Search Talks

We present a data-driven framework for dimensionality reduction and causal inference in climate fields. Given a high-dimensional climate field, the methodology first reduces its dimensionality into a set of regionally constrained patterns. Causal relations among such patterns are then inferred in the interventional sense through the fluctuation-response formalism. To distinguish between true and spurious responses, we propose an analytical null model for the fluctuation-dissipation relation, therefore allowing us for uncertainty estimation at a given confidence level. The framework is then applied to understand the relation between sea surface temperature warming patterns and changes in the net radiative flux at the top of the atmosphere, the so-called "pattern effect". We present a set of new results on the pattern effect and discuss the role of different processes, active at different spatiotemporal scales, in establishing the causal linkages between warming at the surface and radiat...

Horizontal and vertical distributions of mesoscale eddy kinetic energy (EKE), the dominant reservoir of ocean kinetic energy, are influenced by both environmental and dynamical factors. Compared to partitioning across horizontal scales, distributions of EKE in the vertical have been relatively under-observed and under-studied. Using newly collected full-depth observations of horizontal velocity from four unique mooring sites and output from the NOAA GFDL CM2.6 suite, this work presents a characterization of eddy vertical structure and investigates the factorings controlling its spatio-temporal variability. Time series analysis and application of clustering tools reveal geographic patterns in vertical structure. These patterns indicate the role of latitude and bathymetry in moderating the vertical partitioning of EKE. These relationships are interpreted through the lens of theoretical expectation and considered in the context of techniques used to infer or impose vertical structure.

The Bay of Bengal (bay) is a semi-enclosed tropical basin driven by seasonally reversing monsoon winds and a huge quantity of freshwater from rainfall and river runoff. The bay plays a fundamental role in controlling weather systems that make up the Asian summer monsoon system, including monsoon depressions and tropical cyclones. We have used a high resolution (~1 km) regional ocean model of the Bay of Bengal to explore the sub-mesoscale variability in the bay. Model simulations show that the East India Coastal Current (EICC) is extremely rich in submesoscale features compared to the open ocean and exhibit significant seasonal variations. Submesoscale activity over the EICC region is weakest during spring (March-May), slightly stronger during summer monsoon (June-September) and strongest during winter monsoon (November-January). Weak winds during spring and a huge fresh-water gain during summer monsoon tend to weaken submesoscale activity. Investigation of conversion rates of APE to KE...

Surface currents modify wind driven Ekman pumping in the ocean both by modifying the stress itself and by modifying the relationship between the stress and the Ekman transport. The former effect results in a strong mesoscale structure in the wind stress curl, such as is evident from scatterometer data. This mesoscale forcing is anti-correlated with surface vorticity and thus produces a strong damping effect on ocean eddies and currents. Recent work, however, suggests that this damping effect is over-represented in common parameterizations of the air-sea wind stress. The latter effect is referred to as nonlinear Ekman dynamics. These dynamics take the stress as given and add advective terms to the linear balance. Specifically, cross terms involving the Ekman and non-Ekman components of the flow are added to the linear Ekman balance. This is known to produce small scale (e.g., submesoscale) structures in the pumping velocity.

Here, we first review both the ocean surface velocity depen...

Surface currents modify wind driven Ekman pumping in the ocean both by modifying the stress itself and by modifying the relationship between the stress and the Ekman transport. The former effect results in a strong mesoscale structure in the wind stress curl, such as is evident from scatterometer data. This mesoscale forcing is anti-correlated with surface vorticity and thus produces a strong damping effect on ocean eddies and currents. Recent work, however, suggests that this damping effect is over-represented in common parameterizations of the air-sea wind stress. The latter effect is referred to as nonlinear Ekman dynamics. These dynamics take the stress as given and add advective terms to the linear balance. Specifically, cross terms involving the Ekman and non-Ekman components of the flow are added to the linear Ekman balance. This is known to produce small scale (e.g., submesoscale) structures in the pumping velocity.

Here, we first review both the ocean surface velocity depen...

Critical behaviour associated with the occurrence of tipping points is one of the key aspects of the dynamics of the Earth system. Criticality occurs in many different forms and with different characteristic spatial and temporal scales. Past critical transitions have sometimes been associated with mass extinction events, and the snowball/warm Earth dichotomy has played a major role in the emergence of multicellular life. Currently, anthropogenic forcing to the climate system seem to be bringing some multi stable subcomponents of the climate closer to a bifurcation point, as in the case of the Atlantic meridional overturning circulation and the Greenland ice sheet. We will present here a general mathematical framework to look into critical behaviour in the Earth system. We will connect the analysis of the response of the system to perturbation in connection to its global stability properties and discuss ideas for creating robust early warning signals.

Recent efforts in building data-driven surrogates for weather forecasting applications have received a lot of attention and garnered noticeable success. These autoregressive data-driven models yield significantly competitive short-term forecasting performance (often outperforming traditional numerical weather models) at a fraction of the computational cost of numerical models. However, these data-driven models do not remain stable when time-integrated for a long time. Such a long time-integration would provide (1) a method to seamlessly scale a weather model to a climate model and (2) gathering insights into the statistics of that climate system, e.g., the extreme events, owing to the cheap cost of generating multiple ensembles. While many studies have reported this instability, especially for data-driven models of turbulent flow, a causal mechanism for this instability is not clear. Most efforts to obtain stability are ad-hoc and empirical. In this work, we use a canonical quasi-geost...

Permafrost can potentially release more than twice as much carbon than is currently in the atmosphere, and is warming at a rate twice as fast as the rest of the planet. Fundamentally, the thawing permafrost is a phase transition phenomenon, where a solid turns to liquid, albeit on large regional scales and over a period of time that depends on environmental forcing and other factors. In this talk, we present mathematical models that help to understand the processes on the interface "frozen ground-atmosphere" and investigate their criticality.

Eddy viscosity is employed throughout the majority of numerical fluid dynamical models, and has been the subject of a vigorous body of research spanning a variety of disciplines. It has long been recognized that the proper description of eddy viscosity uses tensor mathematics, but in practice it is almost always employed as a scalar due to uncertainty about how to constrain the extra degrees of freedom and physical properties of its tensorial form. This talk will introduce techniques from outside the realm of geophysical fluid dynamics that allow us to consider the eddy viscosity tensor using its eigenvalues and eigenvectors, establishing a new framework by which tensorial eddy viscosity can be tested. This is made possible by a careful analysis of an operation called tensor unrolling, which casts the eigenvalue problem for a fourth-order tensor into a more familiar matrix-vector form, whereby it becomes far easier to understand and manipulate. New constraints are established for th...

Eddy viscosity is employed throughout the majority of numerical fluid dynamical models, and has been the subject of a vigorous body of research spanning a variety of disciplines. It has long been recognized that the proper description of eddy viscosity uses tensor mathematics, but in practice it is almost always employed as a scalar due to uncertainty about how to constrain the extra degrees of freedom and physical properties of its tensorial form. This talk will introduce techniques from outside the realm of geophysical fluid dynamics that allow us to consider the eddy viscosity tensor using its eigenvalues and eigenvectors, establishing a new framework by which tensorial eddy viscosity can be tested. This is made possible by a careful analysis of an operation called tensor unrolling, which casts the eigenvalue problem for a fourth-order tensor into a more familiar matrix-vector form, whereby it becomes far easier to understand and manipulate. New constraints are established for the e...