Climate modeling
Site news
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Although climate models predicted Antarctic sea ice would steadily dwindle, its extent grew for decades until 2016. A new study finds the ice finally receded when wind-driven upwelling unleashed warmer, deeper water.
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New research traces a direct line from warmer, wetter weather to a mosquito-bornedisease epidemic. The findings could help inform policy and interventions to blunt such outbreaks.
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Ripples of air known as atmospheric gravity waves can influence the polar vortex, severe winter weather, and long-term climate patterns. Using AI and machine learning, researchers have developed a way to realistically represent their effects in global climate models.
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Scholars across campus are leveraging AI to drive remarkable advancements in fields from robotics to neuroscience to mining, while fostering a cautious approach to the application of the technology.
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Stanford researchers found increased meltwater and rain explain 60% of a decades-long mismatch between predicted and observed temperatures in the ocean around Antarctica.
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An expert in modeling global climate discusses how new data and new techniques are providing a clearer glimpse of our atmospheric future than ever before.
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Researchers at Stanford and Colorado State University used machine learning to determine how much global warming has influenced extreme weather events in the U.S. and elsewhere in recent years. Their approach could change how scientists study and predict the impact of climate change on extreme weather.
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At Stanford HAI’s recent fall conference, scholars showed how artificial intelligence is opening up new approaches to studying science.
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Artificial intelligence provides new evidence our planet will cross the global warming threshold of 1.5 degrees Celsius within 10 to 15 years. Even with low emissions, we could see 2 C of warming. But a future with less warming remains within reach.
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Stanford scientists are among a growing number of researchers harnessing artificial intelligence techniques to bring more realistic representations of ubiquitous atmospheric ripples into global climate models.
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A Stanford University study shows chaos reigns earlier in midlatitude weather models as temperatures rise. The result? Climate change could be shifting the limits of weather predictability and pushing reliable 10-day forecasts out of reach.
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A better understanding of how gravity waves in the upper atmosphere interact with the jet stream, polar vortex and other phenomena could be key to improved weather predictions and climate models.
