Ed Gerber

Ed Gerber

Professor at the Courant Institute

The double dip gap in ozone trends over the high latitudes

1 minute read

Published:

Aaron Match submitted our work exploring a curious feature of extratropical ozone in simulations of global warming.

In response to rising atmospheric CO2 primarily from the burning of fossil fuels, beneficial ozone in the mid-latitude stratosphere tends to increase due to changes in the winds and temperature-dependent reaction rates. However, these broad increases in ozone are punctuated by reductions (or muted increases) around 10 km and 17 km, which we term the “double dip”. We find that the double dip exists because the warming of the troposphere allows the tops of rainclouds to reach higher altitudes, reducing stratospheric ozone through the injection of ozone-poor tropospheric air. The lower dip around 10 km results intuitively from the deepening of the mid-latitude troposphere. Counterintuitively, the upper dip around 17 km results from deepening of the faraway tropical troposphere, whose remote reductions in tropical ozone are then transported laterally over the midlatitudes. Thus, the double dip depends on both the local and remote deepening of the troposphere, which could complicate a common practice of filtering out the effects of tropospheric expansion that only considers the local component

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Stressed out jet streams!

1 minute read

Published:

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

1 minute read

Published:

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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Published:

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.