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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

4. Tropospheric and Stratospheric Boreal Winter Jet Response to Eddying Ocean in a Seasonal Forecast System.

Author

Hirahara, S., Ishikawa, I., Fujii, Y., Nakano, H., Tsujino, H., Adachi, Y., and Naoe, H.

Subjects
INTERTROPICAL convergence zone, JET streams, OCEAN, METEOROLOGICAL research, OCEAN waves
Abstract

Understanding the impacts of high‐resolution ocean model provides valuable insights for future research. However, the outcomes of sea surface state changes in both the tropics and mid‐latitudes remain unclear, and initialized seasonal forecasts have not been studied extensively. This study investigates the impact of ocean model resolution with the first long‐term hindcast experiment of an eddy‐resolving (0.1°) ocean model used for global seasonal forecasting. We show that using the high‐resolution ocean model significantly changes boreal winter jet streams in the atmosphere, based on the comparison of 30‐year hindcasts with ocean resolutions ranging from 1° to 0.1° for the Japan Meteorological Agency/Meteorological Research Institute Coupled Prediction System version 3. In boreal winters, the cold sea surface bias in the equatorial Pacific is significantly reduced, leading to an equatorward shift in the intertropical convergence zone (ITCZ) and enhanced convective activity in the western equatorial Pacific. The subtropical jet shifts equatorward due to the ITCZ shift and the weakening of equatorward propagation of mid‐latitude atmospheric eddies. The enhanced convective activity in the tropics has a remote influence in the mid‐latitudes, significantly reducing the upward eddy propagation of zonal wavenumber 1. Sea surface warm‐up in the mid‐latitudes partially cancels the reduction impact by enhancing the zonal wavenumber 2. Overall, the polar night jet accelerates due to the reduced supply of eddy forcing. Plain Language Summary: Atmospheric and oceanic eddies play an important role in shaping the climate. In numerical climate simulations, the Earth is divided into a grid of discrete boxes, and the exchange of energy and mass between the boxes is computed step‐by‐step. Coarse grids are often used to reduce the computational cost, but recent studies have suggested that resolving fine ocean phenomena can make a significant difference. In this study, numerical seasonal forecasting experiments with ocean resolutions of 100 km, 25 km, and 10 km are compared to investigate the high‐resolution effects on the atmospheric flow for boreal winter. This is the first 30‐year‐long, retrospective seasonal forecast experiment for the past winters using a global eddy‐resolving (10 km) ocean model. The high‐resolution ocean model greatly warms the surface seawater in the tropical Pacific and in the mid‐latitude oceans. These changes in the sea surface influence atmospheric convection and eddies, with far‐reaching effects on distant regions and altitudes. Such effects on the westerly jet streams, which flow several kilometers to tens of kilometers above the sea surface, are observed in the southward shift of the subtropical jet and the strengthening of the polar night jet. Key Points: Altering the ocean model resolution from 1° to 0.1° in a seasonal forecast model shifts and enhances the subtropical and polar night jetsAtmospheric responses to both tropical and mid‐latitude oceans are observedWave‐mean flow diagnostics indicates that the jet stream responses are more strongly influenced by the tropics [ABSTRACT FROM AUTHOR]

Published
2024
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6. 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., and Wang, Q.

Published
2020
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7. A Synthesis of Global Coastal Ocean Greenhouse Gas Fluxes

Author

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

Published
2024
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9. Eastern Boundary Upwelling Systems in Ocean–Sea Ice Simulations Forced by CORE and JRA55-do: Mean State and Variability at the Surface.

Author

Small, R. J., Kurian, J., Chang, P., Xu, G., Tsujino, H., Yeager, S., Danabasoglu, G., Kim, W. M., Altuntas, A., and Castruccio, F.

Abstract

In this paper we summarize improvements in climate model simulation of eastern boundary upwelling systems (EBUS) when changing the forcing dataset from the Coordinated Ocean-Ice Reference Experiments (CORE; ∼2° winds) to the higher-resolution Japanese 55-year Atmospheric Reanalysis for driving ocean–sea ice models (JRA55-do, ∼0.5°) and also due to refining ocean grid spacing from 1° to 0.1°. The focus is on sea surface temperature (SST), a key variable for climate studies, and which is typically too warm in climate model representation of EBUS. The change in forcing leads to a better-defined atmospheric low-level coastal jet, leading to more equatorward ocean flow and coastal upwelling, both in turn acting to reduce SST over the upwelling regions off the west coast of North America, Peru, and Chile. The refinement of ocean resolution then leads to narrower and stronger alongshore ocean flow and coastal upwelling, and the emergence of strong across-shore temperature gradients not seen with the coarse ocean model. Off northwest Africa the SST bias mainly improves with ocean resolution but not with forcing, while in the Benguela, JRA55-do with high-resolution ocean leads to lower SST but a substantial bias relative to observations remains. Reasons for the Benguela bias are discussed in the context of companion regional ocean model simulations. Finally, we address to what extent improvements in mean state lead to changes to the monthly to interannual variability. It is found that large-scale SST variability in EBUS on monthly and longer time scales is largely governed by teleconnections from climate modes and less sensitive to model resolution and forcing than the mean state. [ABSTRACT FROM AUTHOR]

Published
2024
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11. 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

12. 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

14. 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

17. 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

19. 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

21. Real-time three-dimensional color Doppler echocardiography for characterizing the spatial velocity distribution and quantifying the peak flow rate in the left ventricular outflow tract

Author

Tsujino, H, Jones, M, Shiota, T, Qin, J. X, Greenberg, N. L, Cardon, L. A, Morehead, A. J, Zetts, A. D, Travaglini, A, Bauer, F, Panza, J. A, and Thomas, J. D

Subjects
Life Sciences (General)
Abstract

Quantification of flow with pulsed-wave Doppler assumes a "flat" velocity profile in the left ventricular outflow tract (LVOT), which observation refutes. Recent development of real-time, three-dimensional (3-D) color Doppler allows one to obtain an entire cross-sectional velocity distribution of the LVOT, which is not possible using conventional 2-D echo. In an animal experiment, the cross-sectional color Doppler images of the LVOT at peak systole were derived and digitally transferred to a computer to visualize and quantify spatial velocity distributions and peak flow rates. Markedly skewed profiles, with higher velocities toward the septum, were consistently observed. Reference peak flow rates by electromagnetic flow meter correlated well with 3-D peak flow rates (r = 0.94), but with an anticipated underestimation. Real-time 3-D color Doppler echocardiography was capable of determining cross-sectional velocity distributions and peak flow rates, demonstrating the utility of this new method for better understanding and quantifying blood flow phenomena.

Published
2001
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22. 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

23. 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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24. New digital measurement methods for left ventricular volume using real-time three-dimensional echocardiography: comparison with electromagnetic flow method and magnetic resonance imaging

Author

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

Subjects
Life Sciences (General)
Abstract

AIM: The aim of this study was to investigate the feasibility and accuracy of using symmetrically rotated apical long axis planes for the determination of left ventricular (LV) volumes with real-time three-dimensional echocardiography (3DE). METHODS AND RESULTS: Real-time 3DE was performed in six sheep during 24 haemodynamic conditions with electromagnetic flow measurements (EM), and in 29 patients with magnetic resonance imaging measurements (MRI). LV volumes were calculated by Simpson's rule with five 3DE methods (i.e. apical biplane, four-plane, six-plane, nine-plane (in which the angle between each long axis plane was 90 degrees, 45 degrees, 30 degrees or 20 degrees, respectively) and standard short axis views (SAX)). Real-time 3DE correlated well with EM for LV stroke volumes in animals (r=0.68-0.95) and with MRI for absolute volumes in patients (r-values=0.93-0.98). However, agreement between MRI and apical nine-plane, six-plane, and SAX methods in patients was better than those with apical four-plane and bi-plane methods (mean difference = -15, -18, -13, vs. -31 and -48 ml for end-diastolic volume, respectively, P<0.05). CONCLUSION: Apically rotated measurement methods of real-time 3DE correlated well with reference standards for calculating LV volumes. Balancing accuracy and required time for these LV volume measurements, the apical six-plane method is recommended for clinical use.

Published
2000
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25. 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

26. 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

27. 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

28. 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

29. 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

30. 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

31. 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

32. 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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34. 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

35. 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

36. 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

39. 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

40. 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

44. 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

45. 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

49. Combined Surgical and Intraoperative Endovascular Approach for a Giant Internal Carotid Artery Aneurysm in the High Cervical Region

Author

Masaki H, Hirai M, Naoya Hashimoto, Keigo Matsumoto, Tsujino H, and Mineura K

Subjects
Carotid Artery Diseases, medicine.medical_specialty, medicine.medical_treatment, Aneurysm, medicine.artery, medicine, Humans, cardiovascular diseases, Embolization, Derivation, Ligation, Aged, medicine.diagnostic_test, business.industry, Vascular disease, Angiography, Digital Subtraction, General Medicine, Digital subtraction angiography, Superficial temporal artery, medicine.disease, Embolization, Therapeutic, Surgery, Treatment Outcome, Middle cerebral artery, cardiovascular system, Female, Neurology (clinical), Radiology, business, Vascular Surgical Procedures
Abstract

For the obliteration of a large aneurysm located at the cranial base or high cervical region, several therapeutic strategies including a parent vessel ligation, and endovascular occlusion have been reported, because it is difficult to access the aneurysm itself. We used a combined surgical and endovascular approach for the treatment of a large internal carotid artery aneurysm in the high cervical region. In the present case, we performed superficial temporal artery to middle cerebral artery bypass, then obliterated the aneurysm with distal coil embolization and proximal ligation in one session, using portable digital subtraction angiography. The combined endovascular and surgical approach involves less invasive surgery for complex cerebrovascular lesions.

Published
2002

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