Using data science to understand global climate systems

Climate scientists at the University of Rochester are using data science to understand what drives the global climate system—from deep in the ocean to high in the sky.

Tom Weber uses data from NASA satellite images,
 such as the image above. The color of the surface
 ocean reflects how much phytoplankton biomass
 there is, with the greener color indicating more
 chlorophyll and therefore more phytoplankton. 

Xiaoxuan Wang ’18, a computer science major, is working with earth and environmental sciences professor Tom Weber on a project that combines data science and environmental science to look at the daily concentration of chlorophyll—and therefore phytoplankton—in the Great Lakes from 2002 to 2016.

The project mirrors Weber’s work on ocean carbon cycles by using NASA satellite data. Freshwater and seawater reflect light differently, and generally algorithms to sort this data have been designed for ocean waters. However, Weber and Wang are working with new satellite data from the Great Lakes, which is, Weber says, “the first attempt to visualize plankton growths in the Great Lakes from space.”

Wang uses a computer application called MATLAB to process and organize the large satellite data sets.

Read the Science and Technology Research News story - “Using data science to understand global climate systems.”