We advance climate modeling through artificial intelligence and decades of NASA satellite observations. Our researchers develop and refine sophisticated Earth system models that simulate vegetation dynamics, fire behavior, cloud formation, and atmospheric chemistry – addressing the most significant uncertainties in climate projection.
Beyond modeling climate processes, we characterize the broad impacts of emissions trajectories, with particular emphasis on near-term pathways designed to reduce multiple environmental damages. Our researchers evaluate the effects of the full suite of climate-altering pollutants—from greenhouse gases to aerosols—emitted by specific activities and how these might change under different policies. This work extends beyond global temperature to assess simultaneous responses in regional temperatures, precipitation patterns, and air quality, including quantifying benefits to human and ecosystem health from improved air quality.
Our work includes BiomeE, a next-generation vegetation model that predicts ecosystem responses to climate change across scales from individual plants to global biomes. We've developed pyrE, an interactive fire model that captures the complex feedbacks between wildfires, climate, and human activity. Using machine learning, we tackle critical challenges in cloud physics—one of the largest sources of uncertainty in climate sensitivity estimates.
This research extends beyond Earth. Working with NASA GISS, we apply comparative planetology approaches to exoplanetary environments, using Earth system understanding to interpret observations of distant worlds and, in turn, gaining insights into Earth's climate dynamics.
Our models contribute to IPCC assessments and inform climate projection frameworks used globally. By validating against satellite observations and integrating AI-driven analysis, we accelerate the pace of climate discovery and improve the reliability of long-term projections.
