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Using data to better understand climate change

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Researchers' global water monitoring system detected meandering of the Ucayali River in South America. Adjacent occurrence of water gain regions (red dots) and water loss regions (green dots) all along the river indicate the displacement of water from the green dots to the red dots.

Credit: Understanding Climate Change Expedition


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Building a catalog of global ocean dynamics using a parameter-free, spatio-temporal pattern mining model. Discrete features (shown in red) identified by the research team's model. (Figure adapted from Faghmous, James H., Ivy Frenger, Yuanshun Yao, Robert Warmka, Aron Lindell and Vipin Kumar. "A daily global mesoscale ocean eddy dataset from satellite altimetry." Scientific Data, Nature Publishing Group, 2015.)

Credit: Understanding Climate Change Expedition


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expeditions

Understanding Climate Change: A Data Driven Approach, funded through the National Science Foundation's Expeditions in Computing program, is developing novel computational and data science methods for advancing our understanding of global climate change.

Credit: Geneva Hill


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The researchers' global water monitoring system detected the expansion of lakes in Tibet due to melting glaciers. Red dots represent glacial lakes that have expanded in size since 2000. A zoomed-in view of two regions (shown in yellow) show the gain in the water extent of glacial lakes (in red). The aggregate dynamics in the surface area of all glacial lakes in Tibet for the last 15 years is shown in the time series in the bottom left.

Credit: Understanding Climate Change Expedition


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