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Making climate models relevant for local decision-makers

A climate modeling downscaling method developed by MIT scientists leverages a machine-learning technique called adversarial learning to produce simulations faster and at finer resolutions, making them relevant to use on local levels for assessing risks of extreme weather.

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United-states
Bangladesh
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Boston
Massachusetts
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Colorado
Anamitra-saha
Department-of-earth
Planetary-sciences

Massachusetts Institute Of Technology Expert Named Head Of The Department Of Biological Engineering

Massachusetts Institute Of Technology Expert Named Head Of The Department Of Biological Engineering
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University-of-california-at-berkeley
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Anantha-chandrakasan
Christopher-voigt
Voigt-lab
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Asimov-inc
University-of-california-at-san-francisco

Christopher Voigt named head of the Department of Biological Engineering

International Project Aims to Build Community Resilience to Climate Change Effects

An international project to build community resilience to the effects of climate change, launched by Community Jameel and a research team at MIT, has been recognized as an innovation sprint at the 2023 summit of the United States' and United Arab Emirates' Agriculture Innovation Mission for Climate (AIM4C).

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Agricultural-research-corporation
United-state

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