Session S15: Statistical and Nonlinear Physics of Earth and Its Climate

Live

Over geologic time, Earth's carbon cycle has been intermittently
disrupted by transient changes in the oceans' store of carbon. Each
of these events co-occurs with significant climate change; moreover,
mass extinctions are always accompanied by such disruptions. Yet the
cause of all of these events remains mysterious. Disruptions of the
carbon cycle are typically assumed to represent a proportionate
response to an external stressor, such as enhanced volcanism or the
release of methane. This talk reviews a combination of empirical
evidence and physical theory that suggests instead that many of these
events are characteristic nonlinear responses of the Earth system to
relatively minor perturbations. Two kinds of observations support
this conclusion: the existence of a characteristic carbon flux in the
surges that mark these events, and a tendency of minor events to occur
in pairs. Both observations are consistent with the predictions of a
model of an excitable carbon cycle.   

Live

The annual temperature cycle of the earth closely follows the annual cycle of solar flux. At temperate latitudes, both driving and response cycles are well described by a strong annual sinusoidal component and a non-vanishing semiannual component. A new analysis of historical weather station records in the United States determines persistent annual and semiannual variation with high precision. Historical annual temperature ranges are consistent with prior studies. which show similar phase lags over a variety of latitudes and climate types. Semiannual temperature cycles were much stronger than expected based on the semiannual solar driving. Instead, these cycles were consistent with multiplicative effects of two annual cycles. Our methods provide a quantitative window into the climate’s nonlinear response to solar driving, which is of potential value in testing climate models.   

Live

Predicting impending failure in disordered systems is a principal goal in many fields ranging from earthquake detection to glassy, granular, and mechanical metamaterials. In most cases, particle and bond-level information plays a crucial role in predicting failure, yet this level of detail is often unavailable for complex geophysical systems. In flowing granular materials, machine learning techniques and acoustic emissions analyses demonstrate precursors to failure; yet, real-time detection remains an elusive goal. Here we show that failure of ice mélange, a large-scale granular material that is pushed through fjords by tidewater glaciers, is preceded by a loss of coherent flow. By analyzing terrestrial radar data sampled every 3-minutes, we find that the spatial pattern of strain rates within ice mélange develops large-scale fluctuations as early as 1 hour before an iceberg calving event. We also use a particle dynamics model to show how these fluctuations are likely due to buckling and rearrangements of the quasi-two-dimensional ice mélange. Our results directly implicate ice mélange as a mechanical inhibitor of calving along tidewater glaciers, and further demonstrate the potential for real-time detection of failure in geophysical granular materials.   

Live

Ice shelves, which are thick floating layers of glacier ice extending from the glaciers on land, buttress much of Antarctica and protect the ice sheet from greater rates of mass loss than it is already experiencing. However, field, remotely-sensed, and modeling based data suggest that the stability of these ice-shelves is threatened due to stress variations associated with surface meltwater ponding and drainage. These processes may initiate meltwater-induced vertical fracturing (‘hydrofracturing’) and iceberg capsize, which may ultimately lead to ice-shelf disintegration. For example, the rapid and widespread collapse of the Larsen B ice shelf in 2002 was likely driven by the drainage of about 3000 lakes via a chain reaction style process.

Surface melting and ponding on the surfaces of Antarctic ice shelves is becoming increasingly widespread, and melt rates are predicted to increase significantly this century. Although the most up to date ice-sheet models do not account for the effects of meltwater ponding on ice-shelf stability explicitly, these models respond dramatically to increased ice-shelf melting, predicting up to 1 m of sea-level contribution from Antarctica this century.

By focusing on a variety of field, remotely-sensed and modeling based case studies drawn from my research, I will present recent progress and future research directions in the rapidly growing field of Antarctic ice-shelf surface hydrology and stability. Such case studies will include: i) the first field-based study of ice-shelf flexure in response to the filling and draining of surface lakes; ii) an optical and microwave satellite data based study showing 32-year record melt on the George VI Ice Shelf in the 2019/2020 austral summer; and iii) results from a new process-scale ice shelf model that simulates, for the first time, both ice flow and viscoelastic flexure in response to a variety of surface meltwater phenomena.   

Live

Improved acoustic range estimation supports ocean climate monitoring, ocean model improvement, and underwater navigation, and is limited by the availability of accurate models of ocean sound speed variability. I will describe efforts to test the limits of currently available GCM data to accurately estimate absolute range based on data collected during the PhilSea10 experiment using 510 km source-receiver separation. The methods compare observed acoustic records with synthetic records computed through the GCM ocean sound speed model. The most reliable ranging methods, emphasizing the most reproducible parts of the data records, are able to achieve 20 m or better accuracy. The principles underlying these methods are transportable and are expected to provide reliable range estimates in a broad range of deep-water settings. Generalization to ocean regions with stronger, less well characterized dynamics, is a major challenge, requiring new sources of data to constrain the models.   

Live

Nitrogen dioxide can have deleterious effects on both human health and on environmental safety. Over the past decade, nitrogen oxides emissions are reported to have decreased by up to 40% over major cities in Texas, primarily due to the advancement of technologies and tightening of emission standards. However, the latest shale oil and natural gas boom in West Texas are reversing the decreasing trends of NO₂ levels. This study presents a quantitative analysis of NO₂ levels over Texas, including the main shale regions and the major cities. We analyzed remotely sensed NO₂ column observations from the Ozone Measuring Instrument (OMI) aboard the NASA Aura Satellite as well as in situ surface NO₂ measurements from the EPA Quality System (AQS) network. Both OMI and AQS datasets display distinct emission reduction rates, while OMI demonstrates unique spatial variation in the trends. Our analysis includes the regions of major oil and natural gas activities where NOx emissions are high and AQS monitors are not abundant. We explore how the changes in NOx impact the trends in O₃ and particulate matter using both observations and model study. This study also found dramatic drop of nitrogen dioxide emissions during stay-at-home orders issued across Texas in the middle of March 2020.   

Live

Around the globe, glaciers and ice sheets are shrinking and contributing to sea level rise. Ocean warming has been implicated as a driver of glacier retreat, with submarine melting as the presumed link. However, at the termini of tidewater glaciers, we lack observations of submarine melting or the oceanic processes that control melt. Instead, many studies rely on untested theory and parameterizations to estimate submarine melt rates. These frameworks often hinge on buoyant plumes, whose small-scale dynamics can modulate both the ocean’s impact on the glacier via submarine melting and the glacier’s impact on the ocean via buoyancy forcing. In this talk, I will present data collected near the terminus of LeConte Glacier, Alaska to probe the standard theory for plume-driven melt. In the first half, I will present surveys from autonomous kayaks that reveal ubiquitous meltwater intrusions along the terminus and suggest a mechanism to explain melt rates that are significantly higher than standard theory predicts. In the second half, the bulk fluxes of submarine melt and subglacial discharge are evaluated across a wide range of conditions in six field campaigns to test the theoretical relationship between these two sources of freshwater. Modifications to the standard melt parameterizations are explored, in an effort to work towards an updated representation of melt in ocean-glacier models.   

Live

Periodic spatial patterns of vegetation growth have been observed in dryland ecosystems. These patterns are thought to arise through self-organization in the water-limited environments that support them, and reaction-advection-diffusion models have suggested that the patterns are a precursor to ecosystem collapse as water becomes increasingly scarce. On gently sloped terrain, dryland vegetation patterns often appear as repeating bands of dense vegetation that are decameters wide and spaced on the order of hectometers apart, with bare soil in between. While observations indicate uphill migration of the bands on a century timescale, the water is input during rainstorms that last just a few hours. We explore the impact of assumptions about the fast hydrology associated with overland flow and infiltration during rainstorms on the slow dynamics of the patterns. We consider both temporally periodic and stochastic rain input within a conceptual fast-slow switching model that exploits the difference in timescales involved.   

Live

We extend the theory of sea-ice thickness distribution [Toppaladoddi and Wettlaufer, Phys. Rev. Lett. 115, 148501 (2015)], g(h), to include open water by formulating a new boundary condition for the Fokker-Planck equation for g(h). The Fokker-Planck equation, together with the new boundary condition, is then coupled to a modified version of the observationally consistent sea-ice growth model of Eisenman and Wettlaufer [Proc. Natl. Acad. Sci. USA 106, 28 (2009)] to study the evolution of g(h). We find that g(h) transitions from a single- to a double-peaked distribution in spring, which is in qualitative agreement with recent observations. To understand the cause of this transition, we construct a simpler description of the system using the equivalent Langevin formulation and solve the resulting stochastic ordinary differential equation numerically. Furthermore, we explore the effects of different climatological conditions on the formation of open water.