Projects

Unprecedented Extreme Precipitation Risk Under Climate Warming

This project quantifies how anthropogenic warming increases the likelihood of record-breaking extreme precipitation events worldwide by combining climate model projections with population exposure and socioeconomic vulnerability. We show that low- and lower-middle-income countries face disproportionately higher risks, with projected exposure to unprecedented storms increasing by up to an order of magnitude by +4 °C warming due to the combined effects of intensifying hazards, rapid population growth, and limited adaptive capacity.

Drought Synchronicity Across the United States

This project examines when and why droughts occur simultaneously across multiple U.S. regions using high-resolution climate data from 1980–2021. We show that drought synchronicity has intensified since the early 2000s, particularly in the Great Plains and Midwest, and that atmospheric evaporative demand and large-scale climate modes (e.g., NPGO, PMM) play a key role in amplifying or suppressing these spatially connected droughts.

Investigating Stratopheric Circulation in the DoE climate model E3SMv2 (CMIP6 protocol)

There is a need to understand how well our climate models capture stratospheric motions, especially motivated by climate intervention techniques, such as stratospheric aerosol injections. This work investigates the stratopheric circulation of the DoE’s earth system model E3SMv2, run under CMIP6 guidelines. This work will be used in assessing the variability of the stratosphere and is funded by the CLDERA Grand Challenge.

Proportional-Integral Feedback Controller for simulation Stratospheric Aerosol Injections

Simulating stratospheric aerosol injections (SAI) can range from a simple “dimming” of the sun’s radiation to representing the complete chemical interactions that occur in the stratosphere. This work uses a proportional-integral feedback controller, adapted from dan-visioni that adjusts the rate of the aerosol injection at specified locations based on simultaneously controlling for three temperature metrics. This was to be used in a modified model of E3SMv2, that included a more complete chemical description of the stratosphere. This work was done at Sandia National Laboratory in the FORCEE internship

Precipitation Variance Spectra in Rain Gauges vs Models

Precipitation projections in climate models contain large amounts of uncertainty and suffer from a “drizzle effect”, where the model output precipitation is always lightly raining. As climate models increase their spatial resolution, we would hope to more accurately capture the more extreme precipitation events that have profound impacts on our society. This study looks at the power spectrum of the precipitation variance of low, medium, and high resolution models and compares them to rain gauge information. The goal is to understand if increasing resolution can capture the high frequency high intensity rain events that we see in observation.