The ocean has already absorbed 90% of the excess heat and nearly a quarter of the carbon from human greenhouse gas emissions, but this service has damaged marine ecosystems, coastal environments, and weather patterns that people depend on. This matters because the ocean is so vast and variable that scientists cannot fully observe or predict its response to multiple human-caused stressors. Current knowledge gaps include how natural and human-driven changes alter Atlantic ecosystems, how ocean-shelf-coast connectivity shapes biodiversity and natural hazards, and whether the ocean can continue to absorb excess heat and carbon. Without better understanding, societies cannot effectively adapt to or mitigate climate impacts. If AtlantiS succeeds, it will combine observations from new platforms and sensors with next-generation ocean models and digital tools. This could improve predictions of regional climate shifts, marine ecosystem health, and extreme weather events—information that underpins coastal infrastructure planning, fisheries management, and disaster preparedness. The programme also aims to provide clearer assessments for policymakers on climate mitigation strategies and their feedbacks. While much of this is fundamental science about how the ocean works, the resulting data and models will directly support a sustainable blue economy and safer communities.
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The global ocean is the largest part of the Earth's climate system and acts as a major buffer to climate changes resulting from human activities. By absorbing 90% of excess heat and nearly a quarter of carbon resulting from anthropogenic greenhouse gas emissions, the ocean has already substantially mitigated climate change in the atmosphere and on land. However this service has come at a cost to the health and resilience of the ocean and by extension the people who depend on it. Significant damage has been caused to biodiversity and productivity of marine ecosystems, to shelf seas and coastal environments, and to inland areas through extremes of weather. The futures of regional climate and ecological systems depend on the response of the ocean to multiple anthropogenic stressors. Understanding and predicting the response is fundamental for sustainable development and to guide adaptation and mitigation. The challenge is that the ocean is so large and variable that it cannot be completely and fully observed. Achieving adequate knowledge on all scales requires international coordination of observing and modelling over decades. It requires advancement in technology to expand our ability to observe beyond individual ships. It requires expanding the range of variables measured to include biogeochemistry and ecology. The opportunity now is to lead new capability to combine observations from a widening range of platforms and sensors, next-generation ocean and coupled models, and innovation in digital tools to meet the aspiration of healthy, biologically diverse and resilient marine environments, a sustainable blue economy and communities safe from natural hazards. AtlantiS addresses four interconnected priority knowledge gaps related to natural and anthropogenically driven changes in the global ocean and the Atlantic and its shelf seas, and their impacts on marine ecosystems and human society: i) how natural and anthropogenic drivers of basin and decadal changes alter the Atlantic ecosystem, and the consequences for ecosystem functioning and services; ii) the importance of ocean-shelf-coast connectivity in shaping ecosystems, biodiversity, natural hazards and impacts on society; iii) the implications and feedbacks associated with climate mitigation strategies, and the need for improved assessments and advice to policy makers; iv) the ability of the ocean to continue to mitigate climate change by absorbing excess heat and carbon. The research priorities give direction for underpinning activities that provide critical data, tools and technologies to drive scientific excellence across the UK marine science community. They include sustained ocean observing programmes, next generation models, digital innovation for data and information systems and observing system technology.
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