Early Warning Of Complex Climate Risk With Integrated Artificial Intelligence
Nature Communications
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Abstract: This peer-reviewed article discusses how integrated artificial intelligence (AI) can revolutionize early warning systems for complex climate risks. It critiques conventional systems? failure to predict multi-hazard events, and proposes AI-driven methodologies using meteorological and geospatial foundation models. The paper introduces causal reasoning, personalized alerts, inclusive design, and modular architectures based on FATES principles (Fairness, Accountability, Transparency, Ethics, Sustainability). Kenya features through the Red Cross and Horn of Africa case study, showcasing AI applications in drought anticipatory action. The article advances global standards for digital climate resilience and ethical forecast deployment.