St Nicholas Weather uses OpenAI’s models to support data analysis, research, visualisation and website development. We see generative artificial intelligence (GenAI) as a useful tool for working with environmental data and developing the project, while recognising the importance of human oversight, verification and transparency.
Data analysis and visualisation
AI helps us explore weather and climate datasets, perform calculations, identify patterns and produce graphs and visualisations.
This allows us to investigate our growing archive of local observations and compare individual weather events across time. AI-generated analysis is not treated as evidence in itself: important findings are checked against the underlying data and, where appropriate, reliable external sources.
Research and reports
AI supports research into weather, climate and environmental topics, helping us find and understand information, investigate patterns in our observations and communicate the results.
For example, OpenAI’s GPT-5.6 Sol was used in the preparation of our Weather and Temperature Report 2021–2026. It supported data analysis, graph preparation, research, drafting and document production. The report remained under human editorial direction, with responsibility for the final analysis and published content remaining with the author.
Where external evidence is used, we aim to verify important information against appropriate sources, particularly the Met Office and other scientific and meteorological organisations.
Website development
AI has also become a useful development tool for St Nicholas Weather.
It assists with writing and debugging code, developing interactive features, integrating weather-data APIs, producing data visualisations and improving the design and functionality of the website.
AI has, for example, supported development of our live weather dashboard and the systems used to present station observations online.
Writing and communication
AI may be used to help organise information, improve explanations and make technical or statistical information easier to understand.
We do not automatically publish AI-generated material. St Nicholas Weather remains under human editorial control, and responsibility for what appears on the website remains with us.
AI does not generate our weather observations
AI helps us analyse and present our data; it is not the source of the data.
Measurements such as temperature, humidity, atmospheric pressure, wind, rainfall and solar radiation originate from weather-station instrumentation and associated data services. The underlying observations are independent of any generative AI system.
Human oversight and verification
Generative AI can make mistakes, misinterpret information or produce inaccurate information. Its output is therefore treated as something to evaluate rather than as an authoritative source.
Our approach emphasises human oversight, verification against original data and reliable sources, transparency about the use of AI, and acknowledgement of uncertainty and limitations.
AI, weather and climate
Our interest in AI extends beyond its use on this website. Artificial intelligence and machine learning are increasingly being applied to some of the wider challenges facing meteorology and climate science.
AI-based forecasting systems can learn patterns from enormous quantities of historical and current atmospheric data and produce forecasts extremely quickly. The European Centre for Medium-Range Weather Forecasts (ECMWF), for example, now operates its Artificial Intelligence Forecasting System (AIFS) alongside conventional physics-based numerical weather prediction. AI forecasting is increasingly being used to complement, rather than simply replace, established forecasting methods.
Potential applications include:
- Improving weather prediction by processing very large quantities of observations and model data and identifying complex atmospheric patterns.
- Improving forecasts of extreme and hazardous weather, potentially contributing to earlier and more useful warnings for events such as heavy rainfall, storms, flooding and extreme temperatures.
- Producing forecasts more efficiently, allowing large numbers of model simulations and ensemble forecasts to be generated much more rapidly.
- Improving climate modelling and analysis by helping researchers analyse complex Earth-system datasets, identify relationships and develop new modelling techniques.
- Supporting adaptation to climate change by turning increasingly large environmental datasets into information that can help communities and organisations understand changing risks.
- Supporting mitigation, including applications such as forecasting wind and solar resources, improving energy-system planning and helping climate-sensitive sectors make better-informed decisions.
AI is not a replacement for observations, physical science, conventional modelling or meteorological expertise. The World Meteorological Organization emphasises that AI should operate alongside these established systems and human expertise.
For St Nicholas Weather, this wider development is particularly interesting. Our project combines local environmental observations, digital technology, data analysis and communication. As our observational archive grows, we hope to explore how emerging AI tools can make that information more accessible, understandable and useful.
Ultimately, we see AI as another tool for helping people better understand, predict and respond to the environment around us.