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Lee's paper at the August conference in Bellevue, Washington, combined weather and power outage data for three states – Texas, Michigan and Hawaii –  and used a machine learning model to predict how extreme weather such as thunderstorms, floods and tornadoes would affect local power grids and to estimate the risk for outages. The paper relied on data from the National Weather Service and the U.S. Department of Energy’s Environment for Analysis of Geo-Located Energy Information, or EAGLE-I, database.

Growing up exploring the parklands of India where Rudyard Kipling drew inspiration for The Jungle Book left Saubhagya Rathore with a deep respect and curiosity about the natural world. He later turned that interest into a career in environmental science and engineering, and today he is working at ORNL to improve our understanding of watersheds for better climate prediction and resilience.

Hydrologist Jesús “Chucho” Gomez-Velez is in the right place at the right time with the right tools and colleagues to explain how the smallest processes within river corridors can have a tremendous impact on large-scale ecosystems.

Researchers at 91���� have identified a statistical relationship between the growth of cities and the spread of paved surfaces like roads and sidewalks. These impervious surfaces impede the flow of water into the ground, affecting the water cycle and, by extension, the climate.

Planning for a digitized, sustainable smart power grid is a challenge to which Suman Debnath is using not only his own applied mathematics expertise, but also the wider communal knowledge made possible by his revival of a local chapter of the 91���� professional society.

In the race to identify solutions to the COVID-19 pandemic, researchers at the Department of Energy’s 91���� are joining the fight by applying expertise in computational science, advanced manufacturing, data science and neutron science.