Articles | Volume 22, issue 5
https://doi.org/10.5194/os-22-2691-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-22-2691-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Sep 2026
Research article |
| 07 Sep 2026
| 07 Sep 2026
Current status of ocean observation, ensemble reanalysis and CMIP6 models in describing Antarctic Bottom Water
Siran Chen
School of Atmospheric Sciences, Sun Yat-sen University and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
Jiping Liu
CORRESPONDING AUTHOR
School of Atmospheric Sciences, Sun Yat-sen University and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
Xianxian Han
School of Marine Sciences, Sun Yat-sen University and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
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The Last Glacial Maximum (LGM) marks the most recent extremely cold and dry time period of our planet. Using AWI-ESM, we quantify the relative importance of Earth's orbit, greenhouse gases (GHG) and ice sheets (IS) in determining the LGM climate. Our results suggest that both GHG and IS play important roles in shaping the LGM temperature. Continental ice sheets exert a major control on precipitation, atmospheric dynamics, and the intensity of El Niño–Southern Oscillation.
Cited articles
Azaneu, M., Kerr, R., and Mata, M. M.: Assessment of the representation of Antarctic Bottom Water properties in the ECCO2 reanalysis, Ocean Sci., 10, 923–946, https://doi.org/10.5194/os-10-923-2014, 2014.
Boucher, O., Denvil, S., Levavasseur, G., Cozic, A., Caubel, A., Foujols, M.-A., Meurdesoif, Y., Cadule, P., Devilliers, M., Ghattas, J., Lebas, N., Lurton, T., Mellul, L., Musat, I., Mignot, J., and Cheruy, F.: IPSL IPSL-CM6A-LR model output prepared for CMIP6 CMIP historical, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.5195, 2018.
Burke, A. and Robinson, L. F.: The Southern Ocean's role in carbon exchange during the last deglaciation, Science, 335, 557–561, https://doi.org/10.1126/science.1208163, 2012.
Chassignet, E. P. and Xu, X.: On the importance of high resolution in large-scale ocean models, Adv. Atmos. Sci., 38, 1621–1634, https://doi.org/10.1007/s00376-021-0385-7, 2021.
Chen, S., Liu, J., and Han, X.: Code and processed data for “Current status of ocean observation, ensemble reanalysis and CMIP6 models in describing Antarctic Bottom Water”, Zenodo [data set], https://doi.org/10.5281/zenodo.21466692, 2026.
Copernicus Marine Service: Global Ocean Ensemble Physics Reanalysis, Mercator Ocean International [data set], https://doi.org/10.48670/moi-00024, 2023.
Danabasoglu, G.: NCAR CESM2 model output prepared for CMIP6 CMIP historical, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.7627, 2019.
Gordon, A. L., Huber, B. A., Hellmer, H. H., and Ffield, A.: Deep and bottom water of the Weddell Sea's western rim, Science, 262, 95–97, https://doi.org/10.1126/science.262.5130.95, 1993.
Gouretski, V. and Koltermann, K. P.: How much is the ocean really warming?, Geophys. Res. Lett., 34, https://doi.org/10.1029/2006GL027834, 2007.
Gunn, K. L., Rintoul, S. R., England, M. H., and Bowen, M. M.: Recent reduced abyssal overturning and ventilation in the Australian Antarctic Basin, Nat. Clim. Change, 13, 537–544, https://doi.org/10.1038/s41558-023-01667-8, 2023.
Han, X., Stewart, A. L., Chen, D., Janout, M., Liu, X., Wang, Z., and Gordon, A. L.: Circum-Antarctic bottom water formation mediated by tides and topographic waves, Nat. Commun., 15, 2049, https://doi.org/10.1038/s41467-024-46086-1, 2024.
Han, X., Stewart, A. L., Wang, Z., Yang, Q., Liu, C., and Chen, D.: Tidal effects on Antarctic Bottom Water formation in a changing climate, J. Geophys. Res.-Oceans, 130, https://doi.org/10.1029/2025JC022443, 2025.
Heuzé, C.: Antarctic Bottom Water and North Atlantic Deep Water in CMIP6 models, Ocean Sci., 17, 59–90, https://doi.org/10.5194/os-17-59-2021, 2021.
Hewitt, H. T., Roberts, M., Mathiot, P., Biastoch, A., Blockley, E., Chassignet, E. P., Fox-Kemper, B., Hyder, P., Marshall, D. P., Popova, E., Tréguier, A.-M., Zanna, L., Yool, A., Yu, Y., Beadling, R., Bell, M., Kuhlbrodt, T., Arsouze, T., Bellucci, A., Castruccio, F., Gan, B., Putrasahan, D., Roberts, C. D., Van Roekel, L., and Zhang, Q.: Resolving and parameterising the ocean mesoscale in Earth system models, Curr. Clim. Change Rep., 6, 137–152, https://doi.org/10.1007/s40641-020-00164-w, 2020.
Huang, W.: THU CIESM model output prepared for CMIP6 CMIP historical, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.8843, 2019.
Hurrell, J. W., Holland, M. M., Gent, P. R., Ghan, S., Kay, J. E., Kushner, P. J., Lamarque, J.-F., Large, W. G., Lawrence, D. M., Lindsay, K., Lipscomb, W. H., Long, M. C., Mahowald, N. M., Marsh, D. R., Neale, R. B., Rasch, P. J., Vavrus, S. J., Vertenstein, M., Bader, D. C., Collins, W. D., Hack, J. J., Kiehl, J., and Marshall, S.: NCAR CESM1-CAM5-SE-HR model output prepared for CMIP6 HighResMIP, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.14220, 2020a.
Hurrell, J. W., Holland, M. M., Gent, P. R., Ghan, S., Kay, J. E., Kushner, P. J., Lamarque, J.-F., Large, W. G., Lawrence, D. M., Lindsay, K., Lipscomb, W. H., Long, M. C., Mahowald, N. M., Marsh, D. R., Neale, R. B., Rasch, P. J., Vavrus, S. J., Vertenstein, M., Bader, D. C., Collins, W. D., Hack, J. J., Kiehl, J., and Marshall, S.: NCAR CESM1-CAM5-SE-LR model output prepared for CMIP6 HighResMIP hist-1950, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.14295, 2020b.
Jackett, D. R. and McDougall, T. J.: Minimal adjustment of hydrographic profiles to achieve static stability, J. Atmos. Ocean. Tech., 12, 381–389, https://doi.org/10.1175/1520-0426(1995)012<0381:MAOHPT>2.0.CO;2, 1995.
Johnson, G. C., Purkey, S. G., and Toole, J. M.: Reduced Antarctic meridional overturning circulation reaches the North Atlantic Ocean, Geophys. Res. Lett., 35, https://doi.org/10.1029/2008GL035619, 2008.
Jullion, L., Naveira Garabato, A. C., Meredith, M. P., Holland, P. R., Courtois, P., and King, B. A.: Decadal freshening of the Antarctic Bottom Water exported from the Weddell Sea, J. Climate, 26, 8111–8125, https://doi.org/10.1175/JCLI-D-12-00765.1, 2013.
Kang, S. M., Putrasahan, D. A., Brizuela, N. G., Haak, H., Kröger, J., Marotzke, J., Stevens, B., and von Storch, J.-S.: Km-scale coupled simulation and model–observation SST trend discrepancy, Proc. Natl. Acad. Sci. USA, 123, https://doi.org/10.1073/pnas.2522161123, 2026.
Kobayashi, T.: Changes in Antarctic bottom water off the Wilkes Land coast in the Australian-Antarctic Basin, Deep Sea Res.-Pt. I, 195, 104040, https://doi.org/10.1016/j.dsr.2023.104040, 2023.
Köhl, A.: Evaluation of the GECCO2 ocean synthesis: transports of volume, heat and freshwater in the Atlantic, Q. J. Roy. Meteorol. Soc., 141, 166–181, https://doi.org/10.1002/qj.2347, 2015.
Lellouche, J.-M., Le Galloudec, O., Drévillon, M., Régnier, C., Greiner, E., Garric, G., Ferry, N., Desportes, C., Testut, C.-E., Bricaud, C., Bourdallé-Badie, R., Tranchant, B., Benkiran, M., Drillet, Y., Daudin, A., and De Nicola, C.: Evaluation of global monitoring and forecasting systems at Mercator Océan, Ocean Sci., 9, 57–81, https://doi.org/10.5194/os-9-57-2013, 2013.
Levitus, S., Antonov, J. I., Boyer, T. P., Locarnini, R. A., Garcia, H. E., and Mishonov, A. V.: Global ocean heat content 1955–2008 in light of recently revealed instrumentation problems, Geophys. Res. Lett., 36, https://doi.org/10.1029/2008GL037155, 2009.
Li, Q., England, M. H., Hogg, A. M. C., Rintoul, S. R., and Morrison, A. K.: Abyssal ocean overturning slowdown and warming driven by Antarctic meltwater, Nature, 615, 841–847, https://doi.org/10.1038/s41586-023-05762-w, 2023.
Locarnini, R. A., Mishonov, A. V., Baranova, O. K., Reagan, J. R., Boyer, T. P., Seidov, D., Wang, Z., Garcia, H. E., Bouchard, C., Cross, S. L., Paver, C. R., and Dukhovskoy, D.: World Ocean Atlas 2023, Volume 1: Temperature, edited by: Mishonov, A. V., NOAA Atlas NESDIS 89, 52 pp., https://doi.org/10.25923/54bh-1613, 2024.
Lorenz, S., Jungclaus, J., Schmidt, H., Haak, H., Reick, C., Schupfner, M., Wachsmann, F., Gayler, V., de Vrese, P., Raddatz, T., Mauritsen, T., von Storch, J.-S., Brovkin, V., Claussen, M., Crueger, T., Fiedler, S., Hagemann, S., Hohenegger, C., Jahns, T., Kinne, S., Kornblueh, L., Marotzke, J., Mikolajewicz, U., Modali, K., Müller, W., Nabel, J., Notz, D., Pincus, R., Pohlmann, H., Rast, S., Schnur, R., Schulzweida, U., Six, K., Stevens, B., Roeckner, E., Wieners, K.-H., Esch, M., Giorgetta, M., and Ilyina, T.: MPI-M ICON-ESM-LR model output prepared for CMIP6 CMIP historical, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.6593, 2021.
Lovato, T. and Peano, D.: CMCC CMCC-CM2-SR5 model output prepared for CMIP6 CMIP historical, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.3825, 2020.
MacLachlan, C., Arribas, A., Peterson, K. A., Maidens, A., Fereday, D., Scaife, A. A., Gordon, M., Vellinga, M., Williams, A., Comer, R. E., Camp, J., Xavier, P., and Madec, G.: Global Seasonal forecast system version 5 (GloSea5): a high-resolution seasonal forecast system, Q. J. Roy. Meteorol. Soc., 141, 1072–1084, https://doi.org/10.1002/qj.2396, 2015.
Marinov, I., Gnanadesikan, A., Toggweiler, J. R., and Sarmiento, J. L.: The Southern Ocean biogeochemical divide, Nature, 441, 964–967, https://doi.org/10.1038/nature04883, 2006.
Megann, A., Storkey, D., Aksenov, Y., Alderson, S., Calvert, D., Graham, T., Hyder, P., Siddorn, J., and Sinha, B.: GO5.0: the joint NERC–Met Office NEMO global ocean model for use in coupled and forced applications, Geosci. Model Dev., 7, 1069–1092, https://doi.org/10.5194/gmd-7-1069-2014, 2014.
Ohshima, K. I., Fukamachi, Y., Williams, G. D., Nihashi, S., Roquet, F., Kitade, Y., Tamura, T., Hirano, D., Herraiz-Borreguero, L., Field, I., Hindell, M., Aoki, S., and Wakatsuchi, M.: Antarctic Bottom Water production by intense sea-ice formation in the Cape Darnley polynya, Nat. Geosci., 6, 235–240, https://doi.org/10.1038/ngeo1738, 2013.
Orsi, A. H., Johnson, G. C., and Bullister, J. L.: Circulation, mixing, and production of Antarctic Bottom Water, Prog. Oceanogr., 43, 55–109, https://doi.org/10.1016/S0079-6611(99)00004-X, 1999.
Pardo, P. C., Pérez, F. F., Velo, A., and Gilcoto, M.: Water masses distribution in the Southern Ocean: Improvement of an extended OMP (eOMP) analysis, Prog. Oceanogr., 103, 92–105, https://doi.org/10.1016/j.pocean.2012.06.002, 2012.
Portela, E., Rintoul, S. R., Bestley, S., Herraiz-Borreguero, L., van Wijk, E., McMahon, C. R., Roquet, F., and Hindell, M.: Seasonal transformation and spatial variability of water masses within MacKenzie Polynya, Prydz Bay, J. Geophys. Res.-Oceans, 126, https://doi.org/10.1029/2021JC017748, 2021.
Portela, E., Rintoul, S. R., Herraiz-Borreguero, L., Roquet, F., Bestley, S., van Wijk, E., Tamura, T., McMahon, C. R., Guinet, C., Harcourt, R., and Hindell, M. A.: Controls on dense shelf water formation in four East Antarctic polynyas, J. Geophys. Res.-Oceans, 127, https://doi.org/10.1029/2022JC018804, 2022.
Purkey, S. G. and Johnson, G. C.: Warming of global abyssal and deep Southern Ocean waters between the 1990s and 2000s: Contributions to global heat and sea level rise budgets, J. Climate, 23, 6336–6351, https://doi.org/10.1175/2010JCLI3682.1, 2010.
Purkey, S. G. and Johnson, G. C.: Antarctic Bottom Water warming and freshening: Contributions to sea level rise, ocean freshwater budgets, and global heat gain, J. Climate, 26, 6105–6122, https://doi.org/10.1175/JCLI-D-12-00834.1, 2013.
Purkey, S. G., Smethie, W. M., Gebbie, G., Gordon, A. L., Sonnerup, R. E., Warner, M. J., and Bullister, J. L.: A synoptic view of the ventilation and circulation of Antarctic Bottom Water from chlorofluorocarbons and natural tracers, Annu. Rev. Mar. Sci., 10, 503–527, https://doi.org/10.1146/annurev-marine-121916-063414, 2018.
Rackow, T., Pedruzo-Bagazgoitia, X., Becker, T., Milinski, S., Sandu, I., Aguridan, R., Bechtold, P., Beyer, S., Bidlot, J., Boussetta, S., Deconinck, W., Diamantakis, M., Dueben, P., Dutra, E., Forbes, R., Ghosh, R., Goessling, H. F., Hadade, I., Hegewald, J., Jung, T., Keeley, S., Kluft, L., Koldunov, N., Koldunov, A., Kölling, T., Kousal, J., Kühnlein, C., Maciel, P., Mogensen, K., Quintino, T., Polichtchouk, I., Reuter, B., Sármány, D., Scholz, P., Sidorenko, D., Streffing, J., Sützl, B., Takasuka, D., Tietsche, S., Valentini, M., Vannière, B., Wedi, N., Zampieri, L., and Ziemen, F.: Multi-year simulations at kilometre scale with the Integrated Forecasting System coupled to FESOM2.5 and NEMOv3.4, Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, 2025.
Reagan, J. R., Boyer, T P., García, H. E., Locarnini, R. A., Baranova, O. K., Bouchard, C., Cross, S. L., Mishonov, A. V., Paver, C. R., Seidov, D., Wang, Z., and Dukhovskoy, D.: World Ocean Atlas 2023, NOAA National Centers for Environmental Information [data set], https://doi.org/10.25921/va26-hv25, 2023.
Reagan, J. R., Seidov, D., Wang, Z., Dukhovskoy, D., Boyer, T. P., Locarnini, R. A., Baranova, O. K., Mishonov, A. V., Garcia, H. E., Bouchard, C., Cross, S. L., and Paver, C. R.: World Ocean Atlas 2023, Volume 2: Salinity, edited by: Mishonov, A. V., NOAA Atlas NESDIS 90, 51 pp., https://doi.org/10.25923/70qt-9574, 2024.
Rintoul, S. R.: The global influence of localized dynamics in the Southern Ocean, Nature, 558, 209–218, https://doi.org/10.1038/s41586-018-0182-3, 2018.
Schmidt, C., Morrison, A. K., and England, M. H.: Wind- and sea-ice-driven interannual variability of Antarctic Bottom Water formation, J. Geophys. Res.-Oceans, 128, https://doi.org/10.1029/2023JC019774, 2023.
Scoccimarro, E., Bellucci, A., and Peano, D.: CMCC CMCC-CM2-HR4 model output prepared for CMIP6 CMIP historical, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.3823, 2020.
Semmler, T., Danilov, S., Rackow, T., Sidorenko, D., Hegewald, J., Sein, D., Wang, Q., and Jung, T.: AWI AWI-CM1.1HR model output prepared for CMIP6 HighResMIP hist-1950, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.2676, 2017.
Semmler, T., Danilov, S., Rackow, T., Sidorenko, D., Barbi, D., Hegewald, J., Sein, D., Wang, Q., and Jung, T.: AWI AWI-CM1.1MR model output prepared for CMIP6 CMIP historical, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.2686, 2018.
Silvano, A., Rintoul, S. R., Peña-Molino, B., Hobbs, W. R., van Wijk, E., Aoki, S., Tamura, T., and Williams, G. D.: Freshening by glacial meltwater enhances melting of ice shelves and reduces formation of Antarctic Bottom Water, Sci. Adv., 4, https://doi.org/10.1126/sciadv.aap9467, 2018.
Silvano, A., Foppert, A., Rintoul, S. R., Holland, P. R., Tamura, T., Kimura, N., Castagno, P., Falco, P., Budillon, G., Haumann, F. A., Naveira Garabato, A. C., and Macdonald, A. M.: Recent recovery of Antarctic Bottom Water formation in the Ross Sea driven by climate anomalies, Nat. Geosci., 13, 780–786, https://doi.org/10.1038/s41561-020-00655-3, 2020.
Silvano, A., Purkey, S., Gordon, A. L., Castagno, P., Stewart, A. L., Rintoul, S. R., Foppert, A., Gunn, K. L., Herraiz-Borreguero, L., Aoki, S., Nakayama, Y., Naveira Garabato, A. C., Spingys, C., Akhoudas, C. H., Sallée, J.-B., de Lavergne, C., Abrahamsen, E. P., Meijers, A. J. S., Meredith, M. P., Zhou, S., Tamura, T., Yamazaki, K., Ohshima, K. I., Falco, P., Budillon, G., Hattermann, T., Janout, M. A., Llanillo, P., Bowen, M. M., Darelius, E., Østerhus, S., Nicholls, K. W., Stevens, C., Fernandez, D., Cimoli, L., Jacobs, S. S., Morrison, A. K., Hogg, A. M., Haumann, F. A., Mashayek, A., Wang, Z., Kerr, R., Williams, G. D., and Lee, W. S.: Observing Antarctic Bottom Water in the Southern Ocean, Front. Mar. Sci., 10, 1221701, https://doi.org/10.3389/fmars.2023.1221701, 2023.
Song, Z., Qiao, F., Bao, Y., Shu, Q., Song, Y., and Yang, X.: FIO-QLNM FIO-ESM2.0 model output prepared for CMIP6 CMIP historical, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.9199, 2019.
Storto, A. and Masina, S.: C-GLORSv5: an improved multipurpose global ocean eddy-permitting physical reanalysis, Earth Syst. Sci. Data, 8, 679–696, https://doi.org/10.5194/essd-8-679-2016, 2016.
Swart, N. C., Cole, J. N. S., Kharin, V. V., Lazare, M., Scinocca, J. F., Gillett, N. P., Anstey, J., Arora, V., Christian, J. R., Jiao, Y., Lee, W. G., Majaess, F., Saenko, O. A., Seiler, C., Seinen, C., Shao, A., Solheim, L., von Salzen, K., Yang, D., Winter, B., and Sigmond, M.: CCCma CanESM5 model output prepared for CMIP6 CMIP historical, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.3610, 2019.
Uotila, P., Goosse, H., Haines, K., Chevallier, M., Barthélemy, A., Bricaud, C., Carton, J., Fučkar, N., Garric, G., Iovino, D., Kauker, F., Korhonen, M., Lien, V. S., Marnela, M., Massonnet, F., Mignac, D., Peterson, K. A., Sadikni, R., Shi, L., Tietsche, S., Toyoda, T., Xie, J., and Zhang, Z.: An assessment of ten ocean reanalyses in the polar regions, Clim. Dynam., 52, 1613–1650, https://doi.org/10.1007/s00382-018-4242-z, 2019.
van Wijk, E. M. and Rintoul, S. R.: Freshening drives contraction of Antarctic Bottom Water in the Australian Antarctic Basin, Geophys. Res. Lett., 41, 1657–1664, https://doi.org/10.1002/2013GL058921, 2014.
Voldoire, A.: CMIP6 simulations of the CNRM-CERFACS based on CNRM-CM6-1 model for CMIP experiment historical, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.4066, 2018.
Voldoire, A.: CNRM-CERFACS CNRM-CM6-1-HR model output prepared for CMIP6 CMIP historical, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.4067, 2019.
Williams, G. D., Bindoff, N. L., Marsland, S. J., and Rintoul, S. R.: Formation and export of dense shelf water from the Adélie Depression, East Antarctica, J. Geophys. Res.-Oceans, 113, https://doi.org/10.1029/2007JC004346, 2008.
Williams, G. D., Herraiz-Borreguero, L., Roquet, F., Tamura, T., Ohshima, K. I., Fukamachi, Y., Fraser, A. D., Gao, L., Chen, H., McMahon, C. R., Harcourt, R., and Hindell, M.: The suppression of Antarctic bottom water formation by melting ice shelves in Prydz Bay, Nat. Commun., 7, 12577, https://doi.org/10.1038/ncomms12577, 2016.
Yu, Y.: CAS FGOALS-f3-H model output prepared for CMIP6 HighResMIP hist-1950, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.3316, 2020.
Zhang, S., Wu, Y., Cai, W. J., Cai, W., Feely, R. A., Wang, Z., Tanhua, T., Wang, Y., Liu, C., Li, X., Yang, Q., Ding, M., Xu, Z., Kerr, R., Luo, Y., Cheng, X., Chen, L., and Qi, D.: Transport of anthropogenic carbon from the Antarctic shelf to the deep Southern Ocean triggers acidification, Global Biogeochem. Cy., 37, https://doi.org/10.1029/2023GB007921, 2023.
Zhou, S., Meijers, A. J. S., Meredith, M. P., Abrahamsen, E. P., Holland, P. R., Silvano, A., Sallée, J.-B., and Østerhus, S.: Slowdown of Antarctic Bottom Water export driven by climatic wind and sea-ice changes, Nat. Clim. Change, 13, 701–709, https://doi.org/10.1038/s41558-023-01695-4, 2023.
Ziehn, T., Chamberlain, M., Lenton, A., Law, R., Bodman, R., Dix, M., Wang, Y., Dobrohotoff, P., Srbinovsky, J., Stevens, L., Vohralik, P., Mackallah, C., Sullivan, A., O'Farrell, S., and Druken, K.: CSIRO ACCESS-ESM1.5 model output prepared for CMIP6 CMIP historical, Earth System Grid Federation [data set], https://doi.org/10.22033/ESGF/CMIP6.4272, 2019.
Zuo, H., Balmaseda, M. A., Tietsche, S., Mogensen, K., and Mayer, M.: The ECMWF operational ensemble reanalysis–analysis system for ocean and sea ice: A description of the system and assessment, Ocean Sci., 15, 779–808, https://doi.org/10.5194/os-15-779-2019, 2019.
Short summary
Antarctic Bottom Water influences global ocean circulation, heat storage, and carbon uptake. We compared an observational atlas, an ocean reconstruction, and 16 climate models by separating this water into three regional types. The reconstruction matched the observed large-scale patterns well, but many climate models showed substantial regional temperature and salinity errors. Correcting average biases improved some models, although errors in spatial structure remained.
Antarctic Bottom Water influences global ocean circulation, heat storage, and carbon uptake. We...
