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1. A Synthesis of Global Coastal Ocean Greenhouse Gas Fluxes

Author

Resplandy, L, Hogikyan, A, Müller, JD, Najjar, RG, Bange, HW, Bianchi, D, Weber, T, Cai, W‐J, Doney, SC, Fennel, K, Gehlen, M, Hauck, J, Lacroix, F, Landschützer, P, Le Quéré, C, Roobaert, A, Schwinger, J, Berthet, S, Bopp, L, Chau, TTT, Dai, M, Gruber, N, Ilyina, T, Kock, A, Manizza, M, Lachkar, Z, Laruelle, GG, Liao, E, Lima, ID, Nissen, Cara, Rödenbeck, C, Séférian, R, Toyama, K, Tsujino, H, Regnier, P, Resplandy, L, Hogikyan, A, Müller, JD, Najjar, RG, Bange, HW, Bianchi, D, Weber, T, Cai, W‐J, Doney, SC, Fennel, K, Gehlen, M, Hauck, J, Lacroix, F, Landschützer, P, Le Quéré, C, Roobaert, A, Schwinger, J, Berthet, S, Bopp, L, Chau, TTT, Dai, M, Gruber, N, Ilyina, T, Kock, A, Manizza, M, Lachkar, Z, Laruelle, GG, Liao, E, Lima, ID, Nissen, Cara, Rödenbeck, C, Séférian, R, Toyama, K, Tsujino, H, and Regnier, P

Abstract

The coastal ocean contributes to regulating atmospheric greenhouse gas concentrations by taking up carbon dioxide (CO2) and releasing nitrous oxide (N2O) and methane (CH4). In this second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP2), we quantify global coastal ocean fluxes of CO2, N2O and CH4 using an ensemble of global gap-filled observation-based products and ocean biogeochemical models. The global coastal ocean is a net sink of CO2 in both observational products and models, but the magnitude of the median net global coastal uptake is ∼60% larger in models (−0.72 vs. −0.44 PgC year−1, 1998–2018, coastal ocean extending to 300 km offshore or 1,000 m isobath with area of 77 million km2). We attribute most of this model-product difference to the seasonality in sea surface CO2 partial pressure at mid- and high-latitudes, where models simulate stronger winter CO2 uptake. The coastal ocean CO2 sink has increased in the past decades but the available time-resolving observation-based products and models show large discrepancies in the magnitude of this increase. The global coastal ocean is a major source of N2O (+0.70 PgCO2-e year−1 in observational product and +0.54 PgCO2-e year−1 in model median) and CH4 (+0.21 PgCO2-e year−1 in observational product), which offsets a substantial proportion of the coastal CO2 uptake in the net radiative balance (30%–60% in CO2-equivalents), highlighting the importance of considering the three greenhouse gases when examining the influence of the coastal ocean on climate.

Published
2024

2. A Synthesis of Global Coastal Ocean Greenhouse Gas Fluxes

Author

Resplandy, L., Hogikyan, A., Müller, J. D., Najjar, R. G., Bange, Hermann W., Bianchi, D., Weber, T., Cai, W.‐J., Doney, S. C., Fennel, K., Gehlen, M., Hauck, J., Lacroix, F., Landschützer, P., Le Quéré, C., Roobaert, A., Schwinger, J., Berthet, S., Bopp, L., Chau, T. T. T., Dai, M., Gruber, N., Ilyina, T., Kock, Annette, Manizza, M., Lachkar, Z., Laruelle, G. G., Liao, E., Lima, I. D., Nissen, C., Rödenbeck, C., Séférian, R., Toyama, K., Tsujino, H., Regnier, P., Resplandy, L., Hogikyan, A., Müller, J. D., Najjar, R. G., Bange, Hermann W., Bianchi, D., Weber, T., Cai, W.‐J., Doney, S. C., Fennel, K., Gehlen, M., Hauck, J., Lacroix, F., Landschützer, P., Le Quéré, C., Roobaert, A., Schwinger, J., Berthet, S., Bopp, L., Chau, T. T. T., Dai, M., Gruber, N., Ilyina, T., Kock, Annette, Manizza, M., Lachkar, Z., Laruelle, G. G., Liao, E., Lima, I. D., Nissen, C., Rödenbeck, C., Séférian, R., Toyama, K., Tsujino, H., and Regnier, P.

Abstract

The coastal ocean contributes to regulating atmospheric greenhouse gas concentrations by taking up carbon dioxide (CO2) and releasing nitrous oxide (N2O) and methane (CH4). In this second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP2), we quantify global coastal ocean fluxes of CO2, N2O and CH4 using an ensemble of global gap-filled observation-based products and ocean biogeochemical models. The global coastal ocean is a net sink of CO2 in both observational products and models, but the magnitude of the median net global coastal uptake is similar to 60% larger in models (-0.72 vs. -0.44 PgC year-1, 1998-2018, coastal ocean extending to 300 km offshore or 1,000 m isobath with area of 77 million km2). We attribute most of this model-product difference to the seasonality in sea surface CO2 partial pressure at mid- and high-latitudes, where models simulate stronger winter CO2 uptake. The coastal ocean CO2 sink has increased in the past decades but the available time-resolving observation-based products and models show large discrepancies in the magnitude of this increase. The global coastal ocean is a major source of N2O (+0.70 PgCO2-e year-1 in observational product and +0.54 PgCO2-e year-1 in model median) and CH4 (+0.21 PgCO2-e year-1 in observational product), which offsets a substantial proportion of the coastal CO2 uptake in the net radiative balance (30%-60% in CO2-equivalents), highlighting the importance of considering the three greenhouse gases when examining the influence of the coastal ocean on climate. The coastal ocean regulates greenhouse gases. It acts as a sink of carbon dioxide (CO2) but also releases nitrous oxide (N2O) and methane (CH4) into the atmosphere. This synthesis contributes to the second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP2) and provides a comprehensive view of the coastal air-sea fluxes of these three greenhouse gases at the global scale. We use a multi-faceted approach combining gap-f

Published
2024
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3. A Synthesis of Global Coastal Ocean Greenhouse Gas Fluxes

Author

Resplandy, Laure LR, Hogikyan, A., Müller, Jens Daniel, Najjar, Raymond R.G., Hermann, W. Bange, Bianchi, Daniele, Weber, T., Cai, Wei-Jun, Doney, S. C., Fennel, Katja, Gehlen, Marion, Hauck, J., Lacroix, Fabrice, Landschutzer, Peter, Le Quéré, Corinne, Roobaert, Alizée, Schwinger, J., Berthet, Sarah, Bopp, Laurent, Chau, Thi T. T., Dai, Minhan, Gruber, Nicolas, Ilyina, Tatiana, Kock, A., Manizza, M., Lachkar, Z., Laruelle, Goulven Gildas, Liao, Enhui EL, Lima, I. D., Nissen, C, Rödenbeck, Christian, Séférian, Roland, Toyama, K., Tsujino, H., Regnier, Pierre A.G., Resplandy, Laure LR, Hogikyan, A., Müller, Jens Daniel, Najjar, Raymond R.G., Hermann, W. Bange, Bianchi, Daniele, Weber, T., Cai, Wei-Jun, Doney, S. C., Fennel, Katja, Gehlen, Marion, Hauck, J., Lacroix, Fabrice, Landschutzer, Peter, Le Quéré, Corinne, Roobaert, Alizée, Schwinger, J., Berthet, Sarah, Bopp, Laurent, Chau, Thi T. T., Dai, Minhan, Gruber, Nicolas, Ilyina, Tatiana, Kock, A., Manizza, M., Lachkar, Z., Laruelle, Goulven Gildas, Liao, Enhui EL, Lima, I. D., Nissen, C, Rödenbeck, Christian, Séférian, Roland, Toyama, K., Tsujino, H., and Regnier, Pierre A.G.

Abstract

The coastal ocean contributes to regulating atmospheric greenhouse gas concentrations by taking up carbon dioxide (CO2) and releasing nitrous oxide (N2O) and methane (CH4). In this second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP2), we quantify global coastal ocean fluxes of CO2, N2O and CH4 using an ensemble of global gap-filled observation-based products and ocean biogeochemical models. The global coastal ocean is a net sink of CO2 in both observational products and models, but the magnitude of the median net global coastal uptake is ∼60% larger in models (−0.72 vs. −0.44 PgC year−1, 1998–2018, coastal ocean extending to 300 km offshore or 1,000 m isobath with area of 77 million km2). We attribute most of this model-product difference to the seasonality in sea surface CO2 partial pressure at mid- and high-latitudes, where models simulate stronger winter CO2 uptake. The coastal ocean CO2 sink has increased in the past decades but the available time-resolving observation-based products and models show large discrepancies in the magnitude of this increase. The global coastal ocean is a major source of N2O (+0.70 PgCO2-e year−1 in observational product and +0.54 PgCO2-e year−1 in model median) and CH4 (+0.21 PgCO2-e year−1 in observational product), which offsets a substantial proportion of the coastal CO2 uptake in the net radiative balance (30%–60% in CO2-equivalents), highlighting the importance of considering the three greenhouse gases when examining the influence of the coastal ocean on climate., SCOPUS: ar.j, info:eu-repo/semantics/published

Published
2024

5. Global Carbon Budget 2023

Author

Integr. Assessm. Global Environm. Change, Environmental Sciences, Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Bakker, D. C. E., Hauck, J., Landschützer, P., Le Quéré, C., Luijkx, I. T., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Anthoni, P., Barbero, L., Bates, N. R., Becker, M., Bellouin, N., Decharme, B., Bopp, L., Brasika, I. B. M., Cadule, P., Chamberlain, M. A., Chandra, N., Chau, T.-T.-T., Chevallier, F., Chini, L. P., Cronin, M., Dou, X., Enyo, K., Evans, W., Falk, S., Feely, R. A., Feng, L., Ford, D. J., Gasser, T., Ghattas, J., Gkritzalis, T., Grassi, G., Gregor, L., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Heinke, J., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jacobson, A. R., Jain, A., Jarníková, T., Jersild, A., Jiang, F., Jin, Z., Joos, F., Kato, E., Keeling, R. F., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Körtzinger, A., Lan, X., Lefèvre, N., Li, H., Liu, J., Liu, Z., Ma, L., Marland, G., Mayot, N., McGuire, P. C., McKinley, G. A., Meyer, G., Morgan, E. J., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K. M., Olsen, A., Omar, A. M., Ono, T., Paulsen, M., Pierrot, D., Pocock, K., Poulter, B., Powis, C. M., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Rosan, T. M., Schwinger, J., Séférian, R., Smallman, T. L., Smith, S. M., Sospedra-Alfonso, R., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tans, P. P., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., van Ooijen, E., Wanninkhof, R., Watanabe, M., Wimart-Rousseau, C., Yang, D., Yang, X., Yuan, W., Yue, X., Zaehle, S., Zeng, J., Zheng, B., Integr. Assessm. Global Environm. Change, Environmental Sciences, Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Bakker, D. C. E., Hauck, J., Landschützer, P., Le Quéré, C., Luijkx, I. T., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Anthoni, P., Barbero, L., Bates, N. R., Becker, M., Bellouin, N., Decharme, B., Bopp, L., Brasika, I. B. M., Cadule, P., Chamberlain, M. A., Chandra, N., Chau, T.-T.-T., Chevallier, F., Chini, L. P., Cronin, M., Dou, X., Enyo, K., Evans, W., Falk, S., Feely, R. A., Feng, L., Ford, D. J., Gasser, T., Ghattas, J., Gkritzalis, T., Grassi, G., Gregor, L., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Heinke, J., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jacobson, A. R., Jain, A., Jarníková, T., Jersild, A., Jiang, F., Jin, Z., Joos, F., Kato, E., Keeling, R. F., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Körtzinger, A., Lan, X., Lefèvre, N., Li, H., Liu, J., Liu, Z., Ma, L., Marland, G., Mayot, N., McGuire, P. C., McKinley, G. A., Meyer, G., Morgan, E. J., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K. M., Olsen, A., Omar, A. M., Ono, T., Paulsen, M., Pierrot, D., Pocock, K., Poulter, B., Powis, C. M., Rehder, G., Resplandy, L., Robertson, E., Rödenbeck, C., Rosan, T. M., Schwinger, J., Séférian, R., Smallman, T. L., Smith, S. M., Sospedra-Alfonso, R., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tans, P. P., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., van Ooijen, E., Wanninkhof, R., Watanabe, M., Wimart-Rousseau, C., Yang, D., Yang, X., Yuan, W., Yue, X., Zaehle, S., Zeng, J., and Zheng, B.

Published
2023

6. Simulations of ocean deoxygenation in the historical era: insights from forced and coupled models

Author

Takano, Y., Ilyina, T., Tjiputra, J., Eddebbar, Y.A., Berthet, S., Bopp, L., Buitenhuis, E., Butenschön, M., Christian, J.R., Dunne, J.P., Gröger, M., Hayashida, H., Hieronymus, J., Koenigk, T., Krasting, J.P., Long, M.C., Lovato, T., Nakano, H., Palmieri, J., Schwinger, J., Seferian, R., Suntharalingam, P., Tatebe, H., Tsujino, H., Urakawa, S., Watanabe, M., Yool, A., Takano, Y., Ilyina, T., Tjiputra, J., Eddebbar, Y.A., Berthet, S., Bopp, L., Buitenhuis, E., Butenschön, M., Christian, J.R., Dunne, J.P., Gröger, M., Hayashida, H., Hieronymus, J., Koenigk, T., Krasting, J.P., Long, M.C., Lovato, T., Nakano, H., Palmieri, J., Schwinger, J., Seferian, R., Suntharalingam, P., Tatebe, H., Tsujino, H., Urakawa, S., Watanabe, M., and Yool, A.

Abstract

Ocean deoxygenation due to anthropogenic warming represents a major threat to marine ecosystems and fisheries. Challenges remain in simulating the modern observed changes in the dissolved oxygen (O2). Here, we present an analysis of upper ocean (0-700m) deoxygenation in recent decades from a suite of the Coupled Model Intercomparison Project phase 6 (CMIP6) ocean biogeochemical simulations. The physics and biogeochemical simulations include both ocean-only (the Ocean Model Intercomparison Project Phase 1 and 2, OMIP1 and OMIP2) and coupled Earth system (CMIP6 Historical) configurations. We examine simulated changes in the O2 inventory and ocean heat content (OHC) over the past 5 decades across models. The models simulate spatially divergent evolution of O2 trends over the past 5 decades. The trend (multi-model mean and spread) for upper ocean global O2 inventory for each of the MIP simulations over the past 5 decades is 0.03 ± 0.39×1014 [mol/decade] for OMIP1, −0.37 ± 0.15×1014 [mol/decade] for OMIP2, and −1.06 ± 0.68×1014 [mol/decade] for CMIP6 Historical, respectively. The trend in the upper ocean global O2 inventory for the latest observations based on the World Ocean Database 2018 is −0.98×1014 [mol/decade], in line with the CMIP6 Historical multi-model mean, though this recent observations-based trend estimate is weaker than previously reported trends. A comparison across ocean-only simulations from OMIP1 and OMIP2 suggests that differences in atmospheric forcing such as surface wind explain the simulated divergence across configurations in O2 inventory changes. Additionally, a comparison of coupled model simulations from the CMIP6 Historical configuration indicates that differences in background mean states due to differences in spin-up duration and equilibrium states result in substantial differences in the climate change response of O2. Finally, we discuss gaps and uncertainties in both ocean biogeochemical simulations and observations and explore possible f

Published
2023

7. Global Carbon Budget 2022

Author

Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Gregor, L., Hauck, J., Le Quéré, C., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Alkama, R., Arneth, A., Arora, V. K., Bates, N. R., Becker, M., Bellouin, N., Bittig, H. C., Bopp, L., Chevallier, F., Chini, L. P., Cronin, M., Evans, W., Falk, S., Feely, R. A., Gasser, T., Gehlen, M., Gkritzalis, T., Gloege, L., Grassi, G., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jain, A. K., Jersild, A., Kadono, K., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Landschützer, P., Lefèvre, N., Lindsay, K., Liu, J., Liu, Z., Marland, G., Mayot, N., McGrath, M. J., Metzl, N., Monacci, N. M., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K., Ono, T., Palmer, P. I., Pan, N., Pierrot, D., Pocock, K., Poulter, B., Resplandy, L., Robertson, E., Rödenbeck, C., Rodriguez, C., Rosan, T. M., Schwinger, J., Séférian, R., Shutler, J. D., Skjelvan, I., Steinhoff, T., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tanhua, T., Tans, P. P., Tian, X., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., Walker, A. P., Wanninkhof, R., Whitehead, C., Willstrand Wranne, A., Wright, R., Yuan, W., Yue, C., Yue, X., Zaehle, S., Zeng, J., Zheng, B., Integr. Assessm. Global Environm. Change, Environmental Sciences, Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, College of Life and Environmental Sciences [Exeter], University of Exeter, Rice University [Houston], Center for International Climate and Environmental Research [Oslo] (CICERO), University of Oslo (UiO), Institute of Biogeochemistry and Pollutant Dynamics [ETH Zürich] (IBP), Department of Environmental Systems Science [ETH Zürich] (D-USYS), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich)- Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), Tyndall Centre for Climate Change Research, University of East Anglia [Norwich] (UEA), Meteorology and Air Quality Group, Wageningen University and Research [Wageningen] (WUR), Geophysical Institute [Bergen] (GFI / BiU), University of Bergen (UiB), Bjerknes Centre for Climate Research (BCCR), Department of Biological Sciences [Bergen] (BIO / UiB), University of Bergen (UiB)-University of Bergen (UiB), Meteorology and Air Quality Department [Wageningen] (MAQ), Ludwig-Maximilians-Universität München (LMU), Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Stanford Woods Institute for the Environment, Stanford University, European Commission - Joint Research Centre [Ispra] (JRC), Karlsruhe Institute of Technology (KIT), Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, Austral, Boréal et Carbone (ABC), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Cycles biogéochimiques marins : processus et perturbations (CYBIOM), Earth Sciences, Amsterdam Sustainability Institute, and Isotope Research

Subjects
WIMEK, [SDE.MCG]Environmental Sciences/Global Changes, SDG 13 - Climate Action, Life Science, General Earth and Planetary Sciences, Luchtkwaliteit, Air Quality
Abstract

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based data products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2021, EFOS increased by 5.1 % relative to 2020, with fossil emissions at 10.1 ± 0.5 GtC yr−1 (9.9 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 1.1 ± 0.7 GtC yr−1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 10.9 ± 0.8 GtC yr−1 (40.0 ± 2.9 GtCO2). Also, for 2021, GATM was 5.2 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEAN was 2.9 ± 0.4 GtC yr−1, and SLAND was 3.5 ± 0.9 GtC yr−1, with a BIM of −0.6 GtC yr−1 (i.e. the total estimated sources were too low or sinks were too high). The global atmospheric CO2 concentration averaged over 2021 reached 414.71 ± 0.1 ppm. Preliminary data for 2022 suggest an increase in EFOS relative to 2021 of +1.0 % (0.1 % to 1.9 %) globally and atmospheric CO2 concentration reaching 417.2 ppm, more than 50 % above pre-industrial levels (around 278 ppm). Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2021, but discrepancies of up to 1 GtC yr−1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows (1) a persistent large uncertainty in the estimate of land-use change emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extratropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set. The data presented in this work are available at https://doi.org/10.18160/GCP-2022 (Friedlingstein et al., 2022b).

Published
2022

8. Global Carbon Budget 2022

Author

Integr. Assessm. Global Environm. Change, Environmental Sciences, Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Gregor, L., Hauck, J., Le Quéré, C., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Alkama, R., Arneth, A., Arora, V. K., Bates, N. R., Becker, M., Bellouin, N., Bittig, H. C., Bopp, L., Chevallier, F., Chini, L. P., Cronin, M., Evans, W., Falk, S., Feely, R. A., Gasser, T., Gehlen, M., Gkritzalis, T., Gloege, L., Grassi, G., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jain, A. K., Jersild, A., Kadono, K., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Landschützer, P., Lefèvre, N., Lindsay, K., Liu, J., Liu, Z., Marland, G., Mayot, N., McGrath, M. J., Metzl, N., Monacci, N. M., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K., Ono, T., Palmer, P. I., Pan, N., Pierrot, D., Pocock, K., Poulter, B., Resplandy, L., Robertson, E., Rödenbeck, C., Rodriguez, C., Rosan, T. M., Schwinger, J., Séférian, R., Shutler, J. D., Skjelvan, I., Steinhoff, T., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tanhua, T., Tans, P. P., Tian, X., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., Walker, A. P., Wanninkhof, R., Whitehead, C., Willstrand Wranne, A., Wright, R., Yuan, W., Yue, C., Yue, X., Zaehle, S., Zeng, J., Zheng, B., Integr. Assessm. Global Environm. Change, Environmental Sciences, Friedlingstein, P., O'Sullivan, M., Jones, M. W., Andrew, R. M., Gregor, L., Hauck, J., Le Quéré, C., Luijkx, I. T., Olsen, A., Peters, G. P., Peters, W., Pongratz, J., Schwingshackl, C., Sitch, S., Canadell, J. G., Ciais, P., Jackson, R. B., Alin, S. R., Alkama, R., Arneth, A., Arora, V. K., Bates, N. R., Becker, M., Bellouin, N., Bittig, H. C., Bopp, L., Chevallier, F., Chini, L. P., Cronin, M., Evans, W., Falk, S., Feely, R. A., Gasser, T., Gehlen, M., Gkritzalis, T., Gloege, L., Grassi, G., Gruber, N., Gürses, Ö., Harris, I., Hefner, M., Houghton, R. A., Hurtt, G. C., Iida, Y., Ilyina, T., Jain, A. K., Jersild, A., Kadono, K., Kato, E., Kennedy, D., Klein Goldewijk, K., Knauer, J., Korsbakken, J. I., Landschützer, P., Lefèvre, N., Lindsay, K., Liu, J., Liu, Z., Marland, G., Mayot, N., McGrath, M. J., Metzl, N., Monacci, N. M., Munro, D. R., Nakaoka, S.-I., Niwa, Y., O'Brien, K., Ono, T., Palmer, P. I., Pan, N., Pierrot, D., Pocock, K., Poulter, B., Resplandy, L., Robertson, E., Rödenbeck, C., Rodriguez, C., Rosan, T. M., Schwinger, J., Séférian, R., Shutler, J. D., Skjelvan, I., Steinhoff, T., Sun, Q., Sutton, A. J., Sweeney, C., Takao, S., Tanhua, T., Tans, P. P., Tian, X., Tian, H., Tilbrook, B., Tsujino, H., Tubiello, F., van der Werf, G. R., Walker, A. P., Wanninkhof, R., Whitehead, C., Willstrand Wranne, A., Wright, R., Yuan, W., Yue, C., Yue, X., Zaehle, S., Zeng, J., and Zheng, B.

Published
2022

9. Arctic Sea Ice in CMIP6

Author

Notz, D., Dörr, J., Bailey, D.A., Blockley, E., Bushuk, M., Debernard, J.B., Dekker, E., DeRepentigny, P., Docquier, D., Fuckar, N. S., Fyfe, J.C., Jahn, A., Holland, M., Hunke, E., Iovino, D., Khosravi, N., Massonnet, François, Madec, G., O'Farrell, S., Petty, A., Rana, A., Roach, L., Rosenblum, E., Rousset, C., Semmler, Tido, Stroeve, Julienne, Tremblay, Bruno, Toyoda, T., Tsujino, H., Vancoppenolle, Martin, Notz, D., Dörr, J., Bailey, D.A., Blockley, E., Bushuk, M., Debernard, J.B., Dekker, E., DeRepentigny, P., Docquier, D., Fuckar, N. S., Fyfe, J.C., Jahn, A., Holland, M., Hunke, E., Iovino, D., Khosravi, N., Massonnet, François, Madec, G., O'Farrell, S., Petty, A., Rana, A., Roach, L., Rosenblum, E., Rousset, C., Semmler, Tido, Stroeve, Julienne, Tremblay, Bruno, Toyoda, T., Tsujino, H., and Vancoppenolle, Martin

Abstract

We examine CMIP6 simulations of Arctic sea‐ice area and volume. We find that CMIP6 models produce a wide spread of mean Arctic sea‐ice area, capturing the observational estimate within the multi‐model ensemble spread. The CMIP6 multi‐model ensemble mean provides a more realistic estimate of the sensitivity of September Arctic sea‐ice area to a given amount of anthropogenic CO2 emissions and to a given amount of global warming, compared with earlier CMIP experiments. Still, most CMIP6 models fail to simulate at the same time a plausible evolution of sea‐ice area and of global mean surface temperature. In the vast majority of the available CMIP6 simulations, the Arctic Ocean becomes practically sea‐ice free (sea‐ice area < 1 million km2) in September for the first time before the year 2050 in each of the four emission scenarios SSP1‐1.9, SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5 examined here.

Published
2020

10. An assessment of the Indian Ocean mean state and seasonal cycle in a suite of interannual CORE-II simulations

Author

Rahaman, H., Srinivasu, U., Panickal, S., Durgadoo, J.V., Griffies, S.M., Ravichandran, M., Bozec, A., Cherchi, A., Voldoire, A., Sidorenko, D., Chassignet, E.P., Danabasoglu, G., Tsujino, H., Getzlaff, K., Ilicak, M., Bentsen, M., Long, M.C., Fogli, P.G., Farneti, R., Danilov, S., Marsland, S.J., Valcke, S., Yeager, S.G., Wang, Q., Rahaman, H., Srinivasu, U., Panickal, S., Durgadoo, J.V., Griffies, S.M., Ravichandran, M., Bozec, A., Cherchi, A., Voldoire, A., Sidorenko, D., Chassignet, E.P., Danabasoglu, G., Tsujino, H., Getzlaff, K., Ilicak, M., Bentsen, M., Long, M.C., Fogli, P.G., Farneti, R., Danilov, S., Marsland, S.J., Valcke, S., Yeager, S.G., and Wang, Q.

Abstract

We present an analysis of annual and seasonal mean characteristics of the Indian Ocean circulation and water masses from 16 global ocean–sea-ice model simulations that follow the Coordinated Ocean-ice Reference Experiments (CORE) interannual protocol (CORE-II). All simulations show a similar large-scale tropical current system, but with differences in the Equatorial Undercurrent. Most CORE-II models simulate the structure of the Cross Equatorial Cell (CEC) in the Indian Ocean. We uncover a previously unidentified secondary pathway of northward cross-equatorial transport along 75 °E, thus complementing the pathway near the Somali Coast. This secondary pathway is most prominent in the models which represent topography realistically, thus suggesting a need for realistic bathymetry in climate models. When probing the water mass structure in the upper ocean, we find that the salinity profiles are closer to observations in geopotential (level) models than in isopycnal models. More generally, we find that biases are model dependent, thus suggesting a grouping into model lineage, formulation of the surface boundary, vertical coordinate and surface salinity restoring. Refinement in model horizontal resolution (one degree versus degree) does not significantly improve simulations, though there are some marginal improvements in the salinity and barrier layer results. The results in turn suggest that a focus on improving physical parameterizations (e.g. boundary layer processes) may offer more near-term advances in Indian Ocean simulations than refined grid resolution.

Published
2020

12. Real-time three-dimensional echocardiographic study of left ventricular function after infarct exclusion surgery for ischemic cardiomyopathy

Author

Qin, J. X, Shiota, T, McCarthy, P. M, Firstenberg, M. S, Greenberg, N. L, Tsujino, H, Bauer, F, Travaglini, A, Hoercher, K. J, Buda, T, Smedira, N. G, and Thomas, J. D

Subjects
Life Sciences (General)
Abstract

BACKGROUND: Infarct exclusion (IE) surgery, a technique of left ventricular (LV) reconstruction for dyskinetic or akinetic LV segments in patients with ischemic cardiomyopathy, requires accurate volume quantification to determine the impact of surgery due to complicated geometric changes. METHODS AND RESULTS: Thirty patients who underwent IE (mean age 61+/-8 years, 73% men) had epicardial real-time 3-dimensional echocardiographic (RT3DE) studies performed before and after IE. RT3DE follow-up was performed transthoracically 42+/-67 days after surgery in 22 patients. Repeated measures ANOVA was used to compare the values before and after IE surgery and at follow-up. Significant decreases in LV end-diastolic (EDVI) and end-systolic (ESVI) volume indices were apparent immediately after IE and in follow-up (EDVI 99+/-40, 67+/-26, and 71+/-31 mL/m(2), respectively; ESVI 72+/-37, 40+/-21, and 42+/-22 mL/m(2), respectively; P:<0.05). LV ejection fraction increased significantly and remained higher (0.29+/-0.11, 0.43+/-0.13, and 0.42+/-0.09, respectively, P:<0.05). Forward stroke volume in 16 patients with preoperative mitral regurgitation significantly improved after IE and in follow-up (22+/-12, 53+/-24, and 58+/-21 mL, respectively, P:<0.005). New York Heart Association functional class at an average 285+/-144 days of clinical follow-up significantly improved from 3.0+/-0.8 to 1.8+/-0.8 (P:<0.0001). Smaller end-diastolic and end-systolic volumes measured with RT3DE immediately after IE were closely related to improvement in New York Heart Association functional class at clinical follow-up (Spearman's rho=0.58 and 0.60, respectively). CONCLUSIONS: RT3DE can be used to quantitatively assess changes in LV volume and function after complicated LV reconstruction. Decreased LV volume and increased ejection fraction imply a reduction in LV wall stress after IE surgery and are predictive of symptomatic improvement.

Published
2000

13. Validation of real-time three-dimensional echocardiography for quantifying left ventricular volumes in the presence of a left ventricular aneurysm: in vitro and in vivo studies

Author

Qin, J. X, Jones, M, Shiota, T, Greenberg, N. L, Tsujino, H, Firstenberg, M. S, Gupta, P. C, Zetts, A. D, Xu, Y, Ping Sun, J, Cardon, L. A, Odabashian, J. A, Flamm, S. D, White, R. D, Panza, J. A, and Thomas, J. D

Subjects
Life Sciences (General)
Abstract

OBJECTIVES: To validate the accuracy of real-time three-dimensional echocardiography (RT3DE) for quantifying aneurysmal left ventricular (LV) volumes. BACKGROUND: Conventional two-dimensional echocardiography (2DE) has limitations when applied for quantification of LV volumes in patients with LV aneurysms. METHODS: Seven aneurysmal balloons, 15 sheep (5 with chronic LV aneurysms and 10 without LV aneurysms) during 60 different hemodynamic conditions and 29 patients (13 with chronic LV aneurysms and 16 with normal LV) underwent RT3DE and 2DE. Electromagnetic flow meters and magnetic resonance imaging (MRI) served as reference standards in the animals and in the patients, respectively. Rotated apical six-plane method with multiplanar Simpson's rule and apical biplane Simpson's rule were used to determine LV volumes by RT3DE and 2DE, respectively. RESULTS: Both RT3DE and 2DE correlated well with actual volumes for aneurysmal balloons. However, a significantly smaller mean difference (MD) was found between RT3DE and actual volumes (-7 ml for RT3DE vs. 22 ml for 2DE, p = 0.0002). Excellent correlation and agreement between RT3DE and electromagnetic flow meters for LV stroke volumes for animals with aneurysms were observed, while 2DE showed lesser correlation and agreement (r = 0.97, MD = -1.0 ml vs. r = 0.76, MD = 4.4 ml). In patients with LV aneurysms, better correlation and agreement between RT3DE and MRI for LV volumes were obtained (r = 0.99, MD = -28 ml) than between 2DE and MRI (r = 0.91, MD = -49 ml). CONCLUSIONS: For geometrically asymmetric LVs associated with ventricular aneurysms, RT3DE can accurately quantify LV volumes.

Published
2000
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14. Ocean estimation from an ensemble of global ocean reanalyses

Author

Chevallier, M., Smith, G. C., Dupont, F., Lemieux, J. F., Forget, G., Fujii, Y., Hernandez, Fabrice, Msadek, R., Peterson, K. A., Storto, A., Toyoda, T., Valdivieso, M., Vernieres, G., Zuo, H., Balmaseda, M., Chang, Y. S., Ferry, N., Garric, G., Haines, K., Keeley, S., Kovach, R. M., Kuragano, T., Masina, S., Tang, Y. M., Tsujino, H., Wang, X. C., and Balmaseda, M. (ed.)

Subjects
Arctic, Ice-ocean reanalysis, Sea ice, Data assimilation, Model intercomparison, Ice thickness
Abstract

Ocean-sea ice reanalyses are crucial for assessing the variability and recent trends in the Arctic sea ice cover. This is especially true for sea ice volume, as long-term and large scale sea ice thickness observations are inexistent. Results from the Ocean ReAnalyses Intercomparison Project (ORA-IP) are presented, with a focus on Arctic sea ice fields reconstructed by state-of-the-art global ocean reanalyses. Differences between the various reanalyses are explored in terms of the effects of data assimilation, model physics and atmospheric forcing on properties of the sea ice cover, including concentration, thickness, velocity and snow. Amongst the 14 reanalyses studied here, 9 assimilate sea ice concentration, and none assimilate sea ice thickness data. The comparison reveals an overall agreement in the reconstructed concentration fields, mainly because of the constraints in surface temperature imposed by direct assimilation of ocean observations, prescribed or assimilated atmospheric forcing and assimilation of sea ice concentration. However, some spread still exists amongst the reanalyses, due to a variety of factors. In particular, a large spread in sea ice thickness is found within the ensemble of reanalyses, partially caused by the biases inherited from their sea ice model components. Biases are also affected by the assimilation of sea ice concentration and the treatment of sea ice thickness in the data assimilation process. An important outcome of this study is that the spatial distribution of ice volume varies widely between products, with no reanalysis standing out as clearly superior as compared to altimetry estimates. The ice thickness from systems without assimilation of sea ice concentration is not worse than that from systems constrained with sea ice observations. An evaluation of the sea ice velocity fields reveals that ice drifts too fast in most systems. As an ensemble, the ORA-IP reanalyses capture trends in Arctic sea ice area and extent relatively well. However, the ensemble can not be used to get a robust estimate of recent trends in the Arctic sea ice volume. Biases in the reanalyses certainly impact the simulated air-sea fluxes in the polar regions, and questions the suitability of current sea ice reanalyses to initialize seasonal forecasts.

Published
2017

15. OMIP contribution to CMIP6: Experimental and diagnostic protocol for the physical component of the Ocean Model Intercomparison Project

Author

Griffies, SM, Danabasoglu, G, Durack, PJ, Adcroft, AJ, Balaji, V, Böning, CW, Chassignet, EP, Curchitser, E, Deshayes, J, Drange, H, Fox-Kemper, B, Gleckler, PJ, Gregory, JM, Haak, H, Hallberg, RW, Heimbach, P, Hewitt, HT, Holland, DM, Ilyina, T, Jungclaus, JH, Komuro, Y, Krasting, JP, Large, WG, Marsland, SJ, Masina, S, McDougall, TJ, George Nurser, AJ, Orr, JC, Pirani, A, Qiao, F, Stouffer, RJ, Taylor, KE, Treguier, AM, Tsujino, H, Uotila, P, Valdivieso, M, Wang, Q, Winton, M, Yeager, SG, Griffies, SM, Danabasoglu, G, Durack, PJ, Adcroft, AJ, Balaji, V, Böning, CW, Chassignet, EP, Curchitser, E, Deshayes, J, Drange, H, Fox-Kemper, B, Gleckler, PJ, Gregory, JM, Haak, H, Hallberg, RW, Heimbach, P, Hewitt, HT, Holland, DM, Ilyina, T, Jungclaus, JH, Komuro, Y, Krasting, JP, Large, WG, Marsland, SJ, Masina, S, McDougall, TJ, George Nurser, AJ, Orr, JC, Pirani, A, Qiao, F, Stouffer, RJ, Taylor, KE, Treguier, AM, Tsujino, H, Uotila, P, Valdivieso, M, Wang, Q, Winton, M, and Yeager, SG

Abstract

© Author(s) 2016. The Ocean Model Intercomparison Project (OMIP) is an endorsed project in the Coupled Model Intercomparison Project Phase 6 (CMIP6). OMIP addresses CMIP6 science questions, investigating the origins and consequences of systematic model biases. It does so by providing a framework for evaluating (including assessment of systematic biases), understanding, and improving ocean, sea-ice, tracer, and biogeochemical components of climate and earth system models contributing to CMIP6. Among the WCRP Grand Challenges in climate science (GCs), OMIP primarily contributes to the regional sea level change and near-term (climate/decadal) prediction GCs. OMIP provides (a) an experimental protocol for global ocean/sea-ice models run with a prescribed atmospheric forcing; and (b) a protocol for ocean diagnostics to be saved as part of CMIP6. We focus here on the physical component of OMIP, with a companion paper (Orr et al., 2016) detailing methods for the inert chemistry and interactive biogeochemistry. The physical portion of the OMIP experimental protocol follows the interannual Coordinated Ocean-ice Reference Experiments (CORE-II). Since 2009, CORE-I (Normal Year Forcing) and CORE-II (Interannual Forcing) have become the standard methods to evaluate global ocean/sea-ice simulations and to examine mechanisms for forced ocean climate variability. The OMIP diagnostic protocol is relevant for any ocean model component of CMIP6, including the DECK (Diagnostic, Evaluation and Characterization of Klima experiments), historical simulations, FAFMIP (Flux Anomaly Forced MIP), C4MIP (Coupled Carbon Cycle Climate MIP), DAMIP (Detection and Attribution MIP), DCPP (Decadal Climate Prediction Project), ScenarioMIP, HighResMIP (High Resolution MIP), as well as the ocean/sea-ice OMIP simulations.

Published
2016

16. North and equatorial Pacific Ocean circulation in the CORE-II hindcast simulations

Author

Tseng, Y., Lin, H., Chen, H., Thompson, K., Bentsen, M., Böning, C., Bozec, A., Cassou, C., Chassignet, E., Chow, C., Danabasoglu, G., Danilov, S., Farneti, R., Fogli, P., Fujii, Y., Griffies, S. M., Ilicak, M., Jung, T., Masina, S., Navarra, A., Patara, L., Samuels, B. L., Scheinert, M., Sidorenko, D., Sui, C., Tsujino, H., Valcke, S., Voldoire, A., Wang, Q., Yeager, S., Tseng, Y., Lin, H., Chen, H., Thompson, K., Bentsen, M., Böning, C., Bozec, A., Cassou, C., Chassignet, E., Chow, C., Danabasoglu, G., Danilov, S., Farneti, R., Fogli, P., Fujii, Y., Griffies, S. M., Ilicak, M., Jung, T., Masina, S., Navarra, A., Patara, L., Samuels, B. L., Scheinert, M., Sidorenko, D., Sui, C., Tsujino, H., Valcke, S., Voldoire, A., Wang, Q., and Yeager, S.

Abstract

We evaluate the mean circulation patterns, water mass distributions, and tropical dynamics of the North and Equatorial Pacific Ocean based on a suite of global ocean-sea ice simulations driven by the CORE-II atmospheric forcing from 1963-2007. The first three moments (mean, standard deviation and skewness) of sea surface height and surface temperature variability are assessed against observations. Large discrepancies are found in the variance and skewness of sea surface height and in the skewness of sea surface temperature. Comparing with the observation, most models underestimate the Kuroshio transport in the Asian Marginal seas due to the missing influence of the unresolved western boundary current and meso-scale eddies. In terms of the Mixed Layer Depths (MLDs) in the North Pacific, the two observed maxima associated with Subtropical Mode Water and Central Mode Water formation coalesce into a large pool of deep MLDs in all participating models, but another local maximum associated with the formation of Eastern Subtropical Mode Water can be found in all models with different magnitudes. The main model bias of deep MLDs results from excessive Subtropical Mode Water formation due to inaccurate representation of the Kuroshio separation and of the associated excessively warm and salty Kuroshio water. Further water mass analysis shows that the North Pacific Intermediate Water can penetrate southward in most models, but its distribution greatly varies among models depending not only on grid resolution and vertical coordinate but also on the model dynamics. All simulations show overall similar large scale tropical current system, but with differences in the structures of the Equatorial Undercurrent. We also confirm the key role of the meridional gradient of the wind stress curl in driving the equatorial transport, leading to a generally weak North Equatorial Counter Current in all models due to inaccurate CORE-II equatorial wind fields. Most models show a larger interior

Published
2016

17. OMIP contribution to CMIP6: experimental and diagnostic protocol for the physical component of the Ocean Model Intercomparison Project

Author

Griffies, S. M., Danabasoglu, G., Durack, P., Adcroft, A.J., Balaji, V., Böning, C. W., Chassignet, E. P., Curchitser, E., Deshayes, J., Drange, H., Fox-Kemper, B., Gleckler, P.J., Gregory, J. M., Haak, H., Hallberg, R. W., Heimbach, P., Hewitt, H.T., Holland, D., Ilyina, T., Jungclaus, J. H., Komuro, Y., Krasting, J.P., Large, W. G., Marsland, S. J., Masina, S., McDougall, T.J., Nurser, G., Orr, J.C., Pirani, A., Qiao, F., Stouffer, R.J., Taylor, K.E., Treguier, A.M., Tsujino, H., Uotila, P., Valdivieso, M., Wang, Q., Winton, M., Yeager, S.G., Griffies, S. M., Danabasoglu, G., Durack, P., Adcroft, A.J., Balaji, V., Böning, C. W., Chassignet, E. P., Curchitser, E., Deshayes, J., Drange, H., Fox-Kemper, B., Gleckler, P.J., Gregory, J. M., Haak, H., Hallberg, R. W., Heimbach, P., Hewitt, H.T., Holland, D., Ilyina, T., Jungclaus, J. H., Komuro, Y., Krasting, J.P., Large, W. G., Marsland, S. J., Masina, S., McDougall, T.J., Nurser, G., Orr, J.C., Pirani, A., Qiao, F., Stouffer, R.J., Taylor, K.E., Treguier, A.M., Tsujino, H., Uotila, P., Valdivieso, M., Wang, Q., Winton, M., and Yeager, S.G.

Abstract

The Ocean Model Intercomparison Project (OMIP) is an endorsed project in the Coupled Model Intercomparison Project Phase 6 (CMIP6). OMIP addresses CMIP6 science questions, investigating the origins and consequences of systematic model biases. It does so by providing a framework for evaluating (including assessment of systematic biases), understanding, and improving ocean, seaice, tracer, and biogeochemical components of climate and earth system models contributing to CMIP6. Among the WCRP Grand Challenges in climate science (GCs), OMIP primarily contributes to the regional sea level change and near-term (climate/decadal) prediction GCs. OMIP provides (a) an experimental protocol for global ocean/sea-ice models run with a prescribed atmospheric forcing; and (b) a protocol for ocean diagnostics to be saved as part of CMIP6. We focus here on the physical component of OMIP, with a companion paper (Orr et al., 2016) detailing methods for the inert chemistry and interactive biogeochemistry. The physical portion of the OMIP experimental protocol follows the interannual Coordinated Ocean-ice Reference Experiments (CORE-II). Since 2009, CORE-I (Normal Year Forcing) and CORE-II (Interannual Forcing) have become the standard methods to evaluate global ocean/seaice simulations and to examine mechanisms for forced ocean climate variability. The OMIP diagnostic protocol is relevant for any ocean model component of CMIP6, including the DECK (Diagnostic, Evaluation and Characterization of Klima experiments), historical simulations, FAFMIP (Flux Anomaly Forced MIP), C4MIP (Coupled Carbon Cycle Climate MIP), DAMIP (Detection and Attribution MIP), DCPP (Decadal Climate Prediction Project), ScenarioMIP, High- ResMIP (High Resolution MIP), as well as the ocean/sea-ice OMIP simulations.

Published
2016

18. An assessment of the Arctic Ocean in a suite of interannual CORE-II simulations. Part I: Sea ice and solid freshwater

Author

Wang, Qiang, Ilicak, M., Gerdes, R., Drange, H., Aksenov, Y., Bailey, D.A., Bentsen, M., Biastoch, A., Bozec, A., Böning, C., Cassou, C., Chassignet, E., Coward, A., Curry, B., Danabasoglu, G., Danilov, S., Fernandez, E., Fogli, P., Fujii, Y., Griffies, S. M., Iovino, D., Jahn, A., Jung, T., Large, W. G., Lee, C., Lique, C., Lu, J., Masina, S., Nurser, G., Rabe, B., Roth, C., Salas y Mélia, D., Samuels, B. L., Spence, P., Tsujino, H., Valcke, S., Voldoire, A., Wang, X., Yeager, S.G., Wang, Qiang, Ilicak, M., Gerdes, R., Drange, H., Aksenov, Y., Bailey, D.A., Bentsen, M., Biastoch, A., Bozec, A., Böning, C., Cassou, C., Chassignet, E., Coward, A., Curry, B., Danabasoglu, G., Danilov, S., Fernandez, E., Fogli, P., Fujii, Y., Griffies, S. M., Iovino, D., Jahn, A., Jung, T., Large, W. G., Lee, C., Lique, C., Lu, J., Masina, S., Nurser, G., Rabe, B., Roth, C., Salas y Mélia, D., Samuels, B. L., Spence, P., Tsujino, H., Valcke, S., Voldoire, A., Wang, X., and Yeager, S.G.

Published
2016

19. North Atlantic simulations in Coordinated Ocean-ice Reference Experiments phase II (CORE-II). Part II: Inter-annual to decadal variability

Author

Danabasoglu, G., Yeager, S.G., Kim, W., Behrens, E., Bi, D., Biastoch, A., Bleck, R., Böning, C., Bozec, A., Canuto, V., Cassou, C., Chassignet, E., Coward, A., Danilov, S., Diansky, N., Drange, H., Farneti, R., Fernandez, E., Fogli, P., Forget, G., Fujii, Y., Griffies, S. M., Gusev, A., Heimbach, P., Howard, A., Ilicak, M., Jung, T., Karspeck, A.R., Kelley, M., Large, W. G., Leboissetier, A., Lu, J., Madec, G., Marsland, S. J., Masina, S., Navarra, A., Nurser, G., Pirani, A., Romanou, A., Salas y Mélia, D., Samuels, B. L., Scheinert, M., Sidorenko, Dmitry, Sun, S., Treguier, A.-M., Tsujino, H., Uotila, P., Valcke, S., Voldoire, A., Wang, Qiang, Yashayaev, I., Danabasoglu, G., Yeager, S.G., Kim, W., Behrens, E., Bi, D., Biastoch, A., Bleck, R., Böning, C., Bozec, A., Canuto, V., Cassou, C., Chassignet, E., Coward, A., Danilov, S., Diansky, N., Drange, H., Farneti, R., Fernandez, E., Fogli, P., Forget, G., Fujii, Y., Griffies, S. M., Gusev, A., Heimbach, P., Howard, A., Ilicak, M., Jung, T., Karspeck, A.R., Kelley, M., Large, W. G., Leboissetier, A., Lu, J., Madec, G., Marsland, S. J., Masina, S., Navarra, A., Nurser, G., Pirani, A., Romanou, A., Salas y Mélia, D., Samuels, B. L., Scheinert, M., Sidorenko, Dmitry, Sun, S., Treguier, A.-M., Tsujino, H., Uotila, P., Valcke, S., Voldoire, A., Wang, Qiang, and Yashayaev, I.

Published
2016

20. An assessment of the Arctic Ocean in a suite of interannual CORE-II simulations. Part II: Liquid freshwater

Author

Wang, Q., Ilicak, M., Gerdes, R., Drange, H., Aksenov, Y., Bailey, D.A., Bentsen, M., Biastoch, A., Bozec, A., Böning, C., Cassou, C., Chassignet, E., Coward, A., Curry, B., Danabasoglu, G., Danilov, S., Fernandez, E., Fogli, P., Fujii, Y., Griffies, S. M., Iovino, D., Jahn, A., Jung, T., Large, W. G., Lee, C., Lique, C., Lu, J., Masina, S., Nurser, G., Rabe, B., Roth, C., Salas y Mélia, D., Samuels, B. L., Spence, P., Tsujino, H., Valcke, S., Voldoire, A., Wang, X., Yeager, S.G., Wang, Q., Ilicak, M., Gerdes, R., Drange, H., Aksenov, Y., Bailey, D.A., Bentsen, M., Biastoch, A., Bozec, A., Böning, C., Cassou, C., Chassignet, E., Coward, A., Curry, B., Danabasoglu, G., Danilov, S., Fernandez, E., Fogli, P., Fujii, Y., Griffies, S. M., Iovino, D., Jahn, A., Jung, T., Large, W. G., Lee, C., Lique, C., Lu, J., Masina, S., Nurser, G., Rabe, B., Roth, C., Salas y Mélia, D., Samuels, B. L., Spence, P., Tsujino, H., Valcke, S., Voldoire, A., Wang, X., and Yeager, S.G.

Published
2016

21. An assessment of the Arctic Ocean in a suite of interannual CORE-II simulations. Part I: Sea ice and solid freshwater

Author

Wang, Q., Ilicak, M., Gerdes, R., Drange, H., Aksenov, Y., Bailey, D., Bentsen, M., Biastoch, Arne, Bozec, A., Böning, Claus W., Cassou, C., Chassignet, E., Coward, A. C., Curry, B., Danabasoglu, G., Danilov, S., Fernandez, E., Fogli, P. G., Fujii, Y., Griffies, S. M., Iovino, D., Jahn, A., Jung, T., Large, W. G., Lee, C., Lique, C., Lu, J., Masina, S., Nurser, A. J. G., Rabe, B., Roth, Christina, Salas y Melia, D., Samuels, B. L., Spence, P., Tsujino, H., Valcke, S., Voldoire, A., Wang, X., Yeager, S. G., Wang, Q., Ilicak, M., Gerdes, R., Drange, H., Aksenov, Y., Bailey, D., Bentsen, M., Biastoch, Arne, Bozec, A., Böning, Claus W., Cassou, C., Chassignet, E., Coward, A. C., Curry, B., Danabasoglu, G., Danilov, S., Fernandez, E., Fogli, P. G., Fujii, Y., Griffies, S. M., Iovino, D., Jahn, A., Jung, T., Large, W. G., Lee, C., Lique, C., Lu, J., Masina, S., Nurser, A. J. G., Rabe, B., Roth, Christina, Salas y Melia, D., Samuels, B. L., Spence, P., Tsujino, H., Valcke, S., Voldoire, A., Wang, X., and Yeager, S. G.

Abstract

Highlights: • Arctic sea ice extent and solid freshwater in 14 CORE-II models are inter-compared. • The models better represent the variability than the mean state. • The September ice extent trend is reasonably represented by the model ensemble mean. • The descending trend of ice thickness is underestimated compared to observations. • The models underestimate the reduction in solid freshwater content in recent years. Abstract: The Arctic Ocean simulated in fourteen global ocean-sea ice models in the framework of the Coordinated Ocean-ice Reference Experiments, phase II (CORE II) is analyzed. The focus is on the Arctic sea ice extent, the solid freshwater (FW) sources and solid freshwater content (FWC). Available observations are used for model evaluation. The variability of sea ice extent and solid FW budget is more consistently reproduced than their mean state in the models. The descending trend of September sea ice extent is well simulated in terms of the model ensemble mean. Models overestimating sea ice thickness tend to underestimate the descending trend of September sea ice extent. The models underestimate the observed sea ice thinning trend by a factor of two. When averaged on decadal time scales, the variation of Arctic solid FWC is contributed by those of both sea ice production and sea ice transport, which are out of phase in time. The solid FWC decreased in the recent decades, caused mainly by the reduction in sea ice thickness. The models did not simulate the acceleration of sea ice thickness decline, leading to an underestimation of solid FWC trend after 2000. The common model behavior, including the tendency to underestimate the trend of sea ice thickness and March sea ice extent, remains to be improved.

Published
2016
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22. An assessment of Antarctic Circumpolar Current and Southern Ocean meridional overturning circulation during 1958–2007 in a suite of interannual CORE-II simulations

Author

Farneti, R., Downes, S., Griffies, S. M., Marsland, S. J., Behrens, E., Bentsen, M., Bi, D., Biastoch, A., Böning, C., Bozec, A., Canuto, V., Chassignet, E., Danabasoglu, G., Danilov, S., Diansky, N., Drange, H., Fogli, P., Gusev, A., Hallberg, R. W., Howard, A., Ilicak, M., Jung, T., Kelley, M., Large, W., Leboissetier, A., Long, M., Lu, J., Masina, S., Mishra, A., Navarra, A., Nurser, G., Patara, L, Samuels, B., Sidorenko, D., Tsujino, H., Uotila, P., Wang, Q., Yeager, S., Farneti, R., Downes, S., Griffies, S. M., Marsland, S. J., Behrens, E., Bentsen, M., Bi, D., Biastoch, A., Böning, C., Bozec, A., Canuto, V., Chassignet, E., Danabasoglu, G., Danilov, S., Diansky, N., Drange, H., Fogli, P., Gusev, A., Hallberg, R. W., Howard, A., Ilicak, M., Jung, T., Kelley, M., Large, W., Leboissetier, A., Long, M., Lu, J., Masina, S., Mishra, A., Navarra, A., Nurser, G., Patara, L, Samuels, B., Sidorenko, D., Tsujino, H., Uotila, P., Wang, Q., and Yeager, S.

Abstract

In the framework of the second phase of the Coordinated Ocean-ice Reference Experiments (CORE-II), we present an analysis of the representation of the Antarctic Circumpolar Current (ACC) and Southern Ocean meridional overturning circulation (MOC) in a suite of seventeen global ocean–sea ice models. We focus on the mean, variability and trends of both the ACC and MOC over the 1958–2007 period, and discuss their relationship with the surface forcing. We aim to quantify the degree of eddy saturation and eddy compensation in the models participating in CORE-II, and compare our results with available observations, previous fine-resolution numerical studies and theoretical constraints. Most models show weak ACC transport sensitivity to changes in forcing during the past five decades, and they can be considered to be in an eddy saturated regime. Larger contrasts arise when considering MOC trends, with a majority of models exhibiting significant strengthening of the MOC during the late 20th and early 21st century. Only a few models show a relatively small sensitivity to forcing changes, responding with an intensified eddy-induced circulation that provides some degree of eddy compensation, while still showing considerable decadal trends. Both ACC and MOC interannual variabilities are largely controlled by the Southern Annular Mode (SAM). Based on these results, models are clustered into two groups. Models with constant or two-dimensional (horizontal) specification of the eddy-induced advection coefficient κ show larger ocean interior decadal trends, larger ACC transport decadal trends and no eddy compensation in the MOC. Eddy-permitting models or models with a three-dimensional time varying κ show smaller changes in isopycnal slopes and associated ACC trends, and partial eddy compensation. As previously argued, a constant in time or space κ is responsible for a poor representation of mesoscale eddy effects and cannot properly simulate the sensitivity of the ACC and MOC to ch

Published
2015

23. An assessment of Southern Ocean water masses and sea ice during 1988–2007 in a suite of interannual CORE-II simulations

Author

Downes, S., Farneti, R., Uotila, P., Griffies, S., Marsland, S., Bailey, D., Behrens, E., Bentsen, M., Bi, D., Biastoch, A., Böning, C., Bozec, A., Canuto, V., Chassignet, E., Danabasoglu, G., Danilov, S., Diansky, N., Drange, H., Fogli, P., Gusev, A., Howard, A., Ilicak, M., Jung, T., Kelley, M., Large, W., Leboissetier, A., Long, M., Lu, J., Masina, S., Mishra, A., Navarra, A., Nurser, G., Patara, L, Samuels, B., Sidorenko, D., Spence, P., Tsujino, H., Wang, Q., Yeager, S., Downes, S., Farneti, R., Uotila, P., Griffies, S., Marsland, S., Bailey, D., Behrens, E., Bentsen, M., Bi, D., Biastoch, A., Böning, C., Bozec, A., Canuto, V., Chassignet, E., Danabasoglu, G., Danilov, S., Diansky, N., Drange, H., Fogli, P., Gusev, A., Howard, A., Ilicak, M., Jung, T., Kelley, M., Large, W., Leboissetier, A., Long, M., Lu, J., Masina, S., Mishra, A., Navarra, A., Nurser, G., Patara, L, Samuels, B., Sidorenko, D., Spence, P., Tsujino, H., Wang, Q., and Yeager, S.

Abstract

We characterise the representation of the Southern Ocean water mass structure and sea ice within a suite of 15 global ocean-ice models run with the Coordinated Ocean-ice Reference Experiment Phase II (CORE-II) protocol. The main focus is the representation of the present (1988–2007) mode and intermediate waters, thus framing an analysis of winter and summer mixed layer depths; temperature, salinity, and potential vorticity structure; and temporal variability of sea ice distributions. We also consider the interannual variability over the same 20 year period. Comparisons are made between models as well as to observation-based analyses where available. The CORE-II models exhibit several biases relative to Southern Ocean observations, including an underestimation of the model mean mixed layer depths of mode and intermediate water masses in March (associated with greater ocean surface heat gain), and an overestimation in September (associated with greater high latitude ocean heat loss and a more northward winter sea-ice extent). In addition, the models have cold and fresh/warm and salty water column biases centred near 50°S. Over the 1988–2007 period, the CORE-II models consistently simulate spatially variable trends in sea-ice concentration, surface freshwater fluxes, mixed layer depths, and 200–700 m ocean heat content. In particular, sea-ice coverage around most of the Antarctic continental shelf is reduced, leading to a cooling and freshening of the near surface waters. The shoaling of the mixed layer is associated with increased surface buoyancy gain, except in the Pacific where sea ice is also influential. The models are in disagreement, despite the common CORE-II atmospheric state, in their spatial pattern of the 20-year trends in the mixed layer depth and sea-ice.

Published
2015

24. An assessment of global and regional sea level in a suite of interannual CORE-II simulations: a synopsis

Author

Griffies, S. M., Yin, J., Bates, S., Behrens, E., Bentsen, M., Bi, D., Biastoch, A., Böning, C., Bozec, A., Cassou, C., Chassignet, E., Danabasoglu, G., Danilov, S., Domingues, C., Drange, H., Durack, P., Farneti, R., Fernandez, E., Goddard, P., Greatbatch, R., Ilicak, M., Lu, J., Marsland, S., Mishra, A., Lorbacher, K., Nurser, G., Salas y Mélia, D., Palter, J., Samuels, B., Schröter, J., Schwarzkopf, F., Sidorenko, D., Treguier, A.-M., Tseng, Y., Tsujino, H., Uotila, P., Valcke, S., Voldoire, A., Wang, Q., Winton, M., and Zhang, X.

Abstract

There is a growing number of observation-based measures of sea level related patterns with the advent of the Argo floats (since the early 2000s) and satellite altimeters (since 1993). These measures provide a valuable means to evaluate aspects of global model simulations, such as the global ocean-sea ice simulations run as part of the interannual Coordinated Ocean- ice Reference Experiments Griffies et al. (2009), Danabasoglu et al. (2013). In addition, these CORE-II simulations provide a means for evaluating the likely mechanisms causing sea level variations, particularly when models with different skill are compared against each other and observations. We have conducted an assessment of CORE-II simulations from 13 model configurations Griffies et al. (2013), with a focus on their ability to capture observed trends in ocean heat content as well as the corresponding dynamic sea level over the period 1993- 2007. Here, we provide a synopsis of the assessment.

Published
2013

25. An assessment of global and regional sea level for years 1993–2007 in a suite of interannual CORE-II simulations

Author

Griffies, S.M., Yin, J., Durack, P.J., Goddard, P., Bates, S.C., Behrens, E., Bentsen, M., Bi, D., Biastoch, A., Böning, Claus W., Bozec, A., Chassignet, E., Danabasogl, G., Danilov, S., Domingues, C.M., Drange, H., Farneti, R., Fernandez, E., Greatbatch, R., Holland, D., Ilicak, M., Large, W., Lorbacher, K., Lu, J., Marsland, S., Mishra, A., Nurser, G., Salas y Mélia, D., Palter, J., Samuels, B., Schröter, J., Schwarzkopf, F., Sidorenko, D., Treguier, A.-M., Tseng, Y., Tsujino, H., Uotila, P., Valcke, S., Voldoire, A., Wang, Q., Winton, M., Zhang, X., Griffies, S.M., Yin, J., Durack, P.J., Goddard, P., Bates, S.C., Behrens, E., Bentsen, M., Bi, D., Biastoch, A., Böning, Claus W., Bozec, A., Chassignet, E., Danabasogl, G., Danilov, S., Domingues, C.M., Drange, H., Farneti, R., Fernandez, E., Greatbatch, R., Holland, D., Ilicak, M., Large, W., Lorbacher, K., Lu, J., Marsland, S., Mishra, A., Nurser, G., Salas y Mélia, D., Palter, J., Samuels, B., Schröter, J., Schwarzkopf, F., Sidorenko, D., Treguier, A.-M., Tseng, Y., Tsujino, H., Uotila, P., Valcke, S., Voldoire, A., Wang, Q., Winton, M., and Zhang, X.

Abstract

We provide an assessment of sea level simulated in a suite of global ocean-sea ice models using the interannual CORE atmospheric state to determine surface ocean boundary buoyancy and momentum fluxes. These CORE-II simulations are compared amongst themselves as well as to observation-based estimates. We focus on the final 15 years of the simulations (1993–2007), as this is a period where the CORE-II atmospheric state is well sampled, and it allows us to compare sea level related fields to both satellite and in situ analyses. The ensemble mean of the CORE-II simulations broadly agree with various global and regional observation-based analyses during this period, though with the global mean thermosteric sea level rise biased low relative to observation-based analyses. The simulations reveal a positive trend in dynamic sea level in the west Pacific and negative trend in the east, with this trend arising from wind shifts and regional changes in upper 700 m ocean heat content. The models also exhibit a thermosteric sea level rise in the subpolar North Atlantic associated with a transition around 1995/1996 of the North Atlantic Oscillation to its negative phase, and the advection of warm subtropical waters into the subpolar gyre. Sea level trends are predominantly associated with steric trends, with thermosteric effects generally far larger than halosteric effects, except in the Arctic and North Atlantic. There is a general anti-correlation between thermosteric and halosteric effects for much of the World Ocean, associated with density compensated changes.

Published
2014

26. North Atlantic simulations in Coordinated Ocean-ice Reference Experiments phase II (CORE-II). Part I: Mean states

Author

Danabasoglu, Gokhan, Yeager, Steve G., Bailey, David, Behrens, Erik, Bentsen, M., Bi, D., Biastoch, A., Böning, C., Bozec, A., Canuto, V., Cassou, C., Chassignet, E., Coward, A., Danilov, S., Diansky, N., Drange, H., Farneti, R., Fernandez, E., Fogli, P., Forget, G., Fujii, Y., Griffies, S., Gusev, A., Heimbach, P., Howard, A., Jung, T., Kelley, M., Large, W., Leboissetier, A., Lu, J., Madec, G., Marsland, S., Masina, S., Navarra, A., Nurser, G., Pirani, A., Melia, D., Samuels, B., Scheinert, M., Sidorenko, D., Treguier, A. M., Tsujino, H., Uotila, P., Valcke, S., Voldoire, A., Wang, Qiang, Danabasoglu, Gokhan, Yeager, Steve G., Bailey, David, Behrens, Erik, Bentsen, M., Bi, D., Biastoch, A., Böning, C., Bozec, A., Canuto, V., Cassou, C., Chassignet, E., Coward, A., Danilov, S., Diansky, N., Drange, H., Farneti, R., Fernandez, E., Fogli, P., Forget, G., Fujii, Y., Griffies, S., Gusev, A., Heimbach, P., Howard, A., Jung, T., Kelley, M., Large, W., Leboissetier, A., Lu, J., Madec, G., Marsland, S., Masina, S., Navarra, A., Nurser, G., Pirani, A., Melia, D., Samuels, B., Scheinert, M., Sidorenko, D., Treguier, A. M., Tsujino, H., Uotila, P., Valcke, S., Voldoire, A., and Wang, Qiang

Abstract

Simulation characteristics from eighteen global ocean–sea-ice coupled models are presented with a focus on the mean Atlantic meridional overturning circulation (AMOC) and other related fields in the North Atlantic. These experiments use inter-annually varying atmospheric forcing data sets for the 60-year per- iod from 1948 to 2007 and are performed as contributions to the second phase of the Coordinated Ocean- ice Reference Experiments (CORE-II). The protocol for conducting such CORE-II experiments is summa- rized. Despite using the same atmospheric forcing, the solutions show significant differences. As most models also differ from available observations, biases in the Labrador Sea region in upper-ocean potential temperature and salinity distributions, mixed layer depths, and sea-ice cover are identified as contribu- tors to differences in AMOC. These differences in the solutions do not suggest an obvious grouping of the models based on their ocean model lineage, their vertical coordinate representations, or surface salinity restoring strengths. Thus, the solution differences among the models are attributed primarily to use of different subgrid scale parameterizations and parameter choices as well as to differences in vertica and horizontal grid resolutions in the ocean models. Use of a wide variety of sea-ice models with diverse snow and sea-ice albedo treatments also contributes to these differences. Based on the diagnostics con- sidered, the majority of the models appear suitable for use in studies involving the North Atlantic, but some models require dedicated development effort.

Published
2014

30. Problems and prospects in large-scale ocean circulation models

Author

Hall, J., Harrison, D.E., Stammer, D., Griffies, S.M., Adcroft, A.J., Banks, H., Boning, C.W., Chassignet, E.P., Danabasoglu, G., Danilov, S., Deelersnijder, E., Drange, H., England, M., Fox-Kemper, B., Gerdes, R., Gnanadesikan, A., Greatbatch, R.J., Hallberge, R.W., Hanert, E., Harrison, M.J., Legg, S., Little, C.M., Madec, G., Marsland, S.J., Nikurashin, M., Pirani, A., Simmons, H.L., Schroter, J., Samuels, B.L., Treguier, A-M., Toggweiler, J.R., Tsujino, H., Vallis, G.K., White, L., Hall, J., Harrison, D.E., Stammer, D., Griffies, S.M., Adcroft, A.J., Banks, H., Boning, C.W., Chassignet, E.P., Danabasoglu, G., Danilov, S., Deelersnijder, E., Drange, H., England, M., Fox-Kemper, B., Gerdes, R., Gnanadesikan, A., Greatbatch, R.J., Hallberge, R.W., Hanert, E., Harrison, M.J., Legg, S., Little, C.M., Madec, G., Marsland, S.J., Nikurashin, M., Pirani, A., Simmons, H.L., Schroter, J., Samuels, B.L., Treguier, A-M., Toggweiler, J.R., Tsujino, H., Vallis, G.K., and White, L.

Published
2010

31. Problems and Prospects in Large-Scale Ocean Circulation Models

Author

Griffies, S. M., Adcroft, A. J., Banks, H., Böning, Carmen, Chassignet, E. P., Danabasoglu, G., Danilov, Sergey, Deleersnijder, E., Drange, H., England, M., Fox-Kemper, B., Gerdes, Rüdiger, Gnanadesikan, A., Greatbatch, R. J., Hallberg, R. W., Hanert, E., Harrison, M. J., Legg, S., Little, C. M., Madec, G., Marsland, S. J., Nikurashin, M., Pirani, A., Simmons, H. L., Schröter, Jens, Samuels, B. L., Treguier, A.-M., Toggweiler, J. R., Tsujino, H., Valllis, G. K., White, L., Griffies, S. M., Adcroft, A. J., Banks, H., Böning, Carmen, Chassignet, E. P., Danabasoglu, G., Danilov, Sergey, Deleersnijder, E., Drange, H., England, M., Fox-Kemper, B., Gerdes, Rüdiger, Gnanadesikan, A., Greatbatch, R. J., Hallberg, R. W., Hanert, E., Harrison, M. J., Legg, S., Little, C. M., Madec, G., Marsland, S. J., Nikurashin, M., Pirani, A., Simmons, H. L., Schröter, Jens, Samuels, B. L., Treguier, A.-M., Toggweiler, J. R., Tsujino, H., Valllis, G. K., and White, L.

Published
2009

32. The Effects of Isoniazid and Isoniazid-Derivatives Alone or in Combination with Other Drugs on Experimental Tuberculosis in Mice

Author

Tsujino, H.

Subjects
493.3
Abstract

実験的マウス結核症の生存日数を指標とする方法によつて, PZA単独及びPZAをINHに併用した場合の治療効果について, PZAの投与量を10γ/g, INHの投与量を1γ/gとして検討した。其結果, PZAは単独投与にても若干の治療効果があり, 又INHの抗結核作用を増強せしめる効果がある事が観察された。, この論文は国立情報学研究所の学術雑誌公開支援事業により電子化されました。

Published
1959

37. An assessment of Southern Ocean water masses and sea ice during 1988–2007 in a suite of interannual CORE-II simulations

Author

Claus W. Böning, Simon J. Marsland, Lavinia Patara, Riccardo Farneti, Maxwell Kelley, A. M. Howard, David A. Bailey, Hiroyuki Tsujino, Jianhua Lu, Helge Drange, Matthew C. Long, Vittorio Canuto, Mats Bentsen, Nikolay Diansky, Stephen M. Griffies, Bonita L. Samuels, Anatoly Gusev, Erik Behrens, A. J. George Nurser, Qiang Wang, Dmitry Sidorenko, Alexandra Bozec, Eric P. Chassignet, Arne Biastoch, Gokhan Danabasoglu, Sergey Danilov, Paul Spence, Antonio Navarra, Simona Masina, Pier Giuseppe Fogli, Petteri Uotila, Mehmet Ilicak, Thomas Jung, Akhilesh Mishra, Daohua Bi, Stephanie M. Downes, Anthony Leboissetier, William G. Large, Stephen Yeager, Downes SM, Farneti R, Uotila P, Griffies SM, Marsland SJ, Bailey D, Behrens E, Bentsen M, Bi DH, Biastoch A, Boning C, Bozec A, Canuto VM, Chassignet E, Danabasoglu G, Danilov S, Diansky N, Drange H, Fogli PG, Gusev A, Howard A, Ilicak M, Jung T, Kelley M, Large WG, Leboissetier A, Long M, Lu JH, Masina S, Mishra A, Navarra A, Nurser AJG, Patara L, Samuels BL, Sidorenko D, Spence P, Tsujino H, Wang Q, and Yeager SG

Subjects
Atmospheric Science, geography, Ocean observations, geography.geographical_feature_category, Mixed layer, Antarctic sea ice, Geotechnical Engineering and Engineering Geology, Oceanography, Southern Ocean, CORE-II experiments, Water masses, Sea ice, Ocean dynamics, Sea ice thickness, Computer Science (miscellaneous), Sea ice, Environmental science, Thermohaline circulation, Ocean heat content
Abstract

We characterise the representation of the Southern Ocean water mass structure and sea ice within a suite of 15 global ocean-ice models run with the Coordinated Ocean-ice Reference Experiment Phase II (CORE-II) protocol. The main focus is the representation of the present (1988-2007) mode and intermediate waters, thus framing an analysis of winter and summer mixed layer depths; temperature, salinity, and potential vorticity structure; and temporal variability of sea ice distributions. We also consider the interannual variability over the same 20 year period. Comparisons are made between models as well as to observation-based analyses where available. The CORE-II models exhibit several biases relative to Southern Ocean observations, including an underestimation of the model mean mixed layer depths of mode and intermediate water masses in March (associated with greater ocean surface heat gain), and an overestimation in September (associated with greater high latitude ocean heat loss and a more northward winter sea-ice extent). In addition, the models have cold and fresh/warm and salty water column biases centred near 50 degrees S. Over the 1933-2007 period, the CORE-II models consistently simulate spatially variable trends in sea-ice concentration, surface freshwater fluxes, mixed layer depths, and 200-700 in ocean heat content. In particular, sea-ice coverage around most of the Antarctic continental shelf is reduced, leading to a cooling and freshening of the near surface waters. The shoaling of the mixed layer is associated with increased surface buoyancy gain, except in the Pacific where sea ice is also influential. The models are in disagreement, despite the common CORE-II atmospheric state, in their spatial pattern of the 20-year trends in the mixed layer depth and sea-ice. (C) 2015 Elsevier Ltd. All rights reserved

Published
2015

38. North Atlantic simulations in Coordinated Ocean-ice Reference Experiments phase II (CORE-II). Part II: Inter-annual to decadal variability

Author

Patrick Heimbach, Aurore Voldoire, Anatoly Gusev, Alicia Karspeck, Eric P. Chassignet, Rainer Bleck, Dmitry Sidorenko, Alexandra Bozec, David Salas y Mélia, Anastasia Romanou, Who M. Kim, Gael Forget, Daohua Bi, Vittorio Canuto, Simon J. Marsland, Gokhan Danabasoglu, Simona Masina, Hiroyuki Tsujino, Stephen M. Griffies, Sophie Valcke, Jianhua Lu, Mats Bentsen, Claus W. Böning, Pier Giuseppe Fogli, Gurvan Madec, Anthony Leboissetier, Mehmet Ilicak, Anna Pirani, Thomas Jung, Igor Yashayaev, Andrew C. Coward, Maxwell Kelley, Shan Sun, Yosuke Fujii, A. J. George Nurser, Petteri Uotila, Sergey Danilov, Elodie Fernandez, Steve G. Yeager, Christophe Cassou, Nikolay Diansky, A. M. Howard, William G. Large, Helge Drange, Anne-Marie Tréguier, Bonita L. Samuels, Erik Behrens, Qiang Wang, Arne Biastoch, Riccardo Farneti, Markus Scheinert, Antonio Navarra, National Center for Atmospheric Research [Boulder] (NCAR), Helmholtz Centre for Ocean Research [Kiel] (GEOMAR), Uni Research Climate, Uni Research Ltd, Centre for Australian Weather and Climate Research (CAWCR), NASA Goddard Institute for Space Studies (GISS), NASA Goddard Space Flight Center (GSFC), Center for Ocean-Atmospheric Prediction Studies (COAPS), Florida State University [Tallahassee] (FSU), Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique (CERFACS), National Oceanography Centre (NOC), Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), Institute of Numerical Mathematics [Moscou] (INM-RAS), Russian Academy of Sciences [Moscow] (RAS), University of Bergen (UiB), Abdus Salam International Centre for Theoretical Physics [Trieste] (ICTP), Centro Euro-Mediterraneo per i Cambiamenti Climatici [Bologna] (CMCC), Massachusetts Institute of Technology (MIT), Meteorological Research Institute [Tsukuba] (MRI), Japan Meteorological Agency (JMA), NOAA Geophysical Fluid Dynamics Laboratory (GFDL), National Oceanic and Atmospheric Administration (NOAA), Pacific Northwest National Laboratory (PNNL), Nucleus for European Modeling of the Ocean (NEMO R&D ), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Dipartimento di Matematica e Informatica [Perugia] (DMI), Università degli Studi di Perugia = University of Perugia (UNIPG), National Oceanography Centre [Southampton] (NOC), University of Southampton, International CLIVAR, Princeton University, Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Leibniz-Institut für Meereswissenschaften (IFM-GEOMAR), Laboratoire de physique des océans (LPO), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS), Biomedical Research Imaging Center [North Carolina] (BRIC), University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC)-University of North Carolina System (UNC), Danabasoglu G, Yeager SG, Kim WM, Behrens E, Bentsen M, Bi DH, Biastoch A, Bleck R, Boning C, Bozec A, Canuto VM, Cassou C, Chassignet E, Coward AC, Danilov S, Diansky N, Drange H, Farneti R, Fernandez E, Fogli PG, Forget G, Fujii Y, Griffies SM, Gusev A, Heimbach P, Howard A, Ilicak M, Jung T, Karspeck AR, Kelley M, Large WG, Leboissetier A, Lu JH, Madec G, Marsland SJ, Masina S, Navarra A, Nurser AJG, Pirani A, Romanou A, Melia DSY, Samuels BL, Scheinert M, Sidorenko D, Sun S, Treguier AM, Tsujino H, Uotila P, Valcke S, Voldoire A, Wang Q, Yashayaev I, CERFACS [Toulouse], Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Università degli Studi di Perugia (UNIPG), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), and CERFACS

Subjects
Atmospheric Science, 010504 meteorology & atmospheric sciences, Mixed layer, Phase (waves), [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], Oceanography, 01 natural sciences, Ocean model comparisons, Computer Science (miscellaneous), 14. Life underwater, Atmospheric forcing, Variability in the North Atlantic, 0105 earth and related environmental sciences, Inter-annual to decadal variability and mechanisms, Atlantic meridional overturning circulation variability, 010505 oceanography, Global ocean - sea-ice modelling, Geotechnical Engineering and Engineering Geology, Deep water, Ocean dynamics, Marine Sciences, Sea surface temperature, 13. Climate action, North Atlantic oscillation, Climatology, Global ocean – sea-ice modelling, Ocean model comparisons, Atmospheric forcing, Hydrography, Global ocean – sea-ice modelling, Geology
Abstract

Simulated inter-annual to decadal variability and trends in the North Atlantic for the 1958-2007 period from twenty global ocean - sea-ice coupled models are presented. These simulations are performed as contributions to the second phase of the Coordinated Ocean-ice Reference Experiments (CORE-II). The study is Part II of our companion paper (Danabasoglu et al., 2014) which documented the mean states in the North Atlantic from the same models. A major focus of the present study is the representation of Atlantic meridional overturning circulation (AMOC) variability in the participating models. Relationships between AMOC variability and those of some other related variables, such as subpolar mixed layer depths, the North Atlantic Oscillation (NAO), and the Labrador Sea upper-ocean hydrographic properties, are also investigated. In general, AMOC variability shows three distinct stages. During the first stage that lasts until the mid-to late-1970s, AMOC is relatively steady, remaining lower than its long-term (1958-2007) mean. Thereafter, AMOC intensifies with maximum transports achieved in the mid-to late-1990s. This enhancement is then followed by a weakening trend until the end of our integration period. This sequence of low frequency AMOC variability is consistent with previous studies. Regarding strengthening of AMOC between about the mid-1970s and the mid-1990s, our results support a previously identified variability mechanism where AMOC intensification is connected to increased deep water formation in the subpolar North Atlantic, driven by NAO-related surface fluxes. The simulations tend to show general agreement in their temporal representations of, for example, AMOC, sea surface temperature (SST), and subpolar mixed layer depth variabilities. In particular, the observed variability of the North Atlantic SSTs is captured well by all models. These findings indicate that simulated variability and trends are primarily dictated by the atmospheric datasets which include the influence of ocean dynamics from nature superimposed onto anthropogenic effects. Despite these general agreements, there are many differences among the model solutions, particularly in the spatial structures of variability patterns. For example, the location of the maximum AMOC variability differs among the models between Northern and Southern Hemispheres. (C) 2015 Elsevier Ltd. All rights reserved.

Published
2016

39. North Atlantic simulations in Coordinated Ocean-ice Reference Experiments phase II (CORE-II). Part I: Mean states

Author

Hiroyuki Tsujino, Jianhua Lu, Anatoly Gusev, David A. Bailey, Simon J. Marsland, Yosuke Fujii, Elodie Fernandez, Nikolay Diansky, Claus W. Böning, Gael Forget, Helge Drange, Anne-Marie Tréguier, Andrew C. Coward, Gokhan Danabasoglu, Mats Bentsen, Eric P. Chassignet, William G. Large, Sergey Danilov, A. J. George Nurser, Christophe Cassou, Riccardo Farneti, Bonita L. Samuels, Patrick Heimbach, David Salas y Mélia, Erik Behrens, Stephen M. Griffies, Gurvan Madec, Qiang Wang, Anthony Leboissetier, Arne Biastoch, Maxwell Kelley, Vittorio Canuto, Markus Scheinert, Aurore Voldoire, A. M. Howard, Steve G. Yeager, Thomas Jung, Petteri Uotila, Simona Masina, Pier Giuseppe Fogli, Daohua Bi, Sophie Valcke, Dmitry Sidorenko, Alexandra Bozec, Antonio Navarra, Anna Pirani, National Center for Atmospheric Research [Boulder] (NCAR), Lawrence Berkeley National Laboratory [Berkeley] (LBNL), Uni Research Climate, Uni Research Ltd, Centre for Australian Weather and Climate Research (CAWCR), Leibniz-Institut für Meereswissenschaften (IFM-GEOMAR), Center for Ocean-Atmospheric Prediction Studies (COAPS), Florida State University [Tallahassee] (FSU), NASA Goddard Institute for Space Studies (GISS), NASA Goddard Space Flight Center (GSFC), Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique (CERFACS), CERFACS, National Oceanography Centre (NOC), Massachusetts Institute of Technology (MIT), NOAA Geophysical Fluid Dynamics Laboratory (GFDL), National Oceanic and Atmospheric Administration (NOAA), Nucleus for European Modeling of the Ocean (NEMO R&D ), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Istituto Nazionale di Geofisica e Vulcanologia - Sezione di Bologna (INGV), Istituto Nazionale di Geofisica e Vulcanologia, International CLIVAR, Princeton University, Laboratoire de physique des océans (LPO), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Danabasoglu G, Yeager SG, Bailey D, Behrens E, Bentsen M, Bi D, Biastoch A, Boning C, Bozec A, Canuto VM, Cassou C, Chassignet E, Coward AC, Danilov S, Diansky N, Drange H, Farneti R, Fernandez E, Fogli PG, Forget G, Fujii Y, Griffies SM, Gusev A, Heimbach P, Howard A, Jung T, Kelley M, Large WG, Leboissetier A, Lu J, Madec G, Marsland SJ, Masina S, Navarra A, Nurser AJG, Pirani A, Melia DSY, Samuels BL, Scheinert M, Sidorenko D, Treguier AM, Tsujino H, Uotila P, Valcke S, Voldoire A, and Wangi Q

Subjects
Atmospheric Science, 010504 meteorology & atmospheric sciences, Mixed layer, [SDU.STU.GP]Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph], [SDE.MCG]Environmental Sciences/Global Changes, Atlantic meridional overturning circulation, [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], Oceanography, 01 natural sciences, Ocean model comparisons, Computer Science (miscellaneous), Sea ice, Potential temperature, Hindcast, 14. Life underwater, Atmospheric forcing, 0105 earth and related environmental sciences, geography, geography.geographical_feature_category, 010505 oceanography, Global ocean–sea-ice modelling, Ocean model comparisons, Atmospheric forcing, Experimental design, Atlantic meridional overturning circulation, North Atlantic simulations, Albedo, Geotechnical Engineering and Engineering Geology, Snow, Experimental design, Sea surface temperature, 13. Climate action, Meridional flow, Climatology, Environmental science, Global ocean-sea-ice modelling
Abstract

Simulation characteristics from eighteen global ocean-sea-ice coupled models are presented with a focus on the mean Atlantic meridional overturning circulation (AMOC) and other related fields in the North Atlantic. These experiments use inter-annually varying atmospheric forcing data sets for the 60-year period from 1948 to 2007 and are performed as contributions to the second phase of the Coordinated Oceanice Reference Experiments (CORE-II). The protocol for conducting such CORE-II experiments is summarized. Despite using the same atmospheric forcing, the solutions show significant differences. As most models also differ from available observations, biases in the Labrador Sea region in upper-ocean potential temperature and salinity distributions, mixed layer depths, and sea-ice cover are identified as contributors to differences in AMOC. These differences in the solutions do not suggest an obvious grouping of the models based on their ocean model lineage, their vertical coordinate representations, or surface salinity restoring strengths. Thus, the solution differences among the models are attributed primarily to use of different subgrid scale parameterizations and parameter choices as well as to differences in vertical and horizontal grid resolutions in the ocean models. Use of a wide variety of sea-ice models with diverse snow and sea-ice albedo treatments also contributes to these differences. Based on the diagnostics considered, the majority of the models appear suitable for use in studies involving the North Atlantic, but some models require dedicated development effort. (C) 2013 Elsevier Ltd. All rights reserved.

Published
2014

40. Treatment of polyethylene microplastics degraded by ultraviolet light irradiation causes lysosome-deregulated cell death.

Author

Manabe S, Haga Y, Tsujino H, Ikuno Y, Asahara H, Higashisaka K, and Tsutsumi Y

Subjects
Humans, Mice, Animals, RAW 264.7 Cells, Autophagy drug effects, Autophagy radiation effects, THP-1 Cells, Cell Death drug effects, Cell Death radiation effects, Lysosomes metabolism, Lysosomes drug effects, Ultraviolet Rays adverse effects, Microplastics toxicity, Polyethylene, Apoptosis drug effects, Apoptosis radiation effects
Abstract

Background: Microplastics (MPs), plastic particles < 5 mm in size, are prevalent in the environment, and human exposure to them is inevitable. To assess the potential risk of MPs on human health, it is essential to consider the physicochemical properties of environmental MPs, including polymer types, size, shape, and surface chemical modifications. Notably, environmental MPs undergo degradation due to external factors such as ultraviolet (UV) rays and waves, leading to changes in their surface characteristics. However, limited knowledge exists regarding the health effects of MPs, with a specific focus on their surface degradation. This study concentrates on cytotoxic MPs with surface degradation through UV irradiation, aiming to identify the mechanisms underlying their cell toxicity., Results: Polyethylene (PE) and surface-degraded PE achieved through UV light irradiation were employed as model MPs in this study. We explored the impact of PE and degraded PE on cell death in murine macrophage cell line RAW264.7 cells and human monocyte cell line THP-1 cells. Flow cytometric analysis revealed that degraded PE induced programmed cell death without activating caspase 3, while non-degraded PE did not trigger programmed cell death. These findings suggest that degraded PE might induce programmed cell death through mechanisms other than caspase-driven apoptosis. To understand the mechanisms of cell death, we investigated how cells responded to degraded PE-induced cellular stress. Immunofluorescence and western blotting analyses demonstrated that degraded PE induced autophagosome formation and increased p62 expression, indicating inhibited autophagy flux after exposure to degraded PE. Furthermore, degraded PE exposure led to a decrease in acidic lysosomes, indicating lysosomal dysregulation. These results imply that degraded PE induces lysosomal dysfunction, subsequently causing autophagy dysregulation and cell death., Conclusions: This study unveils that UV-induced degradation of PE results in cell death attributed to lysosomal dysfunction. The findings presented herein provide novel insights into the effects of surface-degraded MPs on biological responses., (© 2024. The Author(s).)

Published
2024
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41. Polyethylene, whose surface has been modified by UV irradiation, induces cytotoxicity: A comparison with microplastics found in beaches.

Author

Ikuno Y, Tsujino H, Haga Y, Manabe S, Idehara W, Hokaku M, Asahara H, Higashisaka K, and Tsutsumi Y

Subjects
Humans, Bathing Beaches, Cell Survival drug effects, Animals, Plastics toxicity, Cell Line, Microplastics toxicity, Ultraviolet Rays, Polyethylene toxicity, Polyethylene chemistry, Water Pollutants, Chemical toxicity
Abstract

Microplastics, plastic particles 5 mm or less in size, are abundant in the environment; hence, the exposure of humans to microplastics is a great concern. Usually, the surface of microplastics found in the environment has undergone degradation by external factors such as ultraviolet rays and water waves. One of the characteristics of changes caused by surface degradation of microplastics is the introduction of oxygen-containing functional groups. Surface degradation alters the physicochemical properties of plastics, suggesting that the biological effects of environmentally degraded plastics may differ from those of pure plastics. However, the biological effects of plastics introduced with oxygen-containing functional groups through degradation are poorly elucidated owing to the lack of a plastic sample that imitates the degradation state of plastics found in the environment. In this study, we investigated the degradation state of microplastics collected from a beach. Next, we degraded a commercially available polyethylene (PE) particles via vacuum ultraviolet (VUV) irradiation and showed that chemical surface state of PE imitates that of microplastics in the environment. We evaluated the cytotoxic effects of degraded PE samples on immune and epithelial cell lines. We found that VUV irradiation was effective in degrading PE within a short period, and concentration-dependent cytotoxicity was induced by degraded PE in all cell lines. Our results indicate that the cytotoxic effect of PE on different cell types depends on the degree of microplastic degradation, which contributes to our understanding of the effects of PE microplastics on humans., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Yudai Ikuno reports financial support was provided by Japan Science and Technology Agency. Yasuo Tsutsumi reports was provided by Japan Society for the Promotion of Science. Hirofumi Tsujino reports financial support was provided by Ministry of Health Labour and Welfare. Yasuo Tsutsumi reports financial support was provided by The Sumitomo Foundation for Environmental Research Projects., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Published
2024
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42. Coculture with macrophages alters ferroptosis susceptibility of triple-negative cancer cells.

Author

Konishi H, Haga Y, Okumura M, Tsujino H, Higashisaka K, and Tsutsumi Y

Abstract

Various treatment options, such as molecular targeted drugs and immune checkpoint blockades, are available for patients with cancer. However, some cancer types are refractory to molecular targeted therapies or acquire drug resistance after long-term treatment. Thus, ferroptosis, a newly defined type of programmed cell death caused by the iron-dependent accumulation of lipid peroxidation, has gained attention as a novel cancer treatment strategy. Understanding cell-cell interactions in the tumor microenvironment is important for the clinical application of ferroptosis inducers. However, the effects of cell-cell interactions on ferroptosis sensitivity remain unclear. Thus, we aimed to evaluate the effects of macrophage-cancer cell interactions on ferroptosis induction. Coculture experiments showed that conditioned medium prepared from macrophages did not alter the ferroptosis sensitivity of cancer cells. By contrast, coculture via transwell, which enables cell-cell interactions through secretion, increased the sensitivity of cancer cells to ferroptosis inducers. Additionally, direct coculture increased the susceptibility of cancer cells to RSL3-induced ferroptosis. Mechanistically, coculture with macrophages upregulated the levels of intracellular ferrous ions and lipid peroxidation in cancer cells. These findings provide novel insights into the mechanisms by which cell-cell interactions influence ferroptosis induction and application of ferroptosis inducers as a cancer treatment option., (© 2024. The Author(s).)

Published
2024
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43. Valproic acid elevates HIF-1α-mediated CGB expression and suppresses glucose uptake in BeWo cells.

Author

Kitahara G, Higashisaka K, Nakamoto Y, Yamamoto R, Okuno W, Serizawa M, Sakahashi Y, Tsujino H, Haga Y, and Tsutsumi Y

Subjects
Pregnancy, Female, Humans, Colforsin metabolism, Glucose Transporter Type 1 genetics, Glucose Transporter Type 1 metabolism, Glucose metabolism, Hypoxia-Inducible Factor 1, alpha Subunit genetics, Hypoxia-Inducible Factor 1, alpha Subunit metabolism, Cell Line, Tumor, Valproic Acid toxicity, Placenta metabolism
Abstract

Placental dysfunction can disrupt pregnancy. However, few studies have assessed the effects of chemical-induced toxicity on placental function. Here, we examined the effects of valproic acid (VPA) as a model chemical on production of hormones and on glucose uptake in human choriocarcinoma cell line BeWo. Cells were treated with forskolin to differentiate into syncytiotrophoblasts, which were then treated with VPA for 72 hr. Real-time RT-PCR analysis showed that VPA significantly increased the mRNA expression of chorionic gonadotropin β (CGB), a hormone that is produced by the placenta in the first trimester of pregnancy, relative to that in the forskolin-only group. It also suppressed the increase in intracellular glucose uptake and GLUT1 level observed in the forskolin-only group. RNA-seq analysis and pathway database analysis revealed that VPA consistently decreased the level of HIF-1α protein and expression of its downstream target genes HK2 and ADM in the hypoxia pathway. Cobalt chloride, a HIF-1α inducer, inhibited CGB upregulation in VPA-treated cells and rescued VPA-induced suppression of glucose uptake and GLUT1 level. Thus, HIF-1α-mediated elevation of CGB expression and suppression of glucose uptake by VPA is a novel mechanism of placental dysfunction.

Published
2024
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44. Impact of multiple H/D replacements on the physicochemical properties of flurbiprofen.

Author

Uchiyama H, Ban K, Nozaki S, Ikeda Y, Ishimoto T, Fujioka H, Kamiya M, Amari R, Tsujino H, Arai M, Yamazoe S, Maekawa K, Kato T, Doi M, Kadota K, Tozuka Y, Tomita N, Sajiki H, Akai S, and Sawama Y

Abstract

Although deuterium incorporation into pharmaceutical drugs is an attractive way to expand drug modalities, their physicochemical properties have not been sufficiently examined. This study focuses on examining the changes in physicochemical properties between flurbiprofen (FP) and flurbiprofen- d 8 ), which was successfully prepared by direct and multiple H/D exchange reactions at the eight aromatic C-H bonds of FP. Although the effect of deuterium incorporation was not observed between the crystal structures of FP and FP- d 8 ), which was successfully prepared by direct and multiple H/D exchange reactions at the eight aromatic C-H bonds of FP. Although the effect of deuterium incorporation was not observed between the crystal structures of FP and FP- d 8 , the melting point and heat of fusion of FP- d 8 were lower than those of FP. Additionally, the solubility of FP- d 8 increased by 2-fold compared to that of FP. Calculation of the interaction energy between FP/FP- d 8 and water molecules using the multi-component density functional theory method resulted in increased solubility of FP- d 8 . These novel and valuable findings regarding the changes in physicochemical properties triggered by deuterium incorporation can contribute to the further development of deuterated drugs., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Published
2023
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45. Fluorouracil exacerbates alpha-crystallin B chain-mediated cell migration in triple-negative breast cancer cell lines.

Author

Yang L, Haga Y, Nishimura A, Tsujii Y, Tanahashi S, Tsujino H, Higashisaka K, and Tsutsumi Y

Subjects
Humans, alpha-Crystallin B Chain genetics, Fluorouracil, Cell Movement, Cell Line, Tumor, Triple Negative Breast Neoplasms metabolism
Abstract

Among triple-negative breast cancer (TNBC) subtypes, the basal-like 2 (BL2) subtype shows the lowest survival rate and the highest risk of metastasis after treatment with chemotherapy. Research has shown that αB-crystallin (CRYAB) is more highly expressed in the basal-like subtypes than in the other subtypes and is associated with brain metastasis in TNBC patients. We therefore hypothesized that αB-crystallin is associated with increased cell motility in the BL2 subtype after treatment with chemotherapy. Here, we evaluated the effect of fluorouracil (5-FU), a typical chemotherapy for the treatment of TNBC, on cell motility by utilizing a cell line with high αB-crystallin expression (HCC1806). A wound healing assay revealed that 5-FU significantly increased cell motility in HCC1806 cells, but not in MDA-MB-231 cells, which have low αB-crystallin expression. Also, cell motility was not increased by 5-FU treatment in HCC1806 cells harboring stealth siRNA targeting CRYAB. In addition, the cell motility of MDA-MB-231 cells overexpressing αB-crystallin was significantly higher than that of MDA-MB-231 cells harboring a control vector. Thus, 5-FU increased cell motility in cell lines with high, but not low, αB-crystallin expression. These results suggest that 5-FU-induced cell migration is mediated by αB-crystallin in the BL2 subtype of TNBC., (© 2023. The Author(s).)

Published
2023
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46. Identification of biomarkers of chronic kidney disease among kidney-derived proteins.

Author

Higashisaka K, Takeya S, Kamada H, Obana M, Maeda M, Kabayama M, Yamamoto K, Ishida N, Isaka R, Tsujino H, Nagano K, Tomiyama N, Rakugi H, Fujio Y, Kamide K, and Tsutsumi Y

Abstract

Background: Chronic kidney disease (CKD) has few objective symptoms, and it is difficult to make an early diagnosis by using existing methods. Therefore, new biomarkers enabling diagnosis of renal dysfunction at an early stage need to be developed. Here, we searched for new biomarkers of CKD by focusing on kidney-derived proteins that could sensitively reflect that organ's disease state., Methods: To identify candidate marker proteins, we performed a proteomics analysis on renal influx and efflux blood collected from the same individual., Results: Proteomics analysis revealed 662 proteins in influx blood and 809 in efflux. From these identified proteins, we selected complement C1q as a candidate; the plasma C1q level was significantly elevated in the renal efflux of donors. Moreover, the plasma concentration of C1q in a mouse model of diabetic nephropathy was significantly increased, in association with increases in blood glucose concentration and urinary protein content. Importantly, we demonstrated that the tendency of C1q to increase in the plasma of CKD patients was correlated with a decrease in their estimated glomerular filtration rate., Conclusion: Overall, our results indicate that our approach of focusing on kidney-derived proteins is useful for identifying new CKD biomarkers and that C1q has potential as a biomarker of renal function., (© 2022. The Author(s).)

Published
2022
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47. Effects of the addition of CeO 2 on the steam reforming of ethanol using novel carbon-Al 2 O 3 and carbon-ZrO 2 composite-supported Co catalysts.

Author

Ishihara A, Tsujino H, and Hashimoto T

Abstract

Novel carbon-Al 2 O 3 and carbon-ZrO 2 composite-supported Co catalysts were prepared using the sol-gel method with polyethylene glycol (PEG) as a carbon source, and the effects of the addition of CeO 2 to catalysts on the steam reforming of ethanol were investigated. The reactions were carried out in a fixed bed reactor with H 2 O/EtOH = 12 (mol/mol) and a temperature range of 300 °C to 600 °C. The catalyst characterization was performed by XRD, nitrogen adsorption and desorption isotherms, TG-DTA, XRF and TEM. Although the carbon-Al 2 O 3 composite-supported Co catalysts exhibited a higher conversion of ethanol than the carbon-ZrO 2 composite-supported Co catalysts, the effect of the addition of CeO 2 was hardly observed for catalysts with Al 2 O 3 . In contrast to the case of catalysts with Al 2 O 3 , the effect of the addition of CeO 2 to catalysts with ZrO 2 on the conversion and the hydrogen yield was observed, and the hydrogen yield at 600 °C exceeded that of catalysts with Al 2 O 3 . 16Co42C31.5Ce10.5Zr exhibited the highest hydrogen yield of 89% at 600 °C. Fine Co metal species were observed for the used ZrO 2 -based catalysts, while Co 3 O 4 peaks were observed for the used Al 2 O 3 -based catalysts. The development of the carbon nanotube-like structure with a diameter of 50 nm was observed with particles having diameters of 30 nm to 50 nm, suggesting that the carbon deposition might occur so as not to deactivate the catalyst., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Published
2021
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48. A New Bitterness Evaluation Index Obtained Using the Taste Sensor for 48 Active Pharmaceutical Ingredients of Pediatric Medicines.

Author

Kojima H, Kurihara T, Yoshida M, Haraguchi T, Nishikawa H, Ikegami S, Okuno T, Yamashita T, Nishikawa J, Tsujino H, Arisawa M, Habara M, Ikezaki H, and Uchida T

Subjects
Child, Humans, Models, Molecular, Biosensing Techniques, Pharmaceutical Preparations analysis, Taste
Abstract

The aim of this study was to evaluate bitterness by using "CCDP; Change in concentration-dependent potential" considering dose-dependency of active pharmaceutical ingredients (APIs) as new and useful bitterness evaluation index compared with bitter sensor output value which is conventional bitterness evaluation index for 48 pediatric medicines from the recent edition of the WHO model list of essential medicines for children (7th edn, 2019). Solutions (0.01, 0.03, 0.1 mM) of the compounds were evaluated by an artificial taste sensor using membranes sensitive to bitterness. The dose-response slope of the sensor outputs was defined as CCDP. On the basis of principal component analysis of CCDPs, chlorpromazine hydrochloride, amitriptyline hydrochloride, propranolol hydrochloride, primaquine phosphate and haloperidol were predicted to express the strongest levels of basic bitterness, surpassing that of quinine hydrochloride. Correlation analysis (Fisher's exact tests and multiple regression analysis) was performed to determine the relation between CCDPs and various physicochemical properties participated in hydrophilicity and hydrophobicity. It is revealed that contribution physicochemical factors are different by individual basic bitterness sensor (AC0, AN0 or BT0), and this result becomes the criterion of the sensor choice to evaluate basic bitterness intensity using basic bitterness sensors. Hydrophobic and hydrophilic interactions could be simulated by ligand docking modeling for haloperidol, miconazole and quinine hydrochloride. The pharmaceutical products need a bitterness evaluation in consideration of concentration-dependency to vary in a dose depending on a patient individual. Thus, it was concluded that CCDP correlated to hydrophilicity and hydrophobicity is useful as a bitterness evaluation index of APIs in pediatric medicines.

Published
2021
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49. Development and Evaluation of a System for the Semi-Quantitative Determination of the Physical Properties of Skin After Exposure to Silver Nanoparticles.

Author

Tao H, Nagano K, Tasaki I, Zhang TQ, Ishizaka T, Gao JQ, Harada K, Hirata K, Tsujino H, Higashisaka K, and Tsutsumi Y

Abstract

In order to ensure the safe usage of silver nanoparticles (nAgs) in cosmetics, it is necessary to reveal the physical properties of nAgs inside the skin, as these properties may change during the process of percutaneous absorption. In this study, we aimed to establish an analytical system based on single particle inductively coupled plasma mass spectrometry (sp-ICP-MS) to determine the physical properties of nAgs in the skin. First, we optimized a pretreatment method for solubilizing the skin samples and then showed that most of the nAgs were recovered by sodium hydroxide treatment while remaining in particle form. For separating the skin into the epidermis and dermis, we screened several conditions of microwave irradiation. The sp-ICP-MS analysis indicated that the application of 200 W for 30 s was optimal, as this condition ensured complete separation of skin layers without changing the physical properties of the majority of nAgs. Finally, we evaluated the in vivo application by analyzing the quantity as well as the physical properties of Ag in the epidermis, dermis, and peripheral blood of mice after exposing the skin to nAgs or Ag + . Subsequent sp-ICP-MS analysis indicated that nAgs could be absorbed and distributed into the deeper layers in the ionized form, whereas Ag + was absorbed and distributed without a change in physical properties. This study indicates that in order to obtain a comprehensive understanding of the response of skin following exposure to nAgs, it is essential to consider the distribution and particle size of not only nAgs but also Ag + released from nAgs into the skin.

Published
2020
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50. Redox State Control of Human Cytoglobin by Direct Electrochemical Method to Investigate Its Function in Molecular Basis.

Author

Mie Y, Takahashi K, Torii R, Jingkai S, Tanaka T, Sueyoshi K, Tsujino H, and Yamashita T

Subjects
Cytoglobin genetics, Cytoglobin metabolism, Electrodes, Electron Transport, Gold chemistry, Humans, Hydrogen Peroxide chemistry, Kinetics, Mutagenesis, Site-Directed, Nanopores, Oxidation-Reduction, Recombinant Proteins biosynthesis, Recombinant Proteins chemistry, Recombinant Proteins isolation & purification, Cytoglobin chemistry, Electrochemical Techniques methods
Abstract

The direct electron transfer between human cytoglobin (Cygb) and the electrode surface, which would allow manipulating the oxidation states of the heme iron in Cygb, was first observed by immobilizing Cygb on a nanoporous gold (NPG) electrode via a carboxy-terminated alkanethiol. The voltammetric performances of the wild type and mutated Cygb-immobilized NPG electrodes were evaluated in the absence or presence of potential substrates. The obtained results demonstrated that the usefulness of the proposed method in understanding the function of Cygb in molecular basis.

Published
2020
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