Insufficient Integrated Earth Climate Models
Current models struggle to accurately predict climate tipping points due to the intricate interplay of diverse climatic factors, hindering proactive intervention efforts. Additionally, designing optimal climate control strategies is challenging because of the nonlinear and multifaceted interactions among economic, technological, and social factors.
Foundational Capabilities (3)
Create more robust integrated assessment models that minimize ungrounded economic assumptions and better capture sensitive intervention points and amplification mechanisms in socioeconomic and political systems.
Build open, composable Earth System Simulation infrastructure based on high-resolution data. De-silo climate data across ESMs, IAMs, observational data to increase collaborative potential.
Traditional ESMs are built using legacy programming languages, which introduce a barrier for new entrants to the field and impede the usage of hybrid machine-learning techniques and modern computing architectures.
Collect high-resolution earth system data: Today’s global models and reanalyses are at tens of kilometers resolution. Build an open dataset of ultra-high-resolution simulations or merged observations (e.g. <1 km, resolving clouds, storms, and local topography). It could train AI to capture fine-scale processes (convection, urban heat islands, etc.) that current models miss.