Ed Gerber

Ed Gerber

Professor at the Courant Institute

How will global warming change the coupling between the troposphere and stratosphere?

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Please see our new paper exploring the impact of global warming stratosphere-troposphere coupling, just submitted to the Journal of Geophysical Research: Atmospheres.

This study, lead by Blanca Ayarazuguena and Andrew Charlton, investigates changes in extreme events in the coupled stratosphere-troposphere system (Sudden Stratospheric Warmings, or SSWs) under extreme global warming (quadroupled CO2). The key findings are:

  • The tropospheric impact of Sudden Stratospheric Warming events in the North Atlantic region will not change with extreme global warming. We can expect the same poleward shift of the jet stream and storm systems following an SSW, as we observe in today’s climate.

  • There is high uncertainty in the change of SSW frequency under extreme warming. Some models predict that the rate of events will be cut in half; others predict a doubling in their number!

  • The boreal polar vortex will form earlier and disappear later under increased CO2, extending the season of stratosphere-troposphere coupling.

While we are interested in understanding these changes in the atmospheric circulation, it is important to stress that these would be the least of our problems if we don’t curb green house emissions. Our world would be radically different if we allow CO2 to reach these levels, perhaps 6-10 degrees warmer with sea level a meter+ higher than today … if not worse. For those of us in New York, that would mean that your run-of-the-mill winter storm would pack the effective storm surge of Hurrican Sandy. Let’s not go there!

This is the first study of the CMIP6 climate models organized through the DynVarMIP. Our field has too many acronyms: the Coupled Model Intercomparision Project, Phase 6, is set of climate simulations by the the world’s best climate prediction systems, organized to support the Intergovernmental Panel on Climate Change’s (IPCC) 6th assessment report. The Dynamics and Variability MIP is a sub-project within the CMIP6 focussed on atmospheric dynamics and stratosphere-troposphere coupling.

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Using Explainable AI and Transfer Learning to understand and predict the maintenance of Atlantic blocking with limited observational data

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Huan Zhang submitted our paper on how to use machine learning to predict the persistence of blocking events to the new Journal of Geophysical Research Machine Learning and Computation, published by the AGU. Blocking events are persistent high pressure systems that “block” the flow of the jet stream. They are associated with extreme weather, as they shift the direction of storms, and, in summer, create heat domes that drive heat waves. A key element of a block is its persistence. Huan developed a convolutional neural network to predict whether an nascent blocking anomaly would persist, or fade away, and then interrogated the network to understand why it worked, and how it could be trained with the short observational record.

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Minah Yang submitted a paper on how to combat data imbalance in regression problems to JAMES. The goal is to improve the performance of data-driven paramterizations, particularly for profiles that are rare, but important. This is a data imbalance problem: we need ensure that the parameterization works well on input-output pairs that are seldom seen in training. Minah proposes a technique based on histogram equalization, visualized below with help from Cece, Minah’s faithful companion! The idea is to oversample or reweight these rare cases during training, to ensure the method learns from them.