AI4ClimateRRR

We are a research cluster supported by the Ken Kennedy Institute at Rice University.

AI4ClimateRRR group photo, 2024-09-25

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Yanmo Weng is a postdoctoral fellow and the cluster coordinator.

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Monthly research discussions, open to the Rice community, will be held September 25, October 23, and November 20 at 12:00 noon. For additional information, please contact James or Yanmo.

Climate change is intensifying extreme weather events, posing unprecedented risks to urban infrastructure and communities. Managing these risks requires predictive understanding of both natural hazards and the response of human systems. While traditional hazard models shed light on many quesitons, they are often subject to sever limitations in resolution, computational efficiency, or geographic transferability.

Our research cluster integrates artificial intelligence and machine learning with physics-based models to advance understanding of climate risks and enhance infrastructure resilience. We are working to develop open-source, computationally efficient, and high-resolution models to inform the management of complex, interconnected systems facing extreme weather in a changing climate. Key focus areas include:

  1. Synthetic Hazard Generation: Creating large datasets of synthetic weather patterns and employing AI for high-resolution downscaling to urban scales.
  2. Infrastructure Systems Response: Characterizing hazard impacts on critical systems using AI- and optimization-enhanced approaches.
  3. Multiscale Earth Observation and Data Assimilation: Leveraging heterogeneous datasets from diverse sources to improve model performance and enable real-time initialization.
  4. Trustworthiness and Validation: Advancing the transparency and reliability of physics-informed AI methods through rigorous evaluation.

Our initial pilot project focuses on real-time flood forecasting and transportation accessibility in the Houston, TX region.

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