Collaborative Research: Global Estimation of Lagrangian Characteristics of the Ocean Circulation

University Of Alaska Fairbanks Campus, Fairbanks AK

Investigators

Abstract

The ocean is a complex turbulent fluid that can be studied in the traditional fixed (Eulerian)coordinate system or a moving (Lagrangian) reference frame that follow the major ocean currents. Four key quantities that may be measured from Lagrangian data are the diffusivity, the Lagrangian integral timescale, the spin parameter and the spectral slope or (equivalently) the fractal dimension. The first three are of active interest to the oceanographic community due to their relevance for increasing the fidelity of the ocean circulation in large-scale ocean and climate models. The fourth quantity, the spectral slope, is potentially of equal importance, yet both its values and it meaning are largely unexplored, and it has yet to be examined on global scale. These Lagrangian characteristics are central to a number of important hypotheses; yet the difficulties in estimating them from data are well known and lead to outstanding uncertainties. As shown herein, these four quantities are tightly connected because they describe the four most important features of the frequency spectrum of Lagrangian velocities - a fact which suggests a new and unified approach to their analysis, by directly investigating the details of the spectrum itself. The proposed study will apply rigorous techniques from Big Data to estimate all four Lagrangian characteristics simultaneously from all available Lagrangian data. The result will be the highest resolution maps yet made of the Lagrangian characteristics, both at surface and at depth. The overarching goal of increasing the realism of the ocean circulation in climate models is a topic of great societal interest, because it would bolster climate variability adaptation and mitigation efforts. More immediately, this project will contribute to the maintenance, improvement, and broader distribution of the only active archive of acoustically tracked float data, one of the most valuable in situ windows into the ocean circulation. Innovative analysis algorithms developed or refined throughout this project will be openly shared with the community, contributing to the software infrastructure that supports scientific research. A new, highly optimized implementation of idealized numerical models for geophysical fluid dynamics will similarly be further developed, and distributed to community, during this project. The application of Big Data techniques to model output, allowing very large datasets to be reduced to much smaller numbers of parameters, will be particularly useful in future model/data intercomparisons. Finally, this project will support a graduate student, who will be trained in the application of Big Data techniques to analyzing numerical model output, as well as an early-career scientist. The approach will build on previous work in several important ways: (i) by making best use of available statistical information, thereby increasing the effective spatial resolution, perhaps dramatically; (ii) by avoiding potentially serious estimation errors arising from interactions of the four parameters; (iii) by allowing quantification of uncertainty; and (iv) by permitting the formal and systematic testing of a number of important physical hypothesis. A parallel analysis of a vastly larger ensemble of trajectories from a realistic model will allow quantification of uncertainties arising from data sparsity, and will enable the model's skill at reproducing observed Lagrangian features to be closely scrutinized. Finally, idealized numerical modeling and theory will provide the bridge to directly connect the observable features of Lagrangian trajectories with the underlying physics. The main intellectual contribution will be to answer a number of important questions, framed in detail herein, such as: Can the influence of surface quasigeostrophy, interior quasigeostrophy, and other processes be distinguished on the basis of their Lagrangian spectra? What does the Lagrangian spectral slope tell us about the nature of ocean turbulence? When and where is anisotropy necessary to effectively describe diffusivity? Does the spin parameter accurately capture the effect of coherent eddies on the background spectrum? These and other questions can be answered with the first global study of Lagrangian velocity spectra, with careful attention to quantifying errors and to establishing the correct physical interpretations of the controlling parameters in different regimes.