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  • Ocean  (3)
  • 33RO19970831-track; Algorithm; CT; DATE/TIME; Depth, bathymetric, interpolated/gridded; DEPTH, water; Distance; extracted from GLOBALVIEW-CO2; extracted from the 2-Minute Gridded Global Relief Data (ETOPO2); extracted from the NCEP/NCAR 40-Year Reanalysis Project; extracted from the World Ocean Atlas 2005; Fugacity of carbon dioxide (water) at equilibrator temperature (wet air); Fugacity of carbon dioxide (water) at sea surface temperature (wet air); LATITUDE; LONGITUDE; PACS_L3; Pressure, atmospheric, interpolated; Pressure at equilibration; Quality flag; Recomputed after SOCAT (Pfeil et al., 2013); Ronald H. Brown; Salinity; Salinity, interpolated; SOCAT; Surface Ocean CO2 Atlas Project; Temperature, water; Temperature at equilibration; Underway cruise track measurements; xCO2 (air), interpolated; xCO2 (water) at equilibrator temperature (dry air)  (2)
  • Air-sea interaction
  • Modeling
Collection
Keywords
Years
  • 1
    Publication Date: 2022-05-25
    Description: This paper is not subject to U.S. copyright. The definitive version was published in Deep Sea Research Part I: Oceanographic Research Papers 74 (2013): 48-63, doi:10.1016/j.dsr.2012.12.005.
    Description: Detection and attribution of hydrographic and biogeochemical changes in the deep ocean are challenging due to the small magnitude of their signals and to limitations in the accuracy of available data. However, there are indications that anthropogenic and climate change signals are starting to manifest at depth. The deep ocean below 2000 m comprises about 50% of the total ocean volume, and changes in the deep ocean should be followed over time to accurately assess the partitioning of anthropogenic carbon dioxide (CO2) between the ocean, terrestrial biosphere, and atmosphere. Here we determine the changes in the interior deep-water inorganic carbon content by a novel means that uses the partial pressure of CO2 measured at 20 °C, pCO2(20), along three meridional transects in the Atlantic and Pacific oceans. These changes are measured on decadal time scales using observations from the World Ocean Circulation Experiment (WOCE)/World Hydrographic Program (WHP) of the 1980s and 1990s and the CLIVAR/CO2 Repeat Hydrography Program of the past decade. The pCO2(20) values show a consistent increase in deep water over the time period. Changes in total dissolved inorganic carbon (DIC) content in the deep interior are not significant or consistent, as most of the signal is below the level of analytical uncertainty. Using an approximate relationship between pCO2(20) and DIC change, we infer DIC changes that are at the margin of detectability. However, when integrated on the basin scale, the increases range from 8–40% of the total specific water column changes over the past several decades. Patterns in chlorofluorocarbons (CFCs), along with output from an ocean model, suggest that the changes in pCO2(20) and DIC are of anthropogenic origin.
    Description: Rik Wanninkhof, Geun-Ha Park, John L. Bullister, and Richard A. Feely appreciate the support from the NOAA Office of Atmospheric and Oceanic Research and the Climate Observation Division. S.C.D. acknowledges support from NOAA Grant NA07OAR4310098. T.T. has been supported by grants from NSF and NOAA.
    Keywords: Ocean ; Carbon dioxide ; CO2 sink ; Anthropogenic carbon ; Deep-water
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
    Publication Date: 2022-05-25
    Description: Author Posting. © American Geophysical Union, 2004. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 109 (2004): C08S11, doi:10.1029/2003JC001831.
    Description: During the two recent GasEx field experiments, direct covariance measurements of air-sea carbon dioxide fluxes were obtained over the open ocean. Concurrently, the National Oceanic and Atmospheric Administration/Coupled-Ocean Atmospheric Response Experiment air-sea gas transfer parameterization was developed to predict gas transfer velocities from measurements of the bulk state of the sea surface and atmosphere. The model output is combined with measurements of the mean air and sea surface carbon dioxide fugacities to provide estimates of the air-sea CO2 flux, and the model is then tuned to the GasEx-1998 data set. Because of differences in the local environment and possibly because of weaknesses in the model, some discrepancies are observed between the predicted fluxes from the GasEx-1998 and GasEx-2001 cases. To provide an estimate of the contribution to the air-sea flux of gas due to wave-breaking processes, the whitecap and bubble parameterizations are removed from the model output. These results show that moderate (approximately 15 m s−1) wind speed breaking wave gas transfer processes account for a fourfold increase in the flux over the modeled interfacial processes.
    Description: This work was supported by the NOAA Office of Global Programs, under the leadership of Dr. Lisa Dilling. WHOI was supported by the National Science Foundation grant OCE-9711218.
    Keywords: Air-sea interaction ; Air-sea flux ; Air-gas transfer
    Repository Name: Woods Hole Open Access Server
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  • 3
    Publication Date: 2022-05-26
    Description: Author Posting. © American Geophysical Union, 2009. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 114 (2009): C12099, doi:10.1029/2009JC005835.
    Keywords: Modeling ; Climate ; Carbon
    Repository Name: Woods Hole Open Access Server
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  • 4
    Publication Date: 2022-05-26
    Description: Author Posting. © American Geophysical Union, 2009. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 114 (2009): C09013, doi:10.1029/2008JC005183.
    Description: Here we use observations and ocean models to identify mechanisms driving large seasonal to interannual variations in dissolved inorganic carbon (DIC) and dissolved oxygen (O2) in the upper ocean. We begin with observations linking variations in upper ocean DIC and O2 inventories with changes in the physical state of the ocean. Models are subsequently used to address the extent to which the relationships derived from short-timescale (6 months to 2 years) repeat measurements are representative of variations over larger spatial and temporal scales. The main new result is that convergence and divergence (column stretching) attributed to baroclinic Rossby waves can make a first-order contribution to DIC and O2 variability in the upper ocean. This results in a close correspondence between natural variations in DIC and O2 column inventory variations and sea surface height (SSH) variations over much of the ocean. Oceanic Rossby wave activity is an intrinsic part of the natural variability in the climate system and is elevated even in the absence of significant interannual variability in climate mode indices. The close correspondence between SSH and both DIC and O2 column inventories for many regions suggests that SSH changes (inferred from satellite altimetry) may prove useful in reducing uncertainty in separating natural and anthropogenic DIC signals (using measurements from Climate Variability and Predictability's CO2/Repeat Hydrography program).
    Description: This report was prepared by K.B.R. under awards NA17RJ2612 and NA08OAR4320752, which includes support through the NOAA Office of Climate Observations (OCO). The statements, findings, conclusions, and recommendations are those of the authors and do not necessarily reflect the views of the National Oceanic and Atmospheric Administration or the U.S. Department of Commerce. Support for K.B.R. was also provided by the Carbon Mitigation Initiative (CMI) through the support of BP, Amaco, and Ford. R.M.K. was supported by NOAA grants NA17RJ2612, NA08OAR4320752, and NA08OAR4310820. F.F.P. was supported by the European Union FP6 CARBOOCEAN Integrated project (contract 51176), the French OVIDE project, and the Spanish Salvador de Madariaga program (PR2006– 0523). This work was also supported by the European NOCES project (EVK2-CT201-00134). Y.Y. and A.I. are partly supported by CREST, JST of Japan. The long-term OISO observational program in the South Indian Ocean is supported by the following three French institutes: INSU (Institut National des Sciences de l’Univers), IPSL (Institute Pierre-Simon Laplace), and IPEV (Institut Paul-Emile Victor).
    Keywords: Modeling ; Climate ; Carbon
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 5
    Publication Date: 2022-12-06
    Description: © The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Boss, E., Waite, A., Karstensen, J., Trull, T., Muller-Karger, F., Sosik, H., Uitz, J., Acinas, S., Fennel, K., Berman-Frank, I., Thomalla, S., Yamazaki, H., Batten, S., Gregori, G., Richardson, A., & Wanninkhof, R. Recommendations for plankton measurements on OceanSITES moorings with relevance to other observing sites. Frontiers in Marine Science, 9, (2022): 929436, https://doi.org/10.3389/fmars.2022.929436.
    Description: Measuring plankton and associated variables as part of ocean time-series stations has the potential to revolutionize our understanding of ocean biology and ecology and their ties to ocean biogeochemistry. It will open temporal scales (e.g., resolving diel cycles) not typically sampled as a function of depth. In this review we motivate the addition of biological measurements to time-series sites by detailing science questions they could help address, reviewing existing technology that could be deployed, and providing examples of time-series sites already deploying some of those technologies. We consider here the opportunities that exist through global coordination within the OceanSITES network for long-term (climate) time series station in the open ocean. Especially with respect to data management, global solutions are needed as these are critical to maximize the utility of such data. We conclude by providing recommendations for an implementation plan.
    Description: This work was partially supported from funding to SCOR WG 154 (P-OBS) provided by national committees of the Scientific Committee on Oceanic Research (SCOR) and from a grant to SCOR from the U.S. National Science Foundation (OCE-1840868). FM-K acknowledges the support provided for participation by the Marine Biodiversity Observation Network (MBON) sponsored by NASA, NOAA, ONR, BOEM. HS acknowledges support from the Simons Foundation.
    Keywords: Plankton ; Ocean ; Measurements ; Sensors ; OceanSITES ; Ocean biology
    Repository Name: Woods Hole Open Access Server
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  • 6
    Publication Date: 2022-10-26
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Roemmich, D., Alford, M. H., Claustre, H., Johnson, K., King, B., Moum, J., Oke, P., Owens, W. B., Pouliquen, S., Purkey, S., Scanderbeg, M., Suga, T., Wijffels, S., Zilberman, N., Bakker, D., Baringer, M., Belbeoch, M., Bittig, H. C., Boss, E., Calil, P., Carse, F., Carval, T., Chai, F., Conchubhair, D. O., d'Ortenzio, F., Dall'Olmo, G., Desbruyeres, D., Fennel, K., Fer, I., Ferrari, R., Forget, G., Freeland, H., Fujiki, T., Gehlen, M., Greenan, B., Hallberg, R., Hibiya, T., Hosoda, S., Jayne, S., Jochum, M., Johnson, G. C., Kang, K., Kolodziejczyk, N., Kortzinger, A., Le Traon, P., Lenn, Y., Maze, G., Mork, K. A., Morris, T., Nagai, T., Nash, J., Garabato, A. N., Olsen, A., Pattabhi, R. R., Prakash, S., Riser, S., Schmechtig, C., Schmid, C., Shroyer, E., Sterl, A., Sutton, P., Talley, L., Tanhua, T., Thierry, V., Thomalla, S., Toole, J., Troisi, A., Trull, T. W., Turton, J., Velez-Belchi, P. J., Walczowski, W., Wang, H., Wanninkhof, R., Waterhouse, A. F., Waterman, S., Watson, A., Wilson, C., Wong, A. P. S., Xu, J., & Yasuda, I. On the future of Argo: A global, full-depth, multi-disciplinary array. Frontiers in Marine Science, 6, (2019): 439, doi:10.3389/fmars.2019.00439.
    Description: The Argo Program has been implemented and sustained for almost two decades, as a global array of about 4000 profiling floats. Argo provides continuous observations of ocean temperature and salinity versus pressure, from the sea surface to 2000 dbar. The successful installation of the Argo array and its innovative data management system arose opportunistically from the combination of great scientific need and technological innovation. Through the data system, Argo provides fundamental physical observations with broad societally-valuable applications, built on the cost-efficient and robust technologies of autonomous profiling floats. Following recent advances in platform and sensor technologies, even greater opportunity exists now than 20 years ago to (i) improve Argo’s global coverage and value beyond the original design, (ii) extend Argo to span the full ocean depth, (iii) add biogeochemical sensors for improved understanding of oceanic cycles of carbon, nutrients, and ecosystems, and (iv) consider experimental sensors that might be included in the future, for example to document the spatial and temporal patterns of ocean mixing. For Core Argo and each of these enhancements, the past, present, and future progression along a path from experimental deployments to regional pilot arrays to global implementation is described. The objective is to create a fully global, top-to-bottom, dynamically complete, and multidisciplinary Argo Program that will integrate seamlessly with satellite and with other in situ elements of the Global Ocean Observing System (Legler et al., 2015). The integrated system will deliver operational reanalysis and forecasting capability, and assessment of the state and variability of the climate system with respect to physical, biogeochemical, and ecosystems parameters. It will enable basic research of unprecedented breadth and magnitude, and a wealth of ocean-education and outreach opportunities.
    Description: DR, MS, and NZ were supported by the US Argo Program through the NOAA Grant NA15OAR4320071 (CIMEC). WO, SJ, and SWi were supported by the US Argo Program through the NOAA Grant NA14OAR4320158 (CINAR). EuroArgo scientists were supported by the two grants: (1) AtlantOS funding by the European Union’s Horizon 2020 Research and Innovation Programme under the Grant Agreement No. 633211 and (2) Monitoring the Oceans and Climate Change with Argo (MOCCA) Co-funded by the European Maritime and Fisheries Fund (EMFF) Project No. SI2.709624. This manuscript represents a contribution to the following research projects for HC, CaS, and FD: remOcean (funded by the European Research Council, grant 246777), NAOS (funded by the Agence Nationale de la Recherche in the frame of the French “Equipement d’avenir” program, grant ANR J11R107-F), AtlantOS (funded by the European Union’s Horizon 2020 Research and Innovation Programme, grant 2014-633211), and the BGC-Argo project funded by the CNES. DB was funded by the EU RINGO project (730944 H2020-INFRADEV-2016-1). RF was supported by the AGS-1835576. GCJ was supported by the Global Ocean Monitoring and Observing Program, National Oceanic and Atmospheric Administration (NOAA), U.S., and the Department of Commerce and NOAA Research. LT was funded under the SOCCOM Grant No. NSF PLR-1425989. VT’s contribution was supported by the French National Research Agency (ANR) through the EQUIPEX NAOS (Novel Argo Observing System) under the reference ANR-10-EQPX-40 and by the European H2020 Research and Innovation Programme through the AtlantOS project under the reference 633211. WW was supported by the Argo Poland program through the Ministry of Sciences and Higher Education Grant No. DIR/WK/2016/12. AmW was funded by the NSF-OCE1434722. K-RK is funded by the National Institute of Meteorological Sciences’ Research and Development Program “Development of Marine Meteorology Monitoring and Next-generation Ocean Forecasting System” under the grant KMA2018-00421. CSchmid is funded by NOAA/AOML and the US Argo Program through NOAA/OOMD. MBa is funded by NOAA/AOML.
    Keywords: Argo ; Floats ; Global ; Ocean ; Warming ; Circulation ; Temperature ; Salinity
    Repository Name: Woods Hole Open Access Server
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  • 7
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    PANGAEA
    In:  NOAA-Atlantic Oceanographic and Meteorological Laboratory, Miami
    Publication Date: 2024-02-17
    Keywords: 33RO19970831-track; Algorithm; CT; DATE/TIME; Depth, bathymetric, interpolated/gridded; DEPTH, water; Distance; extracted from GLOBALVIEW-CO2; extracted from the 2-Minute Gridded Global Relief Data (ETOPO2); extracted from the NCEP/NCAR 40-Year Reanalysis Project; extracted from the World Ocean Atlas 2005; Fugacity of carbon dioxide (water) at equilibrator temperature (wet air); Fugacity of carbon dioxide (water) at sea surface temperature (wet air); LATITUDE; LONGITUDE; PACS_L3; Pressure, atmospheric, interpolated; Pressure at equilibration; Quality flag; Recomputed after SOCAT (Pfeil et al., 2013); Ronald H. Brown; Salinity; Salinity, interpolated; SOCAT; Surface Ocean CO2 Atlas Project; Temperature, water; Temperature at equilibration; Underway cruise track measurements; xCO2 (air), interpolated; xCO2 (water) at equilibrator temperature (dry air)
    Type: Dataset
    Format: text/tab-separated-values, 18646 data points
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  • 8
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    Unknown
    PANGAEA
    In:  NOAA-Atlantic Oceanographic and Meteorological Laboratory, Miami
    Publication Date: 2024-02-17
    Keywords: 33RO19970831-track; Algorithm; CT; DATE/TIME; Depth, bathymetric, interpolated/gridded; DEPTH, water; Distance; extracted from GLOBALVIEW-CO2; extracted from the 2-Minute Gridded Global Relief Data (ETOPO2); extracted from the NCEP/NCAR 40-Year Reanalysis Project; extracted from the World Ocean Atlas 2005; Fugacity of carbon dioxide (water) at equilibrator temperature (wet air); Fugacity of carbon dioxide (water) at sea surface temperature (wet air); LATITUDE; LONGITUDE; PACS_L3; Pressure, atmospheric, interpolated; Pressure at equilibration; Quality flag; Recomputed after SOCAT (Pfeil et al., 2013); Ronald H. Brown; Salinity; Salinity, interpolated; SOCAT; Surface Ocean CO2 Atlas Project; Temperature, water; Temperature at equilibration; Underway cruise track measurements; xCO2 (air), interpolated; xCO2 (water) at equilibrator temperature (dry air)
    Type: Dataset
    Format: text/tab-separated-values, 18623 data points
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