Unlocking a Global Ocean Mixing Dataset: Toward Standardization of Seismic-Derived Ocean Mixing Rates

混合(物理) 标准化 地质学 海洋学 气候学 环境科学 气象学 计算机科学 地理 量子力学 操作系统 物理
作者
Jingxuan Wei,Zeyu Zhao,Kathryn L. Gunn,S. P. S. Gulick,D. J. Shillington,Christopher M. Lowery
出处
期刊:Journal of Atmospheric and Oceanic Technology [American Meteorological Society]
卷期号:42 (6): 675-697
标识
DOI:10.1175/jtech-d-24-0076.1
摘要

Abstract Turbulent mixing is vital for water transformation in the ocean and sustains the global thermohaline circulation. Despite decades of global observations using different platforms, our understanding of ocean turbulence is still limited. More observations are needed to better characterize the spatiotemporal distribution of mixing to reduce uncertainties in climate models. Marine seismic reflection surveys are an untapped data resource for high-resolution ocean turbulence observation. Turbulent mixing can be extracted from seismic data through horizontal internal wave slope spectra. However, to date, a standardized approach to prepare seismic data for this spectral analysis is still lacking, leading to insufficient consideration of the impact of noise on the resulting diffusivities. To address these issues, we perform a full-wavefield synthetic modeling and processing to reveal noise-induced overestimation of diffusivities. We further propose a widely applicable workflow and apply it to three field seismic surveys with increasing noise levels conducted in regions of different turbulence environments: ocean ridges, open ocean interior, and continental slope. The derived diffusivities are benchmarked against direct measurements around the region to show the fidelity of this seismic method. The extended observation records by seismic data across the Kauai Channel and away from the Mid-Atlantic Ridges reveal the importance of topography in modifying the propagation of internal tides and the distribution of turbulent mixing in both near and far fields. Our proposed workflow marks a key advancement toward standardization of seismic-derived ocean mixing rates and holds the potential to unlock massive marine seismic reflection datasets worldwide for ocean mixing characterization.
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