How Can AI Improve Early Warnings for Climate Risks?

In this video, MARKUS REICHSTEIN explores how artificial intelligence can improve early warning systems for climate-related hazards. Starting with a curiosity-driven approach to predicting landscapes from climate data, his research evolved into understanding how ecosystems respond to weather patterns and how these responses can be forecasted. Reichstein and his team analyze the full early warning chain - from observation to decision-making - and identify weak links, especially in impact forecasting and communication. Using AI, they aim to enhance localized predictions and generate intuitive warnings, such as visualizations of expected damage. The study supports the UN’s “Early Warnings for All” initiative and highlights the dual potential of AI to drive both fundamental research and real-world societal impact.

DOI:

https://doi.org/10.21036/LTPUB101197

Max Planck Institute for Biogeochemistry

The research is dedicated to the study of global biogeochemical cycles and their long-term interactions with the biosphere, the atmosphere, the geosphere and the entire climate system. We want to better understand how living organisms - including humans - exchange basic resources such as water, carbon, nitrogen and energy with their environment and how this affects global climate and ecosystems. Biogeochemistry is the science of the Earth's metabolism. Elements essential to life such as carbon, nitrogen, oxygen and phosphorus are constantly undergoing biological, chemical and physical transformations as they are exchanged between different parts of the Earth, the lithosphere, hydrosphere, biosphere and atmosphere. The "biogeochemical cycles" quantitatively describe the distribution and exchange of elements between these components of the Earth system.