The substantial uncertainty in climate feedbacks and especially that of clouds impede our ability to predict climate change. In this talk, I will discuss an observational approach to ascertain the sign and magnitude of the cloud feedback. I will first demonstrate that the long-term measurements of the Atmospheric Emitted Radiance Interferometer (AERI) constitute a Radiative Keeling Curve, which can be used to benchmark the atmospheric radiation changes and specifically the atmospheric greenhouse effect.

Then I will use an Optimal Fingerprinting method to enable an observational quantification of the radiative forcing and feedbacks from the AERI measurements, by leveraging their distinct spectral signatures. Among the results is a surprising, negative longwave feedback of clouds, which partially mitigates the atmospheric greenhouse effect in the mid-latitude land regions.

Yi Huang is a Professor in the Department of Atmospheric and Oceanic Sciences at McGill University, Canada. His research is focused on atmospheric radiation. He obtained his Ph.D. at Princeton University and was a Climate and Global Change Postdoctoral Fellow at Harvard University before joining the faculty at McGill University. He is currently a Sciences & Applications co-Lead of a Canadian satellite mission, High-altitude Aerosols, Water vapour and Clouds (HAWC).

Lieu
IPSL, Jussieu
Salle de conférence de l’IPSL (201)
Couloir 45-55, 2^e étage

Visio
https://cnrs.zoom.us/j/99399324290?pwd=cKCsQVPwDbpcJG29ZBqNse77muFaoW.1