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.
Although they are still in the initial research stages, she says she’s excited about the opportunity to apply her skills in a field beyond her declared major.
“I care about the environment a lot and I wanted to see how programming could be applied in other disciplines,” she says.
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.
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 system 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.”
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?
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 the global climate and its 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.”
Unlocking big data
The bacteria are sensitive to temperature and work more efficiently when it’s warmer. In a warming climate with warming ocean temperatures, bacteria break down carbon faster at shallower depths, and the carbon dioxide escapes back into the atmosphere instead of sinking deeper in the ocean.
He’s worried by what his evidence suggests.
“Humans are dumping way too much carbon dioxide into the atmosphere, warming the oceans, and perturbing the system much faster than natural variations ever have,” he says. “This is a problem given that humans and animals adapted to a particular climate system. If it changes over hundreds of thousands of years, they can adapt, but if things happen on much shorter time scales then there’s no time for ecosystems to adapt.”