I am a postdoctoral scholar working with
Professor Tiffany Shaw at the
Department of the Geophysical Sciences,
University of Chicago.
Previously, I was a scientific assistant at the Climate Dynamics Group of ETH Zurich, and a PhD student at the Environmental Science and Engineering program of Caltech.
I am interested in clouds and their interactions with the large-scale environment.
Clouds are important: they strongly influence Earth's radiation budget and thereby affect Earth's temperature, precipitation, and atmospheric circulation. Clouds are also intriguingly complicated: they span a large range of spatial scales and involve many tightly coupled processes, including dynamics, thermodynamics, radiation, microphysics, and aerosol chemistry. Such complexity makes it very difficult to unravel the essential mechanisms of clouds and to predict their responses and feedbacks in different climate regimes.
My research aims at understanding the robust physical mechanisms and effects of clouds.
I use a hierarchy of models that span across various scales, including idealized general circulation models (GCM), single column models (SCM), and large-scale simulations (LES). Idealized experiments are designed for these models for simplification to the extent possible that the fundamental physical constraints remain valid. Understanding on the essential mechanisms of clouds are thereby developed, and simple analytical models that capture the key processes can be constructed accordingly. This new knowledge can be applied in the actual climate change context, which helps us to reduce the theoretical and modeling uncertainty on cloud responses and feedbacks.
My PhD research with Professor Tapio Schneider and Doctor Joao Teixeira (Caltech/JPL)
My PhD thesis was jointly supervised by Professor Tapio Schneider and Doctor Joao Teixeira. First, I have investigated the subtropical low-cloud response to climate change under large-scale and surface energetic constraints with idealized LES experiments. Simple mechanisms of the trade-wind cumulus response to CO2-driven warming are proposed. Second, I have developed a closure for the physically consistent representation of sub-grid scale (SGS) processes in GCMs, which aims to improve the cloud biases due to the artificial separation between convection and turbulence.
I have worked with Doctors Kyle Pressel and Colleen Kaul in the development of the PyCLES model, a novel Python-based LES code for simulating turbulence, convection, and cloud dynamics at high-order accuracy. I have also worked with Doctor Florent Brient on investigating why the simulated shallowness of present-day tropical low clouds is strongly linked to the predicted magnitude of global warming among the ensemble of CMIP5 climate models.