Scientists Pioneer New Methods In Climate Studies
Using sophisticated new methods of statistical analysis to study patterns of extreme rainfall in India, a handful of members of the National Science Foundation´s (NSF) Expeditions in Computing Program have created a research tool that has already resolved an ongoing debate in the science community and may go on to revolutionize the study of climate change.
Scheduled for official publication in February of next year, the journal Nature Climate Change pre-published the critical paper online on Dec. 19 conducted by engineer and computer-science expert Vipin Kumar of the University of Minnesota and his co-author Auroop Ganguly of the civil and environmental engineering department at Northeastern University in Boston and the Oak Ridge National Laboratory. Using new so-called ℠data-driven methods´, the two NSF members and their team have identified significant geographic variability in India℠s climate over the course of the last 50 years.
And what´s more, they say their methods can be easily adapted for use in studying other regions too.
“Rainfall extremes are rather difficult to characterize over space and time, particularly at regional or local scales,” explained the researchers.
“However, our current understanding of the geographical patterns of heavy rainfall and their changes over time guides water resources and flood hazards management as well as policy negotiations related to urbanization or emissions control.”
Both researchers believe that advances in the field of predictive climatology will become increasingly significant in coming years but noted that currently existing scientific tools are not yet up to the challenge of helping developing countries efficiently manage their resources and avert disasters.
“In vulnerable regions of the world where floods may claim many lives and water drives the economy or in emerging nations which may contribute significantly to the atmospheric inventory of greenhouse gases, major science advances are needed.”
The research team pointed to India as an example of the failure of the science community to help governments navigate nature´s apparent unpredictability.
“[In India] we find that top scientists and peer-reviewed publications do not agree on the nature of observed trends in heavy rainfall over the country [which] has led to scientific controversies and uncertainties about adaptation and mitigation strategies in a vulnerable yet rapidly growing region of the world.”
Yet the new technique pioneered by Kumar and Ganguly´s team could change all that, and some believe that the sophisticated, nuanced approach could be the future of climate change studies.
“This [“¦] study brings together interdisciplinary researchers from multiple institutions to pursue a bold, ambitious research agenda by building reliable predictive models from climate data that could potentially transform how we understand and respond to climate change,” said Vasant Honavar, chief of the NSF´s Division of Information and Intelligence Systems.
Image Caption: Understanding Climate Change: A Data Driven Approach, funded by the Expeditions in Computing program of the National Science Foundation, is developing novel computational and data science methods for advancing our understanding of global climate change. Credit: The artwork was designed by Geneva Hill
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