Science & Technology
Using data science to understand global climate systems
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. (Image credit / NASA)
Climate scientists at the University of Rochester are using data science to understand what drives global climate systems — from deep in the ocean to high in the sky.
Tom Weber, who studies marine ecosystems, and Lee Murray, who studies atmospheric chemistry, both joined the Department of Earth and Environmental Science as assistant professors this academic year.
Earth science and computer science have been closely intertwined since the development of modern computers. Murray notes that modern computers were developed during World War II with three primary motivations: codebreaking, ballistics calculations, and weather forecasting.
“Weather models were the earliest atmospheric models that existed and helped birth the modern digital computer,” he says.
These models have been pushing the limits of technology ever since.
“Originally, much of science was data limited,” Murray says. “We had relatively few data points, and it’s quite fascinating how some of the most brilliant minds of the last century were able to extrapolate from these limited observations. Now we tend to have the opposite problem: we are awash with data from observations and models, and our job as scientists is to extract signal from the noise.”
In addition to their individual research, Murray and Weber will be collaborating on a joint project funded by NASA, in which they will use models and satellite data to explore the global methane cycle and exchange of methane between the atmosphere and ocean and freshwater lakes.
Lee Murray
Assistant professor of earth and environmental sciences
Atmospheric Chemistry and Climate Modeling Group
Last month the World Health Organization released a statement citing air pollution as the leading cause of preventable death in children world-wide; understanding the roles of natural and man-made contributions to air quality in the past and the future is increasingly relevant, says Lee Murray.
Murray develops computer models of the dynamics and composition of the atmosphere, which he compares to NASA satellite data and other surface observations from around the world. He uses high-performance computing (HPC) systems, including the University’s BlueHive cluster, to simulate and predict how air pollution and the climate systems influence each other.
His recent focus has been on understanding atmospheric methane. Methane is both a major precursor for photochemical smog pollution and a powerful greenhouse gas. Historically unregulated, atmospheric methane levels have almost tripled since the Industrial Revolution.
In 2015 New York State committed to 40 percent reductions in its greenhouse gas emissions by 2030 relative to 1990 in its Reforming the Energy Vision (REV) goals, which may target methane reductions from in-state sources.
“A prerequisite for an effective regulatory control is to understand our current source types, totals and distribution, which remain uncertain,” Murray says. “We are in the process of developing an in-state surface monitoring network and modeling framework to relate observed methane to its emission location and type, to aide New York in meeting its greenhouse reduction goals.”
Tom Weber
Assistant professor of earth and environmental sciences
Biogeochemical Oceanography and Climate Modeling Group
What do microscopic phytoplankton in the ocean have to do with climate change and climate systems?
Plenty, according to Tom Weber, who studies the role of the small plants in the ocean carbon cycle as part of an effort to understand global climate systems and the response to perturbations.
“That’s what really sparked my interest in this field: these tiny plants in the ocean can plunge the Earth in and out of huge climatic changes,” Weber says.
Weber uses large data sets collected at sea and by NASA satellite sensors to create numerical models to understand the interactions between marine ecosystems, elemental cycles, and the climate—and the effects of perturbations to that system. He specifically studies the suite of processes that transfers carbon from the atmosphere to the deep ocean, where it is sequestered out of contact with the atmosphere.
Phytoplankton pull carbon from the atmosphere into their biomass through photosynthesis, and pack the carbon into organic particles. These carbon-rich particles eventually sink from the surface ocean and are broken down by bacteria, releasing carbon dioxide. One of Weber’s recent projects includes modeling how deep the carbon sinks before it breaks down.
“That matters because if it breaks down in the shallow ocean, approximately 100 to 1,000 meters, it is circulated back to the surface and into the atmosphere on short time scales,” he says. “If the carbon reaches all the way into the deep ocean, then it’s stored down there for much longer time scales.”