Advancing data-driven extreme weather forecasting
Our Mission
We combine advanced machine learning with atmospheric science to revolutionize extreme weather prediction, helping communities prepare for and respond to severe weather events.
The increasing frequency and severity of natural catastrophes demands a new approach to weather forecasting. Our research focuses on developing cutting-edge prediction models that can help save lives and protect infrastructure.
Learn More About Our ApproachAnnual cost of natural catastrophes in the EU (2021-2023), more than doubling from €17.8bn per year in the previous decade
Total economic losses from natural catastrophes in the EU over the past 42 years, with only one-quarter of these losses insured
Global insurance losses from natural catastrophes in 2023 (Swiss Re estimate)
Featured Research & Academic Partnerships
Collaborating with leading institutions to advance the science of extreme weather prediction
Bogazici University
Prof. Eyuphan Koc
Extreme weather prediction for reducing carbon emissions in the supply chain
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Stanford University
Prof. Omer Karaduman
Extreme weather events and their impact on the wholesale electricity markets driven by renewable energy sources
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Investigator
Murat Uzun
Flood forecasting in central Europe and Turkey. Previously worked on earthquake prediction at MIT using deep learning.
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Open Source Platform
We are on a mission to create the most advanced open extreme weather forecasting infrastructure that is built using the best of both physics and AI models. To achieve this, we are developing state-of-the-art simulation infrastructure from the ground up.
Secondlaw Research provides open interfaces for customization and extension. Our APIs can be used to integrate weather predictions into any system, and our open data formats ensure compatibility across different platforms and tools. As an open system, our platform is designed to evolve with the rapidly advancing fields of machine learning and atmospheric science.