboration between the Met Office and the Alan Turing Institute is paving the way for this future, one forecast at a time. 

As part of our August climate theme of climate anxiety, Emma Lawrance, Neil Jennings and Jessica Newberry Le Vay from Imperial College London have written this guest post on concerns around the psychological impact of working in climate science fields and on others in society alarmed by climate change. 

“Climate change can directly affect the emotional well-being of Earth [climate] scientists and professionals. Like the physical processes of climate change, the emotional effects are complex and multifaceted.”¹ 

The unfolding climate crisis necessitates a rapid transformation of our societies. In practice, this means every career should be a ‘climate career,’ with calls in the UK for climate education to appropriately prepare children for a changing world². It also means that the climate crisis should be the biggest on-going news story around.  

Climate scientists have made it their life’s work to understand and predict what rising concentrations of greenhouse gases in the atmosphere mean for the climate, and what impact it will have on people and the natural world on which societies depend. They are increasingly sounding the alarm that action on climate change is not happening fast enough, while witnessing the spread of misinformation, which can sow doubt and delay meaningful action. 

At the Climate Cares Centre at Imperial College London, we hear from climate experts on the psychological toll of this work and what it can mean for their mental health. What it takes to be faced with the facts of the crisis day after day. To see the gap between the need and pace of action. And to feel the backlash from talking about the result of carbon pollution publicly³ – from media commentators, social media trolls, and sometimes in their own personal relationships. Scientists speak of stress, anxiety, depression and burnout, all while facing a perceived need to separate their emotions from their work as a scientist^{4 5}. 

Widespread impacts on mental health 

While climate scientists may be particularly vulnerable to the psychological toll of climate awareness, the mental health consequences of the climate crisis are widespread. As well as the range of emotions and distress that climate awareness can understandably engender, the escalating consequences of a warming world – such as extreme weather, food and water insecurity, violence, forced migration – are leading to new cases of mental health challenges and worsening existing ones (such as post-traumatic stress, depression and suicide risk). Conversely, but vitally, climate actions can have win-wins for mental health, such as from cleaner air, greener cities, better housing, more equal societies, heathier ways to eat and move around, and stronger social bonds and communities. 

However, the negative consequences of climate change on mental health and wellbeing can reduce the capacity of individuals, communities and systems to be able to take climate action and achieve the necessary transformation of societies. We hear of students turning away from studying climate- and environment-related subjects or leaving climate-related careers because of a lack of support to manage the emotional and mental health impact. While there is a relative paucity of research on the topic, burnout and overwhelm among climate researchers and policymakers may hold back action and put the necessary goal of every career being a climate career at risk.  

Most people around the world care about climate change, more than they think others do, and want appropriate climate action from their leaders^{6 7}. It is vital for those with the knowledge – in science, media and policy – to raise the alarm and highlight the urgent need for action. But different narratives can lead to different responses. At opposite ends of the scale, techno-optimism and fatalism/doomerism⁸ are narratives that lead to present-day inaction. Both fail to acknowledge the uncertainties, nuances and complexities of the present and future, and how these make it both essential and valuable for us to act faster now.  Scientists must walk a tightrope of sounding the alarm, communicating the paths to different possible futures, and helping people hold the uncertainties in ways that still catalyse action. There is much to grieve and be angry about, and much to protect and work towards – a future where the climate crisis creates a reckoning of what we really value, fight for and want to have in abundance⁹. 

So how can those sounding the alarm and working to secure a liveable future be supported? 

In the words of the IPCC reports, resilience requires the capacity for transformation¹⁰. This requires all of us living in the climate crisis, and particularly those who are already experiencing its effects and/or are working to understand and respond to them, to be supported to build psychological resilience to sustain such efforts and thrive in a changing world. 

At the Climate Cares Centre, we have been working with scientists, journalists, policy experts, civil servants and students to support their mental health and wellbeing. We hear that their work has aspects that help their mental health – contributing meaningfully and connecting with others who care – and others that can cause harm – with slow progress and feelings that echo those we hear from the public, including powerlessness, hopelessness, frustration and anger. 

Some of the things that we have heard from people can help:

Decision-makers need to:

• Take visible and proportionate climate action to protect and promote good mental health and wellbeing. This can reduce distress from awareness of insufficient action, help create a vision of hope for the future, and mitigate mental health impacts of climate change.
• Invest in building psychological resilience and capacity for transformation and the ability of people to sustain work in climate-related careers and actions in healthy ways, such as by integrating mental health into climate change education¹¹.

Organisations need to:

• Create space for and normalise climate-related emotions and distress. Everyone will have their own psychological response that can vary over time. We heard from Met Office scientists that they found it helpful to hear “it’s ok to “feel”, and to feel multiple emotions together – it’s “possible to feel both hopeful and anxious about the future”.
• Provide opportunities for both individual and collective support within organisations e.g. ‘climate cafes’ for people to reflect and process emotional responses together, peer networks, and signposting people to resources and support.
• Divest from fossil fuels and provide clear sustainability leadership at an organisational level.
• Provide access to mental health support to ensure that psychological and mental health needs are adequately considered and supported.
• Consider how to communicate internally and externally about climate and mental health – e.g. considering the co-benefits of climate action for health.
• Provide clear institutional support and guidance for appropriate advocacy and activism efforts of staff.

Individuals can benefit from:

• Being reminded that the public cares a lot more about climate change than dominant political and media narratives can lead them to believe; “Other people care more than I think they do”; “Don’t give up. The fact that so many people are worried is a good thing and a driver for real change”; Met Office scientists in a workshop expressing what helped them.
• Being supported to connect with others (reflecting on emotions/experiences and taking action with colleagues, peer networks) and to spend time in nature and with loved ones.
• Support to feel comfortable engaging in advocacy and activism where they feel the need to do so.

Sources of support

Information on climate change and mental health

Supporting mental health

Sharing stories about climate change in responsible ways

Footnotes