Medico-Social Explanation of Life Quality Phenomenon
In: Izvestia of Saratov University. New Series. Series: Sociology. Politology, Band 11, Heft 4, S. 20-26
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In: Izvestia of Saratov University. New Series. Series: Sociology. Politology, Band 11, Heft 4, S. 20-26
In: Advances in Gerontology, Band 4, Heft 4, S. 260-263
ISSN: 2079-0589
This is the final version of the article. Available from EGU via the DOI in this record. ; During the fifth phase of the Coupled Model Intercomparison Project (CMIP5) substantial efforts were made to systematically assess the skill of Earth system models. One goal was to check how realistically representative marine biogeochemical tracer distributions could be reproduced by models. In routine assessments model historical hindcasts were compared with available modern biogeochemical observations. However, these assessments considered neither how close modeled biogeochemical reservoirs were to equilibrium nor the sensitivity of model performance to initial conditions or to the spin-up protocols. Here, we explore how the large diversity in spin-up protocols used for marine biogeochemistry in CMIP5 Earth system models (ESMs) contributes to model-to-model differences in the simulated fields. We take advantage of a 500-year spin-up simulation of IPSL-CM5A-LR to quantify the influence of the spin-up protocol on model ability to reproduce relevant data fields. Amplification of biases in selected biogeochemical fields (O2, NO3, Alk-DIC) is assessed as a function of spin-up duration. We demonstrate that a relationship between spin-up duration and assessment metrics emerges from our model results and holds when confronted with a larger ensemble of CMIP5 models. This shows that drift has implications for performance assessment in addition to possibly aliasing estimates of climate change impact. Our study suggests that differences in spin-up protocols could explain a substantial part of model disparities, constituting a source of model-to-model uncertainty. This requires more attention in future model intercomparison exercises in order to provide quantitatively more correct ESM results on marine biogeochemistry and carbon cycle feedbacks. ; We sincerely thank I. Kriest, F. Joos, the anonymous reviewer and A. Yool for their useful comments on this paper. This work was supported by H2020 project CRESCENDO "Coordinated Research in Earth Systems and Climate: Experiments, kNowledge, Dissemination and Outreach", which received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 641816 and by the EU FP7 project CARBOCHANGE "Changes in carbon uptake and emissions by oceans in a changing climate" which received funding from the European community's Seventh Framework Programme under grant agreement no. 264879. Supercomputing time was provided by GENCI (Grand Equipement National de Calcul Intensif) at CCRT (Centre de Calcul Recherche et Technologie), allocation 016178. Finally, we are grateful to the ESGF project which makes data available for all the community. Roland Séférian is grateful to Aurélien Ribes for his kind advices on statistics. Jerry Tjiputra acknowledges ORGANIC project (239965/F20) funded by the Research Council of Norway. Christoph Heinze and Jerry Tjiputra are grateful for support through project EVA – Earth system modelling of climate variations in the Anthropocene (229771/E10) funded by the Research Council of Norway, as well as CPU-time and mass storage provided through NOTUR project NN2345K as well as NorStore project NS2345K. Keith Lindsay and Scott C. Doney acknowledge support from the National Science Foundation.
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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. ; CRESCENDO project members (CDJ, PF, LB, VB, TI, SZ) acknowledge funding received from the Horizon 2020 European Union's Framework Programme for Research and Innovation under grant agreement no. 641816. CDJ was supported by the Joint UK BEIS/Defra Met Office Hadley Centre Climate Programme (GA01101). HDG was supported by a Marie Curie Career Integration Grant from the European Commission. JP is supported by the German Research Foundation's Emmy Noether Program (PO 1751/1-1).
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In: Izvestia of Saratov University. New Series. Series: Sociology. Politology, Band 11, Heft 3, S. 29-36
Many nations responded to the corona virus disease-2019 (COVID-19) pandemic by restricting travel and other activities during 2020, resulting in temporarily reduced emissions of CO2, other greenhouse gases and ozone and aerosol precursors. We present the initial results from a coordinated Intercomparison, CovidMIP, of Earth system model simulations which assess the impact on climate of these emissions reductions. 12 models performed multiple initial-condition ensembles to produce over 300 simulations spanning both initial condition and model structural uncertainty. We find model consensus on reduced aerosol amounts (particularly over southern and eastern Asia) and associated increases in surface shortwave radiation levels. However, any impact on near-surface temperature or rainfall during 2020–2024 is extremely small and is not detectable in this initial analysis. Regional analyses on a finer scale, and closer attention to extremes (especially linked to changes in atmospheric composition and air quality) are required to test the impact of COVID-19-related emission reductions on near-term climate. © 2021. Crown Copyright. © 2021. Her Majesty the Queen in Right of Canada. This article is published with the permission of the Controller of HMSO and the Queen's Printer for Scotland. Reproduced with the permission of the Minister of Environment and Climate Change Canada. This article has been contributed to by US Government employees and their work is in the public domain in the USA.
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Many nations responded to the corona virus disease-2019 (COVID-19) pandemic by restricting travel and other activities during 2020, resulting in temporarily reduced emissions of CO2, other greenhouse gases and ozone and aerosol precursors. We present the initial results from a coordinated Intercomparison, CovidMIP, of Earth system model simulations which assess the impact on climate of these emissions reductions. 12 models performed multiple initial-condition ensembles to produce over 300 simulations spanning both initial condition and model structural uncertainty. We find model consensus on reduced aerosol amounts (particularly over southern and eastern Asia) and associated increases in surface shortwave radiation levels. However, any impact on near-surface temperature or rainfall during 2020–2024 is extremely small and is not detectable in this initial analysis. Regional analyses on a finer scale, and closer attention to extremes (especially linked to changes in atmospheric composition and air quality) are required to test the impact of COVID-19-related emission reductions on near-term climate. © 2021. Crown Copyright. © 2021. Her Majesty the Queen in Right of Canada. This article is published with the permission of the Controller of HMSO and the Queen's Printer for Scotland. Reproduced with the permission of the Minister of Environment and Climate Change Canada. This article has been contributed to by US Government employees and their work is in the public domain in the USA.
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In: Trudy Kolʹskogo naučnogo centra RAN. Gumanitarnye issledovanija = Humanitarian studies, Band 2, Heft 11, S. 69-83
Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere - the "global carbon budget" - 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 methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (E-FF) are based on energy statistics and cement production data, while emissions from land use change (E-LUC), 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 (G(ATM)) is computed from the annual changes in concentration. The ocean CO2 sink (S-OCEAN) and terrestrial CO2 sink (S-LAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (B-IM), 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 +/- 1 sigma. For the last decade available (2009-2018), E-FF was 9.5 +/- 0.5 GtC yr 1, E-LUC 1.5 +/- 0.7 GtC yr 1, G(ATM) 4.9 +/- 0.02 GtC yr(-1) (2.3 +/- 0.01 ppm yr(-1)), S-OCEAN 2.5 +/- 0.6 GtC yr(-1), and S-LAND 3.2 +/- 0.6 GtC yr(-1), with a budget imbalance B-IM of 0.4 GtC yr(-1) indicating overestimated emissions and/or underestimated sinks. For the year 2018 alone, the growth in E-FF was about 2.1% and fossil emissions increased to 10.0 +/- 0.5 GtC yr 1, reaching 10 GtC yr(-1) for the first time in history, E-LUC was 1.5 +/- 0.7 GtC yr(-1), for total anthropogenic CO2 emissions of 11.5 +/- 0.9 GtC yr(-1) (42.5 +/- 3.3 GtCO(2)). Also for 2018, G(ATM) was 5.1 +/- 0.2 GtC yr(-1) (2.4 +/- 0.1 ppm yr(-1)), S-OCEAN was 2.6 +/- 0.6 GtC yr(-1), and S-LAND was 3.5 +/- 0.7 GtC yr(-1), with a B-IM of 0.3 GtC. The global atmospheric CO2 concentration reached 407.38 +/- 0.1 ppm averaged over 2018. For 2019, preliminary data for the first 6-10 months indicate a reduced growth in E-FF of +0.6% (range of -0.2% to 1.5 %) based on national emissions projections for China, the USA, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. Overall, the mean and trend in the five components of the global carbon budget are consistently estimated over the period 1959-2018, but discrepancies of up to 1 GtC yr(-1) persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations shows (1) no consensus in the mean and trend in land use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models outside the tropics. 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 (Le Quere et al., 2018a, b, 2016, 2015a, b, 2014, 2013).
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Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the "global carbon budget" – 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 methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFF) are based on energy statistics and cement production data, while emissions from land use and 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) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. 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 last decade available (2008–2017), EFF was 9.4±0.5 GtC yr−1, ELUC 1.5±0.7 GtC yr−1, GATM 4.7±0.02 GtC yr−1, SOCEAN 2.4±0.5 GtC yr−1, and SLAND 3.2±0.8 GtC yr−1, with a budget imbalance BIM of 0.5 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For the year 2017 alone, the growth in EFF was about 1.6 % and emissions increased to 9.9±0.5 GtC yr−1. Also for 2017, ELUC was 1.4±0.7 GtC yr−1, GATM was 4.6±0.2 GtC yr−1, SOCEAN was 2.5±0.5 GtC yr−1, and SLAND was 3.8±0.8 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 405.0±0.1 ppm averaged over 2017. For 2018, preliminary data for the first 6–9 months indicate a renewed growth in EFF of +2.7 % (range of 1.8 % to 3.7 %) based on national emission projections for China, the US, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. The analysis presented here shows that the mean and trend in the five components of the global carbon budget are consistently estimated over the period of 1959–2017, but discrepancies of up to 1 GtC yr−1 persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations show (1) no consensus in the mean and trend in land-use change emissions, (2) a persistent low agreement among the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models, originating outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding the global carbon cycle compared with previous publications of this data set (Le Quéré et al., 2018, 2016, 2015a, b, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2018.
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