Ed Gerber

Ed Gerber

Professor at the Courant Institute

On the stability of the stratospheric ozone layer

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Aaron Match submitted a paper on how photochemistry can compensate or amplify perturbations to the ozone layer to journal of Atmospheric Chemistry and Physics, published by the EGU. It has been observed that photochemistry can partially compensate for ozone loss due to CFCs and other ozone depleting substances. The process is known as self healing: decreases in tropical ozone aloft are associated with a counterintuitive increase at lower levels. It is not enough to fully compensate for the loss, but mitigates it. More recently, greenhouse gases have begun to cool the stratosphere, leading to increasing ozone aloft, which is partially compensated for by ozone reduction below (referred to as “reverse self healing”, which is admittedly a rather contorted phrase!). These responses are attributed to the fact that ozone loss increases the penetration of high energy UV radiation, which leads to more ozone production below (and skin cancer for us on the surface), vice versa for ozone increase due to cooling. Aaron asked whether this compensating response is generic, and found it is not! In upper stratosphere, photochemistry can amplify a perturbation, such that ozone loss would lead to more loss. But fortunate for us on the surface, compensation in the lower stratosphere is actually much more significant than appreciated before!

Self healing and reverse self healing have never been quantitatively investigated. Aaron developed an approach to quantify the effect of “photochemical adjustment”, that is, how much changes in the UV flux due to ozone perturbations influences ozone below. Above about 40 km, photochemical adjustment is destablizing, amplifying perturbations, while below 40 km, the adjustment is stabilizing, compensating for perturbations. Fortunately most of the ozone layer is below 40 km, so our atmosphere is largely in a stablizing regime, but this may not have been in the case during the evolution of the atmosphere. On an early Earth with less oxygen, the whole atmosphere may have been in a destabilizing regime.

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Stressed out jet streams!

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Xingjian (Ken) Yan, a precocious undergraduate (now bound for a PhD at MIT) working with Lei Wang and I just submitted a paper exploring the utility of the traffic jam theory of blocking onset for perdiction to Geophysical Research Letters. Ken defined and explored “flux exceedance events”, meteorological situations where the jet stream gets overloaded with storm activity. Nakamura and Huang suggested that this overloaded jet situation creates a pile up storm activity – a traffic jam – leading to blocking events. Ken found that the climatological structure of exceedance events is remarkably similar to that of blocks, but that they appear to be distinct phenomenon: an overloaded jet stream is unfortunately not a reliable harbinger of an atmospheric block.

Protection without poison

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Aaron Match developed a new theory for why the ozone layer is up in the stratosphere, reaching a maximum 26 km above the surface in paper submitted to the journal of Atmospheric Chemistry and Physics. In 1880, Walter Hartley deduced that ozone must be absorbing UV-B and UV-C radiation from the sun, but since it isn’t present at the surface (except in polluted air), this ozone must be somewhere “up there”. The stratosphere wasn’t discovered for a couple more decades, but it turns out that ozone that shields us from this harmful UV radiation is largely between 16 and 40 km above us. It’s a good thing its there: ozone is toxic. If it were uniformly distributed through the atmosphere, the concentration at the surface would be 8 times the EPA safety limit. Why is ozone safely up in the stratosphere, where it protects us without poisoning us? Advanced chemistry climate models can accurately predict the distribution of ozone, but in turns out our text book understanding of the ozone layer were incomplete and gave the wrong explanation for why it reaches a maximum in the stratosphere at 26 km.

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.

So, you have an imperfect data-driven parameterization for climate modeling. How can you make it better?

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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.