From reducing emissions to surviving their consequences, the globe’s power blocs are each racing ahead with their own research and deployment. Adaptation has become the new watchword. Success depends on the capacity to anticipate and withstand an increasing number of weather disasters. There are big political, diplomatic, and commercial implications.
States that control high-resolution models, satellite networks, and secure computing can move resources before disaster hits, calm markets, and negotiate from a position of strength. The UN’s Early Warnings for All initiative (EW4All) aims for universal coverage by 2027, yet half the world still lacks dependable weather forecasting. In practice, the ability to see danger coming depends as much on geopolitics as on geography.
Europe is determined to achieve weather prediction “sovereignty.” The EU’s Destination Earth program, developed with the European Centre for Medium-Range Weather Forecasts and the European Space Agency, runs on EuroHPC supercomputers such as LUMI, powered by Finnish hydropower and recycling waste heat for district heating. It simulates weather pathways within a kilometer’s accuracy, allowing governments to model flood and other risks.
The US combines open data with private computing. NOAA and NASA supply global observations, while the Department of Energy integrates artificial intelligence and exascale systems into grid and climate models. NVIDIA’s Earth-2 platform accelerates forecasts through generative diffusion models, and NASA–USAID’s SERVIR program delivers geospatial AI tools supporting adaptation across Africa, Asia, and Latin America. When coordinated, this mix of openness, computing power, and partnership turns technical advantage into political leverage, though recent funding cuts to early-warning programs have exposed its fragility.
China has built its own architecture of climate intelligence. The China Meteorological Administration operates the FENGYUN network linking satellites, sensors, and supercomputers, and exports this infrastructure and training through the Belt and Road Space Information Corridor to more than thirty African states. Each forecast shared through these channels deepens both dependency and diplomatic reach.
Satellites form the spine of global early warning, from Europe’s Meteosat Third Generation and America’s GOES-R to Japan’s Himawari-9 and China’s latest orbital systems. Networks of Doppler radar, river gauges, and ocean buoys add vital lead time when paired with machine learning. Bangladesh’s system has sharply reduced cyclone deaths, while similar integrations now enhance hurricane forecasts in the Caribbean and strengthen disaster response across the Global South.
No single actor leads this race outright. The US dominates the hardware and cloud platforms that make AI forecasting possible, from NVIDIA’s GPUs to DoE supercomputers, even though it lags on domestic deployment. Europe holds the edge in trusted governance and transparent standards through Destination Earth and Copernicus. China advances fastest in exporting its systems abroad, turning climate services into foreign influence from Southeast Asia to Africa.
Global coverage remains uneven. The World Bank notes that investment in early-warning infrastructure still lags far behind demand. In fragile states, the last mile between data and people often depends on NGOs or community radio. The US and EU both support capacity building through shared satellite data and training programs, but their efforts remain fragmented. NATO’s Climate and Security Impact Assessment calls for integrating climate and disaster intelligence into planning, yet civilian and military systems still operate on incompatible standards.
The US and Europe are aligned in purpose yet rarely integrated in architecture. They share satellite data and research, but they are building parallel AI systems that are not guaranteed to work seamlessly together in a crisis. They cooperate in science, compete in infrastructure, and hesitate in governance.
The absence of universal standards adds to the challenge. Without common thresholds, warnings that cross borders risk confusion and mistrust. The World Meteorological Organization’s WIS 2.0 platform seeks to harmonize global data exchange, while the EU’s Copernicus system continues to promote open access to Sentinel satellite data and training partnerships with countries such as India.
Behind these systems lies an infrastructure race. Forecasting and digital twins depend on advanced chips and cloud computing, largely dominated by American companies. The convergence of data, energy, and prediction is giving rise to what Bloomberg calls the “disaster industrial complex,” a sector where climate prediction, insurance, and reconstruction already shape more than a fifth of the US economy.
Capability brings risks. Sweden’s SIPRI warns that opaque or biased AI models could support coercive policies or mislead vulnerable states. The OECD highlights similar accountability gaps. The EU’s AI Act introduces binding rules for high-risk systems linked to critical infrastructure and safety, a category that implicitly extends to advanced climate and early weather warning applications. Without shared standards for validation and transparency, rival models could issue contradictory forecasts during disasters and turn information into a weapon of confusion.
If the US and Europe want to lead, they must take three practical steps. First, they should align their AI forecasting models through shared testing and validation so that warnings crossing borders come with a single trusted signal. Second, they should extend early warning coverage in the Global South through low-cost delivery networks that translate forecasts into instructions that communities can act upon. Third, they should develop governance rules that ensure climate AI remains explainable, secure, and accountable during disasters when trust is fragile.
AI cannot master the climate, but it can help determine who sees change first and acts fastest. Power will rest with those who can foresee disruption and guide the response.
Maciej Filip Bukowski is the Head of the Energy and Resilience Program at the Casimir Pulaski Foundation in Warsaw and a non-resident fellow with the Center for European Policy Analysis (CEPA).
Bandwidth is CEPA’s online journal dedicated to advancing transatlantic cooperation on tech policy. All opinions expressed on Bandwidth are those of the author alone and may not represent those of the institutions they represent or the Center for European Policy Analysis. CEPA maintains a strict intellectual independence policy across all its projects and publications.
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