Building Tomorrow’s Observing Infrastructure: Technology Trends Shaping the Future of Hydrometeorological Monitoring

As the global climate extremes intensify and hydrometeorological risks rise, scientific capacity to observe, understand and respond must increase. The ongoing effort to establish a 2050 Vision for the WMO Integrated Global Observing System (WIGOS)(*) anticipates a future where Earth system observations – both space- and surface-based – are more integrated, responsive and innovative than ever before. At the core of this transformation lies the infrastructure for hydrometeorological monitoring – an evolving system powered by technology, new partnerships and novel data generation methods. This article outlines the major infrastructure-related technological trends identified through the effort to establish the Vision for WIGOS in 2050 that are expected to influence the next 25 years, for consideration from a budgetary and organizational perspective going forward.

Diversified and distributed observing networks

The global surface-based observing infrastructure is undergoing a fundamental shift that will be characterized by a tiered, adaptive network model which incorporates high-accuracy reference stations, comprehensive backbone networks and emerging or opportunistic systems such as low-cost sensors, mobile platforms and community-contributed observations. Traditional instruments and national networks will remain foundational but will increasingly co-exist with distributed sensors in smart cities, remote regions and marine environments. The result will be a broader, more flexible observing system that reflects the diversity of users and applications it must serve. 

From miniaturization to mobility

Technological innovation is making it possible to deploy advanced sensors across new platforms and remote, previously inaccessible, environments. The miniaturization of weather sensors and their integration into drones and other vehicles and even in wearable devices, such as collars, on animals is transforming how and where data can be collected. Unmanned airborne systems (Figure 1) are emerging as alternatives to traditional radiosondes, offering reusable, lower cost, vertical profiling capabilities with greater range and less environmental impact than current technologies. In the ocean, the deployment of autonomous gliders, unmanned surface vessels and multirole buoys is enabling more persistent and fine-scale monitoring of oceanic and atmospheric conditions. These mobile and adaptive systems will provide critical data coverage in areas where traditional infrastructure is limited or impractical.

Automation and edge processing

Monitoring infrastructure will become increasingly intelligent and automated. The integration of edge computing into observing systems will allow for data processing at the point of collection, reducing latency and bandwidth needs. This will be particularly important in remote or extreme environments, where network access is intermittent. Self-calibrating sensors, powered by solar energy and designed for low maintenance, will improve the resilience and environmental sustainability of monitoring networks. These advances will make it possible to deploy and maintain high-density networks even in regions with limited infrastructure or human resources. 

Integration of surface and space-based systems 

True infrastructure transformation will be realized through integration. Surface and space-based observing systems will be designed and operated in tandem, optimizing coverage, accuracy and complementarity. Ground-based networks will play a key role in calibrating satellite sensors and providing critical vertical profile information. Supersites – sites with co-located instruments from multiple domains – will support the validation of satellite-derived products and algorithm development. This blended approach will enhance the value of both surface and space assets, especially for high-resolution modelling, data assimilation and early warning applications. 

Non-traditional observations join the mainstream

Non-traditional observations, such as those from the Internet of Things, citizen science projects and commercial platforms, are emerging as valuable contributors to global observing systems. Sensors embedded in vehicles, infrastructure and wearable devices will offer dense, hyper-local data that can complement official networks. Animal-borne sensors – under the concept of the Internet of Animals (see Movebank data video below) – are already providing ocean and atmospheric observations from under-sampled regions. Integrating these new data streams into national and international systems will require common data standards, quality assurance protocols and robust governance frameworks. However, their potential to expand observational reach and detail is significant.

Artificial intelligence as an infrastructure enabler

Artificial intelligence (AI) will play a foundational role in the future of hydrometeorological monitoring. AI will support automated quality control, anomaly detection, network optimization (design and management/maintenance) and data fusion. It will also enable the generation of gridded products from multiple data sources, enhancing spatial and temporal resolutions. In the future, AI-driven assistants may deliver tailored, real-time weather and climate insights to individuals, businesses and communities, powered by a seamless integration of surface and space observations. AI will also help address one of the biggest challenges facing future infrastructure: making sense of vastly larger and more complex volumes of data.

An inclusive and equitable global system

A central goal of future hydrometeorological observation systems will be to ensure equitable access to observational data and capabilities across all regions. Investment in monitoring infrastructure must prioritize polar, oceanic and ecologically sensitive zones, and other geographic areas with low observational capacity. Public-private partnerships, regional hubs and new funding mechanisms will be essential to close gaps in coverage and quality, enhance early warnings and improve climate resilience.

As we move toward 2050, hydrometeorological monitoring infrastructure must evolve to meet the needs of a rapidly changing planet, embracing opportunities to advance innovation, data integration and collaboration to build an observing system that is flexible, inclusive, and prepared for the future

 (*) The author wishes to acknowledge effort being made by the expert below in drafting the 2050 Vision for WIGOS under the WIGOS Vision Drafting group, established by the Standing Committee on Earth Observing Systems and Monitoring Networks of WMO Commission for Observation, Infrastructure and Information Systems:

• Stephan Bojinski (EUMETSAT), Mary-Jane Morongwa Bopape (South African Environmental Observation Network (NRF‑SAEON)), Niels Bormann (ECMWF), Sid Ahmed Boukabara (NASA), Sean Burn (EUMETSAT), GUO Jianxia (CMA), Shannon Kaya (ECCC), Agnes Lane (BoM), Anthony McNally (ECMWF), Rosemary Munro (EUMETSAT), Osamu Ochiai (JAXA), Mikael Rattenborg (EUMETSAT, retired), Paolo Ruti (EUMETSAT), Michael Seablom (NASA), Fiona Isobel Smith (BoM), Junhong (June) Wang (University at Albany, SUNY), Elian Augusto WOLFRAM (National Weather Service, Argentina), Lihang Zhou (NOAA)

Contributions are also made by invited speakers to various meetings, including: 

• Amy Chen (NASA), John Eyer (Met Office, retired), Melissa Martin (NASA), Diego Ellis Soto (University of California, Berkeley), Jonathan Taylor (Met Office)

Data from Movebank: The animation was created by Matthias Berger (www.schaeuffelhut-berger.de). The software is Java/OpenGL code written by Matthias Berger. Background imagery comes from Blue Marble—Next Generation, produced by Reto Stöckli, NASA Earth Observatory (NASA Goddard Space Flight Center). The ASTER Global 30-metre Digital Elevation Model was used for lighting calculations. ASTER GDEM is a product of METI and NASA.