Extreme weather prediction and attribution science

Climate action is happening in the dark. We're making trillion-dollar decisions about energy systems, carbon markets, and climate adaptation based on incomplete, outdated, or simply wrong information.

Most of what we think we know about emissions comes from estimates and calculations, not actual measurements. We're guessing at how much carbon forests store, how fast cities are decarbonizing, and whether our climate projects are working. Meanwhile, climate impacts are accelerating faster than our models predicted, and we need precise, real-time data to respond effectively.

This isn't just an academic problem. Investors can't tell which climate projects deliver real results. Cities can't plan infrastructure without knowing their local climate risks. Companies can't manage what they can't measure. The gap between what we need to know and what we actually know is enormous — and it's slowing down everything else.

Global climate models are good at predicting planetary trends, but they struggle with the local details that matter for planning and adaptation. A city needs to know if it will face more flooding, longer droughts, or stronger storms — not just that the planet will be warmer.

This precision gap makes it nearly impossible to design effective adaptation strategies. Infrastructure investments, agricultural planning, and disaster preparedness all depend on understanding local climate risks, but current models often can't provide the detail needed for confident decision-making.

Specialized modeling systems that focus on predicting and understanding extreme weather events like heat waves, droughts, floods, and storms. These tools combine climate models with weather prediction systems to provide detailed forecasts of extreme events and their likelihood under different climate scenarios.

Extreme weather attribution science helps determine how climate change is affecting the frequency and intensity of specific events. This information is crucial for disaster preparedness, insurance planning, and understanding climate risks.