Estimating temporal and spatial variation of ocean surface &amp;lt;i&amp;gt;p&amp;lt;/i&amp;gt;CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; in the North Pacific using a self-organizing map neural network technique

Nakaoka, Shin‐Ichiro; Telszewski, Maciej; Nojiri, Yukihiro; Yasunaka, Sayaka; Miyazaki, Chihiro; Mukai, Hirofumi; Usui, Norihisa

doi:10.5194/bg-10-6093-2013

Cited by 90 publications

(95 citation statements)

References 50 publications

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“…This nicely highlights the overall success of the scientific community in creating observational networks that reduce data coverage issues. The many scientific studies arising from this effort -among many others the recent publications by Nakaoka et al (2013), Landschützer et al (2013Landschützer et al ( , 2014, and Schuster et al (2013) -show that we have come a long way in understanding how ocean CO 2 chemistry is evolving in a world perturbed by fossil fuel emissions. The uncertainties in the trends presented here are, however, substantial and this largely prevents a more thorough understanding of current changes.…”

Section: Discussionmentioning

confidence: 99%

Trends and drivers in global surface ocean pH over the past 3 decades

et al. 2015

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Abstract.We report global long-term trends in surface ocean pH using a new pH data set computed by combining f CO 2 observations from the Surface Ocean CO 2 Atlas (SOCAT) version 2 with surface alkalinity estimates based on temperature and salinity. Trends were determined over the periods 1981-2011 and 1991-2011 for a set of 17 biomes using a weighted linear least squares method. We observe significant decreases in surface ocean pH in ∼ 70 % of all biomes and a mean rate of decrease of 0.0018 ± 0.0004 yr −1 for 1991-2011. We are not able to calculate a global trend for 1981-2011 because too few biomes have enough data for this. In half the biomes, the rate of change is commensurate with the trends expected based on the assumption that the surface ocean pH change is only driven by the surface ocean CO 2 chemistry remaining in a transient equilibrium with the increase in atmospheric CO 2 . In the remaining biomes, deviations from such equilibrium may reflect that the trend of surface ocean f CO 2 is not equal to that of the atmosphere, most notably in the equatorial Pacific Ocean, or may reflect changes in the oceanic buffer (Revelle) factor. We conclude that well-planned and long-term sustained observational networks are key to reliably document the ongoing and future changes in ocean carbon chemistry due to anthropogenic forcing.

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Section: Discussionmentioning

confidence: 99%

Trends and drivers in global surface ocean pH over the past 3 decades

et al. 2015

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“…These relationships were combined with satellite-derived fields of SST and other parameters to obtain the monthly fields of pCO 2 sw. Results from another empirical technique using a neural network (Nakaoka et al, 2013) that has been tested for the Atlantic Ocean (Telszewski et al, 2009) are also included for comparisons in the North Pacific extratropics (Table 1).…”

Section: Methodsmentioning

confidence: 99%

Air–sea CO2 flux in the Pacific Ocean for the period 1990–2009

et al. 2014

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Abstract. Air-sea CO 2 fluxes over the Pacific Ocean are known to be characterized by coherent large-scale structures that reflect not only ocean subduction and upwelling patterns, but also the combined effects of wind-driven gas exchange and biology. On the largest scales, a large net CO 2 influx into the extratropics is associated with a robust seasonal cycle, and a large net CO 2 efflux from the tropics is associated with substantial interannual variability. In this work, we have synthesized estimates of the net air-sea CO 2 flux from a variety of products, drawing upon a variety of approaches in three sub-basins of the Pacific Ocean, i.e., the North Pacific extratropics • N), the tropical Pacific (18 • S-18 • N), and the South Pacific extratropics (44.5-18 • S). These approaches include those based on the measurements of CO 2 partial pressure in surface seawater (pCO 2 sw), inversions of ocean-interior CO 2 data, forward ocean biogeochemistry models embedded in the ocean general circulation models (OBGCMs), a model with assimilation of pCO 2 sw data, and inversions of atmospheric CO 2 measurements. Long-term means, interannual variations and mean seasonal variations of the regionally integrated fluxes were compared in each of the sub-basins over the last two decades, spanning the period from 1990 through 2009. A simple average of the long-term mean fluxes obtained with surface water pCO 2 diagnostics and those obtained with ocean-interior CO 2 inversions are −0.47 ± 0.13 Pg C yr the North Pacific extratropics, +0.44 ± 0.14 Pg C yr −1 in the tropical Pacific, and −0.37 ± 0.08 Pg C yr −1 in the South Pacific extratropics, where positive fluxes are into the atmosphere. This suggests that approximately half of the CO 2 taken up over the North and South Pacific extratropics is released back to the atmosphere from the tropical Pacific. These estimates of the regional fluxes are also supported by the estimates from OBGCMs after adding the riverine CO 2 flux, i.e., −0.49 ± 0.02 Pg C yr −1 in the North Pacific extratropics, +0.41 ± 0.05 Pg C yr −1 in the tropical Pacific, and −0.39 ± 0.11 Pg C yr −1 in the South Pacific extratropics. The estimates from the atmospheric CO 2 inversions show large variations amongst different inversion systems, but their median fluxes are consistent with the estimates from climatological pCO 2 sw data and pCO 2 sw diagnostics. In the South Pacific extratropics, where CO 2 variations in the surface and ocean interior are severely undersampled, the difference in the air-sea CO 2 flux estimates between the diagnostic models and ocean-interior CO 2 inversions is larger (0.18 Pg C yr −1 ). The range of estimates from forward OBGCMs is also large (−0.19 to −0.72 Pg C yr −1 ). Regarding interannual variability of air-sea CO 2 fluxes, positive and negative anomalies are evident in the tropical Pacific during the cold and warm events of the El Niño-Southern Oscillation in the estimates from pCO 2 sw diagnostic models and from OBGCMs. They are consistent in phase with the Southern Oscillation In...

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“…The studies interpolate sparse pCO 2 data from a SOCAT or LDEO synthesis product in time and space by a gap-filling method. Approaches include statistical interpolation Goddijn-Murphy et al, 2015;, multiple linear regression Signorini et al, 2013;Iida et al, 2015), neural network approaches Nakaoka et al, 2013;Sasse et al, 2013;Zeng et al, 2014) and model-based regression and tuning (Valsala and Maksyutov, 2010;Majkut et al, 2014b). Mapping methods may be specific to individual regions ("biomes") (Signorini et al, 2013;Landschützer et al, 2014) or may apply to the full (global) domain (e.g.…”

Section: Scientific Applications Of Socatmentioning

confidence: 99%

A multi-decade record of high-quality fCO2 data in version 3 of the Surface Ocean CO2 Atlas (SOCAT)

Bakker

Pfeil

Landa

et al. 2016

Earth Syst. Sci. Data

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5,812

394

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A new feature is the data set quality control (QC) flag of E for data from alternative sensors and platforms. The accuracy of surface water f CO 2 has been defined for all data set QC flags. Automated range checking has been carried out for all data sets during their upload into SOCAT. The upgrade of the interactive Data Set Viewer (previously known as the Cruise Data Viewer) allows better interrogation of the SOCAT data collection and rapid creation of high-quality figures for scientific presentations. Automated data upload has been launched for version 4 and will enable more frequent SOCAT releases in the future. Highprofile scientific applications of SOCAT include quantification of the ocean sink for atmospheric carbon dioxide and its long-term variation, detection of ocean acidification, as well as evaluation of coupled-climate and ocean-only biogeochemical models. Users of SOCAT data products are urged to acknowledge the contribution of data providers, as stated in the SOCAT Fair Data Use Statement. This ESSD (Earth System Science Data) "living data" publication documents the methods and data sets used for the assembly of this new version of the SOCAT data collection and compares these with those used for earlier versions of the data collection Sabine et al., 2013;Bakker et al., 2014). Individual data set files, included in the synthesis product, can be downloaded here: doi:10.1594/PANGAEA.849770. The gridded products are available here:

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Estimating temporal and spatial variation of ocean surface <i>p</i>CO<sub>2</sub> in the North Pacific using a self-organizing map neural network technique

Cited by 90 publications

References 50 publications

Trends and drivers in global surface ocean pH over the past 3 decades

Trends and drivers in global surface ocean pH over the past 3 decades

Air–sea CO<sub>2</sub> flux in the Pacific Ocean for the period 1990–2009

A multi-decade record of high-quality <i>f</i>CO<sub>2</sub> data in version 3 of the Surface Ocean CO<sub>2</sub> Atlas (SOCAT)

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Estimating temporal and spatial variation of ocean surface &lt;i&gt;p&lt;/i&gt;CO&lt;sub&gt;2&lt;/sub&gt; in the North Pacific using a self-organizing map neural network technique

Cited by 90 publications

References 50 publications

Trends and drivers in global surface ocean pH over the past 3 decades

Trends and drivers in global surface ocean pH over the past 3 decades

Air–sea CO&lt;sub&gt;2&lt;/sub&gt; flux in the Pacific Ocean for the period 1990–2009

A multi-decade record of high-quality &lt;i&gt;f&lt;/i&gt;CO&lt;sub&gt;2&lt;/sub&gt; data in version 3 of the Surface Ocean CO&lt;sub&gt;2&lt;/sub&gt; Atlas (SOCAT)

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Estimating temporal and spatial variation of ocean surface <i>p</i>CO<sub>2</sub> in the North Pacific using a self-organizing map neural network technique

Air–sea CO<sub>2</sub> flux in the Pacific Ocean for the period 1990–2009

A multi-decade record of high-quality <i>f</i>CO<sub>2</sub> data in version 3 of the Surface Ocean CO<sub>2</sub> Atlas (SOCAT)