Articles | Volume 17, issue 16
https://doi.org/10.5194/gmd-17-6415-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-6415-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
30 Aug 2024
Development and technical paper |
| 30 Aug 2024
| 30 Aug 2024
LIGHT-bgcArgo-1.0: using synthetic float capabilities in E3SMv2 to assess spatiotemporal variability in ocean physics and biogeochemistry
Department of Atmospheric and Oceanic Sciences and Institute of Arctic and Alpine Research, University of Colorado, Boulder, Boulder, CO, USA
Nicole S. Lovenduski
Department of Atmospheric and Oceanic Sciences and Institute of Arctic and Alpine Research, University of Colorado, Boulder, Boulder, CO, USA
Mathew Maltrud
Fluid Dynamics and Solid Mechanics (T-3), Los Alamos National Laboratory, Los Alamos, NM, USA
Alison R. Gray
School of Oceanography, University of Washington, Seattle, WA, USA
Yohei Takano
Fluid Dynamics and Solid Mechanics (T-3), Los Alamos National Laboratory, Los Alamos, NM, USA
Polar Oceans Team, British Antarctic Survey, Cambridge, United Kingdom
Kristen Falcinelli
School of Oceanography, University of Washington, Seattle, WA, USA
Jade Sauvé
School of Oceanography, University of Washington, Seattle, WA, USA
Katherine Smith
Fluid Dynamics and Solid Mechanics (T-3), Los Alamos National Laboratory, Los Alamos, NM, USA
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Stephen G. Yeager, Nan Rosenbloom, Anne A. Glanville, Xian Wu, Isla Simpson, Hui Li, Maria J. Molina, Kristen Krumhardt, Samuel Mogen, Keith Lindsay, Danica Lombardozzi, Will Wieder, Who M. Kim, Jadwiga H. Richter, Matthew Long, Gokhan Danabasoglu, David Bailey, Marika Holland, Nicole Lovenduski, Warren G. Strand, and Teagan King
Geosci. Model Dev., 15, 6451–6493, https://doi.org/10.5194/gmd-15-6451-2022, https://doi.org/10.5194/gmd-15-6451-2022, 2022
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The Earth system changes over a range of time and space scales, and some of these changes are predictable in advance. Short-term weather forecasts are most familiar, but recent work has shown that it is possible to generate useful predictions several seasons or even a decade in advance. This study focuses on predictions over intermediate timescales (up to 24 months in advance) and shows that there is promising potential to forecast a variety of changes in the natural environment.
Isabelle Steinke, Paul J. DeMott, Grant B. Deane, Thomas C. J. Hill, Mathew Maltrud, Aishwarya Raman, and Susannah M. Burrows
Atmos. Chem. Phys., 22, 847–859, https://doi.org/10.5194/acp-22-847-2022, https://doi.org/10.5194/acp-22-847-2022, 2022
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Over the oceans, sea spray aerosol is an important source of particles that may initiate the formation of cloud ice, which then has implications for the radiative properties of marine clouds. In our study, we focus on marine biogenic particles that are emitted episodically and develop a numerical framework to describe these emissions. We find that further cloud-resolving model studies and targeted observations are needed to fully understand the climate impacts from marine biogenic particles.
Katherine M. Smith, Skyler Kern, Peter E. Hamlington, Marco Zavatarelli, Nadia Pinardi, Emily F. Klee, and Kyle E. Niemeyer
Geosci. Model Dev., 14, 2419–2442, https://doi.org/10.5194/gmd-14-2419-2021, https://doi.org/10.5194/gmd-14-2419-2021, 2021
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We present a newly developed reduced-order biogeochemical flux model that is complex and flexible enough to capture open-ocean ecosystem dynamics but reduced enough to incorporate into highly resolved numerical simulations with limited additional computational cost. The model provides improved correlations between model output and field data, indicating that significant improvements in the reproduction of real-world data can be achieved with a small number of variables.
Cara Nissen and Meike Vogt
Biogeosciences, 18, 251–283, https://doi.org/10.5194/bg-18-251-2021, https://doi.org/10.5194/bg-18-251-2021, 2021
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Cited articles
Allison, L. C., Roberts, C. D., Palmer, M. D., Hermanson, L., Killick, R. E., Rayner, N. A., Smith, D. M., and Andrews, M. B.: Towards quantifying uncertainty in ocean heat content changes using synthetic profiles, Enviro. Res. Lett., 14, 084037, https://doi.org/10.1088/1748-9326/ab2b0b, 2019. a
André, X., Le Traon, P.-Y., Le Reste, S., Dutreuil, V., Leymarie, E., Malardé, D., Marec, C., Sagot, J., Amice, M., Babin, M., Claustre, H., David, A., D'Ortenzio, F., Kolodziejczyk, N., Lagunas, J. L., Le Menn, M., Moreau, B., Nogré, D., Penkerc'h, C., Poteau, A., Renaut, C., Schaeffer, C., Taillandier, V., and Thierry, V.: Preparing the New Phase of Argo: Technological Developments on Profiling Floats in the NAOS Project, Front. Mar. Sci., 7, 1–22, https://doi.org/10.3389/fmars.2020.577446, 2020. a
Argo: Argo float data and metadata from Global Data Assembly Centre (Argo GDAC) – Snapshot of Argo GDAC of March 10st 2023, SEANOE [data set], https://doi.org/10.17882/42182#100487, 2023. a, b, c
Arteaga, L. A., Boss, E., Behrenfeld, M. J., Westberry, T. K., and Sarmiento, J. L.: Seasonal modulation of phytoplankton biomass in the Southern Ocean, Nat. Commun., 11, 5364, https://doi.org/10.1038/s41467-020-19157-2, 2020. a, b
Behrenfeld, M. J. and Falkowski, P. G.: Photosynthetic rates derived from satellite-based chlorophyll concentration, Limnol. Oceanogr., 42, 1–20, https://doi.org/10.4319/lo.1997.42.1.0001, 1997. a
Bittig, H. C., Maurer, T. L., Plant, J. N., Schmechtig, C., Wong, A. P. S., Claustre, H., Trull, T. W., Udaya Bhaskar, T. V. S., Boss, E., Dall'Olmo, G., Organelli, E., Poteau, A., Johnson, K. S., Hanstein, C., Leymarie, E., Le Reste, S., Riser, S. C., Rupan, A. R., Taillandier, V., Thierry, V., and Xing, X.: A BGC-Argo Guide: Planning, Deployment, Data Handling and Usage, Front. Mar. Sci., 6, https://doi.org/10.3389/fmars.2019.00502, 2019. a
Blunden, J. and Arndt, D. S.: State of the Climate in 2016, B. Am. Meteorol. Soc., 98, Si–S280, https://doi.org/10.1175/2017BAMSStateoftheClimate.1, 2017. a
Brady, R. X., Maltrud, M. E., Wolfram, P. J., Drake, H. F., and Lovenduski, N. S.: The Influence of Ocean Topography on the Upwelling of Carbon in the Southern Ocean, Geophys. Res. Lett., 48, 1–11, https://doi.org/10.1029/2021GL095088, 2021. a, b, c, d
Burrows, S. M., Maltrud, M., Yang, X., Zhu, Q., Jeffery, N., Shi, X., Ricciuto, D., Wang, S., Bisht, G., Tang, J., Wolfe, J., Harrop, B. E., Singh, B., Brent, L., Baldwin, S., Zhou, T., Cameron-Smith, P., Keen, N., Collier, N., Xu, M., Hunke, E. C., Elliott, S. M., Turner, A. K., Li, H., Wang, H., Golaz, J.-C., Bond-Lamberty, B., Hoffman, F. M., Riley, W. J., Thornton, P. E., Calvin, K., and Leung, L. R.: The DOE E3SM v1.1 Biogeochemistry Configuration: Description and Simulated Ecosystem‐Climate Responses to Historical Changes in Forcing, J. Adv. Model. Earth Sys., 12, e2019MS001766, https://doi.org/10.1029/2019MS001766, 2020. a
Chai, F., Johnson, K. S., Claustre, H., Xing, X., Wang, Y., Boss, E., Riser, S., Fennel, K., Schofield, O., and Sutton, A.: Monitoring ocean biogeochemistry with autonomous platforms, Nat. Rev. Earth Environ., 1, 315–326, https://doi.org/10.1038/s43017-020-0053-y, 2020. a
Chamberlain, P., Cornuelle, B., Talley, L. D., Speer, K., Hancock, C., and Riser, S.: Acoustic Float Tracking with the Kalman Smoother, J. Atmos. Ocean. Tech., 40, 15–35, https://doi.org/10.1175/JTECH-D-21-0063.1, 2022. a
Chamberlain, P., Talley, L. D., Cornuelle, B., Mazloff, M., and Gille, S. T.: Optimizing the Biogeochemical Argo Float Distribution, J. Atmos. Ocean. Tech., 40, 1355–1379, https://doi.org/10.1175/JTECH-D-22-0093.1, 2023. a
Chamberlain, P. M., Talley, L. D., Mazloff, M. R., Riser, S. C., Speer, K., Gray, A. R., and Schwartzman, A.: Observing the Ice‐Covered Weddell Gyre With Profiling Floats: Position Uncertainties and Correlation Statistics, J. Geophys. Res.-Oceans, 123, 8383–8410, https://doi.org/10.1029/2017JC012990, 2018. a, b, c
Chelton, D. B., DeSzoeke, R. A., Schlax, M. G., El Naggar, K., and Siwertz, N.: Geographical Variability of the First Baroclinic Rossby Radius of Deformation, J. Phys. Oceanogr., 28, 433–460, https://doi.org/10.1175/1520-0485(1998)028<0433:GVOTFB>2.0.CO;2, 1998. a
Claustre, H., Johnson, K. S., and Takeshita, Y.: Observing the Global Ocean with Biogeochemical-Argo, Annu. Rev. Mar. Sci., 12, 23–48, https://doi.org/10.1146/annurev-marine-010419-010956, 2020. a
Clow, G. L., Lovenduski, N. S., Levy, M. N., Lindsay, K., and Kay, J. E.: The utility of simulated ocean chlorophyll observations: a case study with the Chlorophyll Observation Simulator Package (version 1) in CESMv2.2, Geosci. Model Dev., 17, 975–995, https://doi.org/10.5194/gmd-17-975-2024, 2024. a, b, c
Cornec, M., Claustre, H., Mignot, A., Guidi, L., Lacour, L., Poteau, A., D'Ortenzio, F., Gentili, B., and Schmechtig, C.: Deep Chlorophyll Maxima in the Global Ocean: Occurrences, Drivers and Characteristics, Global Biogeochem. Cy., 35, 1–30, https://doi.org/10.1029/2020GB006759, 2021. a, b, c
Droste, E. S., Hoppema, M., González-Dávila, M., Santana-Casiano, J. M., Queste, B. Y., Dall'Olmo, G., Venables, H. J., Rohardt, G., Ossebaar, S., Schuller, D., Trace-Kleeberg, S., and Bakker, D. C. E.: The influence of tides on the marine carbonate chemistry of a coastal polynya in the south-eastern Weddell Sea, Ocean Sci., 18, 1293–1320, https://doi.org/10.5194/os-18-1293-2022, 2022. a, b
Eayrs, C., Holland, D., Francis, D., Wagner, T., Kumar, R., and Li, X.: Understanding the Seasonal Cycle of Antarctic Sea Ice Extent in the Context of Longer‐Term Variability, Rev. Geophys., 57, 1037–1064, https://doi.org/10.1029/2018RG000631, 2019. a
Energy Exascale Earth System Model Program: Energy Exascale Earth System Model (E3SMv2) code with Argo float simulator, Zenodo [code], https://doi.org/10.5281/zenodo.10094349, 2023. a
Eveleth, R., Cassar, N., Doney, S. C., Munro, D. R., and Sweeney, C.: Biological and physical controls on O2/Ar, Ar and pCO2 variability at the Western Antarctic Peninsula and in the Drake Passage, Deep-Sea Res. Pt. II, 139, 77–88, https://doi.org/10.1016/j.dsr2.2016.05.002, 2017. a, b
Fay, A. R. and McKinley, G. A.: Global open-ocean biomes: mean and temporal variability, Earth Syst. Sci. Data, 6, 273–284, https://doi.org/10.5194/essd-6-273-2014, 2014. a
Ford, D.: Assimilating synthetic Biogeochemical-Argo and ocean colour observations into a global ocean model to inform observing system design, Biogeosciences, 18, 509–534, https://doi.org/10.5194/bg-18-509-2021, 2021. a, b
Garry, F. K., McDonagh, E. L., Blaker, A. T., Roberts, C. D., Desbruyères, D. G., Frajka-Williams, E., and King, B. A.: Model-Derived Uncertainties in Deep Ocean Temperature Trends Between 1990 and 2010, J. Geophys. Res.-Oceans, 124, 1155–1169, https://doi.org/10.1029/2018JC014225, 2019. a
Gasparin, F., Hamon, M., Rémy, E., and Le Traon, P.-Y.: How Deep Argo Will Improve the Deep Ocean in an Ocean Reanalysis, J. Climate, 33, 77–94, https://doi.org/10.1175/JCLI-D-19-0208.1, 2020. a, b, c
Gille, S. T. and Romero, L.: Statistical Behavior of ALACE Floats at the Surface of the Southern Ocean, J. Atmos. Ocean. Tech., 20, 1633–1640, https://doi.org/10.1175/1520-0426(2003)020<1633:SBOAFA>2.0.CO;2, 2003. a, b
Gloege, L., McKinley, G. A., Landschützer, P., Fay, A. R., Frölicher, T. L., Fyfe, J. C., Ilyina, T., Jones, S., Lovenduski, N. S., Rodgers, K. B., Schlunegger, S., and Takano, Y.: Quantifying Errors in Observationally Based Estimates of Ocean Carbon Sink Variability, Global Biogeochem. Cy., 35, 1–14, https://doi.org/10.1029/2020GB006788, 2021. a, b, c
Golaz, J., Caldwell, P. M., Van Roekel, L. P., Petersen, M. R., Tang, Q., Wolfe, J. D., Abeshu, G., Anantharaj, V., Asay‐Davis, X. S., Bader, D. C., Baldwin, S. A., Bisht, G., Bogenschutz, P. A., Branstetter, M., Brunke, M. A., Brus, S. R., Burrows, S. M., Cameron‐Smith, P. J., Donahue, A. S., Deakin, M., Easter, R. C., Evans, K. J., Feng, Y., Flanner, M., Foucar, J. G., Fyke, J. G., Griffin, B. M., Hannay, C., Harrop, B. E., Hoffman, M. J., Hunke, E. C., Jacob, R. L., Jacobsen, D. W., Jeffery, N., Jones, P. W., Keen, N. D., Klein, S. A., Larson, V. E., Leung, L. R., Li, H., Lin, W., Lipscomb, W. H., Ma, P., Mahajan, S., Maltrud, M. E., Mametjanov, A., McClean, J. L., McCoy, R. B., Neale, R. B., Price, S. F., Qian, Y., Rasch, P. J., Reeves Eyre, J. E. J., Riley, W. J., Ringler, T. D., Roberts, A. F., Roesler, E. L., Salinger, A. G., Shaheen, Z., Shi, X., Singh, B., Tang, J., Taylor, M. A., Thornton, P. E., Turner, A. K., Veneziani, M., Wan, H., Wang, H., Wang, S., Williams, D. N., Wolfram, P. J., Worley, P. H., Xie, S., Yang, Y., Yoon, J., Zelinka, M. D., Zender, C. S., Zeng, X., Zhang, C., Zhang, K., Zhang, Y., Zheng, X., Zhou, T., and Zhu, Q.: The DOE E3SM Coupled Model Version 1: Overview and Evaluation at Standard Resolution, J. Adv. Model. Earth Sy., 11, 2089–2129, https://doi.org/10.1029/2018MS001603, 2019. a
Golaz, J. C., Van Roekel, L. P., Zheng, X., Roberts, A. F., Wolfe, J. D., Lin, W., Bradley, A. M., Tang, Q., Maltrud, M. E., Forsyth, R. M., Zhang, C., Zhou, T., Zhang, K., Zender, C. S., Wu, M., Wang, H., Turner, A. K., Singh, B., Richter, J. H., Qin, Y., Petersen, M. R., Mametjanov, A., Ma, P. L., Larson, V. E., Krishna, J., Keen, N. D., Jeffery, N., Hunke, E. C., Hannah, W. M., Guba, O., Griffin, B. M., Feng, Y., Engwirda, D., Di Vittorio, A. V., Dang, C., Conlon, L. A. M., Chen, C. C. J., Brunke, M. A., Bisht, G., Benedict, J. J., Asay-Davis, X. S., Zhang, Y., Zhang, M., Zeng, X., Xie, S., Wolfram, P. J., Vo, T., Veneziani, M., Tesfa, T. K., Sreepathi, S., Salinger, A. G., Reeves Eyre, J. E., Prather, M. J., Mahajan, S., Li, Q., Jones, P. W., Jacob, R. L., Huebler, G. W., Huang, X., Hillman, B. R., Harrop, B. E., Foucar, J. G., Fang, Y., Comeau, D. S., Caldwell, P. M., Bartoletti, T., Balaguru, K., Taylor, M. A., McCoy, R. B., Leung, L. R., and Bader, D. C.: The DOE E3SM Model Version 2: Overview of the Physical Model and Initial Model Evaluation, J. Adv. Model. Earth Sy., 14, 1–51, https://doi.org/10.1029/2022MS003156, 2022. a, b
Gray, A. R., Johnson, K. S., Bushinsky, S. M., Riser, S. C., Russell, J. L., Talley, L. D., Wanninkhof, R., Williams, N. L., and Sarmiento, J. L.: Autonomous Biogeochemical Floats Detect Significant Carbon Dioxide Outgassing in the High-Latitude Southern Ocean, Geophys. Res. Lett., 45, 9049–9057, https://doi.org/10.1029/2018GL078013, 2018. a
Gruber, N., Boyd, P. W., Frölicher, T. L., and Vogt, M.: Biogeochemical extremes and compound events in the ocean, Nature, 600, 395–407, https://doi.org/10.1038/s41586-021-03981-7, 2021. a
Hague, M. and Vichi, M.: Southern Ocean Biogeochemical Argo detect under-ice phytoplankton growth before sea ice retreat, Biogeosciences, 18, 25–38, https://doi.org/10.5194/bg-18-25-2021, 2021. a
Hauck, J., Nissen, C., Landschützer, P., Rödenbeck, C., Bushinsky, S., and Olsen, A.: Sparse observations induce large biases in estimates of the global ocean CO2 sink: An ocean model subsampling experiment, Philos. T. Roy. Soc. A, 381, 20220063, https://doi.org/10.1098/rsta.2022.0063, 2023. a, b
Heimdal, T. H., McKinley, G. A., Sutton, A. J., Fay, A. R., and Gloege, L.: Assessing improvements in global ocean pCO2 machine learning reconstructions with Southern Ocean autonomous sampling, Biogeosciences, 21, 2159–2176, https://doi.org/10.5194/bg-21-2159-2024, 2024. a
Helmuth, B., Russell, B. D., Connell, S. D., Dong, Y., Harley, C. D., Lima, F. P., Sará, G., Williams, G. A., and Mieszkowska, N.: Beyond long-term averages: making biological sense of a rapidly changing world, Climate Change Responses, 1, 6, https://doi.org/10.1186/s40665-014-0006-0, 2014. a
Hoppema, M.: Weddell Sea is a globally significant contributor to deep-sea sequestration of natural carbon dioxide, Deep-Sea Res. Pt. I, 51, 1169–1177, https://doi.org/10.1016/j.dsr.2004.02.011, 2004. a
Jeffery, N., Maltrud, M. E., Hunke, E. C., Wang, S., Wolfe, J., Turner, A. K., Burrows, S. M., Shi, X., Lipscomb, W. H., Maslowski, W., and Calvin, K. V.: Investigating controls on sea ice algal production using E3SMv1.1-BGC, Ann. Glaciol., 61, 51–72, https://doi.org/10.1017/aog.2020.7, 2020. a
Johnson, G. C., Lyman, J. M., and Purkey, S. G.: Informing Deep Argo Array Design Using Argo and Full-Depth Hydrographic Section Data, J. Atmos. Ocean. Tech., 32, 2187–2198, https://doi.org/10.1175/JTECH-D-15-0139.1, 2015. a, b, c, d
Johnson, G. C., Hosoda, S., Jayne, S. R., Oke, P. R., Riser, S. C., Roemmich, D., Suga, T., Thierry, V., Wijffels, S. E., and Xu, J.: Argo – Two Decades: Global Oceanography, Revolutionized, Annu. Re. Mar. Sci., 14, 379–403, https://doi.org/10.1146/annurev-marine-022521-102008, 2022. a, b
Johnson, K. S., Plant, J. N., Dunne, J. P., Talley, L. D., and Sarmiento, J. L.: Annual nitrate drawdown observed by SOCCOM profiling floats and the relationship to annual net community production, J. Geophys. Res.-Oceans, 122, 6668–6683, https://doi.org/10.1002/2017JC012839, 2017. a
Kapsenberg, L. and Cyronak, T.: Ocean acidification refugia in variable environments, Glob. Change Biol., 25, 3201–3214, https://doi.org/10.1111/gcb.14730, 2019. a, b
Kawai, Y. and Wada, A.: Diurnal sea surface temperature variation and its impact on the atmosphere and ocean: A review, J. Oceanogr., 63, 721–744, https://doi.org/10.1007/s10872-007-0063-0, 2007. a
King, B., Thierry, V., Zilberman, N., and Walicka, K.: 3rd Deep-Argo Workshop Report, Tech. rep., https://www.euro-argo.eu/content/download/159856/file/DeepArgoWorkshop2021-Report.pdf (last access: 20 October 2023), 2021. a
Klatt, O., Boebel, O., and Fahrbach, E.: A Profiling Float's Sense of Ice, J. Atmos. Ocean. Tech., 24, 1301–1308, https://doi.org/10.1175/JTECH2026.1, 2007. a, b, c, d
Lamarque, J.-F., Bond, T. C., Eyring, V., Granier, C., Heil, A., Klimont, Z., Lee, D., Liousse, C., Mieville, A., Owen, B., Schultz, M. G., Shindell, D., Smith, S. J., Stehfest, E., Van Aardenne, J., Cooper, O. R., Kainuma, M., Mahowald, N., McConnell, J. R., Naik, V., Riahi, K., and van Vuuren, D. P.: Historical (1850–2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: methodology and application, Atmos. Chem. Phys., 10, 7017–7039, https://doi.org/10.5194/acp-10-7017-2010, 2010. a
Landschützer, P., Gruber, N., Bakker, D. C. E., Stemmler, I., and Six, K. D.: Strengthening seasonal marine CO2 variations due to increasing atmospheric CO2, Nat. Clim. Change, 8, 146–150, https://doi.org/10.1038/s41558-017-0057-x, 2018. a
Long, M. C., Moore, J. K., Lindsay, K., Levy, M., Doney, S. C., Luo, J. Y., Krumhardt, K. M., Letscher, R. T., Grover, M., and Sylvester, Z. T.: Simulations With the Marine Biogeochemistry Library (MARBL), J. Adv. Model. Earth Sy., 13, e2021MS002647, https://doi.org/10.1029/2021MS002647, 2021. a, b
Longhurst, A.: Seasonal cycles of pelagic production and consumption, Prog. Oceanogr., 36, 77–167, https://doi.org/10.1016/0079-6611(95)00015-1, 1995. a
Luo, C., Mahowald, N. M., and del Corral, J.: Sensitivity study of meteorological parameters on mineral aerosol mobilization, transport, and distribution, J. Geophys. Res.-Atmos., 108, 4447, https://doi.org/10.1029/2003JD003483, 2003. a
Matsumoto, G. I., Johnson, K. S., Riser, S., Talley, L., Wijffels, S., and Hotinski, R.: The Global Ocean Biogeochemistry (GO-BGC) Array of Profiling Floats to Observe Changing Ocean Chemistry and Biology, Mar. Technol. Soc. J., 56, 122–123, https://doi.org/10.4031/MTSJ.56.3.25, 2022. a
Mayorga, E., Seitzinger, S. P., Harrison, J. A., Dumont, E., Beusen, A. H., Bouwman, A., Fekete, B. M., Kroeze, C., and Van Drecht, G.: Global Nutrient Export from WaterSheds 2 (NEWS 2): Model development and implementation, Environ. Modell. Softw., 25, 837–853, https://doi.org/10.1016/j.envsoft.2010.01.007, 2010. a
McKee, D. C., Doney, S. C., Della Penna, A., Boss, E. S., Gaube, P., Behrenfeld, M. J., and Glover, D. M.: Lagrangian and Eulerian time and length scales of mesoscale ocean chlorophyll from Bio-Argo floats and satellites, Biogeosciences, 19, 5927–5952, https://doi.org/10.5194/bg-19-5927-2022, 2022. a, b
Meinshausen, M., Vogel, E., Nauels, A., Lorbacher, K., Meinshausen, N., Etheridge, D. M., Fraser, P. J., Montzka, S. A., Rayner, P. J., Trudinger, C. M., Krummel, P. B., Beyerle, U., Canadell, J. G., Daniel, J. S., Enting, I. G., Law, R. M., Lunder, C. R., O'Doherty, S., Prinn, R. G., Reimann, S., Rubino, M., Velders, G. J. M., Vollmer, M. K., Wang, R. H. J., and Weiss, R.: Historical greenhouse gas concentrations for climate modelling (CMIP6), Geosci. Model Dev., 10, 2057–2116, https://doi.org/10.5194/gmd-10-2057-2017, 2017. a
Moore, J. K., Doney, S. C., and Lindsay, K.: Upper ocean ecosystem dynamics and iron cycling in a global three-dimensional model, Global Biogeochem. Cy., 18, GB4028, https://doi.org/10.1029/2004GB002220, 2004. a
Moore, J. K., Lindsay, K., Doney, S. C., Long, M. C., and Misumi, K.: Marine Ecosystem Dynamics and Biogeochemical Cycling in the Community Earth System Model [CESM1(BGC)]: Comparison of the 1990s with the 2090s under the RCP4.5 and RCP8.5 Scenarios, J. Climate, 26, 9291–9312, https://doi.org/10.1175/JCLI-D-12-00566.1, 2013. a
Moreau, S., Boyd, P. W., and Strutton, P. G.: Remote assessment of the fate of phytoplankton in the Southern Ocean sea-ice zone, Nat. Commun., 11, 3108, https://doi.org/10.1038/s41467-020-16931-0, 2020. a
Nguyen, A. T., Heimbach, P., Garg, V. V., Ocaña, V., Lee, C., and Rainville, L.: Impact of Synthetic Arctic Argo-Type Floats in a Coupled Ocean–Sea Ice State Estimation Framework, J. Atmos. Ocean. Tech., 37, 1477–1495, https://doi.org/10.1175/JTECH-D-19-0159.1, 2020. a, b
Nicholson, S.-A., Whitt, D. B., Fer, I., du Plessis, M. D., Lebéhot, A. D., Swart, S., Sutton, A. J., and Monteiro, P. M. S.: Storms drive outgassing of CO2 in the subpolar Southern Ocean, Nat. Commun., 13, 158, https://doi.org/10.1038/s41467-021-27780-w, 2022. a, b
Nissen, C.: Synthetic biogeochemical float data and corresponding Eulerian model fields from E3SMv, PetaLibrary of the University of Colorado, Boulder [data set], https://www.globus.org/ (last access: 27 August 2024), 2023. a
Oke, P. R., Rykova, T., Pilo, G. S., and Lovell, J. L.: Estimating Argo Float Trajectories Under Ice, Earth Space Sci., 9, 1–16, https://doi.org/10.1029/2022EA002312, 2022. a
Ollitrault, M. and Rannou, J.-P.: ANDRO: An Argo-Based Deep Displacement Dataset, J. Atmos. Ocean. Tech., 30, 759–788, https://doi.org/10.1175/JTECH-D-12-00073.1, 2013. a, b
Orr, J. C. and Epitalon, J.-M.: Improved routines to model the ocean carbonate system: mocsy 2.0, Geosci. Model Dev., 8, 485–499, https://doi.org/10.5194/gmd-8-485-2015, 2015. a
Petersen, M. R., Asay‐Davis, X. S., Berres, A. S., Chen, Q., Feige, N., Hoffman, M. J., Jacobsen, D. W., Jones, P. W., Maltrud, M. E., Price, S. F., Ringler, T. D., Streletz, G. J., Turner, A. K., Van Roekel, L. P., Veneziani, M., Wolfe, J. D., Wolfram, P. J., and Woodring, J. L.: An Evaluation of the Ocean and Sea Ice Climate of E3SM Using MPAS and Interannual CORE‐II Forcing, J. Adv. Model. Earth Sy., 11, 2018MS001373, https://doi.org/10.1029/2018MS001373, 2019. a, b
Prend, C. J., Gray, A. R., Talley, L. D., Gille, S. T., Haumann, F. A., Johnson, K. S., Riser, S. C., Rosso, I., Sauvé, J., and Sarmiento, J. L.: Indo‐Pacific Sector Dominates Southern Ocean Carbon Outgassing, Global Biogeochem. Cy., 36, 1–22, https://doi.org/10.1029/2021GB007226, 2022a. a
Prend, C. J., Hunt, J. M., Mazloff, M. R., Gille, S. T., and Talley, L. D.: Controls on the Boundary Between Thermally and Non‐Thermally Driven pCO2 Regimes in the South Pacific, Geophys. Res. Lett., 49, 1–11, https://doi.org/10.1029/2021GL095797, 2022b. a
Prend, C. J., Keerthi, M. G., Lévy, M., Aumont, O., Gille, S. T., and Talley, L. D.: Sub‐Seasonal Forcing Drives Year‐To‐Year Variations of Southern Ocean Primary Productivity, Global Biogeochem. Cy., 36, 1–15, https://doi.org/10.1029/2022GB007329, 2022c. a
Rhein, M., Steinfeldt, R., Kieke, D., Stendardo, I., and Yashayaev, I.: Ventilation variability of Labrador Sea Water and its impact on oxygen and anthropogenic carbon: a review, Philos. T. Roy. Soc. A, 375, 20160321, https://doi.org/10.1098/rsta.2016.0321, 2017. a
Ringler, T., Petersen, M., Higdon, R. L., Jacobsen, D., Jones, P. W., and Maltrud, M.: A multi-resolution approach to global ocean modeling, Ocean Model., 69, 211–232, https://doi.org/10.1016/j.ocemod.2013.04.010, 2013. a
Riser, S. C., Swift, D., and Drucker, R.: Profiling Floats in SOCCOM: Technical Capabilities for Studying the Southern Ocean, J. Geophys. Res.-Oceans, 123, 4055–4073, https://doi.org/10.1002/2017JC013419, 2018. a, b
Rodgers, K. B., Schwinger, J., Fassbender, A. J., Landschützer, P., Yamaguchi, R., Frenzel, H., Stein, K., Müller, J. D., Goris, N., Sharma, S., Bushinsky, S., Chau, T., Gehlen, M., Gallego, M. A., Gloege, L., Gregor, L., Gruber, N., Hauck, J., Iida, Y., Ishii, M., Keppler, L., Kim, J., Schlunegger, S., Tjiputra, J., Toyama, K., Vaittinada Ayar, P., and Velo, A.: Seasonal Variability of the Surface Ocean Carbon Cycle: A Synthesis, Global Biogeochem. Cy., 37, 1–34, https://doi.org/10.1029/2023GB007798, 2023. a
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. Ó., 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., Körtzinger, A., Traon, P.-Y. L., Lenn, Y.-D., 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., and Yasuda, I.: On the Future of Argo: A Global, Full-Depth, Multi-Disciplinary Array, Front. Mar. Sci., 6, 1–28, https://doi.org/10.3389/fmars.2019.00439, 2019. a, b, c, d, e, f, g, h, i
Sarmiento, J. L. and Gruber, N.: Ocean Biogeochemical Dynamics, Princeton University Press, 1st Edn., ISBN 0-691-01707-7, 2006. a
Sarmiento, J. L., Johnson, K. S., Arteaga, L. A., Bushinsky, S. M., Cullen, H. M., Gray, A. R., Hotinski, R. M., Maurer, T. L., Mazloff, M. R., Riser, S. C., Russell, J. L., Schofield, O. M., and Talley, L. D.: The Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) project: A review, Prog. Oceanogr., 7, 103130, https://doi.org/10.1016/j.pocean.2023.103130, 2023. a, b
Schofield, O., Fassbender, A., Hood, M., Hill, K., and Johnson, K.: A global ocean biogeochemical observatory becomes a reality, EOS, 103, https://doi.org/10.1029/2022EO220149, 2022. a
Shadwick, E. H., Wynn-Edwards, C. A., Matear, R. J., Jansen, P., Schulz, E., and Sutton, A. J.: Observed amplification of the seasonal CO2 cycle at the Southern Ocean Time Series, Front. Mar. Sci., 10, 1–11, https://doi.org/10.3389/fmars.2023.1281854, 2023. a, b
Silva, E., Counillon, F., Brajard, J., Korosov, A., Pettersson, L. H., Samuelsen, A., and Keenlyside, N.: Twenty-One Years of Phytoplankton Bloom Phenology in the Barents, Norwegian, and North Seas, Front. Mar. Sci., 8, 1–16, https://doi.org/10.3389/fmars.2021.746327, 2021. a
SOCCOM: “Southern Ocean Carbon and Climate Observations and Modeling” Project, https://soccom.princeton.edu (last access: 31 August 2023), 2023. a
Soppa, M., Völker, C., and Bracher, A.: Diatom Phenology in the Southern Ocean: Mean Patterns, Trends and the Role of Climate Oscillations, Remote Sens., 8, 420, https://doi.org/10.3390/rs8050420, 2016. a
Su, F., Fan, R., Yan, F., Meadows, M., Lyne, V., Hu, P., Song, X., Zhang, T., Liu, Z., Zhou, C., Pei, T., Yang, X., Du, Y., Wei, Z., Wang, F., Qi, Y., and Chai, F.: Widespread global disparities between modelled and observed mid-depth ocean currents, Nat. Commun., 14, 2089, https://doi.org/10.1038/s41467-023-37841-x, 2023. a
Su, J., Strutton, P. G., and Schallenberg, C.: The subsurface biological structure of Southern Ocean eddies revealed by BGC-Argo floats, J. Mar. Syst., 220, 103569, https://doi.org/10.1016/j.jmarsys.2021.103569, 2021. a, b
Takano, Y., Maltrud, M., Sinha, A., Jeffery, N., Smith, K., Conlon, L., Wolfe, J., and Petersen, M.: Global Ocean Carbon Cycle Simulations with the 2 E3SM version 2 (E3SMv2), Zenodo, https://doi.org/10.5281/zenodo.10093369, 2023. a
Talley, L., Feely, R., Sloyan, B., Wanninkhof, R., Baringer, M., Bullister, J., Carlson, C., Doney, S., Fine, R., Firing, E., Gruber, N., Hansell, D., Ishii, M., Johnson, G., Katsumata, K., Key, R., Kramp, M., Langdon, C., Macdonald, A., Mathis, J., McDonagh, E., Mecking, S., Millero, F., Mordy, C., Nakano, T., Sabine, C., Smethie, W., Swift, J., Tanhua, T., Thurnherr, A., Warner, M., and Zhang, J.-Z.: Changes in Ocean Heat, Carbon Content, and Ventilation: A Review of the First Decade of GO-SHIP Global Repeat Hydrography, Annu. Rev. Mar. Sci., 8, 185–215, https://doi.org/10.1146/annurev-marine-052915-100829, 2016. a, b, c
Thomalla, S. J., Racault, M.-F., Swart, S., and Monteiro, P. M. S.: High-resolution view of the spring bloom initiation and net community production in the Subantarctic Southern Ocean using glider data, ICES J. Mar. Sci., 72, 1999–2020, https://doi.org/10.1093/icesjms/fsv105, 2015. a
Torres, O., Kwiatkowski, L., Sutton, A. J., Dorey, N., and Orr, J. C.: Characterizing Mean and Extreme Diurnal Variability of Ocean CO2 System Variables Across Marine Environments, Geophys. Res. Lett., 48, 1–12, https://doi.org/10.1029/2020GL090228, 2021. a, b
Tsujino, H., Urakawa, S., Nakano, H., Small, R. J., Kim, W. M., Yeager, S. G., Danabasoglu, G., Suzuki, T., Bamber, J. L., Bentsen, M., Böning, C. W., Bozec, A., Chassignet, E. P., Curchitser, E., Boeira Dias, F., Durack, P. J., Griffies, S. M., Harada, Y., Ilicak, M., Josey, S. A., Kobayashi, C., Kobayashi, S., Komuro, Y., Large, W. G., Le Sommer, J., Marsland, S. J., Masina, S., Scheinert, M., Tomita, H., Valdivieso, M., and Yamazaki, D.: JRA-55 based surface dataset for driving ocean–sea-ice models (JRA55-do), Ocean Model., 130, 79–139, https://doi.org/10.1016/j.ocemod.2018.07.002, 2018. a
Turner, A. K., Lipscomb, W. H., Hunke, E. C., Jacobsen, D. W., Jeffery, N., Engwirda, D., Ringler, T. D., and Wolfe, J. D.: MPAS-Seaice (v1.0.0): sea-ice dynamics on unstructured Voronoi meshes, Geosci. Model Dev., 15, 3721–3751, https://doi.org/10.5194/gmd-15-3721-2022, 2022. a
Wang, T., Du, Y., and Wang, M.: Overlooked Current Estimation Biases Arising from the Lagrangian Argo Trajectory Derivation Method, J. Phys. Oceanogr., 52, 3–19, https://doi.org/10.1175/JPO-D-20-0287.1, 2022. a, b
Wolfram, P. J., Ringler, T. D., Maltrud, M. E., Jacobsen, D. W., and Petersen, M. R.: Diagnosing Isopycnal Diffusivity in an Eddying, Idealized Midlatitude Ocean Basin via Lagrangian, in Situ, Global, High-Performance Particle Tracking (LIGHT), J. Phys. Oceanogr., 45, 2114–2133, https://doi.org/10.1175/JPO-D-14-0260.1, 2015. a, b
Wong, A. P. S., Wijffels, S. E., Riser, S. C., Pouliquen, S., Hosoda, S., Roemmich, D., Gilson, J., Johnson, G. C., Martini, K., Murphy, D. J., Scanderbeg, M., Bhaskar, T. V. S. U., Buck, J. J. H., Merceur, F., Carval, T., Maze, G., Cabanes, C., André, X., Poffa, N., Yashayaev, I., Barker, P. M., Guinehut, S., Belbéoch, M., Ignaszewski, M., Baringer, M. O., Schmid, C., Lyman, J. M., McTaggart, K. E., Purkey, S. G., Zilberman, N., Alkire, M. B., Swift, D., Owens, W. B., Jayne, S. R., Hersh, C., Robbins, P., West-Mack, D., Bahr, F., Yoshida, S., Sutton, P. J. H., Cancouët, R., Coatanoan, C., Dobbler, D., Juan, A. G., Gourrion, J., Kolodziejczyk, N., Bernard, V., Bourlès, B., Claustre, H., D'Ortenzio, F., Le Reste, S., Le Traon, P.-Y., Rannou, J.-P., Saout-Grit, C., Speich, S., Thierry, V., Verbrugge, N., Angel-Benavides, I. M., Klein, B., Notarstefano, G., Poulain, P.-M., Vélez-Belchí, P., Suga, T., Ando, K., Iwasaska, N., Kobayashi, T., Masuda, S., Oka, E., Sato, K., Nakamura, T., Sato, K., Takatsuki, Y., Yoshida, T., Cowley, R., Lovell, J. L., Oke, P. R., van Wijk, E. M., Carse, F., Donnelly, M., Gould, W. J., Gowers, K., King, B. A., Loch, S. G., Mowat, M., Turton, J., Rama Rao, E. P., Ravichandran, M., Freeland, H. J., Gaboury, I., Gilbert, D., Greenan, B. J. W., Ouellet, M., Ross, T., Tran, A., Dong, M., Liu, Z., Xu, J., Kang, K., Jo, H., Kim, S.-D., and Park, H.-M.: Argo Data 1999–2019: Two Million Temperature-Salinity Profiles and Subsurface Velocity Observations From a Global Array of Profiling Floats, Front. Mar. Sci., 7, 1–23, https://doi.org/10.3389/fmars.2020.00700, 2020. a
Yasunaka, S., Ono, T., Sasaoka, K., and Sato, K.: Global distribution and variability of subsurface chlorophyll a concentrations, Ocean Sci., 18, 255–268, https://doi.org/10.5194/os-18-255-2022, 2022. a
Youngs, M. K., Freilich, M. A., and Lovenduski, N. S.: Air‐Sea CO2 Fluxes Localized by Topography in a Southern Ocean Channel, Geophys. Res. Lett., 50, 1–9, https://doi.org/10.1029/2023GL104802, 2023. a
Zilberman, N. V., Scanderbeg, M., Gray, A. R., and Oke, P. R.: Scripps Argo trajectory-based velocity product 2001-01 to 2020-12, Scripps Argo Trajectory-Based Velocity Product, UC San Diego Library Digital Collections, https://doi.org/10.6075/J0KD1Z35, 2022. a, b
Zilberman, N. V., Scanderbeg, M., Gray, A. R., and Oke, P. R.: Scripps Argo Trajectory-Based Velocity Product: Global Estimates of Absolute Velocity Derived from Core, Biogeochemical, and Deep Argo Float Trajectories at Parking Depth, J. Atmos. Ocean. Tech., 40, 361–374, https://doi.org/10.1175/JTECH-D-22-0065.1, 2023. a, b, c, d
Short summary
Autonomous profiling floats have provided unprecedented observational coverage of the global ocean, but uncertainties remain about whether their sampling frequency and density capture the true spatiotemporal variability of physical, biogeochemical, and biological properties. Here, we present the novel synthetic biogeochemical float capabilities of the Energy Exascale Earth System Model version 2 and demonstrate their utility as a test bed to address these uncertainties.
Autonomous profiling floats have provided unprecedented observational coverage of the global...
