423 results on '"Ilyina T"'
Search Results
2. Boldness as an Individual Trait of Behaviour in a Natural Population of Birds
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Ilyina, T. A., Kiseleva, A. V., Bushuev, A. V., Ivankina, E. V., and Kerimov, A. B.
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- 2024
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3. On the Concentration of Vitamins A and E in the Tissues of the Bank Vole (Myodes (Clethrionomys) glareolus) and Common Shrew (Sorex araneus) Inhabiting Karelia
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Ilyina, T. N., Baishnikova, I. V., Yakimova, A. E., and Zaitseva, I. A.
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- 2024
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4. The Content of Retinol, α-Tocopherol and Glutathione in Tissues of the Wild Boar (Sus scrofa L.) Inhabiting the Northwest of Russia
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Zaitseva, I. A., Baishnikova, I. V., Panchenko, D. V., Kalinina, S. N., Ilyina, T. N., and Antonova, E. P.
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- 2023
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5. Carbon-concentration and carbon-climate feedbacks in CMIP6 models and their comparison to CMIP5 models
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K. Arora, V, Katavouta, A, Williams, RG, Jones, CD, Brovkin, V, Friedlingstein, P, Schwinger, J, Bopp, L, Boucher, O, Cadule, P, Chamberlain, MA, Christian, JR, Delire, C, Fisher, ARA, Hajima, T, Ilyina, T, Joetzjer, E, Kawamiya, M, Koven, CD, Krasting, JP, Law, RM, Lawrence, DM, Lenton, A, Lindsay, K, Pongratz, J, Raddatz, T, Séférian, R, Tachiiri, K, Tjiputra, JF, Wiltshire, A, Wu, T, and Ziehn, T
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Earth Sciences ,Environmental Sciences ,Biological Sciences ,Meteorology & Atmospheric Sciences - Abstract
Results from the fully and biogeochemically coupled simulations in which CO2 increases at a rate of 1%yr-1 (1pctCO2) from its preindustrial value are analyzed to quantify the magnitude of carbon-concentration and carbon-climate feedback parameters which measure the response of ocean and terrestrial carbon pools to changes in atmospheric CO2 concentration and the resulting change in global climate, respectively. The results are based on 11 comprehensive Earth system models from the most recent uncertain over land than over ocean as has been seen in existing studies. These values and their spread from 11 CMIP6 models have not changed significantly compared to CMIP5 models. The absolute values of feedback parameters are lower for land with models that include a representation of nitrogen cycle. The transient climate response to cumulative emissions (TCRE) from the 11 CMIP6 models considered here is 1.77±0.37 ° C EgC-1 and is similar to that found in CMIP5 models (1.63±0.48 °C EgC-1) but with somewhat reduced model spread. The expressions for feedback parameters based on the fully and biogeochemically coupled configurations of the 1pctCO2 simulation are simplified when the small temperature change in the biogeochemically coupled simulation is ignored. Decomposition of the terms of these simplified expressions for the feedback parameters is used to gain insight into the reasons for differing responses among ocean and land carbon cycle models.
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- 2020
6. Retinol and α-Tocopherol Content in the Liver and Skeletal Muscle of Bats (Chiroptera) during Hibernation and Summer Activity
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Ilyina, T. N. and Baishnikova, I. V.
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- 2022
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7. Transportation by Rail of Chemical Enterprise Products Based on Lean Thinking
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Kryuchkova, N. A., Ilyina, T. A., di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Ashmarina, S. I., editor, and Mantulenko, V. V., editor
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- 2022
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8. Prolonged Light Deprivation Modulates the Age-Related Changes in α-Tocopherol Level in Rats
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Baishnikova, I. V., Ilyina, T. N., Khizhkin, E. A., and Ilyukha, V. A.
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- 2022
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9. Adaptive Immunity Systems of Bacteria: Association with Self-Synthesizing Transposons, Polyfunctionality
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Ilyina, T. S.
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- 2022
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10. Heat-Resistant Polyorganosiloxane Dielectrics
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Kostyleva, E. I., Novikov, A. N., Ilyina, T. A., Dedov, N. A., and Shchukina, I. A.
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- 2022
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11. Thank You to Our 2018 Peer Reviewers
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Rajaram, H, Diffenbaugh, N, Camargo, S, Cardenas, MB, Carey, R, Cobb, K, Cory, R, Cronin, M, Dombard, A, Donohue, K, Flesch, L, Giannini, A, Hayes, G, Hogg, A, Ilyina, T, Ivanov, V, Jacobsen, S, Korte, M, Lu, G, Morlighem, M, Magnusdottir, G, Newman, A, Opher, M, Passalacqua, P, Patricola, C, Ritsema, J, Sprintall, J, Su, H, Thornton, J, Williams, P, and Yau, A
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editorial ,reviewers ,Meteorology & Atmospheric Sciences - Abstract
On behalf of the journal, AGU, and the scientific community, the Editors would like to sincerely thank those who reviewed manuscripts for Geophysical Research Letters in 2018. The hours reading and commenting on manuscripts not only improves the manuscripts but also increases the scientific rigor of future research in the field. We particularly appreciate the timely reviews, in light of the demands imposed by the rapid review process at Geophysical Research Letters. With the revival of the “major revisions” decisions, we appreciate the reviewers' efforts on multiple versions of some manuscripts. Many of those listed below went beyond and reviewed three or more manuscripts for our journal, and those are indicated in italics. In total, 4,484 referees contributed to 7,557 individual reviews in journal. Thank you again. We look forward to the coming year of exciting advances in the field and communicating those advances to our community and to the broader public.
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- 2019
12. Developing Soft Skills Among Russian Higher Education Students in Context of Globalization
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Ilyina, T. A., Kryuchkova, N. A., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Ashmarina, Svetlana Igorevna, editor, and Mantulenko, Valentina Vyacheslavovna, editor
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- 2021
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13. Implementing Lean Manufacturing and Solving Motivation Problems in Russian Companies
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Maslova, O. P., Ilyina, T. A., Krichmar, V. A., Safronov, E. G., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Ashmarina, Svetlana Igorevna, editor, Mantulenko, Valentina Vyacheslavovna, editor, and Vochozka, Marek, editor
- Published
- 2021
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14. A Synthesis of Global Coastal Ocean Greenhouse Gas Fluxes
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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.
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- 2024
15. A perspective on the next generation of Earth system model scenarios: towards representative emission pathways (REPs)
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Meinshausen, M., Schleussner, C.-F., Beyer, K., Bodeker, G., Boucher, O., Canadell, J.G., Daniel, J.S., Diongue-Niang, A., Driouech, F., Fischer, E., Forster, P., Grose, M., Hansen, G., Hausfather, Z., Ilyina, T., Kikstra, J., Kimutai, J., King, A.D., Lee, J.-Y., Lennard, C., Lissner, T., Nauels, A., Peters, G.P., Pirani, A., Plattner, G.-K., Pörtner, H., Rogelj, J., Rojas, M., Roy, J., Samset, B.H., Sanderson, B.M., Séférian, R., Seneviratne, S., Smith, C., Szopa, S., Thomas, A., Urge-Vorsatz, D., Velders, G.J.M., Yokohata, T., Ziehn, T., Nicholls, Z., Meinshausen, M., Schleussner, C.-F., Beyer, K., Bodeker, G., Boucher, O., Canadell, J.G., Daniel, J.S., Diongue-Niang, A., Driouech, F., Fischer, E., Forster, P., Grose, M., Hansen, G., Hausfather, Z., Ilyina, T., Kikstra, J., Kimutai, J., King, A.D., Lee, J.-Y., Lennard, C., Lissner, T., Nauels, A., Peters, G.P., Pirani, A., Plattner, G.-K., Pörtner, H., Rogelj, J., Rojas, M., Roy, J., Samset, B.H., Sanderson, B.M., Séférian, R., Seneviratne, S., Smith, C., Szopa, S., Thomas, A., Urge-Vorsatz, D., Velders, G.J.M., Yokohata, T., Ziehn, T., and Nicholls, Z.
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- 2024
16. A perspective on the next generation of Earth system model scenarios: towards representative emission pathways (REPs)
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Meinshausen, M, Schleussner, C-F, Beyer, K, Bodeker, G, Boucher, O, Canadell, JG, Daniel, JS, Diongue-Niang, A, Driouech, F, Fischer, E, Forster, P, Grose, M, Hansen, G, Hausfather, Z, Ilyina, T, Kikstra, JS, Kimutai, J, King, AD, Lee, J-Y, Lennard, C, Lissner, T, Nauels, A, Peters, GP, Pirani, A, Plattner, G-K, Poertner, H, Rogelj, J, Rojas, M, Roy, J, Samset, BH, Sanderson, BM, Seferian, R, Seneviratne, S, Smith, CJ, Szopa, S, Thomas, A, Urge-Vorsatz, D, Velders, GJM, Yokohata, T, Ziehn, T, Nicholls, Z, Meinshausen, M, Schleussner, C-F, Beyer, K, Bodeker, G, Boucher, O, Canadell, JG, Daniel, JS, Diongue-Niang, A, Driouech, F, Fischer, E, Forster, P, Grose, M, Hansen, G, Hausfather, Z, Ilyina, T, Kikstra, JS, Kimutai, J, King, AD, Lee, J-Y, Lennard, C, Lissner, T, Nauels, A, Peters, GP, Pirani, A, Plattner, G-K, Poertner, H, Rogelj, J, Rojas, M, Roy, J, Samset, BH, Sanderson, BM, Seferian, R, Seneviratne, S, Smith, CJ, Szopa, S, Thomas, A, Urge-Vorsatz, D, Velders, GJM, Yokohata, T, Ziehn, T, and Nicholls, Z
- Abstract
In every Intergovernmental Panel on Climate Change (IPCC) Assessment cycle, a multitude of scenarios are assessed, with different scope and emphasis throughout the various Working Group reports and special reports, as well as their respective chapters. Within the reports, the ambition is to integrate knowledge on possible climate futures across the Working Groups and scientific research domains based on a small set of “framing pathways” such as the so-called representative concentration pathways (RCPs) in the Fifth IPCC Assessment Report (AR5) and the shared socioeconomic pathway (SSP) scenarios in the Sixth Assessment Report (AR6). This perspective, initiated by discussions at the IPCC Bangkok workshop in April 2023 on the “Use of Scenarios in AR6 and Subsequent Assessments”, is intended to serve as one of the community contributions to highlight the needs for the next generation of framing pathways that is being advanced under the Coupled Model Intercomparison Project (CMIP) umbrella, which will influence or even predicate the IPCC AR7 consideration of framing pathways. Here we suggest several policy research objectives that such a set of framing pathways should ideally fulfil, including mitigation needs for meeting the Paris Agreement objectives, the risks associated with carbon removal strategies, the consequences of delay in enacting that mitigation, guidance for adaptation needs, loss and damage, and for achieving mitigation in the wider context of societal development goals. Based on this context, we suggest that the next generation of climate scenarios for Earth system models should evolve towards representative emission pathways (REPs) and suggest key categories for such pathways. These framing pathways should address the most critical mitigation policy and adaptation plans that need to be implemented over the next 10 years. In our view, the most important categories are those relevant in the context of the Paris Agreement long-term goal, specific
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- 2024
17. A Synthesis of Global Coastal Ocean Greenhouse Gas Fluxes
- Author
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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
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- 2024
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18. The Role of Bacterial Biofilms in Chronic Infectious Processes and the Search for Methods to Combat Them
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Ilyina, T. S. and Romanova, Yu. M.
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- 2021
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19. Analysis of the Russian and World Marker of Telemedicine and Biochipping: Features and Development Prospects
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Blagoveshchenskaya, O., Ilyina, T., Durneva, E., Krasnova, M., Kaz, Mikhail, editor, Ilina, Tatiana, editor, and Medvedev, Gennady A., editor
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- 2019
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20. A Synthesis of Global Coastal Ocean Greenhouse Gas Fluxes
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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
- Full Text
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21. Effect of Long-Term Light Deprivation on α-Tocopherol Content in Rats during Ontogeny
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Baishnikova, I. V., Ilyina, T. N., Khizhkin, E. A., Ilyukha, V. A., and Vinogradova, I. A.
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- 2021
- Full Text
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22. C4MIP-The Coupled Climate-Carbon Cycle Model Intercomparison Project: Experimental protocol for CMIP6
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Jones, CD, Arora, V, Friedlingstein, P, Bopp, L, Brovkin, V, Dunne, J, Graven, H, Hoffman, F, Ilyina, T, John, JG, Jung, M, Kawamiya, M, Koven, C, Pongratz, J, Raddatz, T, Randerson, JT, and Zaehle, S
- Subjects
Earth Sciences - Abstract
Coordinated experimental design and implementation has become a cornerstone of global climate modelling. Model Intercomparison Projects (MIPs) enable systematic and robust analysis of results across many models, by reducing the influence of ad hoc differences in model set-up or experimental boundary conditions. As it enters its 6th phase, the Coupled Model Intercomparison Project (CMIP6) has grown significantly in scope with the design and documentation of individual simulations delegated to individual climate science communities. The Coupled Climate-Carbon Cycle Model Intercomparison Project (C4MIP) takes responsibility for design, documentation, and analysis of carbon cycle feedbacks and interactions in climate simulations. These feedbacks are potentially large and play a leading-order contribution in determining the atmospheric composition in response to human emissions of CO2 and in the setting of emissions targets to stabilize climate or avoid dangerous climate change. For over a decade, C4MIP has coordinated coupled climate-carbon cycle simulations, and in this paper we describe the C4MIP simulations that will be formally part of CMIP6. While the climate-carbon cycle community has created this experimental design, the simulations also fit within the wider CMIP activity, conform to some common standards including documentation and diagnostic requests, and are designed to complement the CMIP core experiments known as the Diagnostic, Evaluation and Characterization of Klima (DECK). C4MIP has three key strands of scientific motivation and the requested simulations are designed to satisfy their needs: (1) pre-industrial and historical simulations (formally part of the common set of CMIP6 experiments) to enable model evaluation, (2) idealized coupled and partially coupled simulations with 1% per year increases in CO2 to enable diagnosis of feedback strength and its components, (3) future scenario simulations to project how the Earth system will respond to anthropogenic activity over the 21st century and beyond. This paper documents in detail these simulations, explains their rationale and planned analysis, and describes how to set up and run the simulations. Particular attention is paid to boundary conditions, input data, and requested output diagnostics. It is important that modelling groups participating in C4MIP adhere as closely as possible to this experimental design.
- Published
- 2016
23. Erratum to: Retinol and α-Tocopherol Content in the Liver and Skeletal Muscle of Bats (Chiroptera) during Hibernation and Summer Activity
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Ilyina, T. N., Baishnikova, I. V., and Belkin, V. V.
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- 2022
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24. Association of Success in Interspecific Rearing of Nestlings with the Width of Trophic Niche of the Recipient Species in Hollow-Nesting Birds
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Ilyina, T. A., Krupitsky, A. V., and Bushuev, A. V.
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- 2020
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25. Global Carbon Budget 2015
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Le Quéré, C, Moriarty, R, Andrew, RM, Canadell, JG, Sitch, S, Korsbakken, JI, Friedlingstein, P, Peters, GP, Andres, RJ, Boden, TA, Houghton, RA, House, JI, Keeling, RF, Tans, P, Arneth, A, Bakker, DCE, Barbero, L, Bopp, L, Chang, J, Chevallier, F, Chini, LP, Ciais, P, Fader, M, Feely, RA, Gkritzalis, T, Harris, I, Hauck, J, Ilyina, T, Jain, AK, Kato, E, Kitidis, V, Klein Goldewijk, K, Koven, C, Landschützer, P, Lauvset, SK, Lefèvre, N, Lenton, A, Lima, ID, Metzl, N, Millero, F, Munro, DR, Murata, A, S. Nabel, JEM, Nakaoka, S, Nojiri, Y, O'Brien, K, Olsen, A, Ono, T, Pérez, FF, Pfeil, B, Pierrot, D, Poulter, B, Rehder, G, Rödenbeck, C, Saito, S, Schuster, U, Schwinger, J, Séférian, R, Steinhoff, T, Stocker, BD, Sutton, AJ, Takahashi, T, Tilbrook, B, Van Der Laan-Luijkx, IT, Van Der Werf, GR, Van Heuven, S, Vandemark, D, Viovy, N, Wiltshire, A, Zaehle, S, and Zeng, N
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Atmospheric Sciences ,Geochemistry ,Physical Geography and Environmental Geoscience - Abstract
Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates as well as consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2, and land-cover change (some including nitrogen-carbon interactions). We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2005-2014), EFF was 9.0 ± 0.5 GtC yrg'1, ELUC was 0.9 ± 0.5 GtC yrg'1, GATM was 4.4 ± 0.1 GtC yrg'1, SOCEAN was 2.6 ± 0.5 GtC yrg'1, and SLAND was 3.0 ± 0.8 GtC yrg'1. For the year 2014 alone, EFF grew to 9.8 ± 0.5 GtC yrg'1, 0.6 % above 2013, continuing the growth trend in these emissions, albeit at a slower rate compared to the average growth of 2.2 % yrg'1 that took place during 2005-2014. Also, for 2014, ELUC was 1.1 ± 0.5 GtC yrg'1, GATM was 3.9 ± 0.2 GtC yrg'1, SOCEAN was 2.9 ± 0.5 GtC yrg'1, and SLAND was 4.1 ± 0.9 GtC yrg'1. GATM was lower in 2014 compared to the past decade (2005-2014), reflecting a larger SLAND for that year. The global atmospheric CO2 concentration reached 397.15 ± 0.10 ppm averaged over 2014. For 2015, preliminary data indicate that the growth in EFF will be near or slightly below zero, with a projection of g'0.6 [range of g'1.6 to +0.5] %, based on national emissions projections for China and the USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the global economy for the rest of the world. From this projection of EFF and assumed constant ELUC for 2015, cumulative emissions of CO2 will reach about 555 ± 55 GtC (2035 ± 205 GtCO2) for 1870-2015, about 75 % from EFF and 25 % from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quéré et al., 2015, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP-2015).
- Published
- 2015
26. Problems of follicular thyroid carcinoma diagnostics
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Titov, S. E., primary, Lukyanov, S. A., additional, Sergiyko, S. V., additional, Veryaskina, Yu. A., additional, Ilyina, T. E., additional, Kozorezov, E. S., additional, and Vorobyov, S. L., additional
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- 2023
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27. Developing Soft Skills Among Russian Higher Education Students in Context of Globalization
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Ilyina, T. A., primary and Kryuchkova, N. A., additional
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- 2020
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28. Implementing Lean Manufacturing and Solving Motivation Problems in Russian Companies
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Maslova, O. P., primary, Ilyina, T. A., additional, Krichmar, V. A., additional, and Safronov, E. G., additional
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- 2020
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29. A Look at Phage Therapy One Hundred Years After the Bacteriophages Discovery
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Ilyina, T. S., Tolordava, E. R., and Romanova, Yu. M.
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- 2019
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30. Adaptation to Food Deprivation in Mammals: Vitamins A and E
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Ilyina, T. N. and Baishnikova, I. V.
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- 2019
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31. Comparative Research into the Effect of Vitamins A and E on the Differential Leucocyte Count and the Morphometric Parameters of Lymphocytes in Carnivorous Mammals (Carnivora)
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Baishnikova, I. V., Uzenbaeva, L. B., Ilyukha, V. A., Kizhina, A. G., Pechorina, E. F., and Ilyina, T. N.
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- 2019
- Full Text
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32. Analysis of the Russian and World Marker of Telemedicine and Biochipping: Features and Development Prospects
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Blagoveshchenskaya, O., primary, Ilyina, T., additional, Durneva, E., additional, and Krasnova, M., additional
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- 2019
- Full Text
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33. Difficulties and missteps of diagnosis and surgical treatment of patient with multifocal metachronic carcinoma associated with primary hyperparathyroidism
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Sergiiko, S. V., primary, Korotovskii, D. V., additional, Lukyanov, S. A., additional, Baturin, O. G., additional, Butorin, A. S., additional, and Ilyina, T. E., additional
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- 2023
- Full Text
- View/download PDF
34. Climate-driven variability of the Southern Ocean CO 2 sink
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Mayot, N., primary, Le Quéré, C., additional, Rödenbeck, C., additional, Bernardello, R., additional, Bopp, L., additional, Djeutchouang, L. M., additional, Gehlen, M., additional, Gregor, L., additional, Gruber, N., additional, Hauck, J., additional, Iida, Y., additional, Ilyina, T., additional, Keeling, R. F., additional, Landschützer, P., additional, Manning, A. C., additional, Patara, L., additional, Resplandy, L., additional, Schwinger, J., additional, Séférian, R., additional, Watson, A. J., additional, Wright, R. M., additional, and Zeng, J., additional
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- 2023
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- View/download PDF
35. Climate-driven variability of the Southern Ocean CO2 sink
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Mayot, N., Le Quere, C., Roedenbeck, C., Bernardello, R., Bopp, L., Djeutchouang, L. M., Gehlen, M., Gregor, L., Gruber, N., Hauck, J., Iida, Y., Ilyina, T., Keeling, R. F., Landschuetzer, P., Manning, A. C., Patara, L., Resplandy, L., Schwinger, J., Seferian, R., Watson, A. J., Wright, R. M., Zeng, J., Mayot, N., Le Quere, C., Roedenbeck, C., Bernardello, R., Bopp, L., Djeutchouang, L. M., Gehlen, M., Gregor, L., Gruber, N., Hauck, J., Iida, Y., Ilyina, T., Keeling, R. F., Landschuetzer, P., Manning, A. C., Patara, L., Resplandy, L., Schwinger, J., Seferian, R., Watson, A. J., Wright, R. M., and Zeng, J.
- Abstract
The Southern Ocean is a major sink of atmospheric CO2, but the nature and magnitude of its variability remains uncertain and debated. Estimates based on observations suggest substantial variability that is not reproduced by process-based ocean models, with increasingly divergent estimates over the past decade. We examine potential constraints on the nature and magnitude of climate-driven variability of the Southern Ocean CO2 sink from observation-based air-sea O-2 fluxes. On interannual time scales, the variability in the air-sea fluxes of CO2 and O-2 estimated from observations is consistent across the two species and positively correlated with the variability simulated by ocean models. Our analysis suggests that variations in ocean ventilation related to the Southern Annular Mode are responsible for this interannual variability. On decadal time scales, the existence of significant variability in the air-sea CO2 flux estimated from observations also tends to be supported by observation-based estimates of O-2 flux variability. However, the large decadal variability in air-sea CO2 flux is absent from ocean models. Our analysis suggests that issues in representing the balance between the thermal and non-thermal components of the CO2 sink and/or insufficient variability in mode water formation might contribute to the lack of decadal variability in the current generation of ocean models.This article is part of a discussion meeting issue 'Heat and carbon uptake in the Southern Ocean: the state of the art and future priorities'.
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- 2023
- Full Text
- View/download PDF
36. Climate-driven variability of the Southern Ocean CO2 sink
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Mayot, N, Le Quere, C, Rödenbeck, C, Bernardello, R, Bopp, L, Djeutchouang, LM, Gehlen, M, Gregor, L, Gruber, N, Hauck, J, Iida, Y, Ilyina, T, Keeling, RF, Landschtzer, P, Manning, AC, Patara, L, Resplandy, L, Schwinger, J, Sfrian, R, Watson, AJ, Wright, RM, Zeng, J, Mayot, N, Le Quere, C, Rödenbeck, C, Bernardello, R, Bopp, L, Djeutchouang, LM, Gehlen, M, Gregor, L, Gruber, N, Hauck, J, Iida, Y, Ilyina, T, Keeling, RF, Landschtzer, P, Manning, AC, Patara, L, Resplandy, L, Schwinger, J, Sfrian, R, Watson, AJ, Wright, RM, and Zeng, J
- Abstract
The Southern Ocean is a major sink of atmospheric CO 2, but the nature and magnitude of its variability remains uncertain and debated. Estimates based on observations suggest substantial variability that is not reproduced by process-based ocean models, with increasingly divergent estimates over the past decade. We examine potential constraints on the nature and magnitude of climate-driven variability of the Southern Ocean CO 2 sink from observation-based air-sea O 2 fluxes. On interannual time scales, the variability in the air-sea fluxes of CO 2 and O 2 estimated from observations is consistent across the two species and positively correlated with the variability simulated by ocean models. Our analysis suggests that variations in ocean ventilation related to the Southern Annular Mode are responsible for this interannual variability. On decadal time scales, the existence of significant variability in the air-sea CO 2 flux estimated from observations also tends to be supported by observation-based estimates of O 2 flux variability. However, the large decadal variability in air-sea CO 2 flux is absent from ocean models. Our analysis suggests that issues in representing the balance between the thermal and non-thermal components of the CO 2 sink and/or insufficient variability in mode water formation might contribute to the lack of decadal variability in the current generation of ocean models. This article is part of a discussion meeting issue 'Heat and carbon uptake in the Southern Ocean: the state of the art and future priorities'.
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- 2023
37. Global Carbon Budget 2023
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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
38. The need for carbon emissions-driven climate projections in CMIP7
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Sanderson, B.M., Booth, B.B.B., Dunne, J., Eyring, V., Fisher, R.A., Friedlingstein, P., Gidden, M., Hajima, T., Jones, C.D., Jones, C., King, A., Koven, C.D., Lawrence, D.M., Lowe, J., Mengis, N., Peters, G.P., Rogelj, J., Smith, C., Snyder, A.C., Simpson, I.R., Swann, A.L.S., Tebaldi, C., Ilyina, T., Schleussner, C.-F., Seferian, R., Samset, B.H., van Vuuren, D., Zaehle, S., Sanderson, B.M., Booth, B.B.B., Dunne, J., Eyring, V., Fisher, R.A., Friedlingstein, P., Gidden, M., Hajima, T., Jones, C.D., Jones, C., King, A., Koven, C.D., Lawrence, D.M., Lowe, J., Mengis, N., Peters, G.P., Rogelj, J., Smith, C., Snyder, A.C., Simpson, I.R., Swann, A.L.S., Tebaldi, C., Ilyina, T., Schleussner, C.-F., Seferian, R., Samset, B.H., van Vuuren, D., and Zaehle, S.
- Abstract
Previous phases of the Coupled Model Intercomparison Project (CMIP) have primarily focused on simulations driven by atmospheric concentrations of greenhouse gases (GHGs), both for idealized model experiments, and for climate projections of different emissions scenarios. We argue that although this approach was pragmatic to allow parallel development of Earth System Model simulations and detailed socioeconomic futures, carbon cycle uncertainty as represented by diverse, process-resolving Earth System Models (ESMs) is not manifested in the scenario outcomes, thus omitting a dominant source of uncertainty in meeting the Paris Agreement. Mitigation policy is defined in terms of human activity (including emissions), with strategies varying in their timing of net-zero emissions, the balance of mitigation effort between short-lived and long-lived climate forcers, their reliance on land use strategy and the extent and timing of carbon removals. To explore the response to these drivers, ESMs need to explicitly represent complete cycles of major GHGs, including natural processes and anthropogenic influences. Carbon removal and sequestration strategies, which rely on proposed human management of natural systems, are currently represented upstream of ESMs in an idealized fashion during scenario development. However, proper accounting of the coupled system impacts of and feedback on such interventions requires explicit process representation in ESMs to build self-consistent physical representations of their potential effectiveness and risks under climate change. We propose that CMIP7 efforts prioritize simulations driven by CO2 emissions from fossil fuel use, projected deployment of carbon dioxide removal technologies, as well as land use and management, using the process resolution allowed by state-of-the-art ESMs to resolve carbon-climate feedbacks. Post-CMIP7 ambitions should aim to incorporate modeling of non-CO2 GHGs (in particular sources and sinks of methane) and process
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- 2023
39. Simulations of ocean deoxygenation in the historical era: insights from forced and coupled models
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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
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- 2023
40. A perspective on the next generation of Earth system model scenarios: towards representative emission pathways (REPs)
- Author
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Meinshausen, M., Schleussner, C.-F., Beyer, K., Bodeker, G., Boucher, O., Canadell, J.G., Daniel, J.S., Diongue-Niang, A., Driouech, F., Fischer, E., Forster, P., Grose, M., Hansen, G., Hausfather, Z., Ilyina, T., Kikstra, J., Kimutai, J., King, A., Lee, J.-Y., Lennard, C., Lissner, T., Nauels, A., Peters, G.P., Pirani, A., Plattner, G.-K., Pörtner, H., Rogelj, J., Rojas, M., Roy, J., Samset, B.H., Sanderson, B.M., Séférian, R., Seneviratne, S., Smith, C., Szopa, S., Thomas, A., Urge-Vorsatz, D., Velders, G.J.M., Yokohata, T., Ziehn, T., Nicholls, Z., Meinshausen, M., Schleussner, C.-F., Beyer, K., Bodeker, G., Boucher, O., Canadell, J.G., Daniel, J.S., Diongue-Niang, A., Driouech, F., Fischer, E., Forster, P., Grose, M., Hansen, G., Hausfather, Z., Ilyina, T., Kikstra, J., Kimutai, J., King, A., Lee, J.-Y., Lennard, C., Lissner, T., Nauels, A., Peters, G.P., Pirani, A., Plattner, G.-K., Pörtner, H., Rogelj, J., Rojas, M., Roy, J., Samset, B.H., Sanderson, B.M., Séférian, R., Seneviratne, S., Smith, C., Szopa, S., Thomas, A., Urge-Vorsatz, D., Velders, G.J.M., Yokohata, T., Ziehn, T., and Nicholls, Z.
- Abstract
In every IPCC Assessment cycle, a multitude of scenarios are assessed, with different scope and emphasis throughout the various Working Group and Special Reports and their respective chapters. Within the reports, the ambition is to integrate knowledge on possible climate futures across the Working Groups and scientific research domains based on a small set of ‘framing pathways’, such as the so-called RCP pathways from the Fifth IPCC Assessment report (AR5) and the SSP-RCP scenarios in the Sixth Assessment Report (AR6). This perspective, initiated by discussions at the IPCC Bangkok workshop in April 2023 on the “Use of Scenarios in AR6 and Subsequent Assessments”, is intended to serve as one of the community contributions to highlight needs for the next generation of framing pathways that is being advanced under the CMIP umbrella for use in the IPCC AR7. Here we suggest a number of policy research objectives that such a set of framing pathways should ideally fulfil, including mitigation needs for meeting the Paris Agreement objectives, the risks associated with carbon removal strategies, the consequences of delay in enacting that mitigation, guidance for adaptation needs, loss and damage, and for achieving mitigation in the wider context of Societal Development goals. Based on this context we suggest that the next generation of climate scenarios for Earth System Models should evolve towards ‘Representative Emission Pathways’ (REPs) and suggest key categories for such pathways. These ‘framing pathways’ should address the most critical mitigation policy and adaptation needs over the next 5–10 years. In our view the most important categories are those relevant in the context of the Paris Agreement long-term goal, specifically an immediate action (low overshoot) 1.5 °C pathway, and a delayed action (high overshoot) 1.5 °C pathway. Two other key categories are a pathway category approximately in line with current (as expressed by 2023) near- and long-term policy objective
- Published
- 2023
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- View/download PDF
41. On the Concentration of Vitamins A and E in the Tissues of the Bank Vole (Myodes(Clethrionomys) glareolus) and Common Shrew (Sorex araneus) Inhabiting Karelia
- Author
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Ilyina, T. N., Baishnikova, I. V., Yakimova, A. E., and Zaitseva, I. A.
- Abstract
Abstract: We have studied the concentration of vitamins A (retinol) and E (α-tocopherol) in the tissues of the bank vole (Myodes(Clethrionomys) glareolus) and common shrew (Sorex araneus) inhabiting the northern periphery of its natural habitat. The distribution of vitamin A in the common shrew and bank vole tissues is similar: the highest concentration is found in the liver, and the lowest level is found in the heart. Age-related differences in the retinol concentration are detected in the kidneys of the two species, as well as in the skeletal muscle of the shrew. A significantly lower vitamin E concentration is found in all organs of young shrews before wintering, compared to adult overwintered animals, while in the bank vole no such age-related differences are found. Interspecies differences in the levels of vitamins A and E in the liver of overwintered animals are revealed. The results obtained show that the concentration of vitamins A and E in the tissues of the bank vole and the common shrew is determined by metabolic processes and the ecological characteristics of the species. The level of vitamins in the common shrew depends largely on age.
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- 2024
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42. Ocean modelling protocol from RECCAP2-ocean and figures S1-S6 from Climate-driven variability of the Southern Ocean CO2 sink
- Author
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Mayot, N., Le Quéré, C., Rödenbeck, C., Bernardello, R., Bopp, L., Djeutchouang, L. M., Gehlen, M., Gregor, L., Gruber, N., Hauck, J., Iida, Y., Ilyina, T., Keeling, R. F., Landschützer, P., Manning, A. C., Patara, L., Resplandy, L., Schwinger, J., Séférian, R., Watson, A. J., Wright, R. M., and Zeng, J.
- Abstract
We are summarizing the ocean modelling protocol provided by RECCAP2, and supplementary figures associated with figure 3.
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- 2023
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43. Global Carbon Budget 2022
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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).
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- 2022
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44. Post-transcriptional micro-RNAs in diagnostics and personalization of treatment in patients with thyroid tumors: literary review
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Lukyanov, S. A., primary, Sergiyko, S. V., additional, and Ilyina, T. E., additional
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- 2022
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45. The ICON Earth System Model version 1.0
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Jungclaus, J. H., Lorenz, S. J., Schmidt, H., Brovkin, V., Brüggemann, N., Chegini, F., Crüger, T., De‐Vrese, P., Gayler, V., Giorgetta, M. A., Gutjahr, O., Haak, H., Hagemann, S., Hanke, M., Ilyina, T., Korn, P., Kröger, J., Linardakis, L., Mehlmann, C., Mikolajewicz, U., Müller, W. A., Nabel, J. E. M. S., Notz, D., Pohlmann, H., Putrasahan, D. A., Raddatz, T., Ramme, L., Redler, R., Reick, C. H., Riddick, T., Sam, T., Schneck, R., Schnur, R., Schupfner, M., Storch, J.‐S., Wachsmann, F., Wieners, K.‐H., Ziemen, F., Stevens, B., Marotzke, J., Claussen, M., Lorenz, S. J., 1 Max‐Planck‐Institute for Meteorology Hamburg Germany, Schmidt, H., Brovkin, V., Brüggemann, N., Chegini, F., Crüger, T., De‐Vrese, P., Gayler, V., Giorgetta, M. A., Gutjahr, O., Haak, H., Hagemann, S., 4 Helmholtz Zentrum Hereon Geesthacht Germany, Hanke, M., 5 Deutsches Klimarechenzentrum Hamburg Germany, Ilyina, T., Korn, P., Kröger, J., Linardakis, L., Mehlmann, C., Mikolajewicz, U., Müller, W. A., Nabel, J. E. M. S., Notz, D., Pohlmann, H., Putrasahan, D. A., Raddatz, T., Ramme, L., Redler, R., Reick, C. H., Riddick, T., Sam, T., Schneck, R., Schnur, R., Schupfner, M., von Storch, J.‐S., Wachsmann, F., Wieners, K.‐H., Ziemen, F., Stevens, B., Marotzke, J., and Claussen, M.
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Global and Planetary Change ,General Earth and Planetary Sciences ,Environmental Chemistry ,ddc:550.285 ,ddc:551.63 - Abstract
This work documents the ICON‐Earth System Model (ICON‐ESM V1.0), the first coupled model based on the ICON (ICOsahedral Non‐hydrostatic) framework with its unstructured, icosahedral grid concept. The ICON‐A atmosphere uses a nonhydrostatic dynamical core and the ocean model ICON‐O builds on the same ICON infrastructure, but applies the Boussinesq and hydrostatic approximation and includes a sea‐ice model. The ICON‐Land module provides a new framework for the modeling of land processes and the terrestrial carbon cycle. The oceanic carbon cycle and biogeochemistry are represented by the Hamburg Ocean Carbon Cycle module. We describe the tuning and spin‐up of a base‐line version at a resolution typical for models participating in the Coupled Model Intercomparison Project (CMIP). The performance of ICON‐ESM is assessed by means of a set of standard CMIP6 simulations. Achievements are well‐balanced top‐of‐atmosphere radiation, stable key climate quantities in the control simulation, and a good representation of the historical surface temperature evolution. The model has overall biases, which are comparable to those of other CMIP models, but ICON‐ESM performs less well than its predecessor, the Max Planck Institute Earth System Model. Problematic biases are diagnosed in ICON‐ESM in the vertical cloud distribution and the mean zonal wind field. In the ocean, sub‐surface temperature and salinity biases are of concern as is a too strong seasonal cycle of the sea‐ice cover in both hemispheres. ICON‐ESM V1.0 serves as a basis for further developments that will take advantage of ICON‐specific properties such as spatially varying resolution, and configurations at very high resolution., Plain Language Summary: ICON‐ESM is a completely new coupled climate and earth system model that applies novel design principles and numerical techniques. The atmosphere model applies a non‐hydrostatic dynamical core, both atmosphere and ocean models apply unstructured meshes, and the model is adapted for high‐performance computing systems. This article describes how the component models for atmosphere, land, and ocean are coupled together and how we achieve a stable climate by setting certain tuning parameters and performing sensitivity experiments. We evaluate the performance of our new model by running a set of experiments under pre‐industrial and historical climate conditions as well as a set of idealized greenhouse‐gas‐increase experiments. These experiments were designed by the Coupled Model Intercomparison Project (CMIP) and allow us to compare the results to those from other CMIP models and the predecessor of our model, the Max Planck Institute for Meteorology Earth System Model. While we diagnose overall satisfactory performance, we find that ICON‐ESM features somewhat larger biases in several quantities compared to its predecessor at comparable grid resolution. We emphasize that the present configuration serves as a basis from where future development steps will open up new perspectives in earth system modeling., Key Points: This work documents ICON‐ESM 1.0, the first version of a coupled model based on the ICON framework. Performance of ICON‐ESM is assessed by means of CMIP6 Diagnosis, Evaluation, and Characterization of Klima experiments at standard CMIP‐type resolution. ICON‐ESM reproduces the observed temperature evolution. Biases in clouds, winds, sea‐ice, and ocean properties are larger than in MPI‐ESM., European Union H2020 ESM2025, European Union H2020 COMFORT, European Union H2020ESiWACE2, Deutsche Forschungsgemeinschaft TRR181, Deutsche Forschungsgemeinschaft EXC 2037, European Union H2020, Deutscher Wetterdienst, Bundesministerium fuer Bildung und Forschung, http://esgf-data.dkrz.de/search/cmip6-dkrz/, https://mpimet.mpg.de/en/science/modeling-with-icon/code-availability, http://cera-www.dkrz.de/WDCC/ui/Compact.jsp?acronym=RUBY-0_ICON-_ESM_V1.0_Model
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- 2022
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46. Seamless Integration of the Coastal Ocean in Global Marine Carbon Cycle Modeling
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Mathis, M., primary, Logemann, K., additional, Maerz, J., additional, Lacroix, F., additional, Hagemann, S., additional, Chegini, F., additional, Ramme, L., additional, Ilyina, T., additional, Korn, P., additional, and Schrum, C., additional
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- 2022
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47. Global Carbon Budget 2022
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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.
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- 2022
48. Climate-driven variability of the Southern Ocean CO2 sink.
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Mayot, N., Le Quéré, C., Rödenbeck, C., Bernardello, R., Bopp, L., Djeutchouang, L. M., Gehlen, M., Gregor, L., Gruber, N., Hauck, J., Iida, Y., Ilyina, T., Keeling, R. F., Landschützer, P., Manning, A. C., Patara, L., Resplandy, L., Schwinger, J., Séférian, R., and Watson, A. J.
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ANTARCTIC oscillation ,OCEAN ,ATMOSPHERIC carbon dioxide ,MINE ventilation - Abstract
The Southern Ocean is a major sink of atmospheric CO
2 , but the nature and magnitude of its variability remains uncertain and debated. Estimates based on observations suggest substantial variability that is not reproduced by process-based ocean models, with increasingly divergent estimates over the past decade. We examine potential constraints on the nature and magnitude of climate-driven variability of the Southern Ocean CO2 sink from observation-based air–sea O2 fluxes. On interannual time scales, the variability in the air–sea fluxes of CO2 and O2 estimated from observations is consistent across the two species and positively correlated with the variability simulated by ocean models. Our analysis suggests that variations in ocean ventilation related to the Southern Annular Mode are responsible for this interannual variability. On decadal time scales, the existence of significant variability in the air–sea CO2 flux estimated from observations also tends to be supported by observation-based estimates of O2 flux variability. However, the large decadal variability in air–sea CO2 flux is absent from ocean models. Our analysis suggests that issues in representing the balance between the thermal and non-thermal components of the CO2 sink and/or insufficient variability in mode water formation might contribute to the lack of decadal variability in the current generation of ocean models. This article is part of a discussion meeting issue 'Heat and carbon uptake in the Southern Ocean: the state of the art and future priorities'. [ABSTRACT FROM AUTHOR]- Published
- 2023
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49. Filamentous bacteriophages and their role in the virulence and evolution of pathogenic bacteria
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Ilyina, T. S.
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- 2015
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50. Local oceanic CO2 outgassing triggered by terrestrial carbon fluxes during deglacial flooding
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Extier, T., Six, K., Liu, B., Paulsen, H., and Ilyina, T.
- Abstract
Exchange of carbon between the ocean and the atmosphere is a key process that influences past climates via glacial–interglacial variations of the CO2 concentration. The melting of ice sheets during deglaciations induces a sea level rise which leads to the flooding of coastal land areas, resulting in the transfer of terrestrial organic matter to the ocean. However, the consequences of such fluxes on the ocean biogeochemical cycle and on the uptake and release of CO2 are poorly constrained. Moreover, this potentially important exchange of carbon at the land–sea interface is not represented in most Earth system models. We present here the implementation of terrestrial organic matter fluxes into the ocean at the transiently changing land–sea interface in the Max Planck Institute for Meteorology Earth System Model (MPI-ESM) and investigate their effect on the biogeochemistry during the last deglaciation. Our results show that during the deglaciation, most of the terrestrial organic matter inputs to the ocean occurs during Meltwater Pulse 1a (between 15–14 ka) which leads to the transfer of 21.2 Gt C of terrestrial carbon (mostly originating from wood and humus) to the ocean. Although this additional organic matter input is relatively small in comparison to the global ocean inventory (0.06 %) and thus does not have an impact on the global CO2 flux, the terrestrial organic matter fluxes initiate oceanic outgassing in regional hotspots like in Indonesia for a few hundred years. Finally, sensitivity experiments highlight that terrestrial organic matter fluxes are the drivers of oceanic outgassing in flooded coastal regions during Meltwater Pulse 1a. Furthermore, the magnitude of outgassing is rather insensitive to higher carbon-to-nutrient ratios of the terrestrial organic matter. Our results provide a first estimate of the importance of terrestrial organic matter fluxes in a transient deglaciation simulation. Moreover, our model development is an important step towards a fully coupled carbon cycle in an Earth system model applicable to simulations at glacial–interglacial cycles.
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- 2022
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