Stanford University

ESS Wed Seminar: Clouds, Climate Predictions, and Possible Surprises in Warm Climates BY Professor Tapio Schneider, California Institute of Technology, Environmental Science & Engineering

Wednesday, Jan 16, 2019 12:30 PM
Y2E2, Room #111
Students, Alumni/Friends
Department of Earth System Science

While climate change is certain, precisely how climate will change is less clear. Uncertainties arise from the representation of small-scale processes such as clouds and turbulence. Moreover, these uncertainties are poorly quantified; the ensemble of existing climate models may not span the range of possible climate outcomes. I will illustrate this with an example from the dynamics of stratocumulus clouds, which are crucial for Earth’s energy balance. Large-eddy simulations of stratocumulus clouds show that they can exhibit an instability that leads to dramatic global warming under high greenhouse gas concentrations—an instability that does not seem to be captured by current climate models and whose probability of occurrence cannot be assessed with current models.

Breakthroughs in the accuracy of climate projections and in the quantification of their uncertainties are now within reach, thanks to advances in the computational and data sciences and in the availability of Earth observations from space and from the ground. To achieve a leap in accuracy of climate projections, we are developing a new Earth system modeling platform. Developed by a university consortium dubbed the Climate Modeling Alliance (CliMA), it will fuse an Earth system model (ESM) with global observations and targeted local high-resolution simulations of clouds and other elements of the Earth system. CliMA capitalizes on advances in data assimilation and machine learning to develop an ESM that automatically learns from diverse data sources, be they observations from space or data generated computationally in high-resolution simulations.

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