STAMPS@CMU presents:

Detecting multiple anthropogenic forcing agents for attribution of regional precipitation change

by Mark Risser (LBNL)

Online webinar April 19, 2024 at 1:30-2:30 PM ET.
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Abstract
Daily rainfall accumulations are a critical component of the global water cycle, and comprehensive understanding of human-induced changes in rainfall is essential for water resource management and infrastructure design. Detection and attribution methods reveal cause and effect relationships between anthropogenic forcings and changes in daily precipitation by comparing observed changes with those from climate models. However, at sub-continental scales, existing studies are rarely able to conclusively identify human influence on precipitation. In this work, we show that anthropogenic aerosol and greenhouse gas emissions are the primary drivers of precipitation change over the United States and, by simultaneously accounting for both agents, we explicitly decompose the uncertain regional human influence into the individual effects of these agents. Greenhouse gas (GHG) emissions increase mean and extreme precipitation from rain gauge measurements across all seasons, while the decadal-scale effect of global aerosol emissions decreases precipitation. Local aerosol emissions further offset GHG increases in the winter and spring but enhance rainfall during the summer and fall. Our results show that conflicting literature on trends in precipitation over the historical record can be explained by offsetting aerosol and greenhouse gas signals.

Bio

Mark is a Research Scientist in the Climate and Ecosystem Sciences Division at Lawrence Berkeley National Laboratory. He received his Ph.D. in Statistics from the Ohio State University in 2015 (thesis advisor: Catherine Calder). Mark’s primary goal as a statistician is to use data science, Bayesian modeling, and computational tools to identify and quantify climate change. His research focuses on statistical climatology, extreme value analysis, Gaussian processes, and Bayesian modeling.