Research
I use a combination of numerical climate models, statistical models, and in situ observations to understand the factors controlling variability and trends in weather systems that impact human and natural systems. My work aims to build fundamental and predictive understanding of atmospheric phenomena associated with extreme weather in the current climate and in a future climate characterized by higher levels of anthropogenic greenhouse gases.
Phenomenon-focused Research on Climate Variability and Change
My research focuses on specific atmospheric phenomena such as atmospheric rivers, mesoscale convective systems, and frontal zones. I develop and apply advanced detection algorithms, including the TECA Bayesian AR Detector (TECA-BARD), to understand how these phenomena respond to climate change and contribute to extreme precipitation events.
Coastal Climate Change in the Western US
Investigation of coastal fog and marine stratocumulus clouds along the US West Coast. Using idealized regional climate model experiments to challenge long-standing hypotheses about fog sensitivity to ocean temperatures and understand the role of transient weather systems in fog variability.
Climate Change and Extreme Weather
Research on detection and attribution of human-caused climate change impacts on extreme precipitation. Collaborative work using advanced spatial statistics models applied to in situ observations to extract climate change signals from natural weather variability.
Co-occurring Weather Phenomena
Analysis of how multiple weather phenomena (atmospheric rivers, fronts, mesoscale convective systems, tropical cyclones) interact to produce extreme precipitation. This research examines meteorological characteristics when phenomena co-occur and their representation in climate models.
Machine Learning for Climate Science
Evaluation and application of machine learning models for climate research, including assessment of ML atmospheric models' ability to emulate traditional weather models and analysis of low-likelihood high-impact extreme weather events using AI/ML approaches.
Research Methods
Numerical Modeling
Climate and weather models for hypothesis testing
Data Analysis
Novel techniques for large-scale dataset analysis
Theoretical Framework
Fundamental theory to understand physical processes
High-Performance Computing
Petabyte-scale data processing and analysis