Ed Gerber

Ed Gerber

Professor at the Courant Institute

How does stratospheric ozone loss and recovery effect the tropospheric jet stream?

less than 1 minute read

Published:

In a continuation of my collaboration with Chaim Garfinkel, Ian White, and Martin Jucker on the development of MiMA, and with long time colleague (and former office mate!) Seok-Woo Son, we’ve just submitted a paper to the Journal of Climate on the response of the troposphere to stratospheric ozone loss.

We use our idealized model of the atmosphere to understand the mechanism by which the stratospheric ozone loss (or recovery) impacts the troposphere. It is well known that the formation of the ozone hole caused a poleward shift of the tropospheric jet stream. We show that planetary scale stationary waves modulate the timing and amplitude of the jet stream shift, ultimately weakening its response to stratospheric ozone perturbations.

You May Also Enjoy

See the forest and the trees!

1 minute read

Published:

Congratulations to Dave Connelly, who just submitted his first paper! It is about the use of regression forest to represent atmospheric gravity wave momentum transport to JAMES! The manuscript makes two important steps forward. First, it shows that a “boosted forest” approach, where you train each subsequent decision tree on the residual (as sketched below), can out perform a “random forest” where you combine a number of decision trees, averaging the result. This was well known in the ML community, but less so in the climate sciences. Second, Dave found that techniques from interpretable AI could be used to improve the training of a data driven parameterization. Using feature importance metrics, he found that his origional boosted forest wasn’t using enough information about latitude. By forcing the method to predict the latitude as well, he could build trees that incorporate this information more effectively!

The graft-versus-host problem…

less than 1 minute read

Published:

Ofer Shamir just submitted a paper on the use of machine learning to represent atmospheric gravity wave momentum transport to QJRMS. He developed an idealized, one-dimensional model of the Quasi-Biennial Oscillation, where we could systematically compare different data-driven methods. In particular, how can one calibrate a data-driven scheme to work in a biased model (the graft-host problem), and how well can schemes generalize to new conditions, as in a climate change scenario?

Um, what happened to me?

less than 1 minute read

Published:

I flatter myself to think you may have stopped by my webpage over the last year and half and wondered, what happened to Ed? No new papers? No research? Did he drop off the face of the Earth? Sort of. I was on sabbatical at Free University Berlin and Ludwig Maximillian University, Munich for an academic year!