Meeting roles in:
Keeping Coffee and Chocolate on the Table in a Warming World
Comparing Machine Learning and Traditional Downscaling Methods for Climate Projections Under Stratospheric Aerosol Intervention
Nina Grant is a fifth-year PhD candidate in the Atmospheric Science program at Rutgers University, working in the Rutgers Impact Studies of Climate Intervention (RISCI) lab led by Alan Robock and Lili Xia. Since her undergraduate studies at Princeton University, her research has focused on climate intervention impact studies. Her current work examines the effects of stratospheric aerosol injections on agriculture, including their influence on extreme weather and agroclimatic indices in India, their impact on “charismatic” crops like coffee and cocoa, and the use of machine learning in climate intervention research. With a strong interest in science policy and communication, she also serves as an AGU Local Science Partner (https://www.agu.org/honors/local-science-partners) and an ambassador for the Solar Geo Society (https://www.solargeo.org/). Her goal is to contribute to safe and equitable solutions to the climate crisis.