For a broader overview of climate engineering, read our primer: www.srmprimer.org
Research focuses primarily on the interdisciplinary application of engineering feedback analysis, dynamics, and control tools to problems in climate; principally solar climate engineering or geoengineering (and climate dynamics/variability, but there is no ongoing activity in this area). Additional interests include control of fluid dynamics, vibration and noise, and telescope control.
Climate Engineering refers to large-scale intentional intervention in the climate system as a possible additional tool to help manage some impacts of climate change; an example would be adding aerosols to the stratosphere to reflect some sunlight. This doesn’t reduce the need to cut greenhouse gas emissions, nonetheless deploying some amount of Climate Engineering might reduce climate damages, and more research is needed to evaluate it.
Our primary specific focus is GAUSS: Geoengineering Assessment across Uncertainty, Scenarios, and Strategies. Informed choices will require a holistic assessment of geoengineering, or climate engineering, that is not just our best estimate but captures uncertainty, for a range of future scenarios, and for different possible strategies. Simulations that span this space will be made available to the broader research community.
Research is funded by NSF and by the Cornell University Atkinson Center through donations from Cornell alum and from Silver Lining’s Safe Climate Research Initiative (which is supported by LowerCarbon Capital, Matt Cohler, Pritzker Innovation Fund, Bill Trenchard, and the LAD Climate Fund).
Main research questions:
- System Design and Optimization: How can one “design” stratospheric-aerosol climate engineering, using available degrees of freedom (e.g., latitudes, times of year to inject material) to achieve desired objectives? What are the fundamental limits or trade-offs; that is, what can geoengineering do, and what can’t it do?
- Systematic Uncertainty Assessment: Can we quantify how uncertain are our predictions? We need a risk-register: for any given uncertainty (e.g., aerosol microphysics), how uncertain is it, what are the consequences, what are the mitigation options? This is essential to prioritize research.
- Impacts: What would the climate impacts be for different deployment choices?
- Policy and Governance: Research questions need to be informed by the societal context, and vice versa. E.g., what scenarios should we be simulating?
Specific ongoing research:
- In-depth comparison of solar reduction to stratospheric aerosols; solar reduction is a poor proxy for impacts (Daniele Visioni)
- Managing alternate objectives such as precipitation, sea-ice, or ITCZ (Walker Lee)
- How big is the design space; how many degrees of freedom matter? (Yan Zhang)
- What is the impact of geoengineering on atmospheric circulation? (Wei Cheng)
- Can aircraft be designed to get material to the stratosphere at 23-25km? (completed MEng project; Jordan Gurian and Zineb)
- What are the remote effects (or teleconnections) from regional marine sky brightening (Doug MacMartin)
- Addressing Arctic impacts? (Walker Lee and Daniele Visioni)
Other research ideas include (this is a very incomplete list):
- Current simulations use feedback to manage climate goals directly. Design and demonstrate feedback control of aerosol optical depth instead, and then demonstrate an inner/outer loop structure to control surface temperature using desired AOD as the input.
- How sensitive are predictions to uncertainty? What happens if we change parameters influencing aerosol size distribution, for example?
- What would happen if there was a volcanic eruption during a stratospheric aerosol deployment?
- What is the smallest useful global experiment to measure stratospheric aerosol properties? (This isn’t quite my expertise.) What is the signal-to-noise for detecting aerosol optical depth or aerosol size parameters from satellite measurements or balloons; or more generally, what observations are required? A related question would be, what would the first years of a stratospheric aerosol deployment look like?
- Validate an emulator (reduced-order dynamic model) on simulations of stratospheric aerosol injection, and predict the response for different scenarios, including for example predicting the rate-of-change of temperature and precipitation to understand stressors on ecosystems,
- Validate whether taking aerosol fields from the “high-top” model CESM(WACCM) and applying them in the “low-top” version CESM(CAM) yields similar surface climate.
- What would be the impact of a 1-, 2-, or 3-year interruption in deployment? How about an abrupt start?
- Using System identification tools, for example to assess regional climate response to regional Marine Cloud Brightening