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description Publicationkeyboard_double_arrow_right Other literature type , Article 2012Publisher:OpenAlex Funded by:EC | LUISEEC| LUISESebastiaan Luyssaert; Gwénaël Abril; R. J. Andres; David Bastviken; Valentin Bellassen; P. Bergamaschi; Philippe Bousquet; Frédéric Chevallier; Philippe Ciais; M. Corazza; René Dechow; Karl‐Heinz Erb; Giuseppe Etiope; Audrey Fortems-Cheiney; Giacomo Grassi; J. Hartman; Martin Jung; Juliette Lathière; Annalea Lohila; Nils Moosdorf; Sylvestre Njakou Djomo; Juliane Otto; Dario Papale; Wouter Peters; P. Peylin; Peter A. Raymond; Christian Rödenbeck; Sanna Saarnio; Ernst‐Detlef Schulze; Sophie Szopa; Rona L. Thompson; Pieter Johannes Verkerk; Nicolas Vuichard; R. Wang; M. Wattenbach; Sönke Zaehle;Résumé. À l'échelle mondiale, les écosystèmes terrestres ont absorbé environ 30 % des émissions anthropiques au cours de la période 20007-2007 et les gradients interhémisphériques indiquent qu'une fraction importante de la séquestration du carbone terrestre doit se situer au nord de l'équateur. Nous présentons une compilation du bilan de CO2, CO, CH4 et N2O de l'Europe suivant une approche à double contrainte dans laquelle (1) un bilan terrestre dérivé principalement des inventaires de carbone des écosystèmes et (2) un bilan terrestre dérivé des mesures de flux sont confrontés à (3) le bilan atmosphérique dérivé de l'inversion informée par les mesures des concentrations atmosphériques de GES. Un bon accord entre les bilans de GES basés sur les flux (1249 ± 545 Tg C en CO2-eq y−1), les inventaires (1299 ± 200 Tg C en CO2-eq y−1) et les inversions (1210 ± 405 Tg C en CO2-eq y−1) augmente notre confiance que les bilans de GES européens actuels sont exacts. Cependant, l'incertitude reste grande et manque largement d'estimations formelles. Étant donné que les bilans nets terre-atmosphère européens sont déterminés par quelques flux dominants, l'incertitude de ces composantes clés doit être formellement estimée avant que des efforts puissent être déployés pour réduire l'incertitude globale. L'approche à double contrainte a confirmé que la surface terrestre européenne, y compris les eaux intérieures et les zones urbaines, est une source nette de CO2, CO, CH4 et N2O. Cependant, pour tous les écosystèmes à l'exception des terres cultivées, l'absorption de C dépasse les rejets de C et ces 210 ± 70 Tg C y−1 provenant de la combustion de combustibles fossiles sont retirés de l'atmosphère et séquestrés dans les écosystèmes aquatiques terrestres et intérieurs. Si le coût du carbone pour la gestion des écosystèmes est pris en compte, l'absorption nette des écosystèmes a été estimée à diminuer de 45 %, mais indique toujours une séquestration substantielle du carbone. En outre, lorsque l'équilibre est étendu du CO2 vers les principaux GES, l'absorption de C par les écosystèmes terrestres et aquatiques est compensée par les émissions de GES. En tant que tels, les écosystèmes européens sont peu susceptibles de contribuer à atténuer les effets du changement climatique. Resumen. A nivel mundial, los ecosistemas terrestres han absorbido alrededor del 30% de las emisiones antropogénicas durante el período 20007-2007 y los gradientes interhemisféricos indican que una fracción significativa del secuestro de carbono terrestre debe estar al norte del Ecuador. Presentamos una recopilación del balance de CO2, CO, CH4 y N2O de Europa siguiendo un enfoque de doble restricción en el que (1) un balance terrestre derivado principalmente de los inventarios de carbono del ecosistema y (2) un balance terrestre derivado de las mediciones de flujo se enfrentan con (3) el balance atmosférico derivado de la inversión informada por las mediciones de las concentraciones atmosféricas de GEI. Una buena concordancia entre los balances de GEI basados en flujos (1249 ± 545 Tg C en CO2-eq y−1), inventarios (1299 ± 200 Tg C en CO2-eq y−1) e inversiones (1210 ± 405 Tg C en CO2-eq y−1) aumenta nuestra confianza en que los balances de GEI europeos actuales son precisos. Sin embargo, la incertidumbre sigue siendo grande y en gran medida carece de estimaciones formales. Dado que los balances netos tierra-atmósfera europeos están determinados por unos pocos flujos dominantes, la incertidumbre de estos componentes clave debe estimarse formalmente antes de poder realizar esfuerzos para reducir la incertidumbre general. El enfoque de doble restricción confirmó que la superficie terrestre europea, incluidas las aguas interiores y las zonas urbanas, es una fuente neta de CO2, CO, CH4 y N2O. Sin embargo, para todos los ecosistemas, excepto las tierras de cultivo, la absorción de C excede la liberación de C y tales 210 ± 70 Tg C y−1 de la quema de combustibles fósiles se eliminan de la atmósfera y se secuestran en los ecosistemas acuáticos terrestres y continentales. Si se tiene en cuenta el costo de C para la gestión de los ecosistemas, se estimó que la absorción neta de los ecosistemas disminuiría en un 45%, pero aún indica un secuestro sustancial de C. Además, cuando el equilibrio se extiende desde el CO2 hacia los principales GEI, la absorción de C por los ecosistemas terrestres y acuáticos se compensa con las emisiones de GEI. Como tal, es poco probable que los ecosistemas europeos contribuyan a mitigar los efectos del cambio climático. Abstract. Globally, terrestrial ecosystems have absorbed about 30% of anthropogenic emissions over the period 20007–2007 and inter-hemispheric gradients indicate that a significant fraction of terrestrial carbon sequestration must be north of the Equator. We present a compilation of the CO2, CO, CH4 and N2O balance of Europe following a dual constraint approach in which (1) a land-based balance derived mainly from ecosystem carbon inventories and (2) a land-based balance derived from flux measurements are confronted with (3) the atmospheric-based balance derived from inversion informed by measurements of atmospheric GHG concentrations. Good agreement between the GHG balances based on fluxes (1249 ± 545 Tg C in CO2-eq y−1), inventories (1299 ± 200 Tg C in CO2-eq y−1) and inversions (1210 ± 405 Tg C in CO2-eq y−1) increases our confidence that current European GHG balances are accurate. However, the uncertainty remains large and largely lacks formal estimates. Given that European net land-atmosphere balances are determined by a few dominant fluxes, the uncertainty of these key components needs to be formally estimated before efforts could be made to reduce the overall uncertainty. The dual-constraint approach confirmed that the European land surface, including inland waters and urban areas, is a net source for CO2, CO, CH4 and N2O. However, for all ecosystems except croplands, C uptake exceeds C release and us such 210 ± 70 Tg C y−1 from fossil fuel burning is removed from the atmosphere and sequestered in both terrestrial and inland aquatic ecosystems. If the C cost for ecosystem management is taken into account, the net uptake of ecosystems was estimated to decrease by 45% but still indicates substantial C-sequestration. Also, when the balance is extended from CO2 towards the main GHGs, C-uptake by terrestrial and aquatic ecosystems is compensated for by emissions of GHGs. As such the European ecosystems are unlikely to contribute to mitigating the effects of climate change. الخلاصة. على الصعيد العالمي، امتصت النظم الإيكولوجية الأرضية حوالي 30 ٪ من الانبعاثات البشرية المنشأ خلال الفترة 20007-2007 وتشير التدرجات بين نصف الكرة الأرضية إلى أن جزءًا كبيرًا من عزل الكربون الأرضي يجب أن يكون شمال خط الاستواء. نقدم مجموعة من توازن ثاني أكسيد الكربون وثاني أكسيد الكربون والميثان وأكسيد النيتروز في أوروبا باتباع نهج القيد المزدوج الذي (1) يواجه فيه التوازن البري المستمد بشكل أساسي من قوائم جرد الكربون في النظام الإيكولوجي و (2) التوازن البري المستمد من قياسات التدفق (3) التوازن الجوي المستمد من الانعكاس المستنير بقياسات تركيزات غازات الدفيئة في الغلاف الجوي. الاتفاق الجيد بين أرصدة غازات الدفيئة على أساس التدفقات (1249 ± 545 تيراغرام C في مكافئ ثاني أكسيد الكربون y-1)، والمخزونات (1299 ± 200 تيراغرام C في مكافئ ثاني أكسيد الكربون y-1) والانقلابات (1210 ± 405 تيراغرام C في مكافئ ثاني أكسيد الكربون y-1) يزيد من ثقتنا في أن أرصدة غازات الدفيئة الأوروبية الحالية دقيقة. ومع ذلك، لا يزال عدم اليقين كبيرًا ويفتقر إلى حد كبير إلى التقديرات الرسمية. وبالنظر إلى أن صافي الأرصدة الأوروبية للأرض والغلاف الجوي يتحدد بعدد قليل من التدفقات المهيمنة، فإن عدم اليقين في هذه المكونات الرئيسية يحتاج إلى تقدير رسمي قبل أن يتسنى بذل الجهود للحد من عدم اليقين العام. أكد نهج التقييد المزدوج أن سطح الأرض الأوروبي، بما في ذلك المياه الداخلية والمناطق الحضرية، هو مصدر صافي لثاني أكسيد الكربون وثاني أكسيد الكربون والميثان وأكسيد النيتروز. ومع ذلك، بالنسبة لجميع النظم الإيكولوجية باستثناء الأراضي الزراعية، يتجاوز الامتصاص C إطلاق C ويتم إزالة 210 ± 70 Tg Cy -1 من حرق الوقود الأحفوري من الغلاف الجوي ويتم عزله في كل من النظم الإيكولوجية المائية الأرضية والداخلية. إذا تم أخذ التكلفة "ج" لإدارة النظم الإيكولوجية في الاعتبار، فقد قُدر أن صافي امتصاص النظم الإيكولوجية سينخفض بنسبة 45 ٪ ولكنه لا يزال يشير إلى تسلسل "ج" كبير. أيضًا، عندما يتم تمديد الرصيد من ثاني أكسيد الكربون إلى غازات الدفيئة الرئيسية، يتم تعويض امتصاص الكربون من قبل النظم الإيكولوجية الأرضية والمائية بانبعاثات غازات الدفيئة. على هذا النحو، من غير المرجح أن تساهم النظم الإيكولوجية الأوروبية في التخفيف من آثار تغير المناخ.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2007 FrancePublisher:American Geophysical Union (AGU) Publicly fundedAuthors: Vuichard, Nicolas; Soussana, Jean-François, J.-F.; Ciais, Philippe; Viovy, Nicolas; +6 AuthorsVuichard, Nicolas; Soussana, Jean-François, J.-F.; Ciais, Philippe; Viovy, Nicolas; Ammann, Christof; Calanca, Pierluigi; Clifton-Brown, John; Fuhrer, Jürg; Jones, Mike; Martin, Cécile;doi: 10.1029/2005gb002611
We improved a process‐oriented biogeochemical model of carbon and nitrogen cycling in grasslands and tested it against in situ measurements of biomass and CO2 and CH4 fluxes at five European grassland sites. The new version of the model (PASIM) calculates the growth and senescence of aboveground vegetation biomass accounting for sporadic removals when the grassland is cut and for continuous removals when it is grazed. Limitations induced by high leaf area index (LAI), soil water deficits and aging of leaves are also included. We added to this a simple empirical formulation to account for the detrimental impact on vegetation of trampling and excreta by grazing animals. Finally, a more realistic methane emission module than is currently used was introduced on the basis of the quality of the animals' diet. Evaluation of this improved version of PASIM is performed at (1) Laqueuille, France, on grassland continuously grazed by cattle with two plots of intensive and extensive grazing intensities, (2) Oensingen, Switzerland, on cut grassland with two fertilized and nonfertilized plots, and (3) Carlow, Ireland, on grassland that is both cut and grazed by cattle during the growing season. In addition, we compared the modeled animal CH4 emissions with in situ measurements on cattle for two grazing intensities at the grazed grassland site of Laqueuille. Altogether, when all improvements to the PASIM model are included, we found that the new parameterizations resulted into a better fit to the observed seasonal cycle of biomass and of measured CO2 and CH4 fluxes. However, the large uncertainties in measurements of biomass and LAI make simulation of biomass dynamics difficult to make. Also simulations for cut grassland are better than for grazed swards. This work paves the way for simulating greenhouse gas fluxes over grasslands in a spatially explicit manner, in order to quantify and understand the past, present and future role of grasslands in the greenhouse gas budget of the European continent.
Institut national de... arrow_drop_down Institut national des sciences de l'Univers: HAL-INSUArticle . 2007Full-Text: https://hal.inrae.fr/hal-02667117Data sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2007Full-Text: https://hal.inrae.fr/hal-02667117Data sources: Bielefeld Academic Search Engine (BASE)Global Biogeochemical CyclesArticle . 2007 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess Routesbronze 66 citations 66 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert Institut national de... arrow_drop_down Institut national des sciences de l'Univers: HAL-INSUArticle . 2007Full-Text: https://hal.inrae.fr/hal-02667117Data sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2007Full-Text: https://hal.inrae.fr/hal-02667117Data sources: Bielefeld Academic Search Engine (BASE)Global Biogeochemical CyclesArticle . 2007 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1029/2005gb002611&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2020Embargo end date: 21 Sep 2024 FrancePublisher:Wiley Dan Zhu; Benjamin Poulter; Pierre Friedlingstein; Martin Heimann; Martin Heimann; Sebastian Lienert; Nicolas Vuichard; Stephen Sitch; Ralph F. Keeling; Wolfgang Buermann; Wolfgang Buermann; Danica Lombardozzi; Atul K. Jain; Frédéric Chevallier; Vanessa Haverd; Andy Wiltshire; Yue He; Xiangyi Li; Shushi Peng; Vivek K. Arora; Shilong Piao; Shilong Piao; Julia E. M. S. Nabel; Xuhui Wang; Philippe Ciais; Philippe Ciais; Etsushi Kato; Ning Zeng; Yilong Wang; Yilong Wang; Kai Wang;doi: 10.1111/gcb.15162 , 10.48350/153235
pmid: 32415896
AbstractChanging amplitude of the seasonal cycle of atmospheric CO2 (SCA) in the northern hemisphere is an emerging carbon cycle property. Mauna Loa (MLO) station (20°N, 156°W), which has the longest continuous northern hemisphere CO2 record, shows an increasing SCA before the 1980s (p < .01), followed by no significant change thereafter. We analyzed the potential driving factors of SCA slowing‐down, with an ensemble of dynamic global vegetation models (DGVMs) coupled with an atmospheric transport model. We found that slowing‐down of SCA at MLO is primarily explained by response of net biome productivity (NBP) to climate change, and by changes in atmospheric circulations. Through NBP, climate change increases SCA at MLO before the 1980s and decreases it afterwards. The effect of climate change on the slowing‐down of SCA at MLO is mainly exerted by intensified drought stress acting to offset the acceleration driven by CO2 fertilization. This challenges the view that CO2 fertilization is the dominant cause of emergent SCA trends at northern sites south of 40°N. The contribution of agricultural intensification on the deceleration of SCA at MLO was elusive according to land–atmosphere CO2 flux estimated by DGVMs and atmospheric inversions. Our results also show the necessity to adequately account for changing circulation patterns in understanding carbon cycle dynamics observed from atmospheric observations and in using these observations to benchmark DGVMs.
Université de Versai... arrow_drop_down Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2020Full-Text: https://hal.science/hal-02938440Data sources: Bielefeld Academic Search Engine (BASE)Institut national des sciences de l'Univers: HAL-INSUArticle . 2020Full-Text: https://hal.science/hal-02938440Data sources: Bielefeld Academic Search Engine (BASE)Global Change BiologyArticle . 2020 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1111/gcb.15162&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 19 citations 19 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert Université de Versai... arrow_drop_down Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2020Full-Text: https://hal.science/hal-02938440Data sources: Bielefeld Academic Search Engine (BASE)Institut national des sciences de l'Univers: HAL-INSUArticle . 2020Full-Text: https://hal.science/hal-02938440Data sources: Bielefeld Academic Search Engine (BASE)Global Change BiologyArticle . 2020 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1111/gcb.15162&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2023 Netherlands, GermanyPublisher:Copernicus GmbH Funded by:EC | GREEN GODS, , EC | ESM2025 +10 projectsEC| GREEN GODS ,[no funder available] ,EC| ESM2025 ,NSF| ACO: An Open CI Ecosystem to Advance Scientific Discovery (OpenCI) ,NSF| Track 1: ACCESS Resource Allocations Marketplace and Platform Services (RAMPS) ,SNSF| Climate and Environmental Physics: Modeling Global Biogeochemical Cycles in the Earth System 2021-2025 (bgcCEP20) ,NSF| INFEWS: U.S.-China: Integrated systems modeling for sustainable FEW nexus under multi-factor global changes: Innovative comparison between Yellow River and Mississippi River Basins ,UKRI| The UK Earth system modelling project ,NSF| NRT: Addressing resiliency to climate-related hazards and disasters through data-informed decision making ,NSF| Track 2: Customized Multi-tier Assistance, Training, and Computational Help (MATCH) for End User ACCESS to CI ,NSF| Track 3: COre National Ecosystem for CyberinfrasTructure (CONECT) ,UKRI| NCEO LTS-S ,NSF| Track 4: Advanced CI Coordination Ecosystem: Monitoring and Measurement ServicesHanqin Tian; Naiqing Pan; Rona L. Thompson; Josep G. Canadell; P. Suntharalingam; Pierre Regnier; Eric A. Davidson; Michael J. Prather; Philippe Ciais; Marilena Muntean; Shufen Pan; Wilfried Winiwarter; Sönke Zaehle; Feng Zhou; Robert B. Jackson; Hermann W. Bange; Sarah Berthet; Zihao Bian; Daniele Bianchi; Lex Bouwman; Erik T. Buitenhuis; G. S. Dutton; Minpeng Hu; Akihiko Ito; Atul K. Jain; Aurich Jeltsch‐Thömmes; Fortunat Joos; Sian Kou‐Giesbrecht; P. B. Krummel; Lan X; Angela Landolfi; Ronny Lauerwald; Ya Li; Chaoqun Lü; Taylor Maavara; Manfredi Manizza; Dylan B. Millet; Jens Mühle; Prabir K. Patra; Glen P. Peters; Xiaoyu Qin; Peter Raymond; Laure Resplandy; Judith A. Rosentreter; Hao Shi; Qing Sun; Daniele Tonina; Francesco N. Tubiello; Guido R. van der Werf; Nicolas Vuichard; Junjie Wang; Kelley C. Wells; Luke M. Western; Chris Wilson; Jia Yang; Yuanzhi Yao; Yongfa You; Qing Zhu;Abstract. Nitrous oxide (N2O) is a long-lived potent greenhouse gas and stratospheric ozone-depleting substance that has been accumulating in the atmosphere since the preindustrial period. The mole fraction of atmospheric N2O has increased by nearly 25 % from 270 ppb (parts per billion) in 1750 to 336 ppb in 2022, with the fastest annual growth rate since 1980 of more than 1.3 ppb yr−1 in both 2020 and 2021. According to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR6), the relative contribution of N2O to the total enhanced effective radiative forcing of greenhouse gases was 6.4 % for 1750–2022. As a core component of our global greenhouse gas assessments coordinated by the Global Carbon Project (GCP), our global N2O budget incorporates both natural and anthropogenic sources and sinks and accounts for the interactions between nitrogen additions and the biogeochemical processes that control N2O emissions. We use bottom-up (BU: inventory, statistical extrapolation of flux measurements, and process-based land and ocean modeling) and top-down (TD: atmospheric measurement-based inversion) approaches. We provide a comprehensive quantification of global N2O sources and sinks in 21 natural and anthropogenic categories in 18 regions between 1980 and 2020. We estimate that total annual anthropogenic N2O emissions have increased 40 % (or 1.9 Tg N yr−1) in the past 4 decades (1980–2020). Direct agricultural emissions in 2020 (3.9 Tg N yr−1, best estimate) represent the large majority of anthropogenic emissions, followed by other direct anthropogenic sources, including fossil fuel and industry, waste and wastewater, and biomass burning (2.1 Tg N yr−1), and indirect anthropogenic sources (1.3 Tg N yr−1) . For the year 2020, our best estimate of total BU emissions for natural and anthropogenic sources was 18.5 (lower–upper bounds: 10.6–27.0) Tg N yr−1, close to our TD estimate of 17.0 (16.6–17.4) Tg N yr−1. For the 2010–2019 period, the annual BU decadal-average emissions for both natural and anthropogenic sources were 18.2 (10.6–25.9) Tg N yr−1 and TD emissions were 17.4 (15.8–19.20) Tg N yr−1. The once top emitter Europe has reduced its emissions by 31 % since the 1980s, while those of emerging economies have grown, making China the top emitter since the 2010s. The observed atmospheric N2O concentrations in recent years have exceeded projected levels under all scenarios in the Coupled Model Intercomparison Project Phase 6 (CMIP6), underscoring the importance of reducing anthropogenic N2O emissions. To evaluate mitigation efforts and contribute to the Global Stocktake of the United Nations Framework Convention on Climate Change, we propose the establishment of a global network for monitoring and modeling N2O from the surface through to the stratosphere. The data presented in this work can be downloaded from https://doi.org/10.18160/RQ8P-2Z4R (Tian et al., 2023).
OceanRep arrow_drop_down Earth System Science Data (ESSD)Article . 2024 . Peer-reviewedLicense: CC BYData sources: Crossrefhttps://doi.org/10.5194/essd-2...Article . 2023 . Peer-reviewedLicense: CC BYData sources: CrossrefWageningen Staff PublicationsArticle . 2024License: CC BYData sources: Wageningen Staff Publicationsadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 8 citations 8 popularity Average influence Average impulse Top 10% Powered by BIP!
more_vert OceanRep arrow_drop_down Earth System Science Data (ESSD)Article . 2024 . Peer-reviewedLicense: CC BYData sources: Crossrefhttps://doi.org/10.5194/essd-2...Article . 2023 . Peer-reviewedLicense: CC BYData sources: CrossrefWageningen Staff PublicationsArticle . 2024License: CC BYData sources: Wageningen Staff Publicationsadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Boucher, Olivier; Denvil, Sébastien; Levavasseur, Guillaume; Cozic, Anne; Caubel, Arnaud; Foujols, Marie-Alice; Meurdesoif, Yann; Ghattas, Josefine; Cadule, Patricia; Ducharne, Agnès; Vuichard, Nicolas; Cheruy, Frédérique;Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.LS3MIP.IPSL.IPSL-CM6A-LR' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The IPSL-CM6A-LR climate model, released in 2017, includes the following components: atmos: LMDZ (NPv6, N96; 144 x 143 longitude/latitude; 79 levels; top level 80000 m), land: ORCHIDEE (v2.0, Water/Carbon/Energy mode), ocean: NEMO-OPA (eORCA1.3, tripolar primarily 1deg; 362 x 332 longitude/latitude; 75 levels; top grid cell 0-2 m), ocnBgchem: NEMO-PISCES, seaIce: NEMO-LIM3. The model was run by the Institut Pierre Simon Laplace, Paris 75252, France (IPSL) in native nominal resolutions: atmos: 250 km, land: 250 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2015 Germany, France, NetherlandsPublisher:Copernicus GmbH Funded by:EC | GHG EUROPEEC| GHG EUROPENicolas Vuichard; Xiuchen Wu; Xiuchen Wu; Eddy Moors; P. Ciais; N. de Noblet-Ducoudré; Pierre Cellier; Xuhui Wang; P. Di Tommasi; Christine Moureaux; Eric Larmanou; Tanguy Manise; W.W.P. Jans; Luca Vitale; Thomas Grünwald; Vincenzo Magliulo; Jan Elbers; Dominique Ripoche; Tiphaine Tallec; Eric Ceschia; Anne De Ligne; Martin Wattenbach; Benjamin Loubet; Nicolas Viovy; Christian Bernhofer;Abstract. The responses of crop functioning to changing climate and atmospheric CO2 concentration ([CO2]) could have large effects on food production, and impact carbon, water and energy fluxes, causing feedbacks to climate. To simulate the responses of temperate crops to changing climate and [CO2], accounting for the specific phenology of crops mediated by management practice, we present here the development of a process-oriented terrestrial biogeochemical model named ORCHIDEE-CROP (v0), which integrates a generic crop phenology and harvest module and a very simple parameterization of nitrogen fertilization, into the land surface model (LSM) ORCHIDEEv196, in order to simulate biophysical and biochemical interactions in croplands, as well as plant productivity and harvested yield. The model is applicable for a range of temperate crops, but it is tested here for maize and winter wheat, with the phenological parameterizations of two European varieties originating from the STICS agronomical model. We evaluate the ORCHIDEE-CROP (v0) model against eddy covariance and biometric measurements at 7 winter wheat and maize sites in Europe. The specific ecosystem variables used in the evaluation are CO2 fluxes (NEE), latent heat and sensible heat fluxes. Additional measurements of leaf area index (LAI), aboveground biomass and yield are used as well. Evaluation results reveal that ORCHIDEE-CROP (v0) reproduces the observed timing of crop development stages and the amplitude of pertaining LAI changes in contrast to ORCHIDEEv196 in which by default crops have the same phenology than grass. A near-halving of the root mean square error of LAI from 2.38 ± 0.77 to 1.08 ± 0.34 m2 m−2 is obtained between ORCHIDEEv196 and ORCHIDEE-CROP (v0) across the 7 study sites. Improved crop phenology and carbon allocation lead to a general good match between modelled and observed aboveground biomass (with a normalized root mean squared error (NRMSE) of 11.0–54.2 %), crop yield, as well as of the daily carbon and energy fluxes with NRMSE of ~9.0–20.1 and ~9.4–22.3 % for NEE, and sensible and latent heat fluxes, respectively. The model data mistfit for energy fluxes are within uncertainties of the measurements, which themselves show an incomplete energy balance closure within the range 80.6–86.3 %. The remaining discrepancies between modelled and observed LAI and other variables at specific sites are partly attributable to unrealistic representation of management events. In addition, ORCHIDEE-CROP (v0) is shown to have the ability to capture the spatial gradients of carbon and energy-related variables, such as gross primary productivity, NEE, sensible heat fluxes and latent heat fluxes, across the sites in Europe, an important requirement for future spatially explicit simulations. Further improvement of the model with an explicit parameterization of nutrition dynamics and of management, is expected to improve its predictive ability to simulate croplands in an Earth System Model.
Hyper Article en Lig... arrow_drop_down Hyper Article en LigneArticle . 2016Full-Text: https://hal.inrae.fr/hal-02635924/documentData sources: Hyper Article en LigneMémoires en Sciences de l'Information et de la CommunicationArticle . 2016Full-Text: https://hal.inrae.fr/hal-02635924/documentInstitut national des sciences de l'Univers: HAL-INSUArticle . 2016Full-Text: https://hal.science/hal-01587289Data sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2016Full-Text: https://hal.science/hal-01587289Data sources: Bielefeld Academic Search Engine (BASE)Institut national des sciences de l'Univers: HAL-INSUArticle . 2016Full-Text: https://hal.inrae.fr/hal-02635924Data sources: Bielefeld Academic Search Engine (BASE)https://doi.org/10.5194/gmdd-8...Article . 2015 . Peer-reviewedLicense: CC BYData sources: CrossrefGeoscientific Model Development (GMD)Article . 2016 . Peer-reviewedLicense: CC BYData sources: CrossrefGeoscientific Model DevelopmentArticle . 2016Data sources: DANS (Data Archiving and Networked Services)Geoscientific Model DevelopmentArticle . 2016Data sources: DANS (Data Archiving and Networked Services)INRIA a CCSD electronic archive serverArticle . 2016Data sources: INRIA a CCSD electronic archive serverWageningen Staff PublicationsArticle . 2016License: CC BYData sources: Wageningen Staff PublicationsInstitut National de la Recherche Agronomique: ProdINRAArticle . 2016License: CC-BY-ND-NCData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 57 citations 57 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert Hyper Article en Lig... arrow_drop_down Hyper Article en LigneArticle . 2016Full-Text: https://hal.inrae.fr/hal-02635924/documentData sources: Hyper Article en LigneMémoires en Sciences de l'Information et de la CommunicationArticle . 2016Full-Text: https://hal.inrae.fr/hal-02635924/documentInstitut national des sciences de l'Univers: HAL-INSUArticle . 2016Full-Text: https://hal.science/hal-01587289Data sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2016Full-Text: https://hal.science/hal-01587289Data sources: Bielefeld Academic Search Engine (BASE)Institut national des sciences de l'Univers: HAL-INSUArticle . 2016Full-Text: https://hal.inrae.fr/hal-02635924Data sources: Bielefeld Academic Search Engine (BASE)https://doi.org/10.5194/gmdd-8...Article . 2015 . Peer-reviewedLicense: CC BYData sources: CrossrefGeoscientific Model Development (GMD)Article . 2016 . Peer-reviewedLicense: CC BYData sources: CrossrefGeoscientific Model DevelopmentArticle . 2016Data sources: DANS (Data Archiving and Networked Services)Geoscientific Model DevelopmentArticle . 2016Data sources: DANS (Data Archiving and Networked Services)INRIA a CCSD electronic archive serverArticle . 2016Data sources: INRIA a CCSD electronic archive serverWageningen Staff PublicationsArticle . 2016License: CC BYData sources: Wageningen Staff PublicationsInstitut National de la Recherche Agronomique: ProdINRAArticle . 2016License: CC-BY-ND-NCData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2017Embargo end date: 01 Jan 2018 United Kingdom, Germany, Germany, Australia, Australia, Germany, Netherlands, SpainPublisher:Copernicus GmbH Funded by:EC | QUINCY, EC | LUC4C, EC | IMBALANCE-P +9 projectsEC| QUINCY ,EC| LUC4C ,EC| IMBALANCE-P ,EC| CRESCENDO ,RCN| Jordsystem-modellering av klimaforandringer i den antroposene tidsalder; Earth system modelling of climate Variations in the Anthropocene ,EC| RINGO ,EC| FIBER ,RCN| CICEP-Strategic Challenges in International Climate and Energy Policy ,NWO| The distribution and evolution of inert and reactant scalars: from the atmospheric boundary layer to continental scales ,SNSF| Geschichte der Bausteinbearbeitung, insbesondere in der westlichen Schweiz ,RCN| Integrated Carbon Observation System (ICOS)-Norway and Ocean Thematic Centre (OTC) ,EC| HELIXBronte Tilbrook; Bronte Tilbrook; Jessica N. Cross; Guido R. van der Werf; Yukihiro Nojiri; Denis Pierrot; Denis Pierrot; Arne Körtzinger; Andrew J. Watson; Nathalie Lefèvre; Nicolas Metzl; Andrew Lenton; Andrew Lenton; X. Antonio Padin; David R. Munro; Andrew C. Manning; Philippe Ciais; Leticia Barbero; Leticia Barbero; Kees Klein Goldewijk; Kees Klein Goldewijk; Markus Kautz; Ivan D. Lima; Benjamin Poulter; Benjamin Poulter; Sebastian Lienert; Sebastian Lienert; Pieter P. Tans; Oliver Andrews; George C. Hurtt; Janet J. Reimer; Ingunn Skjelvan; Peter Landschützer; Francesco N. Tubiello; Thomas A. Boden; Anthony P. Walker; Pedro M. S. Monteiro; Kim I. Currie; Robert B. Jackson; Vivek K. Arora; Meike Becker; Meike Becker; Benjamin D. Stocker; Nicolas Vuichard; Tatiana Ilyina; Richard A. Houghton; Stephen Sitch; Sönke Zaehle; Christian Rödenbeck; Dorothee C. E. Bakker; Judith Hauck; Jörg Schwinger; Julia E. M. S. Nabel; Jan Ivar Korsbakken; Frédéric Chevallier; Andy Wiltshire; Ralph F. Keeling; Catherine E Cosca; Thomas Gasser; Ingrid T. van der Laan-Luijkx; Richard Betts; Richard Betts; Shin-Ichiro Nakaoka; Ian Harris; Robbie M. Andrew; Roland Séférian; Pierre Friedlingstein; Steven van Heuven; Christopher W. Hunt; Laurent Bopp; Dan Zhu; Julia Pongratz; Gregor Rehder; Louise Chini; Nicolas Viovy; Frank J. Millero; Etsushi Kato; Benjamin Pfeil; Benjamin Pfeil; Glen P. Peters; Josep G. Canadell; Anna Peregon; Atul K. Jain; Corinne Le Quéré; Danica Lombardozzi; Vanessa Haverd; Hanqin Tian;Abstract. 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. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (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 our imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2007–2016), EFF was 9.4 ± 0.5 GtC yr−1, ELUC 1.3 ± 0.7 GtC yr−1, GATM 4.7 ± 0.1 GtC yr−1, SOCEAN 2.4 ± 0.5 GtC yr−1, and SLAND 3.0 ± 0.8 GtC yr−1, with a budget imbalance BIM of 0.6 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1. Also for 2016, ELUC was 1.3 ± 0.7 GtC yr−1, GATM was 6.1 ± 0.2 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1 and SLAND was 2.7 ± 1.0 GtC yr−1, with a small BIM of −0.3 GtC. GATM continued to be higher in 2016 compared to the past decade (2007–2016), reflecting in part the higher fossil emissions and smaller SLAND for that year consistent with El Niño conditions. The global atmospheric CO2 concentration reached 402.8 ± 0.1 ppm averaged over 2016. For 2017, preliminary data indicate a renewed growth in EFF of +2.0 % (range of 0.8 % to 3.0 %) based on national emissions projections for China, USA, 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. For 2017, initial data indicate an increase in atmospheric CO2 concentration of around 5.3 GtC (2.5 ppm), attributed to a combination of increasing emissions and receding El Niño conditions. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Quéré et al., 2016; 2015b; 2015a; 2014; 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017.
OceanRep arrow_drop_down KITopen (Karlsruhe Institute of Technologie)Article . 2018License: CC BYData sources: Bielefeld Academic Search Engine (BASE)University of East Anglia: UEA Digital RepositoryArticle . 2018License: CC BYData sources: Bielefeld Academic Search Engine (BASE)Woods Hole Open Access ServerArticle . 2018License: CC BYFull-Text: https://doi.org/10.18160/GCP-2017Data sources: Bielefeld Academic Search Engine (BASE)https://doi.org/10.5194/essd-2...Article . 2017 . Peer-reviewedLicense: CC BYData sources: CrossrefEarth System Science Data (ESSD)Article . 2018 . Peer-reviewedLicense: CC BYData sources: CrossrefEarth System Science DataOther literature type . 2018Data sources: DANS (Data Archiving and Networked Services)DANS (Data Archiving and Networked Services)Other literature type . 2018Data sources: DANS (Data Archiving and Networked Services)Recolector de Ciencia Abierta, RECOLECTAArticle . 2018 . Peer-reviewedData sources: Recolector de Ciencia Abierta, RECOLECTAWageningen Staff PublicationsArticle . 2018License: CC BYData sources: Wageningen Staff PublicationsElectronic Publication Information CenterArticle . 2017Data sources: Electronic Publication Information CenterElectronic Publication Information CenterArticle . 2018Data sources: Electronic Publication Information CenterEarth System Science Data (ESSD)Article . 2018 . Peer-reviewedData sources: European Union Open Data PortalUniversity of Bristol: Bristol ResearchArticle . 2018Data sources: Bielefeld Academic Search Engine (BASE)University of Tasmania: UTas ePrintsArticle . 2018Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 990 citations 990 popularity Top 0.1% influence Top 1% impulse Top 0.01% Powered by BIP!
visibility 24visibility views 24 download downloads 76 Powered bymore_vert OceanRep arrow_drop_down KITopen (Karlsruhe Institute of Technologie)Article . 2018License: CC BYData sources: Bielefeld Academic Search Engine (BASE)University of East Anglia: UEA Digital RepositoryArticle . 2018License: CC BYData sources: Bielefeld Academic Search Engine (BASE)Woods Hole Open Access ServerArticle . 2018License: CC BYFull-Text: https://doi.org/10.18160/GCP-2017Data sources: Bielefeld Academic Search Engine (BASE)https://doi.org/10.5194/essd-2...Article . 2017 . Peer-reviewedLicense: CC BYData sources: CrossrefEarth System Science Data (ESSD)Article . 2018 . Peer-reviewedLicense: CC BYData sources: CrossrefEarth System Science DataOther literature type . 2018Data sources: DANS (Data Archiving and Networked Services)DANS (Data Archiving and Networked Services)Other literature type . 2018Data sources: DANS (Data Archiving and Networked Services)Recolector de Ciencia Abierta, RECOLECTAArticle . 2018 . Peer-reviewedData sources: Recolector de Ciencia Abierta, RECOLECTAWageningen Staff PublicationsArticle . 2018License: CC BYData sources: Wageningen Staff PublicationsElectronic Publication Information CenterArticle . 2017Data sources: Electronic Publication Information CenterElectronic Publication Information CenterArticle . 2018Data sources: Electronic Publication Information CenterEarth System Science Data (ESSD)Article . 2018 . Peer-reviewedData sources: European Union Open Data PortalUniversity of Bristol: Bristol ResearchArticle . 2018Data sources: Bielefeld Academic Search Engine (BASE)University of Tasmania: UTas ePrintsArticle . 2018Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2020Embargo end date: 21 Sep 2024 France, GermanyPublisher:Wiley Funded by:SNSF | Climate and Environmental..., EC | 4CSNSF| Climate and Environmental Physics: Modeling Global Biogeochemical Cycles in the Earth System (bgcCEP) ,EC| 4CVivek K. Arora; Andy Wiltshire; Wei Li; Dan Zhu; Julia E. M. S. Nabel; Hui Yang; Emilie Joetzjer; Vanessa Harverd; Markus Kautz; Ana Bastos; Pierre Friedlingstein; Pierre Friedlingstein; Sebastian Lienert; Sebastian Lienert; Stephen Sitch; Peter Anthoni; Maurizio Santoro; Yilong Wang; Yuanyuan Huang; Yuanyuan Huang; Philippe Ciais; A. Arneth; Daniel S. Goll; Michael O'Sullivan; N. Vuichard;doi: 10.1111/gcb.15117 , 10.48350/153233
pmid: 32427397
AbstractGaps in our current understanding and quantification of biomass carbon stocks, particularly in tropics, lead to large uncertainty in future projections of the terrestrial carbon balance. We use the recently published GlobBiomass data set of forest above‐ground biomass (AGB) density for the year 2010, obtained from multiple remote sensing and in situ observations at 100 m spatial resolution to evaluate AGB estimated by nine dynamic global vegetation models (DGVMs). The global total forest AGB of the nine DGVMs is 365 ± 66 Pg C, the spread corresponding to the standard deviation between models, compared to 275 Pg C with an uncertainty of ~13.5% from GlobBiomass. Model‐data discrepancy in total forest AGB can be attributed to their discrepancies in the AGB density and/or forest area. While DGVMs represent the global spatial gradients of AGB density reasonably well, they only have modest ability to reproduce the regional spatial gradients of AGB density at scales below 1000 km. The 95th percentile of AGB density (AGB95) in tropics can be considered as the potential maximum of AGB density which can be reached for a given annual precipitation. GlobBiomass data show local deficits of AGB density compared to the AGB95, particularly in transitional and/or wet regions in tropics. We hypothesize that local human disturbances cause more AGB density deficits from GlobBiomass than from DGVMs, which rarely represent human disturbances. We then analyse empirical relationships between AGB density deficits and forest cover changes, population density, burned areas and livestock density. Regression analysis indicated that more than 40% of the spatial variance of AGB density deficits in South America and Africa can be explained; in Southeast Asia, these factors explain only ~25%. This result suggests TRENDY v6 DGVMs tend to underestimate biomass loss from diverse and widespread anthropogenic disturbances, and as a result overestimate turnover time in AGB.
Hyper Article en Lig... arrow_drop_down Global Change BiologyArticle . 2020 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: CrossrefKITopen (Karlsruhe Institute of Technologie)Article . 2020Data sources: Bielefeld Academic Search Engine (BASE)Institut national des sciences de l'Univers: HAL-INSUArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess Routeshybrid 28 citations 28 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert Hyper Article en Lig... arrow_drop_down Global Change BiologyArticle . 2020 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: CrossrefKITopen (Karlsruhe Institute of Technologie)Article . 2020Data sources: Bielefeld Academic Search Engine (BASE)Institut national des sciences de l'Univers: HAL-INSUArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2017 FrancePublisher:Elsevier BV Funded by:EC | IMBALANCE-PEC| IMBALANCE-PHongfang Zhao; Xiuchen Wu; F. Ruget; Nicolas Viovy; Nicolas Vuichard; Laurent Li; Jinfeng Chang; Xuhui Wang; Xuhui Wang; Philippe Ciais; Feng Zhou; Shilong Piao;Whether crop phenology changes are caused by change in managements or by climate change belongs to the category of problems known as detection-attribution. Three type of rice (early, late and single rice) in China show an average increase in Length of Growing Period (LGP) during 1991–2012: 1.0 ± 4.8 day/decade (±standard deviation across sites) for early rice, 0.2 ± 4.5 day/decade for late rice and 2.0±6.0 day/decade for single rice, based on observations from 141 long-term monitoring stations. Positive LGP trends are widespread, but only significant (P < 0.05) at 25% of early rice, 22% of late rice and 38% of single rice sites. We developed a Bayes-based optimization algorithm, and optimized five parameters controlling phenological development in a process-based crop model (ORCHIDEE-crop) for discriminating effects of managements from those of climate change on rice LGP. The results from the optimized ORCHIDEE-crop model suggest that climate change has an effect on LGP trends dependent on rice types. Climate trends have shortened LGP of early rice (−2.0 ± 5.0 day/decade), lengthened LGP of late rice (1.1 ± 5.4 day/decade) and have little impacts on LGP of single rice (−0.4 ± 5.4 day/decade). ORCHIDEE-crop simulations further show that change in transplanting date caused widespread LGP change only for early rice sites, offsetting 65% of climate change induced LGP shortening. The primary drivers of LGP change are thus different among the three types of rice. Management are predominant driver of LGP change for early and single rice. This study shows that complex regional variations of LGP can be reproduced with an optimized crop model. We further suggest that better documenting observational error and management practices can help reduce large uncertainties existed in attribution of LGP change, and future rice crop modelling in global/regional scales should consider different types of rice and variable transplanting dates in order to better account impacts of management and climate change.
Hyper Article en Lig... arrow_drop_down Institut national des sciences de l'Univers: HAL-INSUArticle . 2017Data sources: Bielefeld Academic Search Engine (BASE)École Polytechnique, Université Paris-Saclay: HALArticle . 2017Data sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2017Data sources: Bielefeld Academic Search Engine (BASE)INRIA a CCSD electronic archive serverArticle . 2017Data sources: INRIA a CCSD electronic archive serverAgricultural and Forest MeteorologyArticle . 2017 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 52 citations 52 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert Hyper Article en Lig... arrow_drop_down Institut national des sciences de l'Univers: HAL-INSUArticle . 2017Data sources: Bielefeld Academic Search Engine (BASE)École Polytechnique, Université Paris-Saclay: HALArticle . 2017Data sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2017Data sources: Bielefeld Academic Search Engine (BASE)INRIA a CCSD electronic archive serverArticle . 2017Data sources: INRIA a CCSD electronic archive serverAgricultural and Forest MeteorologyArticle . 2017 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal , Other literature type 2013 United Kingdom, France, United KingdomPublisher:Springer Science and Business Media LLC Funded by:EC | COMBINE, EC | IS-ENESEC| COMBINE ,EC| IS-ENESRachid Benshila; Jean-Philippe Duvel; Patricia Cadule; Sébastien Masson; N. de Noblet; François Lott; Sophie Szopa; Christian Ethé; Laurent Fairhead; Marie-Alice Foujols; S. Parouty; James Lloyd; C. Levy; Marion Marchand; Didier Swingedouw; Sonia Labetoulle; Josefine Ghattas; C. Talandier; C. Talandier; Pierre Friedlingstein; Pierre Friedlingstein; Gurvan Madec; Franck Lefèvre; Eric Guilyardi; Abderrahmane Idelkadi; Martial Mancip; Didier Hauglustaine; Yves Balkanski; Juliette Mignot; David Cugnet; Masa Kageyama; Francis Codron; Z. X. Li; Nicolas Vuichard; Olivier Aumont; Sandrine Bony; Anne Cozic; S. Flavoni; Sylvie Joussaume; Marie-Pierre Lefebvre; Patrick Brockmann; Catherine Rio; Frédérique Cheruy; Thierry Fichefet; Laurent Bopp; Pascale Braconnot; Hugo Bellenger; Yann Meurdesoif; Jean-Louis Dufresne; Slimane Bekki; Frédéric Hourdin; Olivier Marti; Gerhard Krinner; A. Lahellec; L. Guez; Jan Polcher; Ionela Musat; Pascal Terray; Michael Schulz; Jean-Yves Grandpeix; Nicolas Viovy; Sébastien Denvil; Arnaud Caubel;We present the global general circulation model IPSL-CM5 developed to study the long-term response of the climate system to natural and anthropogenic forcings as part of the 5th Phase of the Coupled Model Intercomparison Project (CMIP5). This model includes an interactive carbon cycle, a representation of tropospheric and stratospheric chemistry, and a comprehensive representation of aerosols. As it represents the principal dynamical, physical, and bio-geochemical processes relevant to the climate system, it may be referred to as an Earth System Model. However, the IPSL-CM5 model may be used in a multitude of configurations associated with different boundary conditions and with a range of complexities in terms of processes and interactions. This paper presents an overview of the different model components and explains how they were coupled and used to simulate historical climate changes over the past 150 years and different scenarios of future climate change. A single version of the IPSL-CM5 model (IPSL-CM5A-LR) was used to provide climate projections associated with different socio-economic scenarios, including the different Representative Concentration Pathways considered by CMIP5 and several scenarios from the Special Report on Emission Scenarios considered by CMIP3. Results suggest that the magnitude of global warming projections primarily depends on the socio-economic scenario considered, that there is potential for an aggressive mitigation policy to limit global warming to about two degrees, and that the behavior of some components of the climate system such as the Arctic sea ice and the Atlantic Meridional Overturning Circulation may change drastically by the end of the twenty-first century in the case of a no climate policy scenario. Although the magnitude of regional temperature and precipitation changes depends fairly linearly on the magnitude of the projected global warming (and thus on the scenario considered), the geographical pattern of these changes is strikingly similar for the different scenarios. The representation of atmospheric physical processes in the model is shown to strongly influence the simulated climate variability and both the magnitude and pattern of the projected climate changes.
Hyper Article en Lig... arrow_drop_down ArchiMer - Institutional Archive of IfremerOther literature type . 2013Data sources: ArchiMer - Institutional Archive of IfremerUniversité Grenoble Alpes: HALArticle . 2013Full-Text: https://hal.science/hal-00794170Data sources: Bielefeld Academic Search Engine (BASE)Université de Bretagne Occidentale: HALArticle . 2013Full-Text: https://hal.science/hal-00794170Data sources: Bielefeld Academic Search Engine (BASE)INRIA a CCSD electronic archive serverArticle . 2013Data sources: INRIA a CCSD electronic archive serverNatural Environment Research Council: NERC Open Research ArchiveArticle . 2013Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 1K citations 1,443 popularity Top 0.1% influence Top 0.1% impulse Top 0.01% Powered by BIP!
visibility 83visibility views 83 download downloads 32 Powered bymore_vert Hyper Article en Lig... arrow_drop_down ArchiMer - Institutional Archive of IfremerOther literature type . 2013Data sources: ArchiMer - Institutional Archive of IfremerUniversité Grenoble Alpes: HALArticle . 2013Full-Text: https://hal.science/hal-00794170Data sources: Bielefeld Academic Search Engine (BASE)Université de Bretagne Occidentale: HALArticle . 2013Full-Text: https://hal.science/hal-00794170Data sources: Bielefeld Academic Search Engine (BASE)INRIA a CCSD electronic archive serverArticle . 2013Data sources: INRIA a CCSD electronic archive serverNatural Environment Research Council: NERC Open Research ArchiveArticle . 2013Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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description Publicationkeyboard_double_arrow_right Other literature type , Article 2012Publisher:OpenAlex Funded by:EC | LUISEEC| LUISESebastiaan Luyssaert; Gwénaël Abril; R. J. Andres; David Bastviken; Valentin Bellassen; P. Bergamaschi; Philippe Bousquet; Frédéric Chevallier; Philippe Ciais; M. Corazza; René Dechow; Karl‐Heinz Erb; Giuseppe Etiope; Audrey Fortems-Cheiney; Giacomo Grassi; J. Hartman; Martin Jung; Juliette Lathière; Annalea Lohila; Nils Moosdorf; Sylvestre Njakou Djomo; Juliane Otto; Dario Papale; Wouter Peters; P. Peylin; Peter A. Raymond; Christian Rödenbeck; Sanna Saarnio; Ernst‐Detlef Schulze; Sophie Szopa; Rona L. Thompson; Pieter Johannes Verkerk; Nicolas Vuichard; R. Wang; M. Wattenbach; Sönke Zaehle;Résumé. À l'échelle mondiale, les écosystèmes terrestres ont absorbé environ 30 % des émissions anthropiques au cours de la période 20007-2007 et les gradients interhémisphériques indiquent qu'une fraction importante de la séquestration du carbone terrestre doit se situer au nord de l'équateur. Nous présentons une compilation du bilan de CO2, CO, CH4 et N2O de l'Europe suivant une approche à double contrainte dans laquelle (1) un bilan terrestre dérivé principalement des inventaires de carbone des écosystèmes et (2) un bilan terrestre dérivé des mesures de flux sont confrontés à (3) le bilan atmosphérique dérivé de l'inversion informée par les mesures des concentrations atmosphériques de GES. Un bon accord entre les bilans de GES basés sur les flux (1249 ± 545 Tg C en CO2-eq y−1), les inventaires (1299 ± 200 Tg C en CO2-eq y−1) et les inversions (1210 ± 405 Tg C en CO2-eq y−1) augmente notre confiance que les bilans de GES européens actuels sont exacts. Cependant, l'incertitude reste grande et manque largement d'estimations formelles. Étant donné que les bilans nets terre-atmosphère européens sont déterminés par quelques flux dominants, l'incertitude de ces composantes clés doit être formellement estimée avant que des efforts puissent être déployés pour réduire l'incertitude globale. L'approche à double contrainte a confirmé que la surface terrestre européenne, y compris les eaux intérieures et les zones urbaines, est une source nette de CO2, CO, CH4 et N2O. Cependant, pour tous les écosystèmes à l'exception des terres cultivées, l'absorption de C dépasse les rejets de C et ces 210 ± 70 Tg C y−1 provenant de la combustion de combustibles fossiles sont retirés de l'atmosphère et séquestrés dans les écosystèmes aquatiques terrestres et intérieurs. Si le coût du carbone pour la gestion des écosystèmes est pris en compte, l'absorption nette des écosystèmes a été estimée à diminuer de 45 %, mais indique toujours une séquestration substantielle du carbone. En outre, lorsque l'équilibre est étendu du CO2 vers les principaux GES, l'absorption de C par les écosystèmes terrestres et aquatiques est compensée par les émissions de GES. En tant que tels, les écosystèmes européens sont peu susceptibles de contribuer à atténuer les effets du changement climatique. Resumen. A nivel mundial, los ecosistemas terrestres han absorbido alrededor del 30% de las emisiones antropogénicas durante el período 20007-2007 y los gradientes interhemisféricos indican que una fracción significativa del secuestro de carbono terrestre debe estar al norte del Ecuador. Presentamos una recopilación del balance de CO2, CO, CH4 y N2O de Europa siguiendo un enfoque de doble restricción en el que (1) un balance terrestre derivado principalmente de los inventarios de carbono del ecosistema y (2) un balance terrestre derivado de las mediciones de flujo se enfrentan con (3) el balance atmosférico derivado de la inversión informada por las mediciones de las concentraciones atmosféricas de GEI. Una buena concordancia entre los balances de GEI basados en flujos (1249 ± 545 Tg C en CO2-eq y−1), inventarios (1299 ± 200 Tg C en CO2-eq y−1) e inversiones (1210 ± 405 Tg C en CO2-eq y−1) aumenta nuestra confianza en que los balances de GEI europeos actuales son precisos. Sin embargo, la incertidumbre sigue siendo grande y en gran medida carece de estimaciones formales. Dado que los balances netos tierra-atmósfera europeos están determinados por unos pocos flujos dominantes, la incertidumbre de estos componentes clave debe estimarse formalmente antes de poder realizar esfuerzos para reducir la incertidumbre general. El enfoque de doble restricción confirmó que la superficie terrestre europea, incluidas las aguas interiores y las zonas urbanas, es una fuente neta de CO2, CO, CH4 y N2O. Sin embargo, para todos los ecosistemas, excepto las tierras de cultivo, la absorción de C excede la liberación de C y tales 210 ± 70 Tg C y−1 de la quema de combustibles fósiles se eliminan de la atmósfera y se secuestran en los ecosistemas acuáticos terrestres y continentales. Si se tiene en cuenta el costo de C para la gestión de los ecosistemas, se estimó que la absorción neta de los ecosistemas disminuiría en un 45%, pero aún indica un secuestro sustancial de C. Además, cuando el equilibrio se extiende desde el CO2 hacia los principales GEI, la absorción de C por los ecosistemas terrestres y acuáticos se compensa con las emisiones de GEI. Como tal, es poco probable que los ecosistemas europeos contribuyan a mitigar los efectos del cambio climático. Abstract. Globally, terrestrial ecosystems have absorbed about 30% of anthropogenic emissions over the period 20007–2007 and inter-hemispheric gradients indicate that a significant fraction of terrestrial carbon sequestration must be north of the Equator. We present a compilation of the CO2, CO, CH4 and N2O balance of Europe following a dual constraint approach in which (1) a land-based balance derived mainly from ecosystem carbon inventories and (2) a land-based balance derived from flux measurements are confronted with (3) the atmospheric-based balance derived from inversion informed by measurements of atmospheric GHG concentrations. Good agreement between the GHG balances based on fluxes (1249 ± 545 Tg C in CO2-eq y−1), inventories (1299 ± 200 Tg C in CO2-eq y−1) and inversions (1210 ± 405 Tg C in CO2-eq y−1) increases our confidence that current European GHG balances are accurate. However, the uncertainty remains large and largely lacks formal estimates. Given that European net land-atmosphere balances are determined by a few dominant fluxes, the uncertainty of these key components needs to be formally estimated before efforts could be made to reduce the overall uncertainty. The dual-constraint approach confirmed that the European land surface, including inland waters and urban areas, is a net source for CO2, CO, CH4 and N2O. However, for all ecosystems except croplands, C uptake exceeds C release and us such 210 ± 70 Tg C y−1 from fossil fuel burning is removed from the atmosphere and sequestered in both terrestrial and inland aquatic ecosystems. If the C cost for ecosystem management is taken into account, the net uptake of ecosystems was estimated to decrease by 45% but still indicates substantial C-sequestration. Also, when the balance is extended from CO2 towards the main GHGs, C-uptake by terrestrial and aquatic ecosystems is compensated for by emissions of GHGs. As such the European ecosystems are unlikely to contribute to mitigating the effects of climate change. الخلاصة. على الصعيد العالمي، امتصت النظم الإيكولوجية الأرضية حوالي 30 ٪ من الانبعاثات البشرية المنشأ خلال الفترة 20007-2007 وتشير التدرجات بين نصف الكرة الأرضية إلى أن جزءًا كبيرًا من عزل الكربون الأرضي يجب أن يكون شمال خط الاستواء. نقدم مجموعة من توازن ثاني أكسيد الكربون وثاني أكسيد الكربون والميثان وأكسيد النيتروز في أوروبا باتباع نهج القيد المزدوج الذي (1) يواجه فيه التوازن البري المستمد بشكل أساسي من قوائم جرد الكربون في النظام الإيكولوجي و (2) التوازن البري المستمد من قياسات التدفق (3) التوازن الجوي المستمد من الانعكاس المستنير بقياسات تركيزات غازات الدفيئة في الغلاف الجوي. الاتفاق الجيد بين أرصدة غازات الدفيئة على أساس التدفقات (1249 ± 545 تيراغرام C في مكافئ ثاني أكسيد الكربون y-1)، والمخزونات (1299 ± 200 تيراغرام C في مكافئ ثاني أكسيد الكربون y-1) والانقلابات (1210 ± 405 تيراغرام C في مكافئ ثاني أكسيد الكربون y-1) يزيد من ثقتنا في أن أرصدة غازات الدفيئة الأوروبية الحالية دقيقة. ومع ذلك، لا يزال عدم اليقين كبيرًا ويفتقر إلى حد كبير إلى التقديرات الرسمية. وبالنظر إلى أن صافي الأرصدة الأوروبية للأرض والغلاف الجوي يتحدد بعدد قليل من التدفقات المهيمنة، فإن عدم اليقين في هذه المكونات الرئيسية يحتاج إلى تقدير رسمي قبل أن يتسنى بذل الجهود للحد من عدم اليقين العام. أكد نهج التقييد المزدوج أن سطح الأرض الأوروبي، بما في ذلك المياه الداخلية والمناطق الحضرية، هو مصدر صافي لثاني أكسيد الكربون وثاني أكسيد الكربون والميثان وأكسيد النيتروز. ومع ذلك، بالنسبة لجميع النظم الإيكولوجية باستثناء الأراضي الزراعية، يتجاوز الامتصاص C إطلاق C ويتم إزالة 210 ± 70 Tg Cy -1 من حرق الوقود الأحفوري من الغلاف الجوي ويتم عزله في كل من النظم الإيكولوجية المائية الأرضية والداخلية. إذا تم أخذ التكلفة "ج" لإدارة النظم الإيكولوجية في الاعتبار، فقد قُدر أن صافي امتصاص النظم الإيكولوجية سينخفض بنسبة 45 ٪ ولكنه لا يزال يشير إلى تسلسل "ج" كبير. أيضًا، عندما يتم تمديد الرصيد من ثاني أكسيد الكربون إلى غازات الدفيئة الرئيسية، يتم تعويض امتصاص الكربون من قبل النظم الإيكولوجية الأرضية والمائية بانبعاثات غازات الدفيئة. على هذا النحو، من غير المرجح أن تساهم النظم الإيكولوجية الأوروبية في التخفيف من آثار تغير المناخ.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2007 FrancePublisher:American Geophysical Union (AGU) Publicly fundedAuthors: Vuichard, Nicolas; Soussana, Jean-François, J.-F.; Ciais, Philippe; Viovy, Nicolas; +6 AuthorsVuichard, Nicolas; Soussana, Jean-François, J.-F.; Ciais, Philippe; Viovy, Nicolas; Ammann, Christof; Calanca, Pierluigi; Clifton-Brown, John; Fuhrer, Jürg; Jones, Mike; Martin, Cécile;doi: 10.1029/2005gb002611
We improved a process‐oriented biogeochemical model of carbon and nitrogen cycling in grasslands and tested it against in situ measurements of biomass and CO2 and CH4 fluxes at five European grassland sites. The new version of the model (PASIM) calculates the growth and senescence of aboveground vegetation biomass accounting for sporadic removals when the grassland is cut and for continuous removals when it is grazed. Limitations induced by high leaf area index (LAI), soil water deficits and aging of leaves are also included. We added to this a simple empirical formulation to account for the detrimental impact on vegetation of trampling and excreta by grazing animals. Finally, a more realistic methane emission module than is currently used was introduced on the basis of the quality of the animals' diet. Evaluation of this improved version of PASIM is performed at (1) Laqueuille, France, on grassland continuously grazed by cattle with two plots of intensive and extensive grazing intensities, (2) Oensingen, Switzerland, on cut grassland with two fertilized and nonfertilized plots, and (3) Carlow, Ireland, on grassland that is both cut and grazed by cattle during the growing season. In addition, we compared the modeled animal CH4 emissions with in situ measurements on cattle for two grazing intensities at the grazed grassland site of Laqueuille. Altogether, when all improvements to the PASIM model are included, we found that the new parameterizations resulted into a better fit to the observed seasonal cycle of biomass and of measured CO2 and CH4 fluxes. However, the large uncertainties in measurements of biomass and LAI make simulation of biomass dynamics difficult to make. Also simulations for cut grassland are better than for grazed swards. This work paves the way for simulating greenhouse gas fluxes over grasslands in a spatially explicit manner, in order to quantify and understand the past, present and future role of grasslands in the greenhouse gas budget of the European continent.
Institut national de... arrow_drop_down Institut national des sciences de l'Univers: HAL-INSUArticle . 2007Full-Text: https://hal.inrae.fr/hal-02667117Data sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2007Full-Text: https://hal.inrae.fr/hal-02667117Data sources: Bielefeld Academic Search Engine (BASE)Global Biogeochemical CyclesArticle . 2007 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess Routesbronze 66 citations 66 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert Institut national de... arrow_drop_down Institut national des sciences de l'Univers: HAL-INSUArticle . 2007Full-Text: https://hal.inrae.fr/hal-02667117Data sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2007Full-Text: https://hal.inrae.fr/hal-02667117Data sources: Bielefeld Academic Search Engine (BASE)Global Biogeochemical CyclesArticle . 2007 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2020Embargo end date: 21 Sep 2024 FrancePublisher:Wiley Dan Zhu; Benjamin Poulter; Pierre Friedlingstein; Martin Heimann; Martin Heimann; Sebastian Lienert; Nicolas Vuichard; Stephen Sitch; Ralph F. Keeling; Wolfgang Buermann; Wolfgang Buermann; Danica Lombardozzi; Atul K. Jain; Frédéric Chevallier; Vanessa Haverd; Andy Wiltshire; Yue He; Xiangyi Li; Shushi Peng; Vivek K. Arora; Shilong Piao; Shilong Piao; Julia E. M. S. Nabel; Xuhui Wang; Philippe Ciais; Philippe Ciais; Etsushi Kato; Ning Zeng; Yilong Wang; Yilong Wang; Kai Wang;doi: 10.1111/gcb.15162 , 10.48350/153235
pmid: 32415896
AbstractChanging amplitude of the seasonal cycle of atmospheric CO2 (SCA) in the northern hemisphere is an emerging carbon cycle property. Mauna Loa (MLO) station (20°N, 156°W), which has the longest continuous northern hemisphere CO2 record, shows an increasing SCA before the 1980s (p < .01), followed by no significant change thereafter. We analyzed the potential driving factors of SCA slowing‐down, with an ensemble of dynamic global vegetation models (DGVMs) coupled with an atmospheric transport model. We found that slowing‐down of SCA at MLO is primarily explained by response of net biome productivity (NBP) to climate change, and by changes in atmospheric circulations. Through NBP, climate change increases SCA at MLO before the 1980s and decreases it afterwards. The effect of climate change on the slowing‐down of SCA at MLO is mainly exerted by intensified drought stress acting to offset the acceleration driven by CO2 fertilization. This challenges the view that CO2 fertilization is the dominant cause of emergent SCA trends at northern sites south of 40°N. The contribution of agricultural intensification on the deceleration of SCA at MLO was elusive according to land–atmosphere CO2 flux estimated by DGVMs and atmospheric inversions. Our results also show the necessity to adequately account for changing circulation patterns in understanding carbon cycle dynamics observed from atmospheric observations and in using these observations to benchmark DGVMs.
Université de Versai... arrow_drop_down Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2020Full-Text: https://hal.science/hal-02938440Data sources: Bielefeld Academic Search Engine (BASE)Institut national des sciences de l'Univers: HAL-INSUArticle . 2020Full-Text: https://hal.science/hal-02938440Data sources: Bielefeld Academic Search Engine (BASE)Global Change BiologyArticle . 2020 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 19 citations 19 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert Université de Versai... arrow_drop_down Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2020Full-Text: https://hal.science/hal-02938440Data sources: Bielefeld Academic Search Engine (BASE)Institut national des sciences de l'Univers: HAL-INSUArticle . 2020Full-Text: https://hal.science/hal-02938440Data sources: Bielefeld Academic Search Engine (BASE)Global Change BiologyArticle . 2020 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1111/gcb.15162&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2023 Netherlands, GermanyPublisher:Copernicus GmbH Funded by:EC | GREEN GODS, , EC | ESM2025 +10 projectsEC| GREEN GODS ,[no funder available] ,EC| ESM2025 ,NSF| ACO: An Open CI Ecosystem to Advance Scientific Discovery (OpenCI) ,NSF| Track 1: ACCESS Resource Allocations Marketplace and Platform Services (RAMPS) ,SNSF| Climate and Environmental Physics: Modeling Global Biogeochemical Cycles in the Earth System 2021-2025 (bgcCEP20) ,NSF| INFEWS: U.S.-China: Integrated systems modeling for sustainable FEW nexus under multi-factor global changes: Innovative comparison between Yellow River and Mississippi River Basins ,UKRI| The UK Earth system modelling project ,NSF| NRT: Addressing resiliency to climate-related hazards and disasters through data-informed decision making ,NSF| Track 2: Customized Multi-tier Assistance, Training, and Computational Help (MATCH) for End User ACCESS to CI ,NSF| Track 3: COre National Ecosystem for CyberinfrasTructure (CONECT) ,UKRI| NCEO LTS-S ,NSF| Track 4: Advanced CI Coordination Ecosystem: Monitoring and Measurement ServicesHanqin Tian; Naiqing Pan; Rona L. Thompson; Josep G. Canadell; P. Suntharalingam; Pierre Regnier; Eric A. Davidson; Michael J. Prather; Philippe Ciais; Marilena Muntean; Shufen Pan; Wilfried Winiwarter; Sönke Zaehle; Feng Zhou; Robert B. Jackson; Hermann W. Bange; Sarah Berthet; Zihao Bian; Daniele Bianchi; Lex Bouwman; Erik T. Buitenhuis; G. S. Dutton; Minpeng Hu; Akihiko Ito; Atul K. Jain; Aurich Jeltsch‐Thömmes; Fortunat Joos; Sian Kou‐Giesbrecht; P. B. Krummel; Lan X; Angela Landolfi; Ronny Lauerwald; Ya Li; Chaoqun Lü; Taylor Maavara; Manfredi Manizza; Dylan B. Millet; Jens Mühle; Prabir K. Patra; Glen P. Peters; Xiaoyu Qin; Peter Raymond; Laure Resplandy; Judith A. Rosentreter; Hao Shi; Qing Sun; Daniele Tonina; Francesco N. Tubiello; Guido R. van der Werf; Nicolas Vuichard; Junjie Wang; Kelley C. Wells; Luke M. Western; Chris Wilson; Jia Yang; Yuanzhi Yao; Yongfa You; Qing Zhu;Abstract. Nitrous oxide (N2O) is a long-lived potent greenhouse gas and stratospheric ozone-depleting substance that has been accumulating in the atmosphere since the preindustrial period. The mole fraction of atmospheric N2O has increased by nearly 25 % from 270 ppb (parts per billion) in 1750 to 336 ppb in 2022, with the fastest annual growth rate since 1980 of more than 1.3 ppb yr−1 in both 2020 and 2021. According to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR6), the relative contribution of N2O to the total enhanced effective radiative forcing of greenhouse gases was 6.4 % for 1750–2022. As a core component of our global greenhouse gas assessments coordinated by the Global Carbon Project (GCP), our global N2O budget incorporates both natural and anthropogenic sources and sinks and accounts for the interactions between nitrogen additions and the biogeochemical processes that control N2O emissions. We use bottom-up (BU: inventory, statistical extrapolation of flux measurements, and process-based land and ocean modeling) and top-down (TD: atmospheric measurement-based inversion) approaches. We provide a comprehensive quantification of global N2O sources and sinks in 21 natural and anthropogenic categories in 18 regions between 1980 and 2020. We estimate that total annual anthropogenic N2O emissions have increased 40 % (or 1.9 Tg N yr−1) in the past 4 decades (1980–2020). Direct agricultural emissions in 2020 (3.9 Tg N yr−1, best estimate) represent the large majority of anthropogenic emissions, followed by other direct anthropogenic sources, including fossil fuel and industry, waste and wastewater, and biomass burning (2.1 Tg N yr−1), and indirect anthropogenic sources (1.3 Tg N yr−1) . For the year 2020, our best estimate of total BU emissions for natural and anthropogenic sources was 18.5 (lower–upper bounds: 10.6–27.0) Tg N yr−1, close to our TD estimate of 17.0 (16.6–17.4) Tg N yr−1. For the 2010–2019 period, the annual BU decadal-average emissions for both natural and anthropogenic sources were 18.2 (10.6–25.9) Tg N yr−1 and TD emissions were 17.4 (15.8–19.20) Tg N yr−1. The once top emitter Europe has reduced its emissions by 31 % since the 1980s, while those of emerging economies have grown, making China the top emitter since the 2010s. The observed atmospheric N2O concentrations in recent years have exceeded projected levels under all scenarios in the Coupled Model Intercomparison Project Phase 6 (CMIP6), underscoring the importance of reducing anthropogenic N2O emissions. To evaluate mitigation efforts and contribute to the Global Stocktake of the United Nations Framework Convention on Climate Change, we propose the establishment of a global network for monitoring and modeling N2O from the surface through to the stratosphere. The data presented in this work can be downloaded from https://doi.org/10.18160/RQ8P-2Z4R (Tian et al., 2023).
OceanRep arrow_drop_down Earth System Science Data (ESSD)Article . 2024 . Peer-reviewedLicense: CC BYData sources: Crossrefhttps://doi.org/10.5194/essd-2...Article . 2023 . Peer-reviewedLicense: CC BYData sources: CrossrefWageningen Staff PublicationsArticle . 2024License: CC BYData sources: Wageningen Staff Publicationsadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 8 citations 8 popularity Average influence Average impulse Top 10% Powered by BIP!
more_vert OceanRep arrow_drop_down Earth System Science Data (ESSD)Article . 2024 . Peer-reviewedLicense: CC BYData sources: Crossrefhttps://doi.org/10.5194/essd-2...Article . 2023 . Peer-reviewedLicense: CC BYData sources: CrossrefWageningen Staff PublicationsArticle . 2024License: CC BYData sources: Wageningen Staff Publicationsadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Boucher, Olivier; Denvil, Sébastien; Levavasseur, Guillaume; Cozic, Anne; Caubel, Arnaud; Foujols, Marie-Alice; Meurdesoif, Yann; Ghattas, Josefine; Cadule, Patricia; Ducharne, Agnès; Vuichard, Nicolas; Cheruy, Frédérique;Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.LS3MIP.IPSL.IPSL-CM6A-LR' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The IPSL-CM6A-LR climate model, released in 2017, includes the following components: atmos: LMDZ (NPv6, N96; 144 x 143 longitude/latitude; 79 levels; top level 80000 m), land: ORCHIDEE (v2.0, Water/Carbon/Energy mode), ocean: NEMO-OPA (eORCA1.3, tripolar primarily 1deg; 362 x 332 longitude/latitude; 75 levels; top grid cell 0-2 m), ocnBgchem: NEMO-PISCES, seaIce: NEMO-LIM3. The model was run by the Institut Pierre Simon Laplace, Paris 75252, France (IPSL) in native nominal resolutions: atmos: 250 km, land: 250 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2015 Germany, France, NetherlandsPublisher:Copernicus GmbH Funded by:EC | GHG EUROPEEC| GHG EUROPENicolas Vuichard; Xiuchen Wu; Xiuchen Wu; Eddy Moors; P. Ciais; N. de Noblet-Ducoudré; Pierre Cellier; Xuhui Wang; P. Di Tommasi; Christine Moureaux; Eric Larmanou; Tanguy Manise; W.W.P. Jans; Luca Vitale; Thomas Grünwald; Vincenzo Magliulo; Jan Elbers; Dominique Ripoche; Tiphaine Tallec; Eric Ceschia; Anne De Ligne; Martin Wattenbach; Benjamin Loubet; Nicolas Viovy; Christian Bernhofer;Abstract. The responses of crop functioning to changing climate and atmospheric CO2 concentration ([CO2]) could have large effects on food production, and impact carbon, water and energy fluxes, causing feedbacks to climate. To simulate the responses of temperate crops to changing climate and [CO2], accounting for the specific phenology of crops mediated by management practice, we present here the development of a process-oriented terrestrial biogeochemical model named ORCHIDEE-CROP (v0), which integrates a generic crop phenology and harvest module and a very simple parameterization of nitrogen fertilization, into the land surface model (LSM) ORCHIDEEv196, in order to simulate biophysical and biochemical interactions in croplands, as well as plant productivity and harvested yield. The model is applicable for a range of temperate crops, but it is tested here for maize and winter wheat, with the phenological parameterizations of two European varieties originating from the STICS agronomical model. We evaluate the ORCHIDEE-CROP (v0) model against eddy covariance and biometric measurements at 7 winter wheat and maize sites in Europe. The specific ecosystem variables used in the evaluation are CO2 fluxes (NEE), latent heat and sensible heat fluxes. Additional measurements of leaf area index (LAI), aboveground biomass and yield are used as well. Evaluation results reveal that ORCHIDEE-CROP (v0) reproduces the observed timing of crop development stages and the amplitude of pertaining LAI changes in contrast to ORCHIDEEv196 in which by default crops have the same phenology than grass. A near-halving of the root mean square error of LAI from 2.38 ± 0.77 to 1.08 ± 0.34 m2 m−2 is obtained between ORCHIDEEv196 and ORCHIDEE-CROP (v0) across the 7 study sites. Improved crop phenology and carbon allocation lead to a general good match between modelled and observed aboveground biomass (with a normalized root mean squared error (NRMSE) of 11.0–54.2 %), crop yield, as well as of the daily carbon and energy fluxes with NRMSE of ~9.0–20.1 and ~9.4–22.3 % for NEE, and sensible and latent heat fluxes, respectively. The model data mistfit for energy fluxes are within uncertainties of the measurements, which themselves show an incomplete energy balance closure within the range 80.6–86.3 %. The remaining discrepancies between modelled and observed LAI and other variables at specific sites are partly attributable to unrealistic representation of management events. In addition, ORCHIDEE-CROP (v0) is shown to have the ability to capture the spatial gradients of carbon and energy-related variables, such as gross primary productivity, NEE, sensible heat fluxes and latent heat fluxes, across the sites in Europe, an important requirement for future spatially explicit simulations. Further improvement of the model with an explicit parameterization of nutrition dynamics and of management, is expected to improve its predictive ability to simulate croplands in an Earth System Model.
Hyper Article en Lig... arrow_drop_down Hyper Article en LigneArticle . 2016Full-Text: https://hal.inrae.fr/hal-02635924/documentData sources: Hyper Article en LigneMémoires en Sciences de l'Information et de la CommunicationArticle . 2016Full-Text: https://hal.inrae.fr/hal-02635924/documentInstitut national des sciences de l'Univers: HAL-INSUArticle . 2016Full-Text: https://hal.science/hal-01587289Data sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2016Full-Text: https://hal.science/hal-01587289Data sources: Bielefeld Academic Search Engine (BASE)Institut national des sciences de l'Univers: HAL-INSUArticle . 2016Full-Text: https://hal.inrae.fr/hal-02635924Data sources: Bielefeld Academic Search Engine (BASE)https://doi.org/10.5194/gmdd-8...Article . 2015 . Peer-reviewedLicense: CC BYData sources: CrossrefGeoscientific Model Development (GMD)Article . 2016 . Peer-reviewedLicense: CC BYData sources: CrossrefGeoscientific Model DevelopmentArticle . 2016Data sources: DANS (Data Archiving and Networked Services)Geoscientific Model DevelopmentArticle . 2016Data sources: DANS (Data Archiving and Networked Services)INRIA a CCSD electronic archive serverArticle . 2016Data sources: INRIA a CCSD electronic archive serverWageningen Staff PublicationsArticle . 2016License: CC BYData sources: Wageningen Staff PublicationsInstitut National de la Recherche Agronomique: ProdINRAArticle . 2016License: CC-BY-ND-NCData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 57 citations 57 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert Hyper Article en Lig... arrow_drop_down Hyper Article en LigneArticle . 2016Full-Text: https://hal.inrae.fr/hal-02635924/documentData sources: Hyper Article en LigneMémoires en Sciences de l'Information et de la CommunicationArticle . 2016Full-Text: https://hal.inrae.fr/hal-02635924/documentInstitut national des sciences de l'Univers: HAL-INSUArticle . 2016Full-Text: https://hal.science/hal-01587289Data sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2016Full-Text: https://hal.science/hal-01587289Data sources: Bielefeld Academic Search Engine (BASE)Institut national des sciences de l'Univers: HAL-INSUArticle . 2016Full-Text: https://hal.inrae.fr/hal-02635924Data sources: Bielefeld Academic Search Engine (BASE)https://doi.org/10.5194/gmdd-8...Article . 2015 . Peer-reviewedLicense: CC BYData sources: CrossrefGeoscientific Model Development (GMD)Article . 2016 . Peer-reviewedLicense: CC BYData sources: CrossrefGeoscientific Model DevelopmentArticle . 2016Data sources: DANS (Data Archiving and Networked Services)Geoscientific Model DevelopmentArticle . 2016Data sources: DANS (Data Archiving and Networked Services)INRIA a CCSD electronic archive serverArticle . 2016Data sources: INRIA a CCSD electronic archive serverWageningen Staff PublicationsArticle . 2016License: CC BYData sources: Wageningen Staff PublicationsInstitut National de la Recherche Agronomique: ProdINRAArticle . 2016License: CC-BY-ND-NCData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2017Embargo end date: 01 Jan 2018 United Kingdom, Germany, Germany, Australia, Australia, Germany, Netherlands, SpainPublisher:Copernicus GmbH Funded by:EC | QUINCY, EC | LUC4C, EC | IMBALANCE-P +9 projectsEC| QUINCY ,EC| LUC4C ,EC| IMBALANCE-P ,EC| CRESCENDO ,RCN| Jordsystem-modellering av klimaforandringer i den antroposene tidsalder; Earth system modelling of climate Variations in the Anthropocene ,EC| RINGO ,EC| FIBER ,RCN| CICEP-Strategic Challenges in International Climate and Energy Policy ,NWO| The distribution and evolution of inert and reactant scalars: from the atmospheric boundary layer to continental scales ,SNSF| Geschichte der Bausteinbearbeitung, insbesondere in der westlichen Schweiz ,RCN| Integrated Carbon Observation System (ICOS)-Norway and Ocean Thematic Centre (OTC) ,EC| HELIXBronte Tilbrook; Bronte Tilbrook; Jessica N. Cross; Guido R. van der Werf; Yukihiro Nojiri; Denis Pierrot; Denis Pierrot; Arne Körtzinger; Andrew J. Watson; Nathalie Lefèvre; Nicolas Metzl; Andrew Lenton; Andrew Lenton; X. Antonio Padin; David R. Munro; Andrew C. Manning; Philippe Ciais; Leticia Barbero; Leticia Barbero; Kees Klein Goldewijk; Kees Klein Goldewijk; Markus Kautz; Ivan D. Lima; Benjamin Poulter; Benjamin Poulter; Sebastian Lienert; Sebastian Lienert; Pieter P. Tans; Oliver Andrews; George C. Hurtt; Janet J. Reimer; Ingunn Skjelvan; Peter Landschützer; Francesco N. Tubiello; Thomas A. Boden; Anthony P. Walker; Pedro M. S. Monteiro; Kim I. Currie; Robert B. Jackson; Vivek K. Arora; Meike Becker; Meike Becker; Benjamin D. Stocker; Nicolas Vuichard; Tatiana Ilyina; Richard A. Houghton; Stephen Sitch; Sönke Zaehle; Christian Rödenbeck; Dorothee C. E. Bakker; Judith Hauck; Jörg Schwinger; Julia E. M. S. Nabel; Jan Ivar Korsbakken; Frédéric Chevallier; Andy Wiltshire; Ralph F. Keeling; Catherine E Cosca; Thomas Gasser; Ingrid T. van der Laan-Luijkx; Richard Betts; Richard Betts; Shin-Ichiro Nakaoka; Ian Harris; Robbie M. Andrew; Roland Séférian; Pierre Friedlingstein; Steven van Heuven; Christopher W. Hunt; Laurent Bopp; Dan Zhu; Julia Pongratz; Gregor Rehder; Louise Chini; Nicolas Viovy; Frank J. Millero; Etsushi Kato; Benjamin Pfeil; Benjamin Pfeil; Glen P. Peters; Josep G. Canadell; Anna Peregon; Atul K. Jain; Corinne Le Quéré; Danica Lombardozzi; Vanessa Haverd; Hanqin Tian;Abstract. 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. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (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 our imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2007–2016), EFF was 9.4 ± 0.5 GtC yr−1, ELUC 1.3 ± 0.7 GtC yr−1, GATM 4.7 ± 0.1 GtC yr−1, SOCEAN 2.4 ± 0.5 GtC yr−1, and SLAND 3.0 ± 0.8 GtC yr−1, with a budget imbalance BIM of 0.6 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1. Also for 2016, ELUC was 1.3 ± 0.7 GtC yr−1, GATM was 6.1 ± 0.2 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1 and SLAND was 2.7 ± 1.0 GtC yr−1, with a small BIM of −0.3 GtC. GATM continued to be higher in 2016 compared to the past decade (2007–2016), reflecting in part the higher fossil emissions and smaller SLAND for that year consistent with El Niño conditions. The global atmospheric CO2 concentration reached 402.8 ± 0.1 ppm averaged over 2016. For 2017, preliminary data indicate a renewed growth in EFF of +2.0 % (range of 0.8 % to 3.0 %) based on national emissions projections for China, USA, 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. For 2017, initial data indicate an increase in atmospheric CO2 concentration of around 5.3 GtC (2.5 ppm), attributed to a combination of increasing emissions and receding El Niño conditions. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Quéré et al., 2016; 2015b; 2015a; 2014; 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017.
OceanRep arrow_drop_down KITopen (Karlsruhe Institute of Technologie)Article . 2018License: CC BYData sources: Bielefeld Academic Search Engine (BASE)University of East Anglia: UEA Digital RepositoryArticle . 2018License: CC BYData sources: Bielefeld Academic Search Engine (BASE)Woods Hole Open Access ServerArticle . 2018License: CC BYFull-Text: https://doi.org/10.18160/GCP-2017Data sources: Bielefeld Academic Search Engine (BASE)https://doi.org/10.5194/essd-2...Article . 2017 . Peer-reviewedLicense: CC BYData sources: CrossrefEarth System Science Data (ESSD)Article . 2018 . Peer-reviewedLicense: CC BYData sources: CrossrefEarth System Science DataOther literature type . 2018Data sources: DANS (Data Archiving and Networked Services)DANS (Data Archiving and Networked Services)Other literature type . 2018Data sources: DANS (Data Archiving and Networked Services)Recolector de Ciencia Abierta, RECOLECTAArticle . 2018 . Peer-reviewedData sources: Recolector de Ciencia Abierta, RECOLECTAWageningen Staff PublicationsArticle . 2018License: CC BYData sources: Wageningen Staff PublicationsElectronic Publication Information CenterArticle . 2017Data sources: Electronic Publication Information CenterElectronic Publication Information CenterArticle . 2018Data sources: Electronic Publication Information CenterEarth System Science Data (ESSD)Article . 2018 . Peer-reviewedData sources: European Union Open Data PortalUniversity of Bristol: Bristol ResearchArticle . 2018Data sources: Bielefeld Academic Search Engine (BASE)University of Tasmania: UTas ePrintsArticle . 2018Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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visibility 24visibility views 24 download downloads 76 Powered bymore_vert OceanRep arrow_drop_down KITopen (Karlsruhe Institute of Technologie)Article . 2018License: CC BYData sources: Bielefeld Academic Search Engine (BASE)University of East Anglia: UEA Digital RepositoryArticle . 2018License: CC BYData sources: Bielefeld Academic Search Engine (BASE)Woods Hole Open Access ServerArticle . 2018License: CC BYFull-Text: https://doi.org/10.18160/GCP-2017Data sources: Bielefeld Academic Search Engine (BASE)https://doi.org/10.5194/essd-2...Article . 2017 . Peer-reviewedLicense: CC BYData sources: CrossrefEarth System Science Data (ESSD)Article . 2018 . Peer-reviewedLicense: CC BYData sources: CrossrefEarth System Science DataOther literature type . 2018Data sources: DANS (Data Archiving and Networked Services)DANS (Data Archiving and Networked Services)Other literature type . 2018Data sources: DANS (Data Archiving and Networked Services)Recolector de Ciencia Abierta, RECOLECTAArticle . 2018 . Peer-reviewedData sources: Recolector de Ciencia Abierta, RECOLECTAWageningen Staff PublicationsArticle . 2018License: CC BYData sources: Wageningen Staff PublicationsElectronic Publication Information CenterArticle . 2017Data sources: Electronic Publication Information CenterElectronic Publication Information CenterArticle . 2018Data sources: Electronic Publication Information CenterEarth System Science Data (ESSD)Article . 2018 . Peer-reviewedData sources: European Union Open Data PortalUniversity of Bristol: Bristol ResearchArticle . 2018Data sources: Bielefeld Academic Search Engine (BASE)University of Tasmania: UTas ePrintsArticle . 2018Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2020Embargo end date: 21 Sep 2024 France, GermanyPublisher:Wiley Funded by:SNSF | Climate and Environmental..., EC | 4CSNSF| Climate and Environmental Physics: Modeling Global Biogeochemical Cycles in the Earth System (bgcCEP) ,EC| 4CVivek K. Arora; Andy Wiltshire; Wei Li; Dan Zhu; Julia E. M. S. Nabel; Hui Yang; Emilie Joetzjer; Vanessa Harverd; Markus Kautz; Ana Bastos; Pierre Friedlingstein; Pierre Friedlingstein; Sebastian Lienert; Sebastian Lienert; Stephen Sitch; Peter Anthoni; Maurizio Santoro; Yilong Wang; Yuanyuan Huang; Yuanyuan Huang; Philippe Ciais; A. Arneth; Daniel S. Goll; Michael O'Sullivan; N. Vuichard;doi: 10.1111/gcb.15117 , 10.48350/153233
pmid: 32427397
AbstractGaps in our current understanding and quantification of biomass carbon stocks, particularly in tropics, lead to large uncertainty in future projections of the terrestrial carbon balance. We use the recently published GlobBiomass data set of forest above‐ground biomass (AGB) density for the year 2010, obtained from multiple remote sensing and in situ observations at 100 m spatial resolution to evaluate AGB estimated by nine dynamic global vegetation models (DGVMs). The global total forest AGB of the nine DGVMs is 365 ± 66 Pg C, the spread corresponding to the standard deviation between models, compared to 275 Pg C with an uncertainty of ~13.5% from GlobBiomass. Model‐data discrepancy in total forest AGB can be attributed to their discrepancies in the AGB density and/or forest area. While DGVMs represent the global spatial gradients of AGB density reasonably well, they only have modest ability to reproduce the regional spatial gradients of AGB density at scales below 1000 km. The 95th percentile of AGB density (AGB95) in tropics can be considered as the potential maximum of AGB density which can be reached for a given annual precipitation. GlobBiomass data show local deficits of AGB density compared to the AGB95, particularly in transitional and/or wet regions in tropics. We hypothesize that local human disturbances cause more AGB density deficits from GlobBiomass than from DGVMs, which rarely represent human disturbances. We then analyse empirical relationships between AGB density deficits and forest cover changes, population density, burned areas and livestock density. Regression analysis indicated that more than 40% of the spatial variance of AGB density deficits in South America and Africa can be explained; in Southeast Asia, these factors explain only ~25%. This result suggests TRENDY v6 DGVMs tend to underestimate biomass loss from diverse and widespread anthropogenic disturbances, and as a result overestimate turnover time in AGB.
Hyper Article en Lig... arrow_drop_down Global Change BiologyArticle . 2020 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: CrossrefKITopen (Karlsruhe Institute of Technologie)Article . 2020Data sources: Bielefeld Academic Search Engine (BASE)Institut national des sciences de l'Univers: HAL-INSUArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess Routeshybrid 28 citations 28 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert Hyper Article en Lig... arrow_drop_down Global Change BiologyArticle . 2020 . Peer-reviewedLicense: Wiley Online Library User AgreementData sources: CrossrefKITopen (Karlsruhe Institute of Technologie)Article . 2020Data sources: Bielefeld Academic Search Engine (BASE)Institut national des sciences de l'Univers: HAL-INSUArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2020Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2017 FrancePublisher:Elsevier BV Funded by:EC | IMBALANCE-PEC| IMBALANCE-PHongfang Zhao; Xiuchen Wu; F. Ruget; Nicolas Viovy; Nicolas Vuichard; Laurent Li; Jinfeng Chang; Xuhui Wang; Xuhui Wang; Philippe Ciais; Feng Zhou; Shilong Piao;Whether crop phenology changes are caused by change in managements or by climate change belongs to the category of problems known as detection-attribution. Three type of rice (early, late and single rice) in China show an average increase in Length of Growing Period (LGP) during 1991–2012: 1.0 ± 4.8 day/decade (±standard deviation across sites) for early rice, 0.2 ± 4.5 day/decade for late rice and 2.0±6.0 day/decade for single rice, based on observations from 141 long-term monitoring stations. Positive LGP trends are widespread, but only significant (P < 0.05) at 25% of early rice, 22% of late rice and 38% of single rice sites. We developed a Bayes-based optimization algorithm, and optimized five parameters controlling phenological development in a process-based crop model (ORCHIDEE-crop) for discriminating effects of managements from those of climate change on rice LGP. The results from the optimized ORCHIDEE-crop model suggest that climate change has an effect on LGP trends dependent on rice types. Climate trends have shortened LGP of early rice (−2.0 ± 5.0 day/decade), lengthened LGP of late rice (1.1 ± 5.4 day/decade) and have little impacts on LGP of single rice (−0.4 ± 5.4 day/decade). ORCHIDEE-crop simulations further show that change in transplanting date caused widespread LGP change only for early rice sites, offsetting 65% of climate change induced LGP shortening. The primary drivers of LGP change are thus different among the three types of rice. Management are predominant driver of LGP change for early and single rice. This study shows that complex regional variations of LGP can be reproduced with an optimized crop model. We further suggest that better documenting observational error and management practices can help reduce large uncertainties existed in attribution of LGP change, and future rice crop modelling in global/regional scales should consider different types of rice and variable transplanting dates in order to better account impacts of management and climate change.
Hyper Article en Lig... arrow_drop_down Institut national des sciences de l'Univers: HAL-INSUArticle . 2017Data sources: Bielefeld Academic Search Engine (BASE)École Polytechnique, Université Paris-Saclay: HALArticle . 2017Data sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2017Data sources: Bielefeld Academic Search Engine (BASE)INRIA a CCSD electronic archive serverArticle . 2017Data sources: INRIA a CCSD electronic archive serverAgricultural and Forest MeteorologyArticle . 2017 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 52 citations 52 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert Hyper Article en Lig... arrow_drop_down Institut national des sciences de l'Univers: HAL-INSUArticle . 2017Data sources: Bielefeld Academic Search Engine (BASE)École Polytechnique, Université Paris-Saclay: HALArticle . 2017Data sources: Bielefeld Academic Search Engine (BASE)Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQArticle . 2017Data sources: Bielefeld Academic Search Engine (BASE)INRIA a CCSD electronic archive serverArticle . 2017Data sources: INRIA a CCSD electronic archive serverAgricultural and Forest MeteorologyArticle . 2017 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal , Other literature type 2013 United Kingdom, France, United KingdomPublisher:Springer Science and Business Media LLC Funded by:EC | COMBINE, EC | IS-ENESEC| COMBINE ,EC| IS-ENESRachid Benshila; Jean-Philippe Duvel; Patricia Cadule; Sébastien Masson; N. de Noblet; François Lott; Sophie Szopa; Christian Ethé; Laurent Fairhead; Marie-Alice Foujols; S. Parouty; James Lloyd; C. Levy; Marion Marchand; Didier Swingedouw; Sonia Labetoulle; Josefine Ghattas; C. Talandier; C. Talandier; Pierre Friedlingstein; Pierre Friedlingstein; Gurvan Madec; Franck Lefèvre; Eric Guilyardi; Abderrahmane Idelkadi; Martial Mancip; Didier Hauglustaine; Yves Balkanski; Juliette Mignot; David Cugnet; Masa Kageyama; Francis Codron; Z. X. Li; Nicolas Vuichard; Olivier Aumont; Sandrine Bony; Anne Cozic; S. Flavoni; Sylvie Joussaume; Marie-Pierre Lefebvre; Patrick Brockmann; Catherine Rio; Frédérique Cheruy; Thierry Fichefet; Laurent Bopp; Pascale Braconnot; Hugo Bellenger; Yann Meurdesoif; Jean-Louis Dufresne; Slimane Bekki; Frédéric Hourdin; Olivier Marti; Gerhard Krinner; A. Lahellec; L. Guez; Jan Polcher; Ionela Musat; Pascal Terray; Michael Schulz; Jean-Yves Grandpeix; Nicolas Viovy; Sébastien Denvil; Arnaud Caubel;We present the global general circulation model IPSL-CM5 developed to study the long-term response of the climate system to natural and anthropogenic forcings as part of the 5th Phase of the Coupled Model Intercomparison Project (CMIP5). This model includes an interactive carbon cycle, a representation of tropospheric and stratospheric chemistry, and a comprehensive representation of aerosols. As it represents the principal dynamical, physical, and bio-geochemical processes relevant to the climate system, it may be referred to as an Earth System Model. However, the IPSL-CM5 model may be used in a multitude of configurations associated with different boundary conditions and with a range of complexities in terms of processes and interactions. This paper presents an overview of the different model components and explains how they were coupled and used to simulate historical climate changes over the past 150 years and different scenarios of future climate change. A single version of the IPSL-CM5 model (IPSL-CM5A-LR) was used to provide climate projections associated with different socio-economic scenarios, including the different Representative Concentration Pathways considered by CMIP5 and several scenarios from the Special Report on Emission Scenarios considered by CMIP3. Results suggest that the magnitude of global warming projections primarily depends on the socio-economic scenario considered, that there is potential for an aggressive mitigation policy to limit global warming to about two degrees, and that the behavior of some components of the climate system such as the Arctic sea ice and the Atlantic Meridional Overturning Circulation may change drastically by the end of the twenty-first century in the case of a no climate policy scenario. Although the magnitude of regional temperature and precipitation changes depends fairly linearly on the magnitude of the projected global warming (and thus on the scenario considered), the geographical pattern of these changes is strikingly similar for the different scenarios. The representation of atmospheric physical processes in the model is shown to strongly influence the simulated climate variability and both the magnitude and pattern of the projected climate changes.
Hyper Article en Lig... arrow_drop_down ArchiMer - Institutional Archive of IfremerOther literature type . 2013Data sources: ArchiMer - Institutional Archive of IfremerUniversité Grenoble Alpes: HALArticle . 2013Full-Text: https://hal.science/hal-00794170Data sources: Bielefeld Academic Search Engine (BASE)Université de Bretagne Occidentale: HALArticle . 2013Full-Text: https://hal.science/hal-00794170Data sources: Bielefeld Academic Search Engine (BASE)INRIA a CCSD electronic archive serverArticle . 2013Data sources: INRIA a CCSD electronic archive serverNatural Environment Research Council: NERC Open Research ArchiveArticle . 2013Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s00382-012-1636-1&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 1K citations 1,443 popularity Top 0.1% influence Top 0.1% impulse Top 0.01% Powered by BIP!
visibility 83visibility views 83 download downloads 32 Powered bymore_vert Hyper Article en Lig... arrow_drop_down ArchiMer - Institutional Archive of IfremerOther literature type . 2013Data sources: ArchiMer - Institutional Archive of IfremerUniversité Grenoble Alpes: HALArticle . 2013Full-Text: https://hal.science/hal-00794170Data sources: Bielefeld Academic Search Engine (BASE)Université de Bretagne Occidentale: HALArticle . 2013Full-Text: https://hal.science/hal-00794170Data sources: Bielefeld Academic Search Engine (BASE)INRIA a CCSD electronic archive serverArticle . 2013Data sources: INRIA a CCSD electronic archive serverNatural Environment Research Council: NERC Open Research ArchiveArticle . 2013Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s00382-012-1636-1&type=result"></script>'); --> </script>
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