At LLNL, electrical grid experts and climate scientists work together to bridge the gap between infrastructure and climate modeling. By taking weather variables such as wildfire, flooding, wind, and sunlight that directly impact the electrical grid into consideration, researchers can improve electrical grid model projections for a more stable future. In a new video, LLNL computer scientist Jean-Paul Watson and atmospheric physicist Philip Cameron-Smith explain how the Lab uses computer modeling and supercomputers to address the impacts of climate change and increase the resilience of the nation's infrastructure. Climate models inform electrical grid models, and machine learning algorithms trained on the former help researchers improve the latter. Watch on YouTube.
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