The exchange of carbon dioxide between the ocean and the atmosphere tends to bring waters within the mixed layer toward equilibrium by reducing the partial pressure gradient across the air‐water interface. However, the equilibration process is not instantaneous; in general, there is a lag between forcing and response. The timescale of air‐sea equilibration depends on several factors involving the depth of the mixed layer, wind speed, and carbonate chemistry. We use a suite of observational data sets to generate climatological and seasonal composite maps of the air‐sea equilibration timescale. The relaxation timescale exhibits considerable spatial and seasonal variations that are largely set by changes in mixed layer depth and wind speed. The net effect is dominated by the mixed layer depth; the gas exchange velocity and carbonate chemistry parameters only provide partial compensation. Broadly speaking, the adjustment timescale tends to increase with latitude. We compare the observationally derived air‐sea gas exchange timescale with a model‐derived surface residence time and a data‐derived horizontal transport timescale, which allows us to define two nondimensional metrics of equilibration efficiency. These parameters highlight the tropics, subtropics, and northern North Atlantic as regions of inefficient air‐sea equilibration where carbon anomalies are relatively likely to persist. The efficiency parameters presented here can serve as simple tools for understanding the large‐scale persistence of air‐sea disequilibrium of CO2 in both observations and models.
Using synchrotron-based luminescence excitation spectroscopy in the energy range 4-20 eV at 8 K, the indirect-X optical band-gap transition in cubic boron nitride is determined as 6.36 ± 0.03 eV, and the quasi-direct band-gap energy of hexagonal boron nitride is determined as 5.96 ± 0.04 eV. The composition and structure of the materials are self-consistently established by optically detected x-ray absorption spectroscopy, and both x-ray diffraction and Raman measurements on the same samples give independent confirmation of their chemical and structural purity: together, the results are therefore considered as providing definitive measurements of the optical band-gap energies of the two materials.
Progress within physical oceanography has been concurrent with the increasing sophistication of tools available for its study. The incorporation of machine learning (ML) techniques offers exciting possibilities for advancing the capacity and speed of established methods and for making substantial and serendipitous discoveries. Beyond vast amounts of complex data ubiquitous in many modern scientific fields, the study of the ocean poses a combination of unique challenges that ML can help address. The observational data available is largely spatially sparse, limited to the surface, and with few time series spanning more than a handful of decades. Important timescales span seconds to millennia, with strong scale interactions and numerical modelling efforts complicated by details such as coastlines. This review covers the current scientific insight offered by applying ML and points to where there is imminent potential. We cover the main three branches of the field: observations, theory, and numerical modelling. Highlighting both challenges and opportunities, we discuss both the historical context and salient ML tools. We focus on the use of ML in situ sampling and satellite observations, and the extent to which ML applications can advance theoretical oceanographic exploration, as well as aid numerical simulations. Applications that are also covered include model error and bias correction and current and potential use within data assimilation. While not without risk, there is great interest in the potential benefits of oceanographic ML applications; this review caters to this interest within the research community.
Ocean ventilation is the transfer of tracers and young water from the surface down into the ocean interior. The tracers that can be transported to depth include anthropogenic heat and carbon, both of which are critical to understanding future climate trajectories. Ventilation occurs in both high- and midlatitude regions, but it is the southern midlatitudes that are responsible for the largest fraction of anthropogenic heat and carbon uptake; such Southern Ocean ventilation is the focus of this review. Southern Ocean ventilation occurs through a chain of interconnected mechanisms, including the zonally averaged meridional overturning circulation, localized subduction, eddy-driven mixing along isopycnals, and lateral transport by subtropical gyres. To unravel the complex pathways of ventilation and reconcile conflicting results, here we assess the relative contribution of each of thesemechanisms, emphasizing the three-dimensional and temporally varying nature of the ventilation of the Southern Ocean pycnocline. We conclude that Southern Ocean ventilation depends on multiple processes and that simplified frameworks that explain ventilation changes through a single process are insufficient.
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