Bulletin of the American Physical Society
APS March Meeting 2021
Monday–Friday, March 15–19, 2021; Virtual; Time Zone: Central Daylight Time, USA
Session R15: Rare Events, Tipping Points, and Abrupt Changes in the Climate SystemFocus Live

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Sponsoring Units: GPC Chair: Mary Silber, University of Chicago 
Thursday, March 18, 2021 8:00AM  8:36AM Live 
R15.00001: Large deviation theory, extreme events and abrupt changes in the climate system Invited Speaker: Freddy Bouchet In the climate system, many events of primarily importance, for instance rare extreme events or rare transitions between climate attarctors can not be studied with conventional approaches, because they are too rare and the realisitc models are too complex. We will discuss several new algorithms and new theoretical approaches based on large deviation theory, where huge progress have been made to compute such rare events. We discuss results for the study of extreme heat waves and abrupt climate changes. We will delineate a research program in order for these approaches to be used with the most realistic models in the future in order to pave the way of a quantitative science of rare climate events. 
Thursday, March 18, 2021 8:36AM  8:48AM 
R15.00002: Fingerprinting Heatwaves and Cold Spells and Assessing Their Response to Climate Change using Large Deviation Theory Vera Melinda Galfi, Valerio Lucarini Extreme events provide relevant insights on the dynamics of the climate system and their understanding is key to defining useful strategies for mitigating the impact of climate variability and climate change. By applying large deviation theory to the output of a stateoftheart climate model, we define the climatology of persistent heatwaves and cold spells in some key target regions of the planet by constructing empirically the corresponding rate functions for the surface temperature, and we assess the impact of increasing CO_{2} concentration on such persistent anomalies. In particular, we can better understand the increasing hazard associated to heatwaves in a warmer climate. We show that two 2010 high impact events  summer Russian heatwave and winter Dzud in Mongolia  are associated with atmospheric patterns that are exceptional compared to the typical ones, but typical compared to the climatology of extreme events. Finally, we propose an approximate formula for describing large and persistent temperature fluctuations from easily accessible statistical properties. 
Thursday, March 18, 2021 8:48AM  9:00AM Live 
R15.00003: Asymmetric extreme events of Earth's climate and carbon cycle during the last 66 million years Constantin Arnscheidt, Daniel Rothman The history of Earth's climate and carbon cycle is preserved by carbon and oxygen isotope records in deepsea sediments. Here we show that the subMyr fluctuations in both records have exhibited pronounced, negatively skewed nonGaussian tails throughout most of the past 66 million years. This asymmetry suggests that the climatecarbon cycle system has been intrinsically predisposed towards extreme events involving abrupt global warming and respiration of organic carbon. The fluctuations further obey theoretical relationships predicted for stochastic multiplicative noise processes. We investigate these observations by developing a simple climatecarbon cycle model in which the amplitude of random internal fluctuations increases at higher temperatures. The model replicates the data well, provides a general explanation for the observed pacing of past global warming events by changes in orbital parameters, and is complementary to approaches that seek to explain these events on an individual basis. These results suggest that, as anthropogenic emissions continue, Earth's climate may become more susceptible to extreme warming events on geological timescales. 
Thursday, March 18, 2021 9:00AM  9:36AM Live 
R15.00004: Data assimilation and Uncertainty Quantification in the Geosciences Invited Speaker: Juan Restrepo In the statistics community “Big Data” science is meant to suggest the combining of inferential and computational thinking. We also speak of big data in the geosciences. However, the problems we pursue, e.g. Earth's climate, are often extreme in the number of degrees of freedom, and in many instances, nonstationary in their statistics. 
Thursday, March 18, 2021 9:36AM  9:48AM Live 
R15.00005: Transition path theory analysis of noiseinduced tipping in a stratospheric model Justin Finkel, Jonathan Weare, Dorian Abbot Nonlinear atmospheric dynamics produce rare events that are hard to predict and attribute due to many interacting degrees of freedom. Sudden stratospheric warming is an example where the winter polar vortex rapidly breaks down under wave disturbance, inducing midlatitude cold spells. Numerical simulations reproduce this phenomenon, but the complexity of the physics and data is a challenge for interpretation. We llustrate a description of rare weather events with Transition Path Theory, a mathematical framework that defines and relates extreme event statistics. Though the events that we focus on and their statistics involve very long timescales, we describe an approach to estimating them in high dimensional state spaces using only relatively short simulations of the system. Applying this methodology to a classical loworder stratospheric model with stochastic forcing, we compute optimal predictors, dominant pathways, and return times of noiseinduced regime transitions, and relate them to physical observables. The study aims to motivate the broad potential meteorological utility of Transition Path Theory and of a computational framework to estimate TPT quantities for realistic models. 
Thursday, March 18, 2021 9:48AM  10:00AM Live 
R15.00006: The distribution of ocean surface wave heights and the St. Petersburg paradox Jake Fontana, Paul Johns, Peter PalffyMuhoray We examined over 3.5 billion ocean surface waves measured by 148 buoys across the Pacific ocean to determine the statistical distribution of wave heights. We find that the distribution of ocean surface wave heights accumulate similarly to profits in the St. Petersburg paradox, revealing that the maximum normalized wave height depends linearly on the logarithm of the number of waves. The St. Petersburg paradox model therefore appears to extend beyond material failure[1] and anomalous transport[2], providing a promising strategy to forecast rogue waves. 
Thursday, March 18, 2021 10:00AM  10:12AM Live 
R15.00007: An Improved Framework for the Dynamic Likelihood Filter Dallas Foster, Juan Restrepo We significantly extend the capabilities of the Dynamic Likelihood Filter, a Bayesian data assimilation scheme that uses a computational model and its inherent uncertainties to generate a prior and exploits hyperbolicity in wave problems to timeevolve the likelihood in order to formulate approximations of the conditional probabilities. The methodology is particularly effective when observations have small inherent measurement errors and are sparse in space and time, as is often the case in geophysical wave problems. 
Thursday, March 18, 2021 10:12AM  10:24AM Live 
R15.00008: Spontaneous Stochasticity in Atmospheric Turbulence and Climate Dynamics Gregory Eyink, Dmytro Bandak, Alexei Mailybaev, Nigel Goldenfeld Lorenz^{a }argued that “formally deterministic fluid systems which possess many scales of motion are observationally indistinguishable from indeterministic systems.” Recently, Lorenz’ idea has been related to spontaneous stochasticity, or persistent randomness in solutions of singular deterministic dynamics for fixed initial data, as regularizations and stochastic perturbations are both taken to vanish.^{b,c }We study the effect of thermal noise on turbulent solutions of the incompressible NavierStokes equation and argue that, for fixed deterministic initial data, a stochastic ensemble of nonunique Euler solutions is obtained in the high Reynoldsnumber limit. Our arguments are supported by numerical simulations. Thus, not only the flap of a seagull wing but even the “swerve of the molecules” leads to intrinsic randomness in one eddy turnover time, which “cannot be lengthened by reducing the amplitude of the initial error”.^{a } Our results support arguments that climate models must be intrinsically stochastic, even if they are resolved to 1 km scales and below.^{d} 
Thursday, March 18, 2021 10:24AM  11:00AM Live 
R15.00009: Feedbacks between the worst storms on Earth and lower stratospheric water vapor Invited Speaker: Morgan O'Neill The presence of water vapor in the lower stratosphere is enormously consequential for climate. Physically, it helps set the `cold reservoir’ temperature effectively experienced by the tropospheric heat engine, and an increase in water vapor in the lower stratosphere cools the stratosphere and warms the Earth’s surface. Chemically, an increase in stratospheric water vapor speeds ozone destruction. The stratospheric water budget remains poorly constrained, both observationally and theoretically. Strong thunderstorms are known to be an important secondary source of water vapor to the lower stratosphere, and how they may feedback to large scales in a warming climate is almost completely unknown. 
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