MACHINE INTEGRATION AND LEARNING FOR EARTH SYSTEMS

The mission of the Machine Integration and Learning for Earth Systems (MILES) group is to integrate machine learning throughout community Earth System Science (ESS) modeling and observation pipelines in order to refine our understanding of the Earth System, improve the prediction of weather and climate phenomena and their associated impacts, and enhance the capabilities of community observation, modeling and computing facilities. This mission will be accomplished through

• Researching and developing cutting-edge machine learning approaches for challenges that strategically expand NCAR’s and the broader ESS community’s ability to observe and model the Earth System.
• Building and sustaining key partnerships with scientists and stakeholders throughout NCAR’s labs, the university community, government agencies, and private companies.
• Developing robust machine learning infrastructure and community benchmark evaluations and datasets that can interface with critical ESS modeling and observation systems.
• Educating and empowering a diverse group of ESS students, researchers, and stakeholders on how best to integrate machine learning into their domains through tutorials, workshops, internships, collaborations, and co-development.

CISL SPACEHOLDER

Partners SPACEHOLDER

AI2ES

LEAP