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News Release 11-266

Journal Piece Reveals New Data-driven Methods for Understanding Climate Change

Geographical variability of rainfall extremes in India enhances interpretation of climate change data

Illustration of a 3-D column terminated by blue, green, yellow and gray pixels coming from a globe.

Understanding Climate Change: A Data Driven Approach is a NSF Expedition in Computing program.

December 18, 2011

This material is available primarily for archival purposes. Telephone numbers or other contact information may be out of date; please see current contact information at media contacts.

In February 2012, the journal Nature Climate Change will publish a paper on rainfall extremes in India by principal investigator Vipin Kumar of the University of Minnesota's computer science and engineering department and co-principal investigator Auroop Ganguly of the civil and environmental engineering department at Northeastern University in Boston, members of the National Science Foundation's (NSF) Expeditions project team.

Nature pre-published the paper online today. 

Based on new data-driven methods, or novel adaptations for understanding climate change developed by the Expeditions team, the paper identifies a steady and significant increase in geographical variability within India over the past half-century. The data-driven methods used, say the researchers, can be generalized not just to other regions beyond India, but to both observed and model-simulated climate data as well.

"Rainfall extremes are rather difficult to characterize over space and time, particularly at regional or local scales. 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," the researchers note in the paper. "Thus, 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."

"If we were to use India as a case study, we find that top scientists and peer-reviewed publications do not agree on the nature of observed trends in heavy rainfall over the country," they add. "This has led to scientific controversies and uncertainties about adaptation and mitigation strategies in a vulnerable yet rapidly growing region of the world."

"This Expeditions in Computing project 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," explains Vasant Honavar, NSF program manager in NSF's Division of Information and Intelligent Systems. "The Nature Climate Change piece provides a hint of how sophisticated data mining methods could help fill gaps in our understanding of climate change, and ultimately, produce actionable insights that can help minimize the negative effects of climate change on humans and the environment."

Read the university's full press release.


Media Contacts
Lisa-Joy Zgorski, NSF, (703) 292-8311,

Program Contacts
Vasant G Honavar, NSF, (703) 292-7129,
Vipin Kumar, University of Minnesota, (612) 625-0726,
Auroop Ganguly, Northeastern University, (617) 373-3710,

The National Science Foundation (NSF) is an independent federal agency that supports fundamental research and education across all fields of science and engineering. In fiscal year (FY) 2017, its budget is $7.5 billion. NSF funds reach all 50 states through grants to nearly 2,000 colleges, universities and other institutions. Each year, NSF receives more than 48,000 competitive proposals for funding and makes about 12,000 new funding awards.

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