UW Data Science Postdoctoral Fellow
UW Department of Atmospheric Sciences
David Battisti, Atmospheric Sciences
LuAnne Thompson, Oceanography
Kyle Armour, Atmospheric Sciences and Oceanography
Ph.D., Environmental Science and Engineering, California Institute of Technology (2016)
M.Sc., Environmental Science and Engineering, California Institute of Technology (2013)
B.Sc., Engineering Physics, University of California at Berkeley (2011)
My research is focused on understanding the physical basis of climate variability and climate change. I use physical principles, modeling, and analysis of large data sets to understand large-scale atmospheric and oceanic circulation changes and their influence on Earth’s surface climate.
A key challenge in climate science is to separate observed climate changes into contributions from anthropogenic influences and contributions from natural atmosphere-ocean variability. This is typically accomplished by running a climate model several times in order to average over chaotic natural variability that varies in phase between realizations. However, this approach is computationally expensive and subject to any model biases in the anthropogenic climate response. My research uses pattern recognition methods to more efficiently separate anthropogenic and natural influences on climate, based on differences in their spatial pattern of warming.
I have developed statistical methods that use spatiotemporal covariance information about natural climate variability to efficiently identify it and filter it out. This helps to identify anthropogenic influences on regional climate that would otherwise be hard to detect amongst large amounts of noise from natural variability. These methods can detect the anthropogenic influence on regional climate changes with up to 10 times fewer climate model simulations and can even estimate the anthropogenic climate response from observations, without the use of climate models.
Separating anthropogenic and natural contributions to climate change also helps to better characterize and understand natural climate variability. My work focuses on improving mechanistic understanding of modes of climate variability such as the Atlantic Multidecadal Oscillation and the Pacific Decadal Oscillation (which is a major factor in determining winter temperature anomalies in Seattle).