Climate
Climate

Climate

Artificial Intelligence Climate Climate change Computer modeling Data EAPS machine learning Natural disasters Policy Research School of Science Weather modeling

Making climate models relevant for local decision-makers

A new downscaling method leverages machine learning to speed up climate model simulations at finer resolutions, making them usable on local levels.

Algorithms Artificial Intelligence Climate Climate change Computer modeling Defense Advanced Research Projects Agency (DARPA) Disaster response Earth and atmospheric sciences Environment Fluid dynamics Hurricanes machine learning Mechanical engineering Natural disasters Planetary science Research School of Engineering Weather

MIT-derived algorithm helps forecast the frequency of extreme weather

The new approach “nudges” existing climate simulations closer to future reality.

Artificial Intelligence Climate Computer modeling Electrical Engineering & Computer Science (eecs) Energy Funding Grants Laboratory for Information and Decision Systems (LIDS) Lincoln Laboratory machine learning MIT Schwarzman College of Computing School of Engineering

Generative AI for smart grid modeling

MIT LIDS awarded funding from the Appalachian Regional Commission as part of a multi-state collaborative project to model and test new smart grid technologies for use in rural areas.

Algorithms Artificial Intelligence Cambridge, Boston and region Campus buildings and architecture Climate Climate change Emissions Energy efficiency Environment Facilities Heat Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing Research Sustainability

AI pilot programs look to reduce energy use and emissions on MIT campus

A cross-departmental team is leading efforts to utilize machine learning for increased efficiency in heating and cooling MIT’s buildings.

Agriculture Artificial Intelligence Carbon dioxide Civil and environmental engineering Climate Climate change Computer science and technology Faculty Food J-WAFS Lincoln Laboratory machine learning Plants Profile Research Satellites School of Engineering sensors Water

Detailed images from space offer clearer picture of drought effects on plants

J-WAFS researchers are using remote sensing observations to build high-resolution systems to monitor drought.