65 citations · 232 across the 16 of their papers we have counts for
5 papers · 1 filter
Quantifying Very Extreme Precipitation and Temperature Using Huge Ensembles Generated by Machine Learning-based Climate Model Emulators
Christopher J. Paciorek, Daniel Cooley
Weather extremes produce major impacts on society and ecosystems and are likely to change in likelihood and magnitude with climate change. However, very low probability events are…
Improved return level estimation via a weighted likelihood, latent spatial extremes model
Joshua Hewitt, Miranda J. Fix, Jennifer A. Hoeting +1
Uncertainty in return level estimates for rare events, like the intensity of large rainfall events, makes it difficult to develop strategies to mitigate related hazards, like flood…
Data Mining to Investigate the Meteorological Drivers for Extreme Ground Level Ozone Events
Brook T. Russell, Daniel Cooley, William C. Porter +2
This project aims to explore which combinations of meteorological conditions are associated with extreme ground level ozone conditions. Our approach focuses only on the tail by opt…
Extreme value analysis for evaluating ozone control strategies
Brian Reich, Daniel Cooley, Kristen Foley +2
Tropospheric ozone is one of six criteria pollutants regulated by the US EPA, and has been linked to respiratory and cardiovascular endpoints and adverse effects on vegetation and…
Downscaling extremes: A comparison of extreme value distributions in point-source and gridded precipitation data
Elizabeth C. Mannshardt-Shamseldin, Richard L. Smith, Stephan R. Sain +2
There is substantial empirical and climatological evidence that precipitation extremes have become more extreme during the twentieth century, and that this trend is likely to conti…