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AI for Anticipatory Action: Moving Beyond Climate Forecasting

arXiv 2307.15727 ↗First posted 28 Jul 2023cs.LG cs.AI stat.APcited by 0

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Abstract (arXiv)

Disaster response agencies have been shifting from a paradigm of climate forecasting towards one of anticipatory action: assessing not just what the climate will be, but how it will impact specific populations, thereby enabling proactive response and resource allocation. Machine learning models are becoming exceptionally powerful at climate forecasting, but methodological gaps remain in terms of facilitating anticipatory action. Here we provide an overview of anticipatory action, review relevant applications of machine learning, identify common challenges, and highlight areas where machine learning can uniquely contribute to advancing disaster response for populations most vulnerable to climate change.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 20 of its 71 references that are in the map. First posted on arXiv 28 Jul 2023.

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20 of 71 references.

References · 20

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8 more
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