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Using Data Science to Understand Global Climate Systems


A NASA satellite image.

University of Rochester professor Tom Weber uses large datasets compiled at sea and by satellite sensors to generate numerical models and understand how marine ecosystems, elemental cycles, and the climate interact, and how perturbations impact this system.

Credit: U.S. National Aeronautics and Space Administration

Researchers at the University of Rochester are using data science to understand the phenomena driving the global climate system.

Rochester professor Lee Murray builds computer models of the dynamics and composition of the atmosphere, which he compares to satellite data and other surface observations worldwide. Murray employs high-performance computing systems to model and predict how air pollution and the climate system influence each other.

Meanwhile, Rochester professor Tom Weber uses large datasets compiled at sea and by satellite sensors to generate numerical models and understand how marine ecosystems, elemental cycles, and the climate interact, and how perturbations impact this system. Weber is focused on the sequence of processes that transfers carbon from the atmosphere to the deep ocean.

Murray and Weber also will be collaborating on a joint project that uses computer models and satellite data to examine the global methane cycle.

From University of Rochester NewsCenter
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