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Studying Complexity with Regional Climate Modeling

As a Peace Corps volunteer some 20 years ago, Nathan Moore frequently used discovery-learning techniques – pattern detection, simulations and other methods of integrated problem solving – to help his secondary school students practice the basics of the scientific method. Now the assistant professor of Geography uses the big data capabilities of Michigan State University’s Institute for Cyber-Enabled Research (iCER) to probe the intricacies of land surface processes and their impacts on atmospheric dynamics.

Moore’s research interests lie within regional climate modeling and climate variability; measuring and modeling impacts of human activity on the hydrologic cycle and surface-atmosphere interactions; and regional and global land use/land cover change.

“As a scientist I have focused on examining land-atmosphere interactions, beginning with a study of the effects of irrigation on enhancing rainfall in the Texas Plains,” Moore says, “More recently I have studied the effects of land use change on East African climate using innovative interdisciplinary techniques for incorporating/refining socioeconomic data in the atmospheric model.”

He is also engaged in a NASA-funded project for Amazon basin research that examines the socioeconomic impacts on land cover and its consequent effects on rainfall, where he is attempting to determine the range of uncertainty in precipitation associated with Amazon deforestation rates.

– from the Michigan State University Institute for Cyber-Enabled Research

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