Research

I am interested working towards improving subseasonal and seasonal weather forecasts by using novel computational methods to better understand and simulate relevant atmospheric processes.

Previously, I focused on predictability of the Madden-Julian Oscillation (MJO), which is a convective circulation pattern over the tropical Pacific with a period of 30-70 days. Convection during the MJO induces Rossby waves that can affect weather in the extratropics with a lag of 1-4 weeks. Most global climate models do not have convection schemes that reasonably simulate the MJO itself, let alone proper representation of MJO teleconnections. Improving our simulation and understanding of the MJO has the potential to dramatically improve our long-term weather forecasts. My 2022 paper details an improved index for characterizing the MJO. My 2023 paper investigated the potential predictability of the MJO using a perfect model approach and a novel perturbed forecast initiation technique.

Currently, I am working on a project to correct for mean state model biases in freely-running climate model simulations. Correcting for systematic model biases online could improve longer-term forecasts by correcting the background state that weather propagates through. One of the building blocks of this method is the replay methodology, which I implemented in CESM2. The replay can be easily ported from github here.

I value scientific practices that are 1) accessible and inclusive; 2) uplifiting and non-extractive; 3) open; and 4) a benefit to society. Contact me if you would like to see my detailed values statement, or the flowchart that I use to make decisions based on these values. Also contact me if you are interested in chatting about being queer in the geosciences!