Investing in Observations: How Public-Private Partnerships and Weather Data Infrastructure Produces Economic Benefit

The WMO states that between 1970-2019, over sixty percent of economic losses due to weather-, climate- and water-related disasters were reported for developed economies. While these economic losses were equivalent to less than 0.1% of the gross domestic product (GDP) for most of the disasters, it still resulted in billions of dollars lost per decade. When there are losses, there are also opportunities and innovations. National meteorological services have begun to take a stronger leadership role in improving the economy and providing services that enhance forecasting, provide earlier warnings, safer societies, and utilize climate research for future planning.

The Met Office is advancing its leadership through investment and focus on their weather programs. An independent 2024 assessment by London Economics estimated the Met Office will deliver £56 billion in benefit to the UK economy over the next decade. This value depends entirely on the quality and breadth of weather intelligence and establishes that investment in observation infrastructure is not merely a technical choice but an economic one.   

The Met Office partnered with Synoptic Data, whose cloud-native Data-as-a-Service (DaaS) platform aggregates real-time surface observations from thousands of stations across diverse third-party networks in the UK, Ireland, and wider Europe. Synoptic handles data ingest, automated quality control, format standardization, and secure API-based dissemination — delivering a single, consistent, high-quality observation stream directly into Met Office operational systems, without the overhead of managing individual network relationships.

The Met Office continues to recognize the value of third party data, including citizen science observations, as a critical element of the observation infrastructure required for modern forecasting. Developments in artificial intelligence and machine learning are demonstrating their ability to digest large volumes of data and open up high resolution modeling of the urban environment — a region poorly sampled by traditional NMHS-owned networks.

This presentation will discuss the collaboration and DaaS approach, which represents a replicable, cost-effective framework for NMHSs seeking to expand observational coverage without proportional increases in coordination overhead. By framing observation data access as an enabler of economic value — not just a technical function — this partnership offers a model for how the global meteorological community can justify and scale investment in observation infrastructure.