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- Author or Editor: Nathaniel L. Bindoff x
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Developing a New Oxygen Atlas of the World’s Oceans Using Data Interpolating Variational AnalysisAbstract
We present a new global oxygen atlas. This atlas uses all of the available full water column profiles of oxygen, salinity, and temperature available as part of the World Ocean Database released in 2018. Instead of optimal interpolation, we use the Data Interpolating Variational Analysis (DIVA) approach to map the available profiles onto 108 depth levels between the surface and 6800 m, covering more than 99% of ocean volume. This 1/2° × 1/2° atlas covers the period 1955–2018 in 1-yr intervals. The DIVA method has significant benefits over traditional optimal interpolation. It allows the explicit inclusion of advection and boundary constraints, thus offering improvements in the representations of oxygen, salinity, and temperature in regions of strong flow and near coastal boundaries. We demonstrate these benefits of this mapping approach with some examples from this atlas. We can explore the regional and temporal variations of oxygen in the global oceans. Preliminary analyses confirm earlier analyses that the oxygen minimum zone in the eastern Pacific Ocean has expanded and intensified. Oxygen inventory changes between 1970 and 2010 are assessed and compared against prior studies. We find that the full ocean oxygen inventory decreased by 0.84% ± 0.42%. For this period, temperature-driven solubility changes explain about 21% of the oxygen decline over the full water column; in the upper 100 m, solubility changes can explain all of the oxygen decrease; for the 100–600 m depth range, it can explain only 29%, 19% between 600 and 1000 m, and just 11% in the deep ocean.
Significance Statement
The purpose of this study is to create a new oxygen atlas of the world’s oceans using a technique that better represents the effects of ocean currents and topographic boundaries, and to investigate how oxygen in the ocean has changed over recent decades. We find the total quantity of oxygen in the world’s oceans has decreased by 0.84% since 1970, similar to previous studies. We also examine how much of this change can be explained by changes in water temperature; we find that this can explain all the changes in the upper 100 m but only 21% of the oxygen decline over the whole water column.
Abstract
We present a new global oxygen atlas. This atlas uses all of the available full water column profiles of oxygen, salinity, and temperature available as part of the World Ocean Database released in 2018. Instead of optimal interpolation, we use the Data Interpolating Variational Analysis (DIVA) approach to map the available profiles onto 108 depth levels between the surface and 6800 m, covering more than 99% of ocean volume. This 1/2° × 1/2° atlas covers the period 1955–2018 in 1-yr intervals. The DIVA method has significant benefits over traditional optimal interpolation. It allows the explicit inclusion of advection and boundary constraints, thus offering improvements in the representations of oxygen, salinity, and temperature in regions of strong flow and near coastal boundaries. We demonstrate these benefits of this mapping approach with some examples from this atlas. We can explore the regional and temporal variations of oxygen in the global oceans. Preliminary analyses confirm earlier analyses that the oxygen minimum zone in the eastern Pacific Ocean has expanded and intensified. Oxygen inventory changes between 1970 and 2010 are assessed and compared against prior studies. We find that the full ocean oxygen inventory decreased by 0.84% ± 0.42%. For this period, temperature-driven solubility changes explain about 21% of the oxygen decline over the full water column; in the upper 100 m, solubility changes can explain all of the oxygen decrease; for the 100–600 m depth range, it can explain only 29%, 19% between 600 and 1000 m, and just 11% in the deep ocean.
Significance Statement
The purpose of this study is to create a new oxygen atlas of the world’s oceans using a technique that better represents the effects of ocean currents and topographic boundaries, and to investigate how oxygen in the ocean has changed over recent decades. We find the total quantity of oxygen in the world’s oceans has decreased by 0.84% since 1970, similar to previous studies. We also examine how much of this change can be explained by changes in water temperature; we find that this can explain all the changes in the upper 100 m but only 21% of the oxygen decline over the whole water column.
Abstract
This paper presents a modified objective mapping technique that takes advantage of the strong vertical correlations in ocean temperature profiles. This technique has been used here successfully to generate a uniformly gridded upper-ocean temperature dataset in the southwest Pacific Ocean region from most of the available bathythermograph casts collected between 0°–50°S and 140°E–180°, covering the period from 1955 to 1988. Important advantages of this technique over most previous objective methods are its (i) ability to deal with four-dimensional data (space and time), (ii) improved estimate of the first-guess (polynomial) mean, (iii) preservation of the vertical structure of the ocean temperature data, (iv) computational efficiency, and (v) objective error analysis.
The technique combines empirical orthogonal function (EOF) analysis, using the singular value decomposition, and objective mapping. In this application of the method, a digital “atlas” of upper-ocean temperatures has been created on a grid 2° × 2°, at 5-m depth intervals, and comprises a monthly climatology and two three-monthly time series (January, April, July, and October). The time series include a dataset from 1955 to 1988 to 100-m depth, and a shorter period, deeper dataset from 1973 to 1988 to 450-m depth. Only the first five vertical EOFs are needed to explain about 90% of the total variance in the data and to within the a priori noise estimates. The full four-dimensional temperature field was reconstructed using objective maps of the horizontal coefficients corresponding to each of the significant vertical EOFs. Although the method is statistically suboptimal, the final mapped temperature fields are unbiased and consistent with the a priori noise. In this application, the computing time is reduced by a factor of 36, making the mapping procedure feasible on modern workstations.
Abstract
This paper presents a modified objective mapping technique that takes advantage of the strong vertical correlations in ocean temperature profiles. This technique has been used here successfully to generate a uniformly gridded upper-ocean temperature dataset in the southwest Pacific Ocean region from most of the available bathythermograph casts collected between 0°–50°S and 140°E–180°, covering the period from 1955 to 1988. Important advantages of this technique over most previous objective methods are its (i) ability to deal with four-dimensional data (space and time), (ii) improved estimate of the first-guess (polynomial) mean, (iii) preservation of the vertical structure of the ocean temperature data, (iv) computational efficiency, and (v) objective error analysis.
The technique combines empirical orthogonal function (EOF) analysis, using the singular value decomposition, and objective mapping. In this application of the method, a digital “atlas” of upper-ocean temperatures has been created on a grid 2° × 2°, at 5-m depth intervals, and comprises a monthly climatology and two three-monthly time series (January, April, July, and October). The time series include a dataset from 1955 to 1988 to 100-m depth, and a shorter period, deeper dataset from 1973 to 1988 to 450-m depth. Only the first five vertical EOFs are needed to explain about 90% of the total variance in the data and to within the a priori noise estimates. The full four-dimensional temperature field was reconstructed using objective maps of the horizontal coefficients corresponding to each of the significant vertical EOFs. Although the method is statistically suboptimal, the final mapped temperature fields are unbiased and consistent with the a priori noise. In this application, the computing time is reduced by a factor of 36, making the mapping procedure feasible on modern workstations.
