Lastest Update: 16th August 2024
Graduate researches at Princeton University
Weakening of tropical free tropospheric temperature gradients with global warming
The Weak Temperature Gradient (WTG) approximation is fundamental to tropical atmospheric dynamics, yet its response to global warming is less studied. Here, we use theory and a hierarchy of models to demonstrate that the tropical free-tropospheric horizontal temperature gradients will be even weaker in a warmer climate.
Long story short, weaker atmospheric circulation in a warmer climate causes weaker momentum advection in tropical free-troposphere, then results weaker pressure gradients as required by the momentum equation, which finally translates to weaker temperature gradients according to the hydrostatic balance.
We have a manuscript under review in Journal of the Atmospheric Sciences regarding the above mechanism. We plan to study the implications of weaker tropical free-tropospheric temperature gradient in the future. Do we need to improve the WTG parameterization of large-scale dynamics in convective-scale modeling? Will weaker tropical free-tropospheric temperature gradient affect surface heat extremes and low cloud cover?
Collaborators: Yi Zhang, Stephan Fueglistaler
SST pattern effect on OLR: the role of large-scale convection aggregation
The spatial pattern of tropical SST significantly affects TOA radiation. Many previous studies focused on shortwave radiation: Larger tropical SST gradient causes warmer free-troposphere and stronger inversion in subsiding regions, increasing low clouds and reflecting more shortwave radiation. We instead turn to longwave radiation. Larger tropical SST gradient causes stronger overturning circulation and narrows the convective region. Such large-scale convection aggregation results in the expansion of dry and clear-sky regions, increasing OLR. Our studies have the following key points:
- Tropical SST gradient has comparable impacts on TOA shortwave and longwave radiation in a hierarchy of models.
- Historical (1980-2010) SST warming pattern featuring increasing SST gradient results more negative longwave radiative feedback than uniform SST warming, which is quantitatively explained by convection aggregation.
- OLR responses to SST perturbations at different locations are not additive, because convection aggregation responses are not additive. This can be ultimately explained by non-linear tropical atmospheric dynamics. See the video and paper in Journal of Climate.
Collaborators: Stephan Fueglistaler, Bosong Zhang, Chenggong Wang
Undergraduate researches at Peking University
Reinforcement Learning for Geoengineering
One solar geoengineering method is injecting aerosols in the stratosphere to reflect solar radiation. Different strategies (global distribution + time dependence) of aerosol injection will affect climate differently, and people want to find the ‘best’ strategy that results in a desired climate state. This is an optimization problem and could be solved by reinforcement learning, a machine learning technic widely used in autonomous driving, robotics and AI game playing. This research shows that reinforcement learning gives us effective geoengineering strategies that can prevent global warming and revert climate change. This is my bachelor thesis research, advised by Professor Daniel Koll at Peking University. I also received lots of help from Professor Nicholas Lutsko at UCSD and Dr. Janni Yuval at MIT. The research paper is going to be submitted soon.
Conditional mean temperature tendency decomposition
This research proposes a conditional mean temperature tendency decomposition framework that tells us what processes drive temperature towards or away from extremes at every temperature percentile, which is very useful for extreme events studies. It tells us that horizontal temperature advection drives temperatures toward more extreme values over most land in the midlatitudes, but dampens temperature anomalies in some coastal summer monsoon regions, where extreme temperatures result from other processes. This is my 2021 summer research, advised by Professor Marianna Linz at Harvard University and Professor Gang Chen at UCLA. The research paper is published in Journal of Climate.
Asymmetry of temperature series
Daily mean temperature series at the mid-latitudes usually have an asymmetric property: They cool rapidly and warm gradually. This research shows that such temperature asymmetry is due to the asymmetry of frequency and intensity between cold and warm fronts: In North China Plain, for example, cold fronts are stronger and more frequent than warm fronts, so daily mean temperature series cools rapidly and warms gradually. This is my undergraduate research in 2021, advised by Professor Zuntao Fu at Peking University. The research paper is published in International Journal of Climatology.