Articles | Volume 13, issue 12
https://doi.org/10.5194/essd-13-5663-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-13-5663-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
07 Dec 2021
Data description paper |
| 07 Dec 2021
| 07 Dec 2021
Next generation of Bluelink ocean reanalysis with multiscale data assimilation: BRAN2020
Matthew A. Chamberlain
CORRESPONDING AUTHOR
CSIRO Oceans and Atmosphere, Hobart, TAS, Australia
Peter R. Oke
CSIRO Oceans and Atmosphere, Hobart, TAS, Australia
Russell A. S. Fiedler
CSIRO Oceans and Atmosphere, Hobart, TAS, Australia
Helen M. Beggs
Bureau of Meteorology, Melbourne, VIC, Australia
Gary B. Brassington
Bureau of Meteorology, Sydney, NSW, Australia
Prasanth Divakaran
Bureau of Meteorology, Melbourne, VIC, Australia
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Governments are targeting net-zero emissions later this century with the aim of limiting global warming in line with the Paris Agreement. However, few studies explore the long-term consequences of reaching net-zero emissions and the effects of a delay in reaching net-zero. We use the Australian Earth system model to examine climate evolution under net-zero emissions. We find substantial changes which differ regionally, including continued Southern Ocean warming and Antarctic sea ice reduction.
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Biogeosciences, 21, 3373–3400, https://doi.org/10.5194/bg-21-3373-2024, https://doi.org/10.5194/bg-21-3373-2024, 2024
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How do perpetually slower and warmer oceans sequester carbon? Compared to the preindustrial state, we find that biological productivity declines despite warming-stimulated growth because of a lower nutrient supply from depth. This throttles the biological carbon pump, which still sequesters more carbon because it takes longer to return to the surface. The deep ocean is isolated from the surface, allowing more carbon from the atmosphere to pass through the ocean without contributing to biology.
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Modeling the ocean's carbon and oxygen cycles accurately is challenging. Parameter optimization improves the fit to observed tracers but can introduce artifacts in the biological pump. Organic-matter production and subsurface remineralization rates adjust to compensate for circulation biases, changing the pathways and timescales with which nutrients return to the surface. Circulation biases can thus strongly alter the system’s response to ecological change, even when parameters are optimized.
Alban Planchat, Lester Kwiatkowski, Laurent Bopp, Olivier Torres, James R. Christian, Momme Butenschön, Tomas Lovato, Roland Séférian, Matthew A. Chamberlain, Olivier Aumont, Michio Watanabe, Akitomo Yamamoto, Andrew Yool, Tatiana Ilyina, Hiroyuki Tsujino, Kristen M. Krumhardt, Jörg Schwinger, Jerry Tjiputra, John P. Dunne, and Charles Stock
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Ocean alkalinity is critical to the uptake of atmospheric carbon and acidification in surface waters. We review the representation of alkalinity and the associated calcium carbonate cycle in Earth system models. While many parameterizations remain present in the latest generation of models, there is a general improvement in the simulated alkalinity distribution. This improvement is related to an increase in the export of biotic calcium carbonate, which closer resembles observations.
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We investigate the effects of a warmer climate from the Earth's paleoclimate (last interglacial) on the marine carbon cycle of the Southern Ocean using a carbon-cycle-enabled state-of-the-art climate model. We find a 150 % increase in CO2 outgassing during this period, which results from competition between higher sea surface temperatures and weaker oceanic circulation. From this we unequivocally infer that the carbon uptake by the Southern Ocean will reduce under a future warming scenario.
Nicholas King-Hei Yeung, Laurie Menviel, Katrin J. Meissner, Andréa S. Taschetto, Tilo Ziehn, and Matthew Chamberlain
Clim. Past, 17, 869–885, https://doi.org/10.5194/cp-17-869-2021, https://doi.org/10.5194/cp-17-869-2021, 2021
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The Last Interglacial period (LIG) is characterised by strong orbital forcing compared to the pre-industrial period (PI). This study compares the mean climate state of the LIG to the PI as simulated by the ACCESS-ESM1.5, with a focus on the southern hemispheric monsoons, which are shown to be consistently weakened. This is associated with cooler terrestrial conditions in austral summer due to decreased insolation, and greater pressure and subsidence over land from Hadley cell strengthening.
Masa Kageyama, Louise C. Sime, Marie Sicard, Maria-Vittoria Guarino, Anne de Vernal, Ruediger Stein, David Schroeder, Irene Malmierca-Vallet, Ayako Abe-Ouchi, Cecilia Bitz, Pascale Braconnot, Esther C. Brady, Jian Cao, Matthew A. Chamberlain, Danny Feltham, Chuncheng Guo, Allegra N. LeGrande, Gerrit Lohmann, Katrin J. Meissner, Laurie Menviel, Polina Morozova, Kerim H. Nisancioglu, Bette L. Otto-Bliesner, Ryouta O'ishi, Silvana Ramos Buarque, David Salas y Melia, Sam Sherriff-Tadano, Julienne Stroeve, Xiaoxu Shi, Bo Sun, Robert A. Tomas, Evgeny Volodin, Nicholas K. H. Yeung, Qiong Zhang, Zhongshi Zhang, Weipeng Zheng, and Tilo Ziehn
Clim. Past, 17, 37–62, https://doi.org/10.5194/cp-17-37-2021, https://doi.org/10.5194/cp-17-37-2021, 2021
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The Last interglacial (ca. 127 000 years ago) is a period with increased summer insolation at high northern latitudes, resulting in a strong reduction in Arctic sea ice. The latest PMIP4-CMIP6 models all simulate this decrease, consistent with reconstructions. However, neither the models nor the reconstructions agree on the possibility of a seasonally ice-free Arctic. Work to clarify the reasons for this model divergence and the conflicting interpretations of the records will thus be needed.
Pearse J. Buchanan, P. Jyoteeshkumar Reddy, Richard J. Matear, Matthew A. Chamberlain, Tyler Rohr, Dougal Squire, and Elizabeth H. Shadwick
Biogeosciences, 22, 5349–5385, https://doi.org/10.5194/bg-22-5349-2025, https://doi.org/10.5194/bg-22-5349-2025, 2025
Short summary
Short summary
We calibrate a new version of the World Ocean Model of Biogeochemistry and Trophic dynamics (WOMBAT-lite) using a surrogate machine learning approach. A Gaussian process surrogate trained on 512 simulations emulated tens of thousands, enabling global sensitivity analysis and Bayesian optimization of 26 parameters. We constrain 13 key parameters, improving fit to 8 datasets (chlorophyll a, air–sea CO₂ fluxes, nutrient limitation), and provide an optimal set for community use.
Bartholomé Duboc, Katrin J. Meissner, Laurie Menviel, Nicholas K. H. Yeung, Babette Hoogakker, Tilo Ziehn, and Matthew Chamberlain
Clim. Past, 21, 1093–1122, https://doi.org/10.5194/cp-21-1093-2025, https://doi.org/10.5194/cp-21-1093-2025, 2025
Short summary
Short summary
We use an earth system model to simulate ocean oxygen during two past warm periods, the Last Interglacial (∼ 129–115 ka) and Marine Isotope Stage (MIS) 9e (∼ 336–321 ka). The global ocean is overall less oxygenated compared to the preindustrial simulation. Large regions in the Mediterranean Sea are oxygen deprived in the Last Interglacial simulation, and to a lesser extent in the MIS 9e simulation, due to an intensification and expansion of the African monsoon and enhanced river runoff.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique M. Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda R. Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Xin Lan, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick C. McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data, 17, 965–1039, https://doi.org/10.5194/essd-17-965-2025, https://doi.org/10.5194/essd-17-965-2025, 2025
Short summary
Short summary
The Global Carbon Budget 2024 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2024). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Andrew D. King, Tilo Ziehn, Matthew Chamberlain, Alexander R. Borowiak, Josephine R. Brown, Liam Cassidy, Andrea J. Dittus, Michael Grose, Nicola Maher, Seungmok Paik, Sarah E. Perkins-Kirkpatrick, and Aditya Sengupta
Earth Syst. Dynam., 15, 1353–1383, https://doi.org/10.5194/esd-15-1353-2024, https://doi.org/10.5194/esd-15-1353-2024, 2024
Short summary
Short summary
Governments are targeting net-zero emissions later this century with the aim of limiting global warming in line with the Paris Agreement. However, few studies explore the long-term consequences of reaching net-zero emissions and the effects of a delay in reaching net-zero. We use the Australian Earth system model to examine climate evolution under net-zero emissions. We find substantial changes which differ regionally, including continued Southern Ocean warming and Antarctic sea ice reduction.
Benoît Pasquier, Mark Holzer, and Matthew A. Chamberlain
Biogeosciences, 21, 3373–3400, https://doi.org/10.5194/bg-21-3373-2024, https://doi.org/10.5194/bg-21-3373-2024, 2024
Short summary
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Matthew A. Chamberlain, Tilo Ziehn, and Rachel M. Law
Biogeosciences, 21, 3053–3073, https://doi.org/10.5194/bg-21-3053-2024, https://doi.org/10.5194/bg-21-3053-2024, 2024
Short summary
Short summary
This paper explores the climate processes that drive increasing global average temperatures in zero-emission commitment (ZEC) simulations despite decreasing atmospheric CO2. ACCESS-ESM1.5 shows the Southern Ocean to continue to warm locally in all ZEC simulations. In ZEC simulations that start after the emission of more than 1000 Pg of carbon, the influence of the Southern Ocean increases the global temperature.
Colette Gabrielle Kerry, Moninya Roughan, Shane Keating, David Gwyther, Gary Brassington, Adil Siripatana, and Joao Marcos A. C. Souza
Geosci. Model Dev., 17, 2359–2386, https://doi.org/10.5194/gmd-17-2359-2024, https://doi.org/10.5194/gmd-17-2359-2024, 2024
Short summary
Short summary
Ocean forecasting relies on the combination of numerical models and ocean observations through data assimilation (DA). Here we assess the performance of two DA systems in a dynamic western boundary current, the East Australian Current, across a common modelling and observational framework. We show that the more advanced, time-dependent method outperforms the time-independent method for forecast horizons of 5 d. This advocates the use of advanced methods for highly variable oceanic regions.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
Short summary
Short summary
The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Laurie C. Menviel, Paul Spence, Andrew E. Kiss, Matthew A. Chamberlain, Hakase Hayashida, Matthew H. England, and Darryn Waugh
Biogeosciences, 20, 4413–4431, https://doi.org/10.5194/bg-20-4413-2023, https://doi.org/10.5194/bg-20-4413-2023, 2023
Short summary
Short summary
As the ocean absorbs 25% of the anthropogenic emissions of carbon, it is important to understand the impact of climate change on the flux of carbon between the ocean and the atmosphere. Here, we use a very high-resolution ocean, sea-ice, carbon cycle model to show that the capability of the Southern Ocean to uptake CO2 has decreased over the last 40 years due to a strengthening and poleward shift of the southern hemispheric westerlies. This trend is expected to continue over the coming century.
Benoît Pasquier, Mark Holzer, Matthew A. Chamberlain, Richard J. Matear, Nathaniel L. Bindoff, and François W. Primeau
Biogeosciences, 20, 2985–3009, https://doi.org/10.5194/bg-20-2985-2023, https://doi.org/10.5194/bg-20-2985-2023, 2023
Short summary
Short summary
Modeling the ocean's carbon and oxygen cycles accurately is challenging. Parameter optimization improves the fit to observed tracers but can introduce artifacts in the biological pump. Organic-matter production and subsurface remineralization rates adjust to compensate for circulation biases, changing the pathways and timescales with which nutrients return to the surface. Circulation biases can thus strongly alter the system’s response to ecological change, even when parameters are optimized.
Alban Planchat, Lester Kwiatkowski, Laurent Bopp, Olivier Torres, James R. Christian, Momme Butenschön, Tomas Lovato, Roland Séférian, Matthew A. Chamberlain, Olivier Aumont, Michio Watanabe, Akitomo Yamamoto, Andrew Yool, Tatiana Ilyina, Hiroyuki Tsujino, Kristen M. Krumhardt, Jörg Schwinger, Jerry Tjiputra, John P. Dunne, and Charles Stock
Biogeosciences, 20, 1195–1257, https://doi.org/10.5194/bg-20-1195-2023, https://doi.org/10.5194/bg-20-1195-2023, 2023
Short summary
Short summary
Ocean alkalinity is critical to the uptake of atmospheric carbon and acidification in surface waters. We review the representation of alkalinity and the associated calcium carbonate cycle in Earth system models. While many parameterizations remain present in the latest generation of models, there is a general improvement in the simulated alkalinity distribution. This improvement is related to an increase in the export of biotic calcium carbonate, which closer resembles observations.
Dipayan Choudhury, Laurie Menviel, Katrin J. Meissner, Nicholas K. H. Yeung, Matthew Chamberlain, and Tilo Ziehn
Clim. Past, 18, 507–523, https://doi.org/10.5194/cp-18-507-2022, https://doi.org/10.5194/cp-18-507-2022, 2022
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We investigate the effects of a warmer climate from the Earth's paleoclimate (last interglacial) on the marine carbon cycle of the Southern Ocean using a carbon-cycle-enabled state-of-the-art climate model. We find a 150 % increase in CO2 outgassing during this period, which results from competition between higher sea surface temperatures and weaker oceanic circulation. From this we unequivocally infer that the carbon uptake by the Southern Ocean will reduce under a future warming scenario.
Hakase Hayashida, Meibing Jin, Nadja S. Steiner, Neil C. Swart, Eiji Watanabe, Russell Fiedler, Andrew McC. Hogg, Andrew E. Kiss, Richard J. Matear, and Peter G. Strutton
Geosci. Model Dev., 14, 6847–6861, https://doi.org/10.5194/gmd-14-6847-2021, https://doi.org/10.5194/gmd-14-6847-2021, 2021
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Ice algae are tiny plants like phytoplankton but they grow within sea ice. In polar regions, both phytoplankton and ice algae are the foundation of marine ecosystems and play an important role in taking up carbon dioxide in the atmosphere. However, state-of-the-art climate models typically do not include ice algae, and therefore their role in the climate system remains unclear. This project aims to address this knowledge gap by coordinating a set of experiments using sea-ice–ocean models.
Nicholas King-Hei Yeung, Laurie Menviel, Katrin J. Meissner, Andréa S. Taschetto, Tilo Ziehn, and Matthew Chamberlain
Clim. Past, 17, 869–885, https://doi.org/10.5194/cp-17-869-2021, https://doi.org/10.5194/cp-17-869-2021, 2021
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The Last Interglacial period (LIG) is characterised by strong orbital forcing compared to the pre-industrial period (PI). This study compares the mean climate state of the LIG to the PI as simulated by the ACCESS-ESM1.5, with a focus on the southern hemispheric monsoons, which are shown to be consistently weakened. This is associated with cooler terrestrial conditions in austral summer due to decreased insolation, and greater pressure and subsidence over land from Hadley cell strengthening.
Masa Kageyama, Louise C. Sime, Marie Sicard, Maria-Vittoria Guarino, Anne de Vernal, Ruediger Stein, David Schroeder, Irene Malmierca-Vallet, Ayako Abe-Ouchi, Cecilia Bitz, Pascale Braconnot, Esther C. Brady, Jian Cao, Matthew A. Chamberlain, Danny Feltham, Chuncheng Guo, Allegra N. LeGrande, Gerrit Lohmann, Katrin J. Meissner, Laurie Menviel, Polina Morozova, Kerim H. Nisancioglu, Bette L. Otto-Bliesner, Ryouta O'ishi, Silvana Ramos Buarque, David Salas y Melia, Sam Sherriff-Tadano, Julienne Stroeve, Xiaoxu Shi, Bo Sun, Robert A. Tomas, Evgeny Volodin, Nicholas K. H. Yeung, Qiong Zhang, Zhongshi Zhang, Weipeng Zheng, and Tilo Ziehn
Clim. Past, 17, 37–62, https://doi.org/10.5194/cp-17-37-2021, https://doi.org/10.5194/cp-17-37-2021, 2021
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The Last interglacial (ca. 127 000 years ago) is a period with increased summer insolation at high northern latitudes, resulting in a strong reduction in Arctic sea ice. The latest PMIP4-CMIP6 models all simulate this decrease, consistent with reconstructions. However, neither the models nor the reconstructions agree on the possibility of a seasonally ice-free Arctic. Work to clarify the reasons for this model divergence and the conflicting interpretations of the records will thus be needed.
Cited articles
Argo: Argo float data and metadata from Global Data Assembly Centre (Argo
GDAC), SEANOE [data set], https://doi.org/10.17882/42182, 2021. a
Banzon, V. F., Reynolds, R. W., Stokes, D., and Xue, Y.: A
1/4-Spatial-Resolution Daily Sea Surface Temperature Climatology Based on a
Blended Satellite and in situ Analysis, J. Climate, 27, 8221–8228,
https://doi.org/10.1175/JCLI-D-14-00293.1, 2014. a
Bi, D., Marsland, S. J., Uotila, P., O'Farrell, S., Fiedler, R.,
Sullivan, A., Griffies, S. M., Zhou, X., and Hirst, A. C.: ACCESS
OM, the Ocean-Sea Ice Core of the ACCESS Coupled Model, Aust.
Meteorol. Ocean., 63, 213–232, 2013. a
Brassington, G. B., Freeman, J., Huang, X., Pugh, T., Oke, P. R., Sandery, P. A., Taylor, A., Andreu-Burillo, I., Schiller, A., Griffin, D. A., Fiedler, R., Mansbridge, J., Beggs, H., and Spillman, C. M.: Ocean model, analysis and prediction system: version 2, CAWCR Technical Report 52, Centre for Australian Weather and Climate Research, 2012. a
Cabanes, C., Grouazel, A., von Schuckmann, K., Hamon, M., Turpin, V., Coatanoan, C., Paris, F., Guinehut, S., Boone, C., Ferry, N., de Boyer Montégut, C., Carval, T., Reverdin, G., Pouliquen, S., and Le Traon, P.-Y.: The CORA dataset: validation and diagnostics of in-situ ocean temperature and salinity measurements, Ocean Sci., 9, 1–18, https://doi.org/10.5194/os-9-1-2013, 2013. a
Carrier, M. J., Osborne, J. J., Ngodock, H. E., Smith, S. R., Souopgui, I., and
D’Addezio, J. M.: A Multiscale Approach to High-Resolution Ocean Profile
Observations within a 4DVAR Analysis System, Mon. Weather Rev., 147,
627–643, https://doi.org/10.1175/MWR-D-17-0300.1, 2019. a
Chamberlain, M. A., Oke, P. R., and Fiedler, R.: Bluelink Ocean Reanalysis –
BRAN2020, NCI Data Catalogue, https://doi.org/10.25914/6009627c7af03,
2021b. a, b
Chiswell, S. M., Bostock, H. C., Sutton, P. J., and Williams, M. J.: Physical
oceanography of the deep seas around New Zealand: a review, New Zealand
J. Mar. Freshw. Res., 49, 286–317,
https://doi.org/10.1080/00288330.2014.992918, 2015. a
Coleman, M. A., Roughan, M., Macdonald, H. S., Connell, S. D., Gillanders,
B. M., Kelaher, B. P., and Steinberg, P. D.: Variation in the strength of
continental boundary currents determines continent-wide connectivity in kelp,
J. Ecol., 99, 1026–1032, https://doi.org/10.1111/j.1365-2745.2011.01822.x,
2011. a
Delworth, T. L., Broccoli, A. J., Rosati, A., Stouffer, R. J.,
Balaji, V., Beesley, J. A., Cooke, W. F., Dixon, K. W., Dunne, J.,
Dunne, K. A., Durachta, J. W., Findell, K. L., Ginoux, P.,
Gnanadesikan, A., Gordon, C. T., Griffies, S. M., Gudgel, R.,
Harrison, M. J., Held, I. M., Hemler, R. S., Horowitz, L. W.,
Klein, S. A., Knutson, T. R., Kushner, P. J., Langenhorst, A. R.,
Lee, H.-C., Lin, S.-J., Lu, J., Malyshev, S. L., Milly, P. C. D.,
Ramaswamy, V., Russell, J., Schwarzkopf, M. D., Shevliakova, E.,
Sirutis, J. J., Spelman, M. J., Stern, W. F., Winton, M.,
Wittenberg, A. T., Wyman, B., Zeng, F., and Zhang, R.: GFDL's CM2
Global Coupled Climate Models. Part I: Formulation and Simulation
Characteristics, J. Climate, 19, 643–674, https://doi.org/10.1175/JCLI3629.1,
2006. a
Divakaran, P. and Brassington, G. B.: Arterial ocean circulation of the
southeast Indian Ocean, Geophys. Res. Lett., 38, L01802,
https://doi.org/10.1029/2010GL045574, 2011. a
Embury, O., Bulgin, C., and Mittaz, J.: ESA Sea Surface Temperature Climate
Change Initiative (SST_cci): Advanced Very High Resolution Radiometer
(AVHRR) Level 2 Preprocessed (L2P) Climate Data Record, version 2.1, Centre
for Environmental Data Analysis [data set],
https://doi.org/10.5285/373638ed9c434e78b521cbe01ace5ef7, 2019a. a
Embury, O., Bulgin, C., and Mittaz, J.: ESA Sea Surface Temperature Climate
Change Initiative (SST_cci): Along-Track Scanning Radiometer (ATSR) Level 2
Preprocessed (L2P) Climate Data Record, version 2.1, Centre for
Environmental Data Analysis [data set], https://doi.org/10.5285/916b93aaf1474ce793171a33ca4c5026,
2019b. a
Feng, M., Zhang, X., Oke, P., Monselesan, D., Chamberlain, M., Matear, R., and
Schiller, A.: Invigorating ocean boundary current systems around Australia
during 1979–2014: As simulated in a near-global eddy-resolving ocean model,
J. Geophys. Res.-Oceans, 121, 3395–3408, 2016. a
Gentemann, C. L., Meissner, T., and Wentz, F. J.: Accuracy of Satellite
Sea Surface Temperatures at 7 and 11 GHz, IEEE T. Geosci.
Remote S., 48, 1009–1018, https://doi.org/10.1109/TGRS.2009.2030322, 2010. a
Good, S., Embury, O., Bulgin, C., and Mittaz, J.: ESA Sea Surface Temperature
Climate Change Initiative (SST_cci): Level 4 Analysis Climate Data Record,
version 2.1, Centre for Environmental Data Analysis [data set],
https://doi.org/10.5285/62c0f97b1eac4e0197a674870afe1ee6, 2019. a
Hartog, J. R., Hobday, A. J., Matear, R., and Feng, M.: Habitat overlap between
southern bluefin tuna and yellowfin tuna in the east coast longline fishery –
implications for present and future spatial management, Deep-Sea Res.
Pt. II, 58, 746–752,
https://doi.org/10.1016/j.dsr2.2010.06.005, 2011. a
Henley, B. J., Gergis, J., Karoly, D. J., Power, S., Kennedy, J., and Folland,
C. K.: A Tripole Index for the Interdecadal Pacific Oscillation, Clim.
Dynam., 45, 3077–3090, https://doi.org/10.1007/s00382-015-2525-1, 2015. a, b
Kiss, A. E., Hogg, A. McC., Hannah, N., Boeira Dias, F., Brassington, G. B., Chamberlain, M. A., Chapman, C., Dobrohotoff, P., Domingues, C. M., Duran, E. R., England, M. H., Fiedler, R., Griffies, S. M., Heerdegen, A., Heil, P., Holmes, R. M., Klocker, A., Marsland, S. J., Morrison, A. K., Munroe, J., Nikurashin, M., Oke, P. R., Pilo, G. S., Richet, O., Savita, A., Spence, P., Stewart, K. D., Ward, M. L., Wu, F., and Zhang, X.: ACCESS-OM2 v1.0: a global ocean–sea ice model at three resolutions, Geosci. Model Dev., 13, 401–442, https://doi.org/10.5194/gmd-13-401-2020, 2020. a
Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., Onogi,
K., Kamahori, H., Kobayashi, C., Endo, H., Miyaoka, K., and Takahaski, K.: The JRA-55 reanalysis:
General specifications and basic characteristics, J.
Meteorol. Soc. Jpn., 93, 5–48, 2015. a
Li, Z., McWilliams, J. C., Ide, K., and Farrara, J. D.: Coastal ocean data
assimilation using a multi-scale three-dimensional variational scheme, Ocean
Dynam., 65, 1001–1015, https://doi.org/10.1007/s10236-015-0850-x, 2015. a
Locarnini, R., Mishonov, A., Antonov, J., Boyer, T., Garcia, H., Baranova, O.,
Zweng, M., Paver, C., Reagan, J., Johnson, D., Hamilton, M., and Seidov, D.:
World Ocean Atlas 2013, Volume 1: Temperature, in: NOAA Atlas NESDIS 74,
edited by: Levitus, S. and Mishonov, A., U.S. Government Printing
Office, Washington, DC, 40 pp., 2013. a, b
Merchant, C. J., Embury, O., Bulgin, C. E., Block, T., Corlett, G. K., Fiedler,
E., Good, S. A., Mittaz, J., Rayner, N. A., Berry, D., Eastwood, S., Taylor, M., Tsushima, Y., Waterfall, A., Wilson, R., and Donlon, C.:
Satellite-based time-series of sea-surface temperature since 1981 for climate
applications, Sci. Data, 6, 1–18, https://doi.org/10.1038/s41597-019-0236-x,
2019. a, b, c, d
Minnett, P. J., Kilpatrick, K. A., Podestá, G. P., Evans, R. H., Szczodrak,
M. D., Izaguirre, M. A., Williams, E. J., Walsh, S., Reynolds, R. M., Bailey,
S. W., Armstrong, E. M., and Vazquez-Cuervo, J.: Skin Sea-Surface Temperature
from VIIRS on Suomi-NPP–NASA Continuity Retrievals, Remote Sensing, 12, 3369,
https://doi.org/10.3390/rs12203369, 2020. a
Naval Oceanographic Office: METOP-A AVHRR GAC L2P swath SST data set. Ver.
1.0, PO.DAAC [data set], CA, USA, https://doi.org/10.5067/GHMTG-2PN02, 2014a. a
Naval Oceanographic Office: METOP-B AVHRR GAC L2P swath SST data set. Ver.
1.0, PO.DAAC [data set], CA, USA,
https://doi.org/10.5067/GHMTB-2PN02, 2014b. a
Naval Oceanographic Office: N-18 AVHRR GAC L2P swath SST data set. Ver.
1.0, PO.DAAC [data set], CA, USA,
https://doi.org/10.5067/GH18G-2PN02, 2014c. a
Naval Oceanographic Office: N-19 AVHRR GAC L2P swath SST data set. Ver.
1.0, PO.DAAC [data set], CA, USA,
https://doi.org/10.5067/GH19G-2PN02, 2014d. a
NOAA Office of Satellite and Product Operations: Sea Surface temperature
retrievals produced by NOAA/NESDIS/OSPO office from VIIRS sensor. Ver. 2.61
, PO.DAAC [data set], CA, USA,
https://doi.org/10.5067/GHVRS-2PO61, 2019. a
Oke, P. R. and Griffin, D. A.: The cold-core eddy and strong upwelling off the
coast of New South Wales in early 2007, Deep-Sea Res., 58, 574–591,
https://doi.org/10.1016/j.dsr2.2010.06.006, 2011. a, b
Oke, P. R. and Sakov, P.: Representation error of oceanic observations for data
assimilation, J. Atmos. Ocean. Tech., 25, 1004–1017,
2008. a
Oke, P. R. and Schiller, A.: Impact of Argo, SST, and altimeter data on an
eddy-resolving ocean reanalysis, Geophys. Res. Let., 34, L19601,
https://doi.org/10.1029/2007GL031549, 2007. a
Oke, P. R., Schiller, A., Griffin, D. A., and Brassington, G. B.: Ensemble data
assimilation for an eddy-resolving ocean model of the Australian region,
Q. J. Roy. Meteorol. Soc., 131, 3301–3311,
https://doi.org/10.1256/qj.05.95, 2005. a
Oke, P. R., Sakov, P., and Corney, S. P.: Impacts of localisation in the EnKF
and EnOI: experiments with a small model, Ocean Dynam., 57, 32–45,
https://doi.org/10.1007/s10236-006-0088-8, 2007. a
Oke, P. R., Brassington, G. B., Griffin, D. A., and Schiller, A.: The Bluelink
Ocean Data Assimilation System (BODAS), Ocean Model., 21, 46–70,
https://doi.org/10.1016/j.ocemod.2007.11.002, 2008. a
Oke, P. R., Sakov, P., and Schulz, E.: A comparison of shelf observation
platforms for assimilation in an eddy-resolving ocean model, Dynam.
Atmos. Oceans, 48, 121–142,
https://doi.org/10.1016/j.dynatmoce.2009.04.002, 2009. a
Oke, P. R., Griffin, D. A., Schiller, A., Matear, R. J., Fiedler, R., Mansbridge, J., Lenton, A., Cahill, M., Chamberlain, M. A., and Ridgway, K.: Evaluation of a near-global eddy-resolving ocean model, Geosci. Model Dev., 6, 591–615, https://doi.org/10.5194/gmd-6-591-2013, 2013a. a, b, c
Oke, P. R., Sakov, P., Cahill, M. L., Dunn, J. R., Fiedler, R., Griffin, D. A.,
Mansbridge, J. V., Ridgway, K. R., and Schiller, A.: Towards a dynamically
balanced eddy-resolving ocean reanalysis: BRAN3, Ocean Model., 67,
52–70, https://doi.org/10.1016/j.ocemod.2013.03.008, 2013b. a, b, c, d
Oke, P. R., Griffin, D. A., Rykova, T., and de Oliveira, H. B.: Ocean
circulation in the Great Australian Bight in an eddy-resolving ocean
reanalysis: The eddy field, seasonal and interannual variability, Deep-Sea
Res. Pt. II, 157–158, 11–26,
https://doi.org/10.1016/j.dsr2.2018.09.012, 2018. a, b, c, d
Oke, P. R., Roughan, M., Cetina-Heredia, P., Pilo, G. S., Ridgway, K. R.,
Rykova, T., Archer, M. R., Coleman, R. C., Kerry, C. G., Rocha, C.,
Schaeffer, A., and Vitarelli, E.: Revisiting the circulation of the East
Australian Current: Its path, separation, and eddy field, Prog.
Oceanogr., 176, 102139, https://doi.org/10.1016/j.pocean.2019.102139, 2019. a
Oke, P. R., Chamberlain, M. A., Fiedler, R. A. S., Bastos De Oliveira, H.,
Beggs, H. M., and Brassington, G. B.: Combining Argo and satellite data using
model-derived covariances: Blue Maps, Front. Earth Sci., 9, 485,
https://doi.org/10.3389/feart.2021.696985, 2021. a, b, c
O’Carroll, A. G., Armstrong, E. M., Beggs, H. M., Bouali, M., Casey, K. S.,
Corlett, G. K., Dash, P., Donlon, C. J., Gentemann, C. L., Høyer, J. L.,
Ignatov, A., Kabobah, K., Kachi, M., Kurihara, Y., Karagali, I., Maturi, E.,
Merchant, C. J., Marullo, S., Minnett, P. J., Pennybacker, M., Ramakrishnan,
B., Ramsankaran, R., Santoleri, R., Sunder, S., Saux Picart, S.,
Vázquez-Cuervo, J., and Wimmer, W.: Observational Needs of Sea Surface
Temperature, Front. Mar. Sci., 6, 420,
https://doi.org/10.3389/fmars.2019.00420, 2019. a, b
Petrenko, B., Ignatov, A., Kihai, Y., Stroup, J., and Dash, P.: Evaluation and
selection of SST regression algorithms for JPSS VIIRS, J. Geophys.
Res.-Atmos., 119, 4580–4599, https://doi.org/10.1002/2013JD020637, 2014. a
Pilo, G. S., Oke, P. R., Rykova, T., Coleman, R., and Ridgway, K.: Do East
Australian Current anticyclonic eddies leave the Tasman Sea?, J.
Geophys. Res.-Oceans, 120, 8099–8114, 2015. a
Rayner, N. A., Parker, D. E., Horton, E. B., Folland, C. K., Alexander, L. V.,
Rowell, D. P., Kent, E. C., and Kaplan, A.: Global analyses of sea surface
temperature, sea ice, and night marine air temperature since the late
nineteenth century, J. Geophys. Res.-Atmos., 108, 4407,
https://doi.org/10.1029/2002JD002670, 2003. a
Rodi, W.: Examples of calculation methods for flow and mixing in stratified
fluids, J. Geophys. Res.-Oceans, 92, 5305–5328, 1987. 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, 439, https://doi.org/10.3389/fmars.2019.00439, 2019. a
Sakov, P. and Sandery, P.: An adaptive quality control procedure for data
assimilation, Tellus A, 69, 1318031, https://doi.org/10.1080/16000870.2017.1318031, 2017. a
Scharroo, R., Leuliette, E., Lillibridge, J., Byrne, D., Naeije, M.,
and Mitchum, G.: RADS: Consistent Multi-Mission Products, in: 20 Years of
Progress in Radar Altimetry, edited by: Ouwehand, L., ESA
Special Publication, 710, p. 69, 2013. a
Schiller, A. and Oke, P. R.: Dynamics of ocean surface mixed layer variability
in the Indian Ocean, J. Geophys. Res.-Oceans, 120,
4162–4186, https://doi.org/10.1002/2014JC010538, 2015. a
Schiller, A., Oke, P. R., Brassington, G., Entel, M., Fiedler, R., Griffin,
D. A., and Mansbridge, J. V.: Eddy-resolving ocean circulation in the
Asian-Australian region inferred from an ocean reanalysis effort, Prog.
Oceanogr., 76, 334–365, https://doi.org/10.1016/j.pocean.2008.01.003,
2008a. a
Schiller, A., Oke, P. R., Brassington, G. B., Entel, M., Fiedler, R., Griffin,
D. A., and Mansbridge, J. V.: Eddy-resolving ocean circulation in the
Asian-Australian region inferred from an ocean reanalysis effort,
Prog. Oceanogr., 76, 334–365, https://doi.org/10.1016/j.pocean.2008.01.003,
2008b. a, b, c, d, e, f, g
Schiller, A., Ridgway, K. R., Steinberg, C. R., and Oke, P. R.: Dynamics of
three anomalous SST events in the Coral Sea, Geophys. Res.
Lett., 36, L06606, https://doi.org/10.1029/2008GL036997, 2009. a, b
Schiller, A., Brassington, G. B., Oke, P., Cahill, M., Divakaran, P., Entel,
M., Freeman, J., Griffin, D., Herzfeld, M., Hoeke, R., Huang, X., Jones, E.,
King, E., Parker, B., Pitman, T., Rosebrock, U., Sweeney, J., Taylor, A.,
Thatcher, M., Woodham, R., and Zhong, A.: Bluelink ocean forecasting
Australia: 15 years of operational ocean service delivery with societal,
economic and environmental benefits, J. Oper. Oceanogr., 13,
1–18, https://doi.org/10.1080/1755876X.2019.1685834, 2020. a
Steven, A. D. L., Baird, M. E., Brinkman, R., Car, N. J., Cox, S. J., Herzfeld,
M., Hodge, J., Jones, E., King, E., Margvelashvili, N., Robillot, C., Robson,
B., Schroeder, T., Skerratt, J., Tickell, S., Tuteja, N., Wild-Allen, K., and
Yu, J.: eReefs: An operational information system for managing the Great
Barrier Reef, J. Oper. Oceanogr., 12, S12–S28,
https://doi.org/10.1080/1755876X.2019.1650589, 2019. a
Tanguy, S., Jerome, G., Sylvie, P., and Gilles, R.: CORA, Coriolis Ocean
Dataset for Reanalysis, SEANOE [data set], https://doi.org/10.17882/46219, 2019. a
Tissier, A.-S., Brankart, J.-M., Testut, C.-E., Ruggiero, G., Cosme, E., and Brasseur, P.: A multiscale ocean data assimilation approach combining spatial and spectral localisation, Ocean Sci., 15, 443–457, https://doi.org/10.5194/os-15-443-2019, 2019. a
Tsujino, H., Urakawa, S., Nakano, H., Small, R. J., Kim, W. M., Yeager, S. G.,
Danabasoglu, G., Suzuki, T., Bamber, J. L., Bentsen, M., Boening, C., Bozec,
A., Chassignet, E., Curchitser, E., Dias, F. B., Durack, P. J., Griffies,
S. M., Harada, Y., Ilicak, M., Josey, S., Kobayashi, C., Kobayashi, S.,
Komuro, Y., Large, W. G., Le Sommer, J., Marsland, S., Masina, S., Scheinert,
M., Tomita, H., Valdivieso, M., and Yamazaki, D.:
input4MIPs.CMIP6.OMIP.MRI.MRI-JRA55-do-1-5-0, Version 20200916, Earth System Grid Federation [data set],
https://doi.org/10.22033/ESGF/input4MIPs.15017, 2020.
a
Wong, A. P., 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., Buck, J. J., 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, Kr. E., Purkey, S. G., Zilberman, N., Alkire, M. B., Swift, D., Owens, W. B., Hersh, C., Robbins, P., West-Mack, D., Bahr, F., Yoshida, S., Sutton, P. J., Cancouët, R., Coatanoan, C., Dobbler, D., Juan, Andrea 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., 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., Ouellet, M., Ross, T., Tran, A., Dong, M., Liu, Z., Xu, Jia., Kang, Ki., Jo, H., Kim, S., and Park, H.:
Argo Data 1999–2019: Two Million Temperature-Salinity Profiles and
Subsurface Velocity Observations From a Global Array of Profiling Floats,
Front. Mar. Sci., 7, 700,https://doi.org/10.3389/fmars.2020.00700, 2020. a
Zweng, M. M., Reagan, J. R., Antonov, J. I., Locarnini, R. A., Mishonov, A. V.,
Boyer, T. P., Garcia, H. . E., Baranova, O. K., Paver, C. R., Johnson, D. R.,
Seidov, D., and Biddle, M.: World Ocean Atlas 2013, Volume 2: Salinity, in:
NOAA Atlas NESDIS 74, edited by: Levitus, S. and Mishonov, A.,
U.S. Government Printing Office, Washington, DC, 39 pp., 2013. a, b, c
Short summary
BRAN2020 is a dynamical reconstruction of the ocean, combining observations with a high-resolution global ocean model. BRAN2020 currently spans January 1993 to December 2019, assimilating in situ temperature and salinity, as well as satellite-based sea level and sea surface temperature. A new multiscale approach to data assimilation constrains the broad-scale ocean properties and turbulent mesoscale dynamics in two steps, showing closer agreement to observations than all previous versions.
BRAN2020 is a dynamical reconstruction of the ocean, combining observations with a...
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