Paper in Nature Climate Change Highlighted by NSF
A paper led by Prof. Auroop Ganguly about geographical patterns in observed rainfall extremes over India has been published in the February 2012 issue of the journal Nature Climate Change and highlighted as a significant news item on the website of the National Science Foundation. The paper helps resolve a long-standing debate and develops an important new insight on the important issues related to weather extremes. First, no uniform trend was found in the extremes of Indian rainfall over the last half-century, which contradicts some of the previously published literature but supports a few others. Second, a steady and significant increasing trend was discovered in the geographical variability of rainfall extremes, or in the extent to which the extreme values differ from each other in space. When taken together, the findings have relevance for the management of water resources and flood hazards in India as well as for policy decisions related to urbanization, changes in land use, and emissions negotiations. Sophisticated statistical methods specifically designed to analyze extreme value patterns and associated uncertainties in space and time were used to obtain the insights. The research was led by Prof. Ganguly and funded by the National Science Foundation, the Oak Ridge National Laboratory (ORNL), and the Department of Science and Technology of the Government of India. Other authors include Subimal Ghosh from the Indian Institute of Technology Bombay, Shih-Chieh Kao from ORNL, Debasish Das from Temple University.
Source: News @ Northeastern
Auroop Ganguly, an associate professor of civil and environmental engineering at Northeastern University, studies climate change and extreme weather events — such as hurricanes, rainfall and heat waves — from an interdisciplinary perspective.
Expanding his research beyond the science of climate change and developing data-driven climate assessments, Ganguly focuses on how climate-related extreme events affect water sustainability, how communities adapt to and mitigate the effects of severe storms and floods and how government officials could use climate and weather research to make sound policy decisions.
Knowing whether melting Arctic Sea ice is opening up new navigable pathways for seafaring vessels has the potential to shape national security policies, Ganguly noted, discussing prior work he led for the U.S. Department of Defense. As he put it, “All these issues are interrelated.”
Ganguly, who joined Northeastern’s faculty in the fall, recently led a new study that explored extreme rainfall events during monsoons in India.
The research team found that the frequency or intensity of extreme rainfall events over the last 50 years has not increased on the average, but that there has been a steady and significant rise in the spatial variability of Indian rainfall extremes. Spatial variability is a statistical measure of how much extreme rainfall at one particular geographic location differs from that of another.
Spatial variability can drastically complicate policy issues and water– and flood– hazard management in the affected regions, he said.
“We know there is global warming, but this won’t impact each and everything in a similar way,” Ganguly said. “In some cases, regional processes will dominate. So in the context of Indian rainfall, there are things like urbanization, deforestation and changes in land use that may be more relevant to explaining this trend. Are these contributing along with global warming? That’s what we’re interested in.”
The findings were published online on Dec. 18 in the journal Nature Climate Change. Ganguly led an interdisciplinary team of researchers from the Indian Institute of Technology Bombay, Temple University and the Oak Ridge National Laboratory (ORNL) in Tennessee, where Ganguly worked before coming to Northeastern. ORNL and the Indian government partially funded the research effort.
“Our findings highlight the need for systematic examination of global versus regional drivers of trends in Indian rainfall extremes, and this may help to inform flood hazard preparedness and water resource management in the region,” the researchers wrote. The data-driven methods can be adapted to other regions of the world, both for observations and for model simulations.
Ganguly is a co-principal investigator of a larger research team, led by the University of Minnesota and funded by the National Science Foundation’s Expeditions in Computing program, that has been developing new data-driven methods for understanding climate change. The project’s focus on remotely sensed observations and climate-model simulations is expected to fuel major innovations in computational and data-intensive sciences.
“Data-driven methods for understanding climate change can help address large science gaps with major societal relevance,” Ganguly said.