Using data to help deal with ever-changing and unpredictable weather conditions

Storm Dennis flooding — (Image credit: Getty Images)

Britain might be in the middle of a heatwave, but cast your mind back a few weeks, and you’ll remember the rain.

In fact, Met Office estimates suggest 2026 has seen well-above-average rainfall, with some areas recording their wettest conditions in over 100 years during January and February, followed by a notably unsettled and wet spell across May and early June.

Such are the fluctuations in weather conditions that sudden rainfall can result in flooding, creating huge challenges for residents and public sector organizations. It’s into this fast-changing environment that an innovative project between Ordnance Survey (OS), Britain’s national mapping service, and technology specialist Snowflake aims to bring data-led clarity.

The two businesses have worked together to create an Intelligent Flood Readiness Model (IFRM), which has identified 1.2 million undefended buildings at risk of flooding in England, many in the most deprived parts of the country.

Harnessing the power of data-led insight

The initiative is opening eyes to data-powered opportunities, according to Tim Chilton, managing geospatial consultant at OS.

“We’re trying to create a broader conversation around the types of things technology can do across government,” he says.

“Several parties have come to us and said, ‘This is interesting, can we talk?’ What I'm trying to do on behalf of OS is to create those conversations and ask, ‘What could you achieve with our data and this kind of technology?’”

Chilton helps OS explore new commercial opportunities from its treasure troves of data. The organization started working with Snowflake in 2024. The organization uses the Snowflake Marketplace to share open data with public-sector organizations and explore commercial avenues. The priority now is ensuring OS embraces other data-led advances.

“We have a platform strategy, which is about putting our data where the customer works,” he says.

“The person who uses our data might work in geospatial, they might be a data scientist, and increasingly, as you'll find with the IFRM, they could be a businessperson who wants to ask a natural language query and be confident the results are correct.”

That approach resonates with Snowflake’s longer-term business strategy. At its recent Summit 2026 event in San Francisco, senior executives outlined the company’s plans to use agentic AI to open data access to IT and non-IT professionals. Chilton says the IFRM is an exemplar of the joined-up initiatives that will help organizations make the most of data in the age of AI.

“The model is about Snowflake and us talking about how AI can supercharge the timelines around having a problem and trying to solve it. Geospatial data really brings that data-led journey to life. A lot of government strategies are based around multi-year plans, but the climate is changing more frequently and regularly in more extreme ways than before,” he says.

“The question we asked was, ‘How could we use technology and bring in the latest data to check that those plans are still right for specific areas and even individual buildings?’ We hoped the model could help us keep on top of the issues and monitor and measure the impact of that plan on the ground.”

Finding the path forward

OS and Snowflake started the initiative in early 2026. After spending a couple of months working on the model, including ensuring the right data sets were being tapped, the organizations recognized that other sources could provide further depth, particularly the National Geographic Database. Chilton says the model will continue to be honed iteratively.

“If someone says, ‘Ah, but you didn't include this data that we've just released,’ we can say, ‘Good point, give us a week, and we'll give you some early results with your data included,’” he says.

“So, the model is a collaborative way of working, where we’re reacting to those changes in the model and the data that it uses.”

The model combines six data streams into a single layer. This layer produces key insights. For example, cross-referencing OS building datasets with the Indices of Deprivation in England identifies where physical vulnerability intersects with social risk. This insight is then layered against other information, such as Environment Agency flood and risk data.

Chilton says three key steps were crucial in the development of the model. First, project staff used the Snowflake CoCo agent to turn text-heavy documents, such as Flood Risk Management Plans, into data that the model could read in natural language.

Second, Snowflake’s semantic layer technology helped the model to understand, with guidance from OS experts, the meaning of attributes in the organization’s data sets. Finally, project staff used the Snowflake CoWork agent to create a natural language interface that allows anyone to ask questions about flood readiness.

“That capability was amazingly well received,” he says. “People can use the interface to query six well-organized and well-formatted data sets. The extraction of insights from documents, the semantic layer, and the CoWork frontend combined to create this powerful capability.”

The right data, in the right hands

"Data is at the heart of making informed decisions. As this project shows, it's rare that one body holds all the relevant data or that this data is in the same format,” says Fawad Qureshi, global field CTO at Snowflake.

“But we're now in an era where technology can bring together the right people and the right data to collaborate on making better-informed decisions."

By combining OS building data with information on flooding, social deprivation, and 3,000 pages of Flood Risk Management Plans, the model allows decision-makers to understand the potential impact of flooding in more detail than ever before. Chilton says these insights will help policymakers better understand the likelihood of flooding.

“There are already flood risk models; that idea is not new,” he says. “What is new is the ability to bring in much more granular data tied to flood risks. Not everyone in government was aware we had that level of detail. This initiative has provided an effective, practical application of some of our knowledge.”

Further work is planned in the wake of the model’s success. OS aims to make it easier for users to ask questions of data. The organization is exploring new technologies, including AI, to make data more accessible, enabling a wider range of users to unlock its value.

“We're actually ahead of the curve in comparison to many of our customers and our partners,” says Chilton.

“We're educating through doing and sharing demonstrators and great case studies like this model, and gradually you can see that cultural shift with people saying, ‘I get it, I know why there's a lot of fuss about AI and data, and we're going to give it a go.”

Other potential data sources include information from the Office for National Statistics, the British Geological Survey, and the National Underground Asset Register. In fact, OS aims to deliver an integrated approach to data within the next 12 months. Chilton returns to his key message for other digital leaders in the public sector considering AI projects.

“Give it a go,” he says. “I've seen the governance, security, data protection, and robustness of these tools. We've gone through the due diligence process, and Snowflake is a system that we trust to hold our data.”

Mark Samuels is a freelance writer specializing in business and technology. For the past two decades, he has produced extensive work on subjects such as the adoption of technology by C-suite executives.

At ITPro, Mark has provided long-form content on C-suite strategy, particularly relating to chief information officers (CIOs), as well as digital transformation case studies, and explainers on cloud computing architecture.

Mark has written for publications including Computing, The Guardian, ZDNet, TechRepublic, Times Higher Education, and CIONET.

Before his career in journalism, Mark achieved a BA in geography and MSc in World Space Economy at the University of Birmingham, as well as a PhD in economic geography at the University of Sheffield.