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75 results on '"Climatic Research Unit"'

1. A Basis for Forecasting the Arctic Sea Ice over a Few Months to Many Years.

Author: UNIVERSITY OF EAST ANGLIA NORWICH (ENGLAND) CLIMATIC RESEARCH UNIT, Lamb,H H, UNIVERSITY OF EAST ANGLIA NORWICH (ENGLAND) CLIMATIC RESEARCH UNIT, and Lamb,H H
Abstract: An 80-year set of sea-ice data has been collected and digitized, and work is in progress to verify this data set. Principal component analysis has been used to identify 'typical' mean sea level (MSL) pressure anomaly patterns and their temporal variations, and these have been correlated with long series of sea ice indices for various regions. Time series analysis of these sea ice and MSL pressure data has revealed characteristic time scales of variation, as well as significant long-term trends. In addition, studies have been made of various mechanisms which may have been responsible for the fluctuations in the atmospheric circulation and sea ice. (Author)
Published: 1979

2. Global and Hemispheric Temperature Anomalies: Land and Marine Instrumental Records (1850 - 2015)

Author: Briffa, K. [Climatic Research Unit (CRU), University of East Anglia, Norwich, United Kingdom]
Published: 2016
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3. Climate system research

Author: Kelly, P [East Anglia Univ., Norwich (UK). Climatic Research Unit]
Published: 1990
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4. A small climate-amplifying effect of climate-carbon cycle feedback

Author: Xuanze Zhang, Yiqi Luo, Kun Huang, Philippe Ciais, Wei Zhao, Xiaogu Zheng, Zhonglei Wang, Yongqiang Zhang, Ying-Ping Wang, Peter Rayner, Jing Tian, Shilong Piao, Jianyang Xia, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-ATC (ICOS-ATC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), This study was funded by the National Key Research and Development Program of China (2017YFA0604603), the CAS Pioneer Talent Program, and the National Key Research and Development Program of China (2016YFA0602501). X.Z.Z. was also sponsored by the National Natural Science Foundation of China (42001019) and the Shanghai Sailing Program (19YF1413100). Y.P.W. was supported by the National Environmental Science Program (climate change and earth system science). P.C. acknowledges support from the European Research Council Synergy grant ERC-2013-SyG-610028 IMBALANCE-P. We gratefully thank Dr. Pierre Friedlingstein for providing constructive comments. We acknowledge the following data providers and model developers: the Global Carbon Project, the University of East Anglia Climatic Research Unit (CRU), the NASA Goddard Institute for Space Studies, the NOAA, and Berkeley Earth. We also gratefully thank Drs Chris Jones and Vivek Arora for providing the outputs of 11 C4MIP and nine CMIP5 models., and European Project: 610028,EC:FP7:ERC,ERC-2013-SyG,IMBALANCE-P(2014)
Subjects: 010504 meteorology & atmospheric sciences, Scale (ratio), Science, General Physics and Astronomy, 010502 geochemistry & geophysics, 01 natural sciences, 7. Clean energy, General Biochemistry, Genetics and Molecular Biology, Article, Carbon cycle, Projection and prediction, symbols.namesake, Control theory, Feedback analysis, Sensitivity (control systems), [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Climate and Earth system modelling, 0105 earth and related environmental sciences, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Multidisciplinary, General Chemistry, Function (mathematics), Feedback loop, Earth system science, 13. Climate action, Fourier analysis, symbols, Environmental science
Abstract: The climate-carbon cycle feedback is one of the most important climate-amplifying feedbacks of the Earth system, and is quantified as a function of carbon-concentration feedback parameter (β) and carbon-climate feedback parameter (γ). However, the global climate-amplifying effect from this feedback loop (determined by the gain factor, g) has not been quantified from observations. Here we apply a Fourier analysis-based carbon cycle feedback framework to the reconstructed records from 1850 to 2017 and 1000 to 1850 to estimate β and γ. We show that the β-feedback varies by less than 10% with an average of 3.22 ± 0.32 GtC ppm−1 for 1880–2017, whereas the γ-feedback increases from −33 ± 14 GtC K−1 on a decadal scale to −122 ± 60 GtC K−1 on a centennial scale for 1000–1850. Feedback analysis further reveals that the current amplification effect from the carbon cycle feedback is small (g is 0.01 ± 0.05), which is much lower than the estimates by the advanced Earth system models (g is 0.09 ± 0.04 for the historical period and is 0.15 ± 0.08 for the RCP8.5 scenario), implying that the future allowable CO2 emissions could be 9 ± 7% more. Therefore, our findings provide new insights about the strength of climate-carbon cycle feedback and about observational constraints on models for projecting future climate., How to curb climate change is uncertain, in part because determination of allowable emissions depends on models with low accuracy. Here the authors re-analyze climate-carbon feedbacks and find that CO2 emissions could be 9 ± 7% higher and still meet Paris Agreement goals.
Published: 2021

5. Indian Ocean Dipole influence on Indian summer monsoon and ENSO: A review

Author: Satyaban B. Ratna, K. P. Sooraj, Pascal Terray, Swadhin K. Behera, Syam Sankar, Annalisa Cherchi, Istituto di Scienze dell'Atmosfera e del Clima [Bologna] (ISAC), National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), Océan et variabilité du climat (VARCLIM), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Climatic Research Unit [Norwich] (CRU), University of East Anglia [Norwich] (UEA), Cochin University of Science and Technology (CUSAT), Indian Institute of Tropical Meteorology (IITM), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Jasti Chowdary, Anant Parekh, and C. Gnanaseelan
Subjects: air-sea coupling, projections, Indian Ocean Dipole, Forcing (mathematics), coupled climate models, remote forcing, Indian ocean, El Niño Southern Oscillation, Indian summer monsoon, [SDU]Sciences of the Universe [physics], General Circulation Model, Climatology, biases, Environmental science, Indian summer monsoon rainfall, ENSO, Teleconnection
Abstract: International audience; The Indian Ocean Dipole (IOD) is one of the dominant modes of variability of the tropical Indian Ocean and it has been suggested to have a crucial role in the teleconnection between the Indian summer monsoon and El Niño Southern Oscillation (ENSO). The main ideas at the base of the influence of the IOD on the ENSO-monsoon teleconnection include the possibility that it may strengthen summer rainfall over India, as well as the opposite, and also that it may produce a remote forcing on ENSO itself. In the future, the IOD is projected to increase in frequency and amplitude with mean conditions mimicking the characteristics of its positive phase. Still, state-of-the-art global climate models have large biases in representing mean state and variability of both IOD and ISM, with potential consequences for their future projections. However, the characteristics of the IOD and ENSO are likely to continue in a future warmer world, with a persistence of their linkage.
Published: 2021

6. Heterozygous Variants in KMT2E Cause a Spectrum of Neurodevelopmental Disorders and Epilepsy

Author: Anne H. O’Donnell-Luria, Lynn S. Pais, Víctor Faundes, Jordan C. Wood, Abigail Sveden, Victor Luria, Rami Abou Jamra, Andrea Accogli, Kimberly Amburgey, Britt Marie Anderlid, Silvia Azzarello-Burri, Alice A. Basinger, Claudia Bianchini, Lynne M. Bird, Rebecca Buchert, Wilfrid Carre, Sophia Ceulemans, Perrine Charles, Helen Cox, Lisa Culliton, Aurora Currò, Florence Demurger, James J. Dowling, Benedicte Duban-Bedu, Christèle Dubourg, Saga Elise Eiset, Luis F. Escobar, Alessandra Ferrarini, Tobias B. Haack, Mona Hashim, Solveig Heide, Katherine L. Helbig, Ingo Helbig, Raul Heredia, Delphine Héron, Bertrand Isidor, Amy R. Jonasson, Pascal Joset, Boris Keren, Fernando Kok, Hester Y. Kroes, Alinoë Lavillaureix, Xin Lu, Saskia M. Maas, Gustavo H.B. Maegawa, Carlo L.M. Marcelis, Paul R. Mark, Marcelo R. Masruha, Heather M. McLaughlin, Kirsty McWalter, Esther U. Melchinger, Saadet Mercimek-Andrews, Caroline Nava, Manuela Pendziwiat, Richard Person, Gian Paolo Ramelli, Luiza L.P. Ramos, Anita Rauch, Caitlin Reavey, Alessandra Renieri, Angelika Rieß, Amarilis Sanchez-Valle, Shifteh Sattar, Carol Saunders, Niklas Schwarz, Thomas Smol, Myriam Srour, Katharina Steindl, Steffen Syrbe, Jenny C. Taylor, Aida Telegrafi, Isabelle Thiffault, Doris A. Trauner, Helio van der Linden, Silvana van Koningsbruggen, Laurent Villard, Ida Vogel, Julie Vogt, Yvonne G. Weber, Ingrid M. Wentzensen, Elysa Widjaja, Jaroslav Zak, Samantha Baxter, Siddharth Banka, Lance H. Rodan, Jeremy F. McRae, Stephen Clayton, Tomas W. Fitzgerald, Joanna Kaplanis, Elena Prigmore, Diana Rajan, Alejandro Sifrim, Stuart Aitken, Nadia Akawi, Mohsan Alvi, Kirsty Ambridge, Daniel M. Barrett, Tanya Bayzetinova, Philip Jones, Wendy D. Jones, Daniel King, Netravathi Krishnappa, Laura E. Mason, Tarjinder Singh, Adrian R. Tivey, Munaza Ahmed, Uruj Anjum, Hayley Archer, Ruth Armstrong, Jana Awada, Meena Balasubramanian, Diana Baralle, Angela Barnicoat, Paul Batstone, David Baty, Chris Bennett, Jonathan Berg, Birgitta Bernhard, A. Paul Bevan, Maria Bitner-Glindzicz, Edward Blair, Moira Blyth, David Bohanna, Louise Bourdon, David Bourn, Lisa Bradley, Angela Brady, Simon Brent, Carole Brewer, Kate Brunstrom, David J. Bunyan, John Burn, Natalie Canham, Bruce Castle, Kate Chandler, Elena Chatzimichali, Deirdre Cilliers, Angus Clarke, Susan Clasper, Jill Clayton-Smith, Virginia Clowes, Andrea Coates, Trevor Cole, Irina Colgiu, Amanda Collins, Morag N. Collinson, Fiona Connell, Nicola Cooper, Lara Cresswell, Gareth Cross, Yanick Crow, Mariella D’Alessandro, Tabib Dabir, Rosemarie Davidson, Sally Davies, Dylan de Vries, John Dean, Charu Deshpande, Gemma Devlin, Abhijit Dixit, Angus Dobbie, Alan Donaldson, Dian Donnai, Deirdre Donnelly, Carina Donnelly, Angela Douglas, Sofia Douzgou, Alexis Duncan, Jacqueline Eason, Sian Ellard, Ian Ellis, Frances Elmslie, Karenza Evans, Sarah Everest, Tina Fendick, Richard Fisher, Frances Flinter, Nicola Foulds, Andrew Fry, Alan Fryer, Carol Gardiner, Lorraine Gaunt, Neeti Ghali, Richard Gibbons, Harinder Gill, Judith Goodship, David Goudie, Emma Gray, Andrew Green, Philip Greene, Lynn Greenhalgh, Susan Gribble, Rachel Harrison, Lucy Harrison, Victoria Harrison, Rose Hawkins, Liu He, Stephen Hellens, Alex Henderson, Sarah Hewitt, Lucy Hildyard, Emma Hobson, Simon Holden, Muriel Holder, Susan Holder, Georgina Hollingsworth, Tessa Homfray, Mervyn Humphreys, Jane Hurst, Ben Hutton, Stuart Ingram, Melita Irving, Lily Islam, Andrew Jackson, Joanna Jarvis, Lucy Jenkins, Diana Johnson, Elizabeth Jones, Dragana Josifova, Shelagh Joss, Beckie Kaemba, Sandra Kazembe, Rosemary Kelsell, Bronwyn Kerr, Helen Kingston, Usha Kini, Esther Kinning, Gail Kirby, Claire Kirk, Emma Kivuva, Alison Kraus, Dhavendra Kumar, V. K. Ajith Kumar, Katherine Lachlan, Wayne Lam, Anne Lampe, Caroline Langman, Melissa Lees, Derek Lim, Cheryl Longman, Gordon Lowther, Sally A. Lynch, Alex Magee, Eddy Maher, Alison Male, Sahar Mansour, Karen Marks, Katherine Martin, Una Maye, Emma McCann, Vivienne McConnell, Meriel McEntagart, Ruth McGowan, Kirsten McKay, Shane McKee, Dominic J. McMullan, Susan McNerlan, Catherine McWilliam, Sarju Mehta, Kay Metcalfe, Anna Middleton, Zosia Miedzybrodzka, Emma Miles, Shehla Mohammed, Tara Montgomery, David Moore, Sian Morgan, Jenny Morton, Hood Mugalaasi, Victoria Murday, Helen Murphy, Swati Naik, Andrea Nemeth, Louise Nevitt, Ruth Newbury-Ecob, Andrew Norman, Rosie O’Shea, Caroline Ogilvie, Kai-Ren Ong, Soo-Mi Park, Michael J. Parker, Chirag Patel, Joan Paterson, Stewart Payne, Daniel Perrett, Julie Phipps, Daniela T. Pilz, Martin Pollard, Caroline Pottinger, Joanna Poulton, Norman Pratt, Katrina Prescott, Sue Price, Abigail Pridham, Annie Procter, Hellen Purnell, Oliver Quarrell, Nicola Ragge, Raheleh Rahbari, Josh Randall, Julia Rankin, Lucy Raymond, Debbie Rice, Leema Robert, Eileen Roberts, Jonathan Roberts, Paul Roberts, Gillian Roberts, Alison Ross, Elisabeth Rosser, Anand Saggar, Shalaka Samant, Julian Sampson, Richard Sandford, Ajoy Sarkar, Susann Schweiger, Richard Scott, Ingrid Scurr, Ann Selby, Anneke Seller, Cheryl Sequeira, Nora Shannon, Saba Sharif, Charles Shaw-Smith, Emma Shearing, Debbie Shears, Eamonn Sheridan, Ingrid Simonic, Roldan Singzon, Zara Skitt, Audrey Smith, Kath Smith, Sarah Smithson, Linda Sneddon, Miranda Splitt, Miranda Squires, Fiona Stewart, Helen Stewart, Volker Straub, Mohnish Suri, Vivienne Sutton, Ganesh Jawahar Swaminathan, Elizabeth Sweeney, Kate Tatton-Brown, Cat Taylor, Rohan Taylor, Mark Tein, I. Karen Temple, Jenny Thomson, Marc Tischkowitz, Susan Tomkins, Audrey Torokwa, Becky Treacy, Claire Turner, Peter Turnpenny, Carolyn Tysoe, Anthony Vandersteen, Vinod Varghese, Pradeep Vasudevan, Parthiban Vijayarangakannan, Emma Wakeling, Sarah Wallwark, Jonathon Waters, Astrid Weber, Diana Wellesley, Margo Whiteford, Sara Widaa, Sarah Wilcox, Emily Wilkinson, Denise Williams, Nicola Williams, Louise Wilson, Geoff Woods, Christopher Wragg, Michael Wright, Laura Yates, Michael Yau, Chris Nellåker, Michael Parker, Helen V. Firth, Caroline F. Wright, David R. FitzPatrick, Jeffrey C. Barrett, Matthew E. Hurles, Department of Medicine 1, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Center for Medical Genetics, Istituto di Scienze e Tecnologie della Cognizione, Consiglio Nazionale delle Ricerche (ISTC, CNR), Istituto di Scienze e Tecnologie della Cognizione, Station biologique de Roscoff [Roscoff] (SBR), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Génétique médicale [Centre Hospitalier de Vannes], Centre hospitalier Bretagne Atlantique (Morbihan) (CHBA), Department of Pediatrics, University of Michigan [Ann Arbor], University of Michigan System-University of Michigan System, Centre de Génétique Chromosomique [Hôpital Saint Vincent de Paul], Hôpital Saint Vincent de Paul-Groupement des Hôpitaux de l'Institut Catholique de Lille (GHICL), Université catholique de Lille (UCL)-Université catholique de Lille (UCL), Institut de Génétique et Développement de Rennes (IGDR), Université de Rennes (UR)-Centre National de la Recherche Scientifique (CNRS)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Service de génétique médicale, Centre Hospitalier Universitaire Vaudois [Lausanne] (CHUV), Institute of Human Genetics, Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM)-Helmholtz Zentrum München = German Research Center for Environmental Health, Groupe de Recherche Clinique : Déficience Intellectuelle et Autisme (GRC), Université Pierre et Marie Curie - Paris 6 (UPMC), Children’s Hospital of Philadelphia (CHOP ), Service de Génétique Médicale, Centre hospitalier universitaire de Nantes (CHU Nantes), Department of Public Health Sciences, Karolinska Institutet [Stockholm], Department of Molecular and Human Genetics, Baylor College of Medicine (BCM), Baylor University-Baylor University, Institute of Medical Genetics, Universität Zürich [Zürich] = University of Zurich (UZH), Università degli Studi di Camerino = University of Camerino (UNICAM), Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), University of Oxford, GeneDx [Gaithersburg, MD, USA], Department of Clinical Genetics (Academic Medical Center, University of Amsterdam), VU University Medical Center [Amsterdam], Marseille medical genetics - Centre de génétique médicale de Marseille (MMG), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Department of Clinical Genetics, Aarhus University Hospital, Boston Children's Hospital, Wellcome Trust Genome Campus, The Wellcome Trust Sanger Institute [Cambridge], Institute of Biomedical Engineering [Oxford] (IBME), Climatic Research Unit, University of East Anglia [Norwich] (UEA), Imperial College London, St Mary's Hospital, East Anglian Medical Genetics Service, Cytogenetics Laboratory, Addenbrooke's Hospital, Sheffield Children's NHS Foundation Trust, Regional Genetic Service, St Mary's Hospital, Manchester, Genetics, University of Southampton, Great Ormond Street Hospital for Children [London] (GOSH), Yorkshire Regional Clinical Genetics Service, Chapel Allerton Hospital, Molecular and Clinical Medicine [Dundee, UK] (School of Medicine), University of Dundee [UK]-Ninewells Hospital & Medical School [Dundee, UK], Department of Clinical Genetics, Oxford Regional Genetics Service, The Churchill hospital, North West Thames Regional Genetics, Northwick Park Hospital, Royal Devon & Exeter Hospital, Wessex Clinical Genetics Service, Wessex clinical genetics service, Manchester University NHS Foundation Trust (MFT), West Midlands Regional Genetics Service, Birmingham Women's and Children's NHS Foundation Trust, Our Lady's hospital for Sick Children, Our Lady's Hospital for Sick Children, Guy's Hospital [London], University Hospitals Leicester, University of Edinburgh, Belfast City Hospital, Ferguson-Smith Centre for Clinical Genetics, Yorkhill Hospitals, Institute of Medical Genetics, Heath Park, Cardiff, The London Clinic, Nottingham City Hospital, Clinical Genetics Department, St Michael's Hospital, Department of Genetic Medicine, Nottingham Clinical Genetics Service, Nottingham University Hospitals NHS Trust (NUH), Royal Devon and Exeter Foundation Trust, Histopathology, St. George's Hospital, Teesside Genetics Unit, James Cook University (JCU), Kansas State University, Liverpool Women's NHS Foundation Trust, Department of Medical Genetics, HMNC Brain Health, North West Thames Regional Genetics Service, Northwick Park Hospital, Harrow, Leicester Royal Infirmary, University Hospitals Leicester-University Hospitals Leicester, Ninewells Hospital and Medical School [Dundee], Academic Centre on Rare Diseases (ACoRD), University College Dublin [Dublin] (UCD), Oxford Brookes University, Institute of medicinal plant development, Chinese Academy of Medical Sciences, Newcastle Upon Tyne Hospitals NHS Trust, Service d'explorations fonctionnelles respiratoires [Lille], Department of Computer Science - Trinity College Dublin, University of Dublin, Department of Clinical Genetics (Sheffield Children’s NHS Foundation Trust), Division of Medical & Molecular Genetics, NHS Greater Glasgow & Clyde [Glasgow] (NHSGGC), Department of Clinical Genetics [Churchill Hospital], Churchill Hospital Oxford Centre for Haematology, Weizmann Institute of Science [Rehovot, Israël], Southampton General Hospital, Western General Hospital, Head of the Department of Medical Genetics, University of Birmingham [Birmingham], SW Thames Regional Genetics Service, St Georgeâ™s University of London, London, Institut Cochin (IC UM3 (UMR 8104 / U1016)), Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), All Wales Medical Genetics Services, Singleton Hospital, Central Manchester University Hospitals NHS Foundation Trust, University of North Texas (UNT), Clinical Genetics, Northern Genetics Service, Newcastle University [Newcastle], United Kingdom Met Office [Exeter], Institute of Medical Genetics (University Hospital of Wales), University Hospital of Wales (UHW), West Midlands Regional Genetics Laboratory and Clinical Genetics Unit, Birmingham Women's Hospital, Laboratory of Molecular Genetics, National Institute of Child Health and Human Development, National Institutes of Health, Department of Genetics, Cell- and Immunobiology, Semmelweis University, University Hospitals Bristol, Marketing (MKT), EESC-GEM Grenoble Ecole de Management, Addenbrookes Hospital, West of Scotland Genetics Service (Queen Elizabeth University Hospital), University Hospital Birmingham Queen Elizabeth, Department of Clnical Genetics, Chapel Allerton Hospital, Department of Clinical Genetics, Northampton General Hospital, Northampton, Royal Devon and Exeter Hospital [Exeter, UK] (RDEH), Guy's and St Thomas' Hospital [London], School of Computer Science, Bangor University, University Hospital Southampton, Clinical Genetics Unit, St Georges, University of London, Medical Genetics, Cardiff University, Research and Development, Futurelab, Nottingham Regional Genetics Service [Nottingham, UK], Nottingham University Hospitals NHS Trust (NUH)-City Hospital Campus [Nottingham, UK], University of St Andrews [Scotland], Clinical Genetics Service, Nottingham University Hospitals NHS Trust - City Hospital Campus, West Midlands Regional Genetics Unit, Department of Neurology, Johns Hopkins University (JHU), Oxford University Hospitals NHS Trust, St James's University Hospital, Leeds Teaching Hospitals NHS Trust, Addenbrooke's Hospital, Cambridge University NHS Trust, Institute of Human Genetics, Newcastle, Division of Biological Stress Response [Amsterdam, The Netherlands], The Netherlands Cancer Institute [Amsterdam, The Netherlands], Johns Hopkins Bloomberg School of Public Health [Baltimore], Birmingham Women’s Hospital, Department of Genetics, Portuguese Oncology Institute, Molecular Genetics, IWK Health Centre, IWK health centre, North West london hospitals NHS Trust, Department of Clinical Genetics (Queen Elizabeth University Hospital, Glasgow), Queen Elizabeth University Hospital (Glasgow), Birmingham women's hospital, Birmingham, Ethox Centre, Department of Public Health and Primary Health Care, University of Oxford, Badenoch Building, Old Road Campus, Headington, R01 HD091846, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Human Genome Research Institute, National Institutes of Health’s National Institute of Child Health and Human Development, Boston Children’s Hospital Faculty Development Fellowship, UM1HG008900, Broad Center for Mendelian Genomics, Chile’s National Commission for Scientific and Technological Research, DFG WE4896/3-1, German Research Society, WT 100127, Health Innovation Challenge Fund, Comprehensive Clinical Research Network, Skaggs-Oxford Scholarship, 10/H0305/83, Cambridge South REC, REC GEN/284/12, Republic of Ireland, WT098051, Wellcome Sanger Institute, 72160007, Comisión Nacional de Investigación Científica y Tecnológica, Children's Hospital of Philadelphia, Technische Universität Kaiserslautern, 1DH1813319, Dietmar Hopp Stiftung, National Institute for Health Research, Department of Health & Social Care, Service de neurologie 1 [CHU Pitié-Salpétrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Hôpital Saint Vincent de Paul-GHICL, Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM)-Helmholtz-Zentrum München (HZM)-German Research Center for Environmental Health, Service de Génétique Cytogénétique et Embryologie [CHU Pitié-Salpêtrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Università degli Studi di Camerino (UNICAM), University of Oxford [Oxford], Institut National de la Santé et de la Recherche Médicale (INSERM)-Aix Marseille Université (AMU), Nottingham University Hospitals NHS Trust, Nottingham University Hospitals, SW Thames Regional Genetics Service, St Georgeâ™s University of London, London, University Hospital of Wales, Grenoble Ecole de Management, Royal Devon and Exeter Hospital, City Hospital Campus [Nottingham, UK]-Nottingham University Hospitals NHS Trust [UK], ANS - Complex Trait Genetics, Human Genetics, ARD - Amsterdam Reproduction and Development, ACS - Pulmonary hypertension & thrombosis, Service de Neurologie [CHU Pitié-Salpêtrière], IFR70-CHU Pitié-Salpêtrière [AP-HP], GHICL-Hôpital Saint Vincent de Paul, Centre National de la Recherche Scientifique (CNRS)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Friedrich-Alexander d'Erlangen-Nuremberg, Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-CHU Pitié-Salpêtrière [APHP], Centre Hospitalier Bretagne Atlantique [Vannes], Technische Universität München [München] (TUM)-Helmholtz-Zentrum München (HZM)-German Research Center for Environmental Health, Service de Génétique et Cytogénétique [CHU Pitié-Salpêtrière], University of Zürich [Zürich] (UZH), Università di Camerino (UNICAM), Birmingham Women's Hospital Healthcare NHS Trust, University Hospitals of Leicester, Sheffield Children’s Hospital, Weizmann Institute of Science, and Grenoble Ecole de Management (GEM)
Subjects: 0301 basic medicine, Male, Microcephaly, [SDV]Life Sciences [q-bio], Haploinsufficiency, autism, epilepsy, epileptic encephalopathy, global developmental delay, H3K4 methylation, intellectual disability, KMT2E, neurodevelopmental disorder, Adolescent, Adult, Child, Child, Preschool, DNA-Binding Proteins, Epilepsy, Female, Humans, Infant, Neurodevelopmental Disorders, Pedigree, Phenotype, Young Adult, Genetic Variation, Heterozygote, 0302 clinical medicine, Neurodevelopmental disorder, Intellectual disability, Global developmental delay, Genetics (clinical), ComputingMilieux_MISCELLANEOUS, Genetics, 0303 health sciences, Hypotonia, 030220 oncology & carcinogenesis, medicine.symptom, Rare cancers Radboud Institute for Health Sciences [Radboudumc 9], 03 medical and health sciences, Report, medicine, Journal Article, Expressivity (genetics), Preschool, 030304 developmental biology, [SDV.GEN]Life Sciences [q-bio]/Genetics, business.industry, Macrocephaly, medicine.disease, 030104 developmental biology, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, Autism, business, 030217 neurology & neurosurgery
Abstract: Contains fulltext : 206572.pdf (Publisher’s version ) (Open Access) We delineate a KMT2E-related neurodevelopmental disorder on the basis of 38 individuals in 36 families. This study includes 31 distinct heterozygous variants in KMT2E (28 ascertained from Matchmaker Exchange and three previously reported), and four individuals with chromosome 7q22.2-22.23 microdeletions encompassing KMT2E (one previously reported). Almost all variants occurred de novo, and most were truncating. Most affected individuals with protein-truncating variants presented with mild intellectual disability. One-quarter of individuals met criteria for autism. Additional common features include macrocephaly, hypotonia, functional gastrointestinal abnormalities, and a subtle facial gestalt. Epilepsy was present in about one-fifth of individuals with truncating variants and was responsive to treatment with anti-epileptic medications in almost all. More than 70% of the individuals were male, and expressivity was variable by sex; epilepsy was more common in females and autism more common in males. The four individuals with microdeletions encompassing KMT2E generally presented similarly to those with truncating variants, but the degree of developmental delay was greater. The group of four individuals with missense variants in KMT2E presented with the most severe developmental delays. Epilepsy was present in all individuals with missense variants, often manifesting as treatment-resistant infantile epileptic encephalopathy. Microcephaly was also common in this group. Haploinsufficiency versus gain-of-function or dominant-negative effects specific to these missense variants in KMT2E might explain this divergence in phenotype, but requires independent validation. Disruptive variants in KMT2E are an under-recognized cause of neurodevelopmental abnormalities.
Published: 2019

7. Iron Biogeochemistry in the High Latitude North Atlantic Ocean

Author: Achterberg, Eric, Steigenberger, Sebastian, Marsay, Chris, Le Moigne, Frédéric A.C., Painter, Stuart, Baker, Alex, Connelly, Douglas, Moore, C. Mark, Tagliabue, Alessandro, Tanhua, Toste, Institut méditerranéen d'océanologie (MIO), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Helmholtz Centre for Ocean Research [Kiel] (GEOMAR), Analyse et synthèse sonores [Paris], Sciences et Technologies de la Musique et du Son (STMS), Centre National de la Recherche Scientifique (CNRS)-IRCAM-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-IRCAM-Université Pierre et Marie Curie - Paris 6 (UPMC), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Leibniz-Institut für Meereswissenschaften (IFM-GEOMAR), National Oceanography Centre [Southampton] (NOC), University of Southampton, Skidaway Institute of Oceanography, Institute of Oceanography, Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich, NR4 7TJ, United Kingdom, SCHOOL OF ENVIRONMENTAL SCIENCES UNIVERSITY OF LIVERPOOL GBR, Partenaires IRSTEA, and Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, lcsh:R, lcsh:Medicine, lcsh:Q, lcsh:Science
Abstract: International audience; Iron (Fe) is an essential micronutrient for marine microbial organisms, and low supply controls productivity in large parts of the world's ocean. The high latitude North Atlantic is seasonally Fe limited, but Fe distributions and source strengths are poorly constrained. Surface ocean dissolved Fe (DFe) concentrations were low in the study region (
Published: 2018

8. GRACE satellite-based drought index indicating increased impact of drought over major basins in China during 2002–2017

Author: Baoyi Hu, Xiaoming Feng, Zhangli Sun, Philippe Ciais, Bojie Fu, Xianfeng Liu, Shaanxi Normal University (SNNU), Laboratory of Environmental Nanomaterials, Research Center for Eco-environmental Sciences, Beijing, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ICOS-ATC (ICOS-ATC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Institute of Tibetan Plateau Research Chinese Academy of Sciences P.O. Box 2871, 18 Shuang Qing Road Beijing 100085, China (J.L.-Z.) (INSTITUTE OF TIBETAN PLATEAU RESEARCH), Institute of Tibetan Plateau Research, Department of Hydraulic Engineering, State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing, 100084, National Basic Research Program of China (973 Program): 2017YFA0604700 Fundamental Research Funds for the Central Universities: GK202003068, GK201901009 China Postdoctoral Science Foundation: 2019M650859, 2019T120142 41722104, 41801333, 41991230 Chinese Academy of Sciences, CAS: QYZDY-SSW-DQC025, The authors would like to thank the Goddard Earth Sciences Data and Information Services Center ( http://grace.jpl.nasa.gov ) and the Center for Space Research ( http://www2.csr.utexas.edu/grace/RL05_mascons.html ) for providing global datasets of the JPL and CSR Mascon solutions and the total water content obtained from the Noah land hydrology model in the GLDAS v2 during 2002-2017. The authors would also like to thank the Earth System Research Laboratory of National Oceanic and Atmospheric Administration for providing PDSI dataset, the Institutional Repository of the Spanish National Research Council for providing SPEI dataset, and the University of East Anglia Climatic Research Unit for providing the precipitation dataset. This work was sponsored by the National Natural Science Foundation (Nos. 41991230 , 41722104 and 41801333 ), the National Key Research and Development Program of China ( 2017YFA0604700 ), the Chinese Academy of Sciences (QYZDY-SSW-DQC025), the China Postdoctoral Science Foundation ( 2019M650859 and 2019T120142 ), and the Fundamental Research Funds for the Central Universities ( GK201901009 , GK202003068 )., Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), and Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)
Subjects: 0106 biological sciences, GRACE satellite, Atmospheric Science, Index (economics), 010504 meteorology & atmospheric sciences, Drainage basin, Structural basin, Drought severity, 01 natural sciences, [SDV.SA.SF]Life Sciences [q-bio]/Agricultural sciences/Silviculture, forestry, China, 0105 earth and related environmental sciences, Global and Planetary Change, geography, geography.geographical_feature_category, Water storage, Drought assessment, Forestry, 15. Life on land, Drought duration, 6. Clean water, Current (stream), 13. Climate action, Environmental science, Satellite, Drought frequency, Physical geography, Surface runoff, Agronomy and Crop Science, 010606 plant biology & botany
Abstract: International audience; The frequency of recurrence of drought has major societal, economical, and environmental impacts. However, our ability to capture drought conditions accurately are limited due to the uncertainties in current drought indices. In the present study, we proposed a Gravity Recovery and Climate Experiment (GRACE) total water storage (TWS) based drought severity index (DSI) using the detrended GRACE-TWS time series, to eliminate the effect of non-climatic factors on drought estimation and reflect true drought conditions. Based on the improved GRACE-DSI, we characterized the drought conditions over major basins in China during 2002–2017. Our results indicate that the improved GRACE-DSI can reasonably capture the drought process compared to existing non-detrended GRACE-based drought indices. The observed behavior of GRACE-DSI time series agrees reasonably well with the Palmer drought severity index, standardized precipitation index, and standardized runoff index, although differences exist due to intrinsic differences in the indicators of drought. Spatially, the Yellow River Basin, Huai River Basin, Hai River Basin, Southwest River Basin, and Continental River Basin share a similar pattern with droughts prevailing after 2013, and with both increases in duration and severity of the drought episodes. Moreover, pixel-based drought assessment also suggests an increasing trend in drought frequency in most basins in China during the GRACE era, with a prominent drought event in the Southwest River Basin beginning in April 2015 and ending in May 2016, with a severity of -25.38 and affecting 39.47 % of the total basin area. Our analyses demonstrate that the proposed GRACE-DSI can serve as a useful tool for integrated drought monitoring and provide a better understanding of drought conditions in major basins in China during 2002–2017.
Published: 2020

9. Creating a proof-of-concept climate service to assess future renewable energy mixes in Europe: An overview of the C3S ECEM project

Author: A. Troccoli, C. Goodess, P. Jones, L. Penny, S. Dorling, C. Harpham, L. Dubus, S. Parey, S. Claudel, D.-H. Khong, P. E. Bett, H. Thornton, T. Ranchin, L. Wald, Y.-M. Saint-Drenan, M. De Felice, D. Brayshaw, E. Suckling, B. Percy, J. Blower, Climatic Research Unit, University of East Anglia [Norwich] (UEA), King Abdul Aziz University (KAU), School of Environmental Sciences [Norwich], EDF (EDF), UK Met Office, United Kingdom Met Office [Exeter], Centre Observation, Impacts, Énergie (O.I.E.), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Agenzia Nazionale per le nuove Tecnologie, l’energia e lo sviluppo economico sostenibile (ENEA), University of Reading (UOR), and Institute of Environmental Analytics
Subjects: Atmospheric Science, Computer science, 020209 energy, media_common.quotation_subject, Climate change, 02 engineering and technology, lcsh:QC851-999, 7. Clean energy, Order (exchange), 0202 electrical engineering, electronic engineering, information engineering, Energy supply, lcsh:Science, Robustness (economics), media_common, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, business.industry, Ecological Modeling, [SPI.NRJ]Engineering Sciences [physics]/Electric power, Environmental economics, Pollution, lcsh:QC1-999, Renewable energy, Reference data, Geophysics, 13. Climate action, Proof of concept, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Service (economics), lcsh:Q, lcsh:Meteorology. Climatology, business, lcsh:Physics
Abstract: The EU Copernicus Climate Change Service (C3S) European Climatic Energy Mixes (ECEM) has produced, in close collaboration with prospective users, a proof-of-concept climate service, or Demonstrator, designed to enable the energy industry and policy makers assess how well different energy supply mixes in Europe will meet demand, over different time horizons (from seasonal to long-term decadal planning), focusing on the role climate has on the mixes. The concept of C3S ECEM, its methodology and some results are presented here. The first part focuses on the construction of reference data sets for climate variables based on the ERA-Interim reanalysis. Subsequently, energy variables were created by transforming the bias-adjusted climate variables using a combination of statistical and physically-based models. A comprehensive set of measured energy supply and demand data was also collected, in order to assess the robustness of the conversion to energy variables. Climate and energy data have been produced both for the historical period (1979–2016) and for future projections (from 1981 to 2100, to also include a past reference period, but focusing on the 30 year period 2035–2065). The skill of current seasonal forecast systems for climate and energy variables has also been assessed. The C3S ECEM project was designed to provide ample opportunities for stakeholders to convey their needs and expectations, and assist in the development of a suitable Demonstrator. This is the tool that collects the output produced by C3S ECEM and presents it in a user-friendly and interactive format, and it therefore constitutes the essence of the C3S ECEM proof-of-concept climate service.
Published: 2018

10. Global Carbon Budget 2017

Author: Le Quéré, Corinne, Andrew, Robbie M., Friedlingstein, Pierre, Sitch, Stephen, Pongratz, Julia, Manning, Andrew C., Korsbakken, Jan Ivar, Peters, Glen P., Canadell, Josep G., Jackson, Robert B., Boden, Thomas A., Tans, Pieter P., Andrews, Oliver D., Arora, Vivek, Bakker, Dorothee C. E., Barbero, Leticia, Becker, Meike, Betts, Richard, Bopp, Laurent, Chevallier, Frédéric, Chini, Louise P., Ciais, Philippe, Cosca, Catherine E., Cross, Jessica, Currie, Kim, Gasser, Thomas, Harris, Ian, Hauck, Judith, Haverd, Vanessa, Houghton, Richard A., Hunt, Christopher W., Hurtt, George, Ilyina, Tatiana, Jain, Atul K., Kato, Etsushi, Kautz, Markus, Keeling, Ralph F., Klein Goldewijk, Kees, Körtzinger, Arne, Landschützer, Peter, Lefèvre, Nathalie, Lenton, Andrew, Lienert, Sebastian, Lima, Ivan D., Lombardozzi, Danica, Metzl, Nicolas, Millero, Frank J., Monteiro, Pedro M. S., Munro, David R., Nabel, Julia E. M. S., Nakaoka, Shin-ichiro, Nojiri, Yukihiro, Padin, X. Antonio, Peregon, Anna, Pfeil, Benjamin, Pierrot, Denis, Poulter, Benjamin, Rehder, Gregor, Reimer, Janet, Rödenbeck, Christian, Schwinger, Jörg, Séférian, Roland, Skjelvan, Ingunn, Stocker, Benjamin D., Tian, Hanqin, Tilbrook, Bronte, Tubiello, Francesco, van der Laan-Luijkx, Ingrid T., Van Der Werf, Guido R., Van Heuven, Steven M. A. C., Viovy, Nicolas, Vuichard, Nicolas, Walker, Anthony P., Watson, Andrew J., Wiltshire, Andrew J., Zaehle, Sönke, Zhu, Dan, Tyndall Centre for Climate Change Research, University of East Anglia [Norwich] (UEA), Center for International Climate and Environmental Research [Oslo] (CICERO), University of Oslo (UiO), College of Engineering, Mathematics and Physical Sciences, University of Exeter, College of Life and Environmental Sciences, University of Exeter, Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Global Carbon Project, CSIRO Marine and Atmospheric Research, Department of Earth System Science [Stanford] (ESS), Stanford EARTH, Stanford University-Stanford University, Climate Change Science Institute [Oak Ridge] (CCSI), Oak Ridge National Laboratory [Oak Ridge] (ORNL), UT-Battelle, LLC-UT-Battelle, LLC, ESRL Chemical Sciences Division [Boulder] (CSD), NOAA Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA)-National Oceanic and Atmospheric Administration (NOAA), Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, Cooperative Institute for Marine and Atmospheric Studies, Rosenstiel School for Marine and Atmospheric Science (CIMAS), Rosenstiel School of Marine and Atmospheric Science (RSMAS), University of Miami [Coral Gables]-University of Miami [Coral Gables], NOAA Atlantic Oceanographic and Meteorological Laboratory (AOML), National Oceanic and Atmospheric Administration (NOAA), Bjerknes Centre for Climate Research (BCCR), Department of Biological Sciences [Bergen] (BIO / UiB), University of Bergen (UiB)-University of Bergen (UiB), Geophysical Institute [Bergen] (GFI / BiU), University of Bergen (UiB), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Department of Geographical Sciences, University of Maryland [College Park], University of Maryland System-University of Maryland System, ICOS-ATC (ICOS-ATC), NOAA Pacific Marine Environmental Laboratory [Seattle] (PMEL), National Institute of Water and Atmospheric Research [Wellington] (NIWA), International Institute for Applied Systems Analysis [Laxenburg] (IIASA), Climatic Research Unit, Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), Commonwealth Scientific and Industrial Research Organisation (CSIRO), Woods Hole Oceanographic Institution (WHOI), Ocean Process Analysis Laboratory, University of New Hampshire (UNH), Department of Atmospheric Sciences [Urbana], University of Illinois at Urbana-Champaign [Urbana], University of Illinois System-University of Illinois System, The Institute of Applied Energy (IAE), Karlsruher Institut für Technologie (KIT), University of California [San Diego] (UC San Diego), University of California, PBL Netherlands Environmental Assessment Agency, Christian-Albrechts-Universität zu Kiel (CAU), Austral, Boréal et Carbone (ABC), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU), CISRO Oceans and Atmosphere, Antarctic Climate & Ecosystem Cooperative Research Centre, University of Tasmania [Hobart, Australia] (UTAS), Climate and Environmental Physics [Bern] (CEP), Physikalisches Institut [Bern], Universität Bern [Bern]-Universität Bern [Bern], Oeschger Centre for Climate Change Research (OCCR), University of Bern, National Center for Atmospheric Research [Boulder] (NCAR), Cycles biogéochimiques marins : processus et perturbations (CYBIOM), Department of Ocean Sciences, University of Miami [Coral Gables], Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento em Lisboa (INESC-ID), Instituto Superior Técnico, Universidade Técnica de Lisboa (IST)-Instituto de Engenharia de Sistemas e Computadores (INESC), University of Wisconsin Whitewater, National Institute for Environmental Studies (NIES), Montana State University (MSU), Max-Planck-Institut für Biogeochemie (MPI-BGC), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Shandong Agricultural University (SDAU), Antarctic Climate and Ecosystems Cooperative Research Centre (ACE-CRC), Wageningen University and Research [Wageningen] (WUR), Faculty of Earth and Life Sciences [Amsterdam] (FALW), Vrije Universiteit Amsterdam [Amsterdam] (VU), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), NASA Ames Research Center (ARC), Biogeochemical Systems Department [Jena], Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft-Max-Planck-Gesellschaft, and Huazhong University of Science and Technology [Wuhan] (HUST)
Subjects: [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph]
Abstract: International audience; 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 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 high fossil emissions and the small SLAND consistent with El Niño conditions. The global atmospheric CO2 concentration reached 402.8 ± 0.1 ppm averaged over 2016. For 2017, preliminary data for the first 6–9 months 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 (GDP) corrected for recent changes in the carbon intensity of the economy for the rest of the world. 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, a, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017 (GCP, 2017).
Published: 2018

11. The ECEM climate service: how reanalysis can help energy planning

Author: Laurent Dubus, Matteo de Felice, Sandra Claudel, Yves-Marie Saint-Drenan, Troccoli, Alberto M., Clare Goodess, Siyue Zhang, Thierry Ranchin, Hazel Thornton, EDF (EDF), Agenzia Nazionale per le nuove Tecnologie, l’energia e lo sviluppo economico sostenibile (ENEA), Centre Observation, Impacts, Énergie (O.I.E.), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Climatic Research Unit, University of East Anglia [Norwich] (UEA), University of East Anglia, UK Met Office, European Project: Copernicus C3S_441,ECEM, Agenzia Nazionale per le nuove Tecnologie, l’energia e lo sviluppo economico sostenibile = Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), and Mines Paris - PSL (École nationale supérieure des mines de Paris)
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, [SPI.NRJ]Engineering Sciences [physics]/Electric power
Abstract: International audience; European Climatic Energy Mixes (ECEM) is a Copernicus Climate Change Service (C3S) activity which isdeveloping, in close collaboration with the energy sector, a proof-of-concept model – or demonstrator. Its purposeis to enable the energy industry and policy makers to assess how well energy supply will meet demand in Europeover different time horizons, focusing on the role climate has on energy supply and demand.This presentation sums up how energy time series were modelled and computed at country level and dailytime step for the whole Europe.Bias-adjusted Essential Climate Variables from ERA-Interim over a European domain for 1979-2016 were used tocalculate electricity demand and generation from wind, solar and hydro power. Different strategies were adopteddepending on the target variable, and the availability of measured data to calibrate and validate the energy models.For demand, individual models were set up for each country, using a general approach based on GeneralizedAdditive Models. Hydro power generation could not be modelled precisely using a physical model at plant level,due to the lack of a plants database; hence a simplified statistical model approach was chosen, and gives goodresults. Wind and solar power generation were modelled with both statistical and physical models.Results of these different models and approaches will be presnted, and compared to actual measurements orestimations of electricity demand and supply. Comparison will also be made with other projects.We will then present how the produced time series are integrated into the ECEM demonstrator, and howsuch information can be exploited to analyze and understand the supply/demand balance problem at the Europeanscale. We will also discuss some critical needs for the further development of such services, including theavailability of energy data.
Published: 2017

12. Climate data and the energy sector: the ECEM experience

Author: Matteo de Felice, Laurent Dubus, Sandra Claudel, Duc-Huy Khong, Thierry Ranchin, Lucien Wald, Hazel Thornton, Alberto Troccoli, Agenzia Nazionale per le nuove Tecnologie, l’energia e lo sviluppo economico sostenibile (ENEA), EDF (EDF), Centre Observation, Impacts, Énergie (O.I.E.), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), UK Met Office, Climatic Research Unit, and University of East Anglia [Norwich] (UEA)
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, [SPI.NRJ]Engineering Sciences [physics]/Electric power
Abstract: International audience; ECEM is a Copernicus Climate Change Services project focused on the role climate has on the European energymix (supply/demand).Climate data is converted into energy variables (energy demand and production for renewable energy sources) at country-level using statistical and physical models. Energy dataset have been gathered from a wide range of sources (e.g. ENTSO-E data and individual countries TSOs’ data) to build a common database to be used to analyse the relationship between climate information and the energy sector. For the climate side, ERA-INTERIM reanalysis has been used for the essential climate variables after a bias-correction procedure. Modelling results reveal the uniqueness of each national power system, underlining the need of a diverse set of modelling methodologies. In fact, both physical and statistical models have been used, calibrated with all the available observed climate and energy data. Results demonstrate the good performance of the climate data as predictors for the target energy variables: cross-validation error for daily national electricity demand is below 2.5% while for RES generation it is commonly below 10%. Furthermore, the work has highlighted the need of high-quality and complete metadata to maximise the impact of the produced data on the targeted user community.
Published: 2017

13. Global carbon budget 2013

Author: Bronte Tilbrook, Glen P. Peters, Andy Wiltshire, Abdirahman M Omar, Almut Arneth, A. Arvanitis, Joanna Isobel House, Richard A. Houghton, Pieter P. Tans, Benjamin D. Stocker, Josep G. Canadell, Nathalie Lefèvre, S. van Heuven, C. Le Quéré, Steve D Jones, Christian Rödenbeck, Pierre Regnier, R. Moriarty, T. Ono, Robbie M. Andrew, Stephen Sitch, Geun-Ha Park, Louise Chini, Atul K. Jain, Philippe Ciais, Fabienne Maignan, Anna B. Harper, Etsushi Kato, S. Saito, Benjamin Pfeil, Jörg Schwinger, Gregg Marland, Kees Klein Goldewijk, Michael R. Raupach, Ian Harris, Laurent Bopp, Thomas A. Boden, Arne Körtzinger, Sönke Zaehle, Nicolas Viovy, Dorothee C. E. Bakker, Pierre Friedlingstein, Rik Wanninkhof, Benjamin Poulter, Taro Takahashi, Joachim Segschneider, Scott C. Doney, Ralph F. Keeling, Robert J. Andres, Charles D. Koven, Tyndall Centre for Climate Change Research, University of East Anglia [Norwich] (UEA), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-ATC (ICOS-ATC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), University of Exeter, Appalachian State University, University, Tyndall Centre for Climate Change Research and School of Environmental Sciences, College of Life and Environmental Sciences [Exeter], NOAA Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA), Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT), Climatic Research Unit, University of East Anglia, University of Illinois at Urbana-Champaign [Urbana], University of Illinois System, The Institute of Applied Energy (IAE), PBL Netherlands Environmental Assessment Agency, Leibniz-Institut für Meereswissenschaften (IFM-GEOMAR), Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research (UFZ), Austral, Boréal et Carbone (ABC), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Netherlands Institute for Radio Astronomy (ASTRON), National Institute of Advanced Industrial Science and Technology (AIST), Chemistry Department [Massachusetts Institute of Technology], Massachusetts Institute of Technology (MIT), Université libre de Bruxelles (ULB), Max-Planck-Institut für Biogeochemie (MPI-BGC), Japan Meteorological Agency (JMA), Bjerknes Centre for Climate Research (BCCR), Department of Biological Sciences [Bergen] (BIO / UiB), University of Bergen (UiB)-University of Bergen (UiB), Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Centre for Isotope Research [Groningen] (CIO), University of Groningen [Groningen], NOAA Atlantic Oceanographic and Meteorological Laboratory (AOML), Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Max Planck Institute for Biogeochemistry (MPI-BGC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636))
Subjects: 010504 meteorology & atmospheric sciences, 530 Physics, Mathematics and natural scienses: 400::Geosciences: 450::Meteorology: 453 [VDP], MODELS, Matematikk og naturvitenskap: 400::Geofag: 450::Oseanografi: 452 [VDP], Earth and Planetary Sciences(all), [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], 010501 environmental sciences, Atmospheric sciences, 7. Clean energy, 01 natural sciences, 12. Responsible consumption, Carbon cycle, Atmosphere, Matematikk og naturvitenskap: 400::Geofag: 450::Meteorologi: 453 [VDP], carbon budget, chemistry.chemical_compound, METHANE, carbon sinks, Mathematics and natural scienses: 400::Geosciences: 450::Oceanography: 452 [VDP], Deforestation, CARBON DIOXIDE, ddc:550, Climate change, fossil fuels, Energy statistics, Land use change, lcsh:Environmental sciences, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, lcsh:GE1-350, lcsh:QE1-996.5, Biosphere, Généralités, Vegetation, 15. Life on land, lcsh:Geology, Earth sciences, chemistry, 13. Climate action, Carbon dioxide, General Earth and Planetary Sciences, Environmental science, Sink (computing)
Abstract: Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates, consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil-fuel combustion and cement production (EFF) are based on energy statistics, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (G ATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated for the first time in this budget with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2 and land cover change (some including nitrogen-carbon interactions). All uncertainties are reported as ±1σ ,reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2003-2012), EFF was 8.6±0.4 GtC yr-1, ELUC 0.9±0.5 GtC yr-1, GATM 4.3±0.1 GtC yr-1, SOCEAN 2.5±0.5 GtC yr -1, and SLAND 2.8±0.8 GtC yr-1. For year 2012 alone, EFF grew to 9.7±0.5 GtC yr-1, 2.2% above 2011, reflecting a continued growing trend in these emissions, G ATM was 5.1±0.2 GtC yr-1, SOCEAN was 2.9±0.5 GtC yr-1, and assuming an ELUC of 1.0±0.5 GtC yr-1 (based on the 2001-2010 average), S LAND was 2.7±0.9 GtC yr-1. GATM was high in 2012 compared to the 2003-2012 average, almost entirely reflecting the high EFF. The global atmospheric CO2 concentration reached 392.52±0.10 ppm averaged over 2012. We estimate that EFF will increase by 2.1% (1.1- 3.1 %) to 9.9±0.5 GtC in 2013, 61% above emissions in 1990, based on projections of world gross domestic product and recent changes in the carbon intensity of the economy.With this projection, cumulative emissions ofCO2 will reach about 535±55 GtC for 1870-2013, about 70% from EFF (390±20 GtC) and 30% from ELUC (145±50 GtC). This paper also documents any changes in the methods and data sets used in this new carbon budget from previous budgets (Le Quéré et al. 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP-2013-V2.3). © 2014 Author(s) CC Attribution 3.0 License., 0, SCOPUS: ar.j, info:eu-repo/semantics/published
Published: 2014
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14. Global and hemispheric annual temperature variations between 1861 and 1988

Author: Wright, P [East Anglia Univ., Norwich (UK). Climatic Research Unit]
Published: 1990

15. Sudden stratospheric warmings and tropospheric blockings in a multi-century simulation of the IPSL-CM5A coupled climate model

Author: François Lott, Jessica Vial, Timothy J. Osborn, Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École des Ponts ParisTech (ENPC)-École polytechnique (X)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich, NR4 7TJ, United Kingdom, Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)
Subjects: Atmospheric Science, Coupled model intercomparison project, 010504 meteorology & atmospheric sciences, Blocking (radio), [SDU.STU.GP]Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph], 0207 environmental engineering, Rossby wave, Northern Hemisphere, 02 engineering and technology, Sudden stratospheric warming, Atmospheric sciences, 01 natural sciences, Troposphere, 13. Climate action, North Atlantic oscillation, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Climatology, Climate model, 020701 environmental engineering, Geology, [SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography, 0105 earth and related environmental sciences
Abstract: International audience; The relation between sudden stratospheric warmings (SSWs) and blocking events is analyzed in a multi-centennial pre-industrial simulation of the Institut Pierre Simon Laplace coupled model (IPSL-CM5A), prepared for the fifth phase of the coupled model intercomparison project. The IPSL model captures a fairly realistic distribution of both SSWs and tropospheric blocking events, albeit with a tendency to overestimate the frequency of blocking in the western Pacific and underestimate it in the Euro-Atlantic sector. The 1000-year long simulation reveals statistically significant differences in blocking frequency and duration over the 40-day periods preceding and following the onset of SSWs. More specifically, there is an enhanced blocking frequency over Eurasia before SSWs, followed by an westward displacement of blocking anomalies over the Atlantic region as SSWs evolve and then decline. The frequency of blocking is reduced over the western Pacific sector during the life-cycle of SSWs, while the model simulates no significant relationship with eastern Pacific blocks. Finally, these changes in blocking frequency tend to be associated with a shift in the distribution of blocking lifetime toward longer-lasting blocking events before the onset of SSWs and shorter-lived blocks after the warmings. This study systematically verifies that the results are consistent with the two pictures that (1) blockings produce planetary scale anomalies that can force vertically propagating Rossby waves and then SSWs when the waves break and (2) SSWs affect blockings in return, for instance via the effect they have on the North Atlantic Oscillation. © 2013 Springer-Verlag Berlin Heidelberg.
Published: 2013
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16. Global Carbon Budget 2016

Author: Ian Harris, Richard A. Houghton, Josep G. Canadell, Pieter P. Tans, Abdirahman M Omar, Thomas A. Boden, Leticia Barbero, Arne Körtzinger, Adrienne J. Sutton, Guido R. van der Werf, Frank J. Millero, Benjamin D. Stocker, Julia E. M. S. Nabel, Louise Chini, Denis Pierrot, Scott C. Doney, Shin-Ichiro Nakaoka, Andrew Lenton, Kim I. Currie, Nicolas Viovy, Pedro M. S. Monteiro, Sönke Zaehle, Oliver Andrews, Philippe Ciais, Peter Landschützer, Ute Schuster, Stephen Sitch, Pierre Friedlingstein, Vanessa Haverd, Simone R. Alin, Judith Hauck, Christian Rödenbeck, Atul K. Jain, Nathalie Lefèvre, Ingrid T. van der Laan-Luijkx, Joe R. Melton, Mario Hoppema, Benjamin Poulter, Frédéric Chevallier, Taro Takahashi, Hanqin Tian, Thanos Gkritzalis, Tsuneo Ono, Etsushi Kato, Andrew C. Manning, Roland Séférian, Danica Lombardozzi, Jörg Schwinger, Jan Ivar Korsbakken, David R. Munro, Corinne Le Quéré, Anthony P. Walker, Laurent Bopp, Peter Anthoni, Bronte Tilbrook, Glen P. Peters, Andy Wiltshire, Sebastian Lienert, Are Olsen, Ralph F. Keeling, Nicolas Metzl, Robbie M. Andrew, Christine Delire, Joe Salisbury, Kees Klein Goldewijk, K. O'Brien, Ingunn Skjelvan, Tyndall Centre for Climate Change Research, University of East Anglia [Norwich] (UEA), Center for International Climate and Environmental Research [Oslo] (CICERO), University of Oslo (UiO), Global Carbon Project (GCP), CSIRO Marine and Atmospheric Research (CSIRO-MAR), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO)-Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), College of Life and Environmental Sciences, University of Exeter, Centre for Ocean and Atmospheric Sciences [Norwich] (COAS), School of Environmental Sciences [Norwich], University of East Anglia [Norwich] (UEA)-University of East Anglia [Norwich] (UEA), Oak Ridge National Laboratory [Oak Ridge] (ORNL), UT-Battelle, LLC, NOAA Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA), Woods Hole Oceanographic Institution (WHOI), University of California [San Diego] (UC San Diego), University of California, NOAA Pacific Marine Environmental Laboratory [Seattle] (PMEL), Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), NOAA Atlantic Oceanographic and Meteorological Laboratory (AOML), Cooperative Institute for Marine and Atmospheric Studies (CIMAS), Rosenstiel School of Marine and Atmospheric Science (RSMAS), University of Miami [Coral Gables]-University of Miami [Coral Gables], Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Department of Geographical Sciences, University of Maryland [College Park], University of Maryland System-University of Maryland System, ICOS-ATC (ICOS-ATC), National Institute of Water and Atmospheric Research [Wellington] (NIWA), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), College of Engineering, Mathematics and Physical Sciences [Exeter] (EMPS), University of Exeter, Flanders Marine Institute, VLIZ, Climatic Research Unit, University of East Anglia, Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), Commonwealth Scientific and Industrial Research Organisation (CSIRO), Oceans and Atmosphere Flagship, PBL Netherlands Environmental Assessment Agency, STMicroelectronics [Crolles] (ST-CROLLES), The Institute of Applied Energy (IAE), Christian-Albrechts-Universität zu Kiel (CAU), Helmholtz Centre for Ocean Research [Kiel] (GEOMAR), Max-Planck-Institut für Meteorologie (MPI-M), Max-Planck-Gesellschaft, Austral, Boréal et Carbone (ABC), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Oceans and Atmosphere Flagship (CSIRO), CSIRO Oceans and Atmosphere Flagship, Équipe CO2 (E-CO2), Department of Ocean Sciences, University of Miami [Coral Gables], Department of Civil and Environmental Engineering [Berkeley] (CEE), University of California [Berkeley], University of California-University of California, University of Wisconsin Whitewater, Max Planck Institute for Meteorology (MPI-M), National Institute for Environmental Studies (NIES), NASA Langley Research Center [Hampton] (LaRC), National Institute of Advanced Industrial Science and Technology (AIST), Entrepôts, Représentation et Ingénierie des Connaissances (ERIC), Université Lumière - Lyon 2 (UL2)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, Max-Planck-Institut, Ocean Process Analysis Laboratory (OPAL), University of New Hampshire (UNH), Bjerknes Centre for Climate Research (BCCR), Department of Biological Sciences [Bergen] (BIO / UiB), University of Bergen (UiB)-University of Bergen (UiB), Imperial College London, Scripps Institution of Oceanography (SIO), Joint Institute for the Study of the Atmosphere and Ocean (JISAO), University of Washington [Seattle], Institute of Space and Astronautical Science (ISAS), Japan Aerospace Exploration Agency [Sagamihara] (JAXA), Shandong Agricultural University (SDAU), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Wageningen University and Research [Wageningen] (WUR), Faculty of Earth and Life Sciences [Amsterdam] (FALW), Vrije Universiteit Amsterdam [Amsterdam] (VU), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), School of Earth and Environment [Leeds] (SEE), University of Leeds, Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Biogeochemical Systems Department [Jena], Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft-Max-Planck-Gesellschaft, Environmental Sciences, Faculty of Earth and Life Sciences, Earth and Climate, University of California (UC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), University of California [Berkeley] (UC Berkeley), University of California (UC)-University of California (UC), and Scripps Institution of Oceanography (SIO - UC San Diego)
Subjects: Meteorologie en Luchtkwaliteit, 010504 meteorology & atmospheric sciences, Meteorology and Air Quality, 530 Physics, Climate change, [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], 02 engineering and technology, 010501 environmental sciences, Atmospheric sciences, 01 natural sciences, 7. Clean energy, Carbon cycle, Latitude, SDG 17 - Partnerships for the Goals, Deforestation, ddc:550, SDG 13 - Climate Action, Life Science, lcsh:Environmental sciences, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, lcsh:GE1-350, WIMEK, business.industry, Fossil fuel, lcsh:QE1-996.5, Biosphere, Vegetation, 15. Life on land, 021001 nanoscience & nanotechnology, lcsh:Geology, Earth sciences, 13. Climate action, General Earth and Planetary Sciences, Environmental science, Sink (computing), 0210 nano-technology, business
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 all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates and consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models. We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2006–2015), EFF was 9.3 ± 0.5 GtC yr−1, ELUC 1.0 ± 0.5 GtC yr−1, GATM 4.5 ± 0.1 GtC yr−1, SOCEAN 2.6 ± 0.5 GtC yr−1, and SLAND 3.1 ± 0.9 GtC yr−1. For year 2015 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1, showing a slowdown in growth of these emissions compared to the average growth of 1.8 % yr−1 that took place during 2006–2015. Also, for 2015, ELUC was 1.3 ± 0.5 GtC yr−1, GATM was 6.3 ± 0.2 GtC yr−1, SOCEAN was 3.0 ± 0.5 GtC yr−1, and SLAND was 1.9 ± 0.9 GtC yr−1. GATM was higher in 2015 compared to the past decade (2006–2015), reflecting a smaller SLAND for that year. The global atmospheric CO2 concentration reached 399.4 ± 0.1 ppm averaged over 2015. For 2016, preliminary data indicate the continuation of low growth in EFF with +0.2 % (range of −1.0 to +1.8 %) based on national emissions projections for China and USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. In spite of the low growth of EFF in 2016, the growth rate in atmospheric CO2 concentration is expected to be relatively high because of the persistence of the smaller residual terrestrial sink (SLAND) in response to El Niño conditions of 2015–2016. From this projection of EFF and assumed constant ELUC for 2016, cumulative emissions of CO2 will reach 565 ± 55 GtC (2075 ± 205 GtCO2) for 1870–2016, about 75 % from EFF and 25 % from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quéré et al., 2015b, a, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2016).
Published: 2016

17. How climate data can help improve planning within the wind sector

Author: Alberto Troccoli, Colin Harpham, Philip Jones, Lucien Wald, Thierry Ranchin, Sylvie Parey, Laurent Dubus, Climatic Research Unit, University of East Anglia [Norwich] (UEA), Centre Observation, Impacts, Énergie (O.I.E.), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), and EDF (EDF)
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, [SPI.NRJ]Engineering Sciences [physics]/Electric power
Abstract: International audience; The Copernicus Earth Observation Programme is a €4 billion project funded by the European Union providing free data and tools to understand environmental change. This abstract outlines how the European Climatic Energy Mixes (ECEM) project, a pilot project of the Copernicus Climate Change Service (C3S), one of six Copernicus services, is using climate data from the programme to support the wind industry. Approach The Copernicus Programme is a global network of thousands of land, air and marine based sensors, as well as a family of dedicated satellites, making millions of observations a day to build a comprehensive picture of the Earth’s climate. C3S will combine observations of the climate system with the latest science to develop authoritative, quality-assured information about the past, current and future states of the climate in Europe and worldwide. Proof of concepts such as the ECEM are using this data to deve lop demonstrators, as part of the C3S pilot projects, to enable the wind industry to plan for and adapt to Europe’s changing climate. Main body of abstract The ability to use data from thousands of global sensors has a wide range of applications, from identifying prime locations for new wind turbine developments to mitigating climate risk by understanding how windstorms could impact the industry. C3S will help provide innovative solutions to challenges within the industry; in particular how to forecast wind yield and identify viable opportunities for wind development and storage investment within Europe’s generation mix. ECEM is a proof of concept climate service that is working to enable the energy industry and policy makers to assess how different energy supply mixes in Europe will meet demand over different time horizons, from seasonal to long-term planning spanning decades. By assessing the uncertainty of seasonal climate forecasts and projections, ECEM will inform climate-sensitive energy projects, such as wind, about their production under varying climate conditions and how they would meet demand at the European scale under differing energy generation scenarios. The presentation presents an assessment of wind speed and power as produced by essential historical datasets called reanalyses taking many wind speed measurements, including tower data, as reference. Two scaling methods are compared to calibrate the reanalysis, for both on-shore and offshore locations. This calibration is a key first step to providing a benchmark for climate model data such as climate forecasts and projections. An assessment of the physical coherence/co-variability between calibrated wind speed and other climate variables, such as solar radiation, is also carried out to achieve an optimal spatial and temporal co-variability, which is critical when attempting to achieve a balanced energy supply. Conclusion Harnessing data is integral to the future of the wind industry, from identifying the best locations to place turbines and target investment to ensuring that projects and infrastructure are sustainable as Europe’s climate continues to change. The calibration of wind speed as produced by a widely used re-analysis product, ERA-Interim, as the basis wind resource assessments, is discussed with this presentation. Many measurement stations, both on-shore and offshore, are used for this calibration. This work is also important in pointing to the dominant climate drivers influencing overall supply-demand balance at both national and continental scales, such as in the case of winter-time North Atlantic Oscillation, which can have a profound influence on wind power. The outcomes of ECEM’s work can help provide methods for the wind industry to plan its long-term future. Learning objectives • The ways in which energy supply and demand over Europe are affected by the spatial and temporal variations of their climate drivers; • How climate modelling can enable the wind industry to target development and investment.
Published: 2016

18. Regional climate model data used within the SWURVE project – 1: projected changes in seasonal patterns and estimation of PET

Author: Hayley J. Fowler, Marie Ekström, Geert Lenderink, Declan Conway, T. A. Buishand, Philip Jones, EGU, Publication, Climatic Research Unit [Norwich], School of Environmental Sciences [Norwich], University of East Anglia [Norwich] (UEA)-University of East Anglia [Norwich] (UEA), Water Resource Systems Research Laboratory, Newcastle University [Newcastle], Royal Netherlands Meteorological Institute (KNMI), School of Development Studies, and University of East Anglia [Norwich] (UEA)
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Estimation, 010504 meteorology & atmospheric sciences, [SDU.OCEAN] Sciences of the Universe [physics]/Ocean, Atmosphere, Anomaly (natural sciences), Hydrological modelling, 0207 environmental engineering, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, Climate change, 02 engineering and technology, 01 natural sciences, [SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces, environment, 13. Climate action, Evapotranspiration, Climatology, [SDU.STU] Sciences of the Universe [physics]/Earth Sciences, Environmental science, Climate model, Precipitation, Water cycle, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, 020701 environmental engineering, 0105 earth and related environmental sciences
Abstract: Climate data for studies within the SWURVE (Sustainable Water: Uncertainty, Risk and Vulnerability in Europe) project, assessing the risk posed by future climatic change to various hydrological and hydraulic systems were obtained from the regional climate model HadRM3H, developed at the Hadley Centre of the UK Met Office. This paper gives some background to HadRM3H; it also presents anomaly maps of the projected future changes in European temperature, rainfall and potential evapotranspiration (PET, estimated using a variant of the Penman formula). The future simulations of temperature and rainfall, following the SRES A2 emissions scenario, suggest that most of Europe will experience warming in all seasons, with heavier precipitation in winter in much of western Europe (except for central and northern parts of the Scandinavian mountains) and drier summers in most parts of western and central Europe (except for the north-west and the eastern part of the Baltic Sea). Particularly large temperature anomalies (>6°C) are projected for north-east Europe in winter and for southern Europe, Asia Minor and parts of Russia in summer. The projected PET displayed very large increases in summer for a region extending from southern France to Russia. The unrealistically large values could be the result of an enhanced hydrological cycle in HadRM3H, affecting several of the input parameters to the PET calculation. To avoid problems with hydrological modelling schemes, PET was re-calculated, using empirical relationships derived from observational values of temperature and PET.
Published: 2007

19. Global carbon budget 2014

Author: Joanna Isobel House, Roland Séférian, Stephen Sitch, Robbie M. Andrew, C. Cosca, Jörg Schwinger, Thomas A. Boden, Truls Johannessen, Michael R. Raupach, Pieter P. Tans, Nicolas Metzl, Jeremy T. Mathis, Ying-Ping Wang, R. Moriarty, G. R. van der Werf, Christian Rödenbeck, Peter Landschützer, Ute Schuster, Benjamin D. Stocker, Benjamin Poulter, Taro Takahashi, Kees Klein Goldewijk, Joachim Segschneider, Philippe Ciais, Almut Arneth, Andrew Lenton, Pierre Friedlingstein, Frédéric Chevallier, Laurent Bopp, C. Le Quéré, Etsushi Kato, Wouter Peters, Atul K. Jain, Camilla S. Landa, T. Ono, Ning Zeng, Charles D. Koven, Ralph F. Keeling, Yann Bozec, Joe Salisbury, Ivan D. Lima, Yukihiro Nojiri, Are Olsen, Steve D Jones, Shushi Peng, Mario Hoppema, Richard A. Houghton, Tobias Steinhoff, Bronte Tilbrook, Glen P. Peters, S. Saito, Benjamin Pfeil, Andy Wiltshire, Adrienne J. Sutton, Louise Chini, Josep G. Canadell, Vassilis Kitidis, Ian Harris, Pierre Regnier, Gregg Marland, Nicolas Viovy, Rik Wanninkhof, Tyndall Centre for Climate Change Research, University of East Anglia [Norwich] (UEA), Center for International Climate and Environmental Research [Oslo] (CICERO), University of Oslo (UiO), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-ATC (ICOS-ATC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Karlsruhe Institute of Technology (KIT), College of Life and Environmental Sciences [Exeter], University of Exeter, NOAA Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA), Oak Ridge National Laboratory [Oak Ridge] (ORNL), UT-Battelle, LLC, CHImie Marine (CHIM), Adaptation et diversité en milieu marin (AD2M), Station biologique de Roscoff [Roscoff] (SBR), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Station biologique de Roscoff [Roscoff] (SBR), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Global Carbon Project, CSIRO Marine and Atmospheric Research, Department of Geographical Sciences, University of Maryland [College Park], University of Maryland System-University of Maryland System, Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), NOAA Pacific Marine Environmental Laboratory [Seattle] (PMEL), Climatic Research Unit, University of East Anglia, Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), Woods Hole Oceanographic Institution (WHOI), University of Bristol [Bristol], Department of Atmospheric Sciences [Urbana], University of Illinois at Urbana-Champaign [Urbana], University of Illinois System-University of Illinois System, Geophysical Institute [Bergen] (GFI / BiU), University of Bergen (UiB), Bjerknes Centre for Climate Research (BCCR), Department of Biological Sciences [Bergen] (BIO / UiB), University of Bergen (UiB)-University of Bergen (UiB), Institute of Applied Energy (IAE), Earth Science Division [LBNL Berkeley] (ESD), Lawrence Berkeley National Laboratory [Berkeley] (LBNL), Plymouth Marine Laboratory (PML), Plymouth Marine Laboratory, PBL Netherlands Environmental Assessment Agency, Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research (UFZ), Institute of Biogeochemistry and Pollutant Dynamics [ETH Zürich] (IBP), Department of Environmental Systems Science [ETH Zürich] (D-USYS), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich)- Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Oceans and Atmosphere Flagship (CSIRO), CSIRO Oceans and Atmosphere Flagship, Appalachian State University, University, Équipe CO2 (E-CO2), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institute of Cancer Epidemiology, Danish Cancer Society, National Institute of Advanced Industrial Science and Technology (AIST), Swedish Defence Research Agency [Stockholm] (FOI), Meteorology and Air Quality Department [Wageningen] (MAQ), Wageningen University and Research [Wageningen] (WUR), Montana State University (MSU), Australian National University (ANU), Université libre de Bruxelles (ULB), Max-Planck-Institut für Biogeochemie (MPI-BGC), Japan Meteorological Agency (JMA), University of New Hampshire (UNH), Météo-France [Paris], Météo France, Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Helmholtz Centre for Ocean Research [Kiel] (GEOMAR), Imperial College London, Oeschger Centre for Climate Change Research (OCCR), University of Bern, Joint Institute for the Study of the Atmosphere and Ocean (JISAO), University of Washington [Seattle], Department of Mechanical Science and Engineering, Nagoya University, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Faculty of Earth and Life Sciences [Amsterdam] (FALW), Vrije Universiteit Amsterdam [Amsterdam] (VU), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), NOAA Atlantic Oceanographic and Meteorological Laboratory (AOML), Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Department of Atmospheric and Oceanic Science [College Park] (AOSC), Earth and Climate, Amsterdam Global Change Institute, Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), and Météo-France
Subjects: Meteorologie en Luchtkwaliteit, ENVIRONMENT SIMULATOR JULES, 010504 meteorology & atmospheric sciences, earth system model, environment simulator jules, 010501 environmental sciences, 01 natural sciences, land-use change, chemistry.chemical_compound, ComputingMethodologies_SYMBOLICANDALGEBRAICMANIPULATION, ddc:550, SDG 13 - Climate Action, Land use, land-use change and forestry, DIOXIDE EMISSIONS, lcsh:Environmental sciences, lcsh:GE1-350, EARTH SYSTEM MODEL, lcsh:QE1-996.5, Biosphere, terrestrial ecosystems, Vegetation, LAND-USE CHANGE, FLUX VARIABILITY, Climatology, Carbon dioxide, INTERANNUAL VARIABILITY, FIRE EMISSIONS, international-trade, Meteorology and Air Quality, 530 Physics, interannual variability, Climate change, co2 flux variability, [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], Carbon cycle, Latitude, ANTHROPOGENIC CO2 UPTAKE, Deforestation, Mathematics and natural scienses: 400::Zoology and botany: 480::Ecology: 488 [VDP], TheoryofComputation_ANALYSISOFALGORITHMSANDPROBLEMCOMPLEXITY, SDG 14 - Life Below Water, ATMOSPHERIC CO2, 0105 earth and related environmental sciences, atmospheric co2, WIMEK, Généralités, 15. Life on land, dioxide emissions, TERRESTRIAL ECOSYSTEMS, lcsh:Geology, Earth sciences, mixed-layer scheme, chemistry, 13. Climate action, General Earth and Planetary Sciences, Environmental science, Matematikk og naturvitenskap: 400::Zoologiske og botaniske fag: 480::Økologi: 488 [VDP], MathematicsofComputing_DISCRETEMATHEMATICS
Abstract: Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates, consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuel combustion and cement production (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2, and land-cover-change (some including nitrogen-carbon interactions). We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2004-2013) EFF was 8.9 ± 0.4 GtC yr-1, ELUC 0.9 ± 0.5 GtC yr-1, GATM 4.3 ± 0.1 GtC yr-1, SOCEAN 2.6 ± 0.5 GtC yr-1, and SLAND 2.9 ± 0.8 GtC yr-1. For year 2013 alone, EFF grew to 9.9 ± 0.5 GtC yr-1, 2.3% above 2012, continuing the growth trend in these emissions, ELUC was 0.9 ± 0.5 GtC yr-1, GATM was 5.4 ± 0.2 GtC yr-1, SOCEAN was 2.9 ± 0.5 GtC yr-1, and SLAND was 2.5 ± 0.9 GtC yr-1. GATM was high in 2013, reflecting a steady increase in EFF and smaller and opposite changes between SOCEAN and SLAND compared to the past decade (2004-2013). The global atmospheric CO2 concentration reached 395.31 ± 0.10 ppm averaged over 2013. We estimate that EFF will increase by 2.5% (1.3-3.5%) to 10.1 ± 0.6 GtC in 2014 (37.0 ± 2.2 GtCO2 yr-1), 65% above emissions in 1990, based on projections of world gross domestic product and recent changes in the carbon intensity of the global economy. From this projection of EFF and assumed constant ELUC for 2014, cumulative emissions of CO2 will reach about 545 ± 55 GtC (2000 ± 200 GtCO2) for 1870-2014, about 75% from EFF and 25% from ELUC. This paper documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this living data set (Le Quéré et al. 2013, 2014). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP-2014)., 0, SCOPUS: ar.j, info:eu-repo/semantics/published
Published: 2015

20. Global Carbon Budget 2015

Author: Douglas Vandemark, Robert J. Andres, Charles D. Koven, Christian Rödenbeck, Benjamin Poulter, Taro Takahashi, Leticia Barbero, Yukihiro Nojiri, Fiz F. Pérez, Judith Hauck, Jörg Schwinger, S. Nakaoka, Ralph F. Keeling, Etsushi Kato, Gregor Rehder, Pieter P. Tans, Aki Murata, Thanos Gkritzalis, C. Le Quéré, Nathalie Lefèvre, Julia E. M. S. Nabel, R. Moriarty, T. Ono, Laurent Bopp, Tatiana Ilyina, Jinfeng Chang, Thomas A. Boden, Joanna Isobel House, Jan Ivar Korsbakken, Roland Séférian, Atul K. Jain, Marianela Fader, Frank J. Millero, S. van Heuven, Philippe Ciais, Are Olsen, Adrienne J. Sutton, Richard A. Houghton, Louise Chini, Robbie M. Andrew, Denis Pierrot, Tobias Steinhoff, David R. Munro, Nicolas Metzl, Richard A. Feely, Peter Landschützer, Dorothee C. E. Bakker, Pierre Friedlingstein, I. T. van der Laan-Luijkx, Siv K. Lauvset, Kees Klein Goldewijk, Ute Schuster, Benjamin D. Stocker, Andrew Lenton, Ian Harris, Vassilis Kitidis, Stephen Sitch, Ning Zeng, Bronte Tilbrook, Glen P. Peters, S. Saito, Benjamin Pfeil, Andy Wiltshire, Sönke Zaehle, Ivan D. Lima, Karen O'Brien, Almut Arneth, Frédéric Chevallier, G. R. van der Werf, Nicolas Viovy, Josep G. Canadell, Natural Environment Research Council (UK), Norwegian Research Council, European Commission, Department of Energy (US), Helmholtz Association, Leverhulme Trust, Department of Energy and Climate Change (UK), European Research Council, National Aeronautics and Space Administration (US), Department for Environment, Food and Rural Affairs (UK), Department of Commerce (US), National Science Foundation (US), Ministry of Environment (Japan), Institut national des sciences de l'Univers (France), Institut Polaire Français Paul Emile Victor, German Research Foundation, Gobierno de España, Bundesministerium für Bildung und Forschung, European Space Agency, Research Council of Norway, Swiss National Science Foundation, National Energy Research Scientific Computing Center (US), Scripps Institution of Oceanography (US), Leerstoel Ridder, Environmental Sciences, Sub Algemeen Math. Inst, Tyndall Centre for Climate Change Research, University of East Anglia [Norwich] (UEA), Center for International Climate and Environmental Research [Oslo] (CICERO), University of Oslo (UiO), Oceans and Atmosphere Research, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), College of Life and Environmental Sciences [Exeter], University of Exeter, Exeter Climate Systems, College of Engineering, Mathematics and Physical Science, University of Exeter, Exeter, United Kingdom, Carbon Dioxide Information Analysis Center [Oak Ridge] (CDIAC), U.S. Department of Energy [Washington] (DOE), Woods Hole Oceanographic Institution (WHOI), University of Bristol [Bristol], Scripps Institution of Oceanography (SIO), University of California [San Diego] (UC San Diego), University of California-University of California, NOAA Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA), Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT), Rosenstiel School of Marine and Atmospheric Science (RSMAS), University of Miami [Coral Gables], Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Department of Geographical Sciences, University of Maryland [College Park], University of Maryland System-University of Maryland System, ICOS-ATC (ICOS-ATC), Institut méditerranéen de biodiversité et d'écologie marine et continentale (IMBE), Centre National de la Recherche Scientifique (CNRS)-Institut de recherche pour le développement [IRD] : UMR237-Aix Marseille Université (AMU)-Avignon Université (AU), NOAA Pacific Marine Environmental Laboratory [Seattle] (PMEL), Flanders Marine Institute, VLIZ, Climatic Research Unit [Norwich] (CRU), Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Department of Atmospheric Sciences [Urbana], University of Illinois at Urbana-Champaign [Urbana], University of Illinois System-University of Illinois System, The Institute of Applied Energy (IAE), Plymouth Marine Laboratory (PML), Plymouth Marine Laboratory, PBL Netherlands Environmental Assessment Agency, Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research (UFZ), Institute of Applied Energy (IAE), Institute of Biogeochemistry and Pollutant Dynamics [ETH Zürich] (IBP), Department of Environmental Systems Science [ETH Zürich] (D-USYS), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich)- Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Bjerknes Centre for Climate Research (BCCR), Department of Biological Sciences [Bergen] (BIO / UiB), University of Bergen (UiB)-University of Bergen (UiB), Geophysical Institute [Bergen] (GFI / BiU), University of Bergen (UiB), Austral, Boréal et Carbone (ABC), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Oceans and Atmosphere Flagship (CSIRO), CSIRO Oceans and Atmosphere Flagship, Équipe CO2 (E-CO2), Department of Ocean Sciences, Department of Atmospheric and Oceanic Sciences [Boulder] (ATOC), University of Colorado [Boulder], Institute of Arctic and Alpine Research (INSTAAR), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), National Institute for Environmental Studies (NIES), National Institute of Advanced Industrial Science and Technology (AIST), Instituto de Investigaciones Marinas, Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Cooperative Institute for Marine and Atmospheric Studies (CIMAS), University of Miami [Coral Gables]-University of Miami [Coral Gables], Max-Planck-Institut für Biogeochemie (MPI-BGC), Japan Meteorological Agency (JMA), Météo-France [Paris], Météo France, Helmholtz Centre for Ocean Research [Kiel] (GEOMAR), Imperial College London, Joint Institute for the Study of the Atmosphere and Ocean (JISAO), University of Washington [Seattle], Lamont-Doherty Earth Observatory (LDEO), Columbia University [New York], Wageningen University and Research [Wageningen] (WUR), Faculty of Earth and Life Sciences [Amsterdam] (FALW), Vrije Universiteit Amsterdam [Amsterdam] (VU), Centre for Isotope Research [Groningen] (CIO), University of Groningen [Groningen], Ocean Process Analysis Laboratory, University of New Hampshire (UNH), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Max Planck Institute for Biogeochemistry (MPI-BGC), Department of Atmospheric and Oceanic Science [College Park] (AOSC), European Project: 603542,EC:FP7:ENV,FP7-ENV-2013-two-stage,LUC4C(2013), European Project: 282672,EC:FP7:ENV,FP7-ENV-2011,EMBRACE(2011), European Project: 264879,EC:FP7:ENV,FP7-ENV-2010,CARBOCHANGE(2011), Scripps Institution of Oceanography (SIO - UC San Diego), University of California (UC)-University of California (UC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Avignon Université (AU)-Aix Marseille Université (AMU)-Institut de recherche pour le développement [IRD] : UMR237-Centre National de la Recherche Scientifique (CNRS), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Institute of Arctic Alpine Research [University of Colorado Boulder] (INSTAAR), Météo-France, Earth and Climate, and Geology and Geochemistry
Subjects: Meteorologie en Luchtkwaliteit, ENVIRONMENT SIMULATOR JULES, 010504 meteorology & atmospheric sciences, 010501 environmental sciences, Atmospheric sciences, 7. Clean energy, 01 natural sciences, Physical Geography and Environmental Geoscience, chemistry.chemical_compound, FOSSIL-FUEL COMBUSTION, CO2 FLUX VARIABILITY, SDG 13 - Climate Action, Meteorology & Atmospheric Sciences, Geosciences, Multidisciplinary, DIOXIDE EMISSIONS, lcsh:Environmental sciences, lcsh:GE1-350, EARTH SYSTEM MODEL, lcsh:QE1-996.5, Biosphere, Geology, Vegetation, LAND-USE CHANGE, COVER CHANGE, Carbon dioxide, Physical Sciences, INTERANNUAL VARIABILITY, Meteorology and Air Quality, Life on Land, MIXED-LAYER SCHEME, Climate change, [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], 12. Responsible consumption, Carbon cycle, Latitude, Atmospheric Sciences, Atmosphere, Deforestation, Life Science, SDG 14 - Life Below Water, ATMOSPHERIC CO2, 0105 earth and related environmental sciences, Science & Technology, WIMEK, 15. Life on land, Climate Action, lcsh:Geology, Geochemistry, chemistry, 13. Climate action, General Earth and Planetary Sciences, Environmental science
Abstract: 48 pages, 9 figures, 10 tables.-- Proyecto Carbochange, Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates as well as consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover-change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models forced by observed climate, CO2, and land-cover change (some including nitrogen–carbon interactions). We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2005–2014), EFF was 9.0 ± 0.5 GtC yr−1, ELUC was 0.9 ± 0.5 GtC yr−1, GATM was 4.4 ± 0.1 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1, and SLAND was 3.0 ± 0.8 GtC yr−1. For the year 2014 alone, EFF grew to 9.8 ± 0.5 GtC yr−1, 0.6 % above 2013, continuing the growth trend in these emissions, albeit at a slower rate compared to the average growth of 2.2 % yr−1 that took place during 2005–2014. Also, for 2014, ELUC was 1.1 ± 0.5 GtC yr−1, GATM was 3.9 ± 0.2 GtC yr−1, SOCEAN was 2.9 ± 0.5 GtC yr−1, and SLAND was 4.1 ± 0.9 GtC yr−1. GATM was lower in 2014 compared to the past decade (2005–2014), reflecting a larger SLAND for that year. The global atmospheric CO2 concentration reached 397.15 ± 0.10 ppm averaged over 2014. For 2015, preliminary data indicate that the growth in EFF will be near or slightly below zero, with a projection of −0.6 [range of −1.6 to +0.5] %, based on national emissions projections for China and the USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the global economy for the rest of the world. From this projection of EFF and assumed constant ELUC for 2015, cumulative emissions of CO2 will reach about 555 ± 55 GtC (2035 ± 205 GtCO2) for 1870–2015, about 75 % from EFF and 25 % from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quéré et al., 2015, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2015)., NERC provided funding to C. Le Quéré, R. Moriarty, and the GCP through their International Opportunities Fund specifically to support this publication (NE/103002X/1). G. P. Peters and R. M. Andrew were supported by the Norwegian Research Council (236296). J. G. Canadell was supported by the Australian Climate Change Science Programme. S. Sitch was supported by EU FP7 for funding through projects LUC4C (GA603542). R. J. Andres was supported by US Department of Energy, Office of Science, Biological and Environmental Research (BER) programmes under US Department of Energy contract DE-AC05- 00OR22725. T. A. Boden was supported by US Department of Energy, Office of Science, Biological and Environmental Research (BER) programmes under US Department of Energy contract DE-AC05-00OR22725.J. I. House was supported by the Leverhulme foundation and the EU FP7 through project LUC4C (GA603542). P. Friedlingstein was supported by the EU FP7 for funding through projects LUC4C (GA603542) and EMBRACE (GA282672). A. Arneth was supported by the EU FP7 for funding through LUC4C (603542), and the Helmholtz foundation and its ATMO programme. D. C. E. Bakker was supported by the EU FP7 for funding through project CARBOCHANGE (284879), the UK Ocean Acidification Research Programme (NE/H017046/1; funded by the Natural Environment Research Council, the Department for Energy and Climate Change and the Department for Environment, Food and Rural Affairs). L. Barbero was supported by NOAA’s Ocean Acidification Program and acknowledges support for this work from the National Aeronautics and Space Administration (NASA) ROSES Carbon Cycle Science under NASA grant 13-CARBON13_2-0080. P. Ciais acknowledges support from the European Research Council through Synergy grant ERC-2013-SyG-610028 “IMBALANCE-P”. M. Fader was supported by the EU FP7 for funding through project LUC4C (GA603542). J. Hauck was supported by the Helmholtz Postdoc Programme (Initiative and Networking Fund of the Helmholtz Association). R. A. Feely and A. J. Sutton were supported by the Climate Observation Division, Climate Program Office, NOAA, US Department of Commerce. A. K. Jain was supported by the US National Science Foundation (NSF AGS 12-43071) the US Department of Energy, Office of Science and BER programmes (DOE DE-SC0006706) and NASA LCLUC programme (NASA NNX14AD94G). E. Kato was supported by the ERTDF (S-10) from the Ministry of Environment, Japan. K. Klein Goldewijk was supported by the Dutch NWO VENI grant no. 863.14.022. S. K. Lauvset was supported by the project “Monitoring ocean acidification in Norwegian waters” from the Norwegian Ministry of Climate and Environment. V. Kitidis was supported by the EU FP7 for funding through project CARBOCHANGE (264879). C. Koven was supported by the Director, Office of Science, Office of Biological and Environmental Research of the US Department of Energy under contract no. DE-AC02-05CH11231 as part of their Regional and Global Climate Modeling Program. P. Landschützer was supported by GEOCarbon. I. T. van der Lann-Luijkx received financial support from OCW/NWO for ICOS-NL and computing time from NWO (SH-060-13). I. D. Lima was supported by the US National Science Foundation (NSF AGS-1048827). N. Metzl was supported by Institut National des Sciences de l’Univers (INSU) and Institut Paul Emile Victor (IPEV) for OISO cruises. D. R. Munro was supported by the US National Science Foundation (NSF PLR-1341647 and NSF AOAS-0944761). J. E. M. S. Nabel was supported by the German Research Foundation’s Emmy Noether Programme (PO1751/1-1) and acknowledges Julia Pongratz and Kim Naudts for their contributions. Y. Nojiri and S. Nakaoka were supported by the Global Environment Research Account for National Institutes (1432) by the Ministry of Environment of Japan. A. Olsen appreciates support from the Norwegian Research Council (SNACS, 229752). F. F. Pérez were supported by BOCATS (CTM2013-41048-P) project co-founded by the Spanish government and the Fondo Europeo de Desarrollo Regional (FEDER). B. Pfeil was supported through the European Union’s Horizon 2020 research and innovation programme AtlantOS under grant agreement no. 633211. D. Pierrot was supported by NOAA through the Climate Observation Division of the Climate Program Office. B. Poulter was supported by the EU FP7 for funding through GEOCarbon. G. Rehder was supported by BMBF (Bundesministerium für Bildung und Forschung) through project ICOS, grant no. 01LK1224D. U. Schuster was supported by NERC UKOARP (NE/H017046/1), NERC RAGANRoCC (NE/K002473/1), the European Space Agency (ESA) OceanFlux Evolution project, and EU FP7 CARBOCHANGE (264879). T. Steinhoff was supported by ICOS-D (BMBF FK 01LK1101C) and EU FP7 for funding through project CARBOCHANGE (264879). J. Schwinger was supported by the Research Council of Norway through project EVA (229771). T. Takahashi was supported by grants from NOAA and the Comer Education and Science Foundation. B. Tilbrook was supported by the Australian Department of Environment and the Integrated Marine Observing System. B. D. Stocker was supported by the Swiss National Science Foundation and FP7 funding through project EMBRACE (282672). S. van Heuven was supported by the EU FP7 for funding through project CARBOCHANGE (264879). G. R. van der Werf was supported by the European Research Council (280061). A. Wiltshire was supported by the Joint UK DECC/Defra Met Office Hadley Centre Climate Programme (GA01101) and EU FP7 Funding through project LUC4C (603542). S. Zaehle was supported by the European Research Council (ERC) under the Eu ropean Union’s Horizon 2020 research and innovation programme (QUINCY; grant agreement no. 647204). ISAM (PI: Atul K. Jain) simulations were carried out at the National Energy Research Scientific Computing Center (NERSC), which is supported by the US DOE under contract DE-AC02-05CH11231. Contributions from the Scripps Institution of Oceanography were supported under DoE grant DE-SC0012167 and by Schmidt Philanthropies. This is NOAA-PMEL contribution number 4400
Published: 2015

21. Regional climate model data used within the SWURVE project 2: addressing uncertainty in regional climate model data for five European case study areas

Author: Philip Jones, B. Hingray, Abdelkader Mezghani, Marie Ekström, EGU, Publication, Climatic Research Unit, University of East Anglia [Norwich] (UEA), Laboratory of Hydrology and Land Improvement, Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Department of Radio and Space Science [Göteborg], Chalmers University of Technology [Göteborg], Hydrology and Land Improvement Laboratory (HYDRAM), Ecole Polytechnique Fédérale de Lausanne (EPFL), and Climatic Research Unit (CRU)
Subjects: Uniform distribution (continuous), 010504 meteorology & atmospheric sciences, rainfall, 0207 environmental engineering, Climate change, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, Probability density function, 02 engineering and technology, 01 natural sciences, Normal distribution, Precipitation, [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology, 020701 environmental engineering, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, 0105 earth and related environmental sciences, [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Global temperature, [SDU.OCEAN] Sciences of the Universe [physics]/Ocean, Atmosphere, regional climate model, Uncertainty, temperature, [SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces, environment, Europe, 13. Climate action, Climatology, [SDU.STU] Sciences of the Universe [physics]/Earth Sciences, Environmental science, Probability distribution, Climate model
Abstract: To aid assessments of the impact of climate change on water related activities in the case study regions (CSRs) of the EC-funded project SWURVE, estimates of uncertainty in climate model data need to be developed. This paper compares two methods for estimating uncertainty in annual surface temperature and precipitation for the period 2070–2099. Both combine probability distribution functions for global temperature increase and for scaling variables (i.e. the change in regional temperature/precipitation per degree of global annual average temperature change) to produce a probability distribution for regional temperature and precipitation. The methods differ in terms of the distribution used for the respective probability distribution function. For scaling variables, the first method assumes a uniform distribution, whilst the second method assumes a normal distribution. For the probability distribution function of global annual average temperature change, the first method uses a uniform distribution and the second uses a log-normal approximation to a distribution derived from Wigley and Raper, 2001. Although the methods give somewhat different ranges of change, they agree on how temperature and precipitation in each of the CSRs are likely to change relative to each other. For annual surface temperature, both methods predict increases in all CSRs, although somewhat less so for NW England (5th and 95th percentiles vary between 1.1–1.9°C to 3.8–5.7°C) and about 1.7–3.1°C to 5.3–8.6°C for the others. For precipitation, most probability distributions (except for NW England) show predominantly decreasing precipitation, particularly so for the Iberian CSR (5th and 95th percentiles vary from –29.3 to –44% to –9.6 to –4%).

22. Global carbon budget 2014

Author: Le Quéré, Corinne, Moriarty, Róisín, Andrew, Robbie M., Peters, Glen P., Ciais, Philippe, Friedlingstein, Pierre, Jones, Stephen D., Sitch, Stephen, Tans, Pieter P., Arneth, Almut, Boden, Thomas A., Bopp, Laurent, Bozec, Yann, Canadell, Josep G., Chevallier, Frédéric, Cosca, Catherine E., Harris, Ian, Hoppema, Mario, Houghton, Richard A., House, J., Jain, Atul K., Johannessen, Truls, Kato, Etsushi, Keeling, Ralph F., Kitidis, Vassilis, Klein Goldewijk, Kees, Koven, C., Landa, Camilla S., Landschützer, Peter, Lenton, Andrew, Lima, Ivan D., Marland, Gregg, Mathis, Jeremy T., Metzl, Nicolas, Nojiri, Yukihiro, Olsen, Are, Ono, Tsuneo, Peters, Wouter, Pfeil, Benjamin, Poulter, Benjamin, Raupach, M. R., Regnier, P., Rödenbeck, Christian, Saito, Shu, Salisbury, Joseph E., Schuster, Ute, Schwinger, Jörg, Séférian, Roland, Segschneider, Joachim, Steinhoff, Tobias, Stocker, Benjamin D., Sutton, Adrienne J., Takahashi, Taro, Tilbrook, Bronte, Van Der Werf, Guido R., Viovy, Nicolas, Wang, Y.-P., Wanninkhof, Rik H., Wiltshire, Andrew J., Zeng, N., Lefèvre, Nathalie, Tyndall Centre for Climate Change Research, University of East Anglia [Norwich] (UEA), Tyndall Centre for Climate Change Research and School of Environmental Sciences, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), University of Exeter, College of Life and Environmental Sciences [Exeter], NOAA Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA), Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT), Division technique INSU/SDU (DTI), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), NOAA Pacific Marine Environmental Laboratory [Seattle] (PMEL), Climatic Research Unit, University of East Anglia, Department of Bentho-pelagic processes, Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), University of Illinois at Urbana-Champaign [Urbana], University of Illinois System, Geophysical Institute [Bergen], University of Bergen (UIB), The Institute of Applied Energy (IAE), Plymouth Marine Laboratory (PML), Plymouth Marine Laboratory, PBL Netherlands Environmental Assessment Agency, Helmholtz Centre for Environmental Research (UFZ), Institute of Biogeochemistry and Pollutant Dynamics [ETH Zürich] (IBP), Department of Environmental Systems Science [ETH Zürich] (D-USYS), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology in Zürich [Zürich] (ETH Zürich)-Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology in Zürich [Zürich] (ETH Zürich), Centre for Australian Weather and Climate Research, CSIRO Marine and Atmospheric Research, Appalachian State University, University, Équipe CO2 (E-CO2), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN), National Institute of Advanced Industrial Science and Technology (AIST), Centre for Isotope Research [Groningen] (CIO), University of Groningen [Groningen], Université libre de Bruxelles (ULB), Max-Planck-Institut für Biogeochemie (MPI-BGC), Japan Meteorological Agency (JMA), Bjerknes Centre for Climate Research (BCCR), Department of Biological Sciences [Bergen] (BIO), University of Bergen (UIB)-University of Bergen (UIB), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Helmholtz Centre for Ocean Research [Kiel] (GEOMAR), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), NOAA Atlantic Oceanographic and Meteorological Laboratory (AOML), Met Office Hadley Centre (MOHC), United Kingdom Met Office [Exeter], Department of Atmospheric and Oceanic Science [College Park] (AOSC), University of Maryland [College Park], University of Maryland System-University of Maryland System, and Austral, Boréal et Carbone (ABC)
Subjects: 010504 meteorology & atmospheric sciences, 13. Climate action, [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], 15. Life on land, 010501 environmental sciences, 7. Clean energy, 01 natural sciences, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences
Abstract: Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe datasets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates, consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuel combustion and cement production (EFF) are based on energy statistics and cement production data, respectively, while emissions from Land-Use Change (ELUC), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent Dynamic Global Vegetation Models forced by observed climate, CO2 and land cover change (some including nitrogen-carbon interactions). We compare the variability and mean land and ocean fluxes to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2004–2013), EFF was 8.9 ± 0.4 GtC yr−1, ELUC 0.9 ± 0.5 GtC yr−1, GATM 4.3 ± 0.1 GtC yr−1, SOCEAN 2.6 ± 0.5 GtC yr−1, and SLAND 2.9 ± 0.8 GtC yr−1. For year 2013 alone, EFF grew to 9.9 ± 0.5 GtC yr−1, 2.3% above 2012, contining the growth trend in these emissions. ELUC was 0.9 ± 0.5 GtC yr−1, GATM was 5.4 ± 0.2 GtC yr−1, SOCEAN was 2.9 ± 0.5 GtC yr−1 and SLAND was 2.5 ± 0.9 GtC yr−1. GATM was high in 2013 reflecting a steady increase in EFF and smaller and opposite changes between SOCEAN and SLAND compared to the past decade (2004–2013). The global atmospheric CO2 concentration reached 395.31 ± 0.10 ppm averaged over 2013. We estimate that EFF will increase by 2.5% (1.3–3.5%) to 10.1 ± 0.6 GtC in 2014 (37.0 ± 2.2 GtCO2 yr−1), 65% above emissions in 1990, based on projections of World Gross Domestic Product and recent changes in the carbon intensity of the economy. From this projection of EFF and assumed constant ELUC for 2014, cumulative emissions of CO2 will reach about 545 ± 55 GtC (2000 ± 200 GtCO2) for 1870–2014, about 75% from EFF and 25% from ELUC. This paper documents changes in the methods and datasets used in this new carbon budget compared with previous publications of this living dataset (Le Quéré et al., 2013, 2014). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2014). Italic font highlights significant methodological changes and results compared to the Le Quéré et al. (2014) manuscript that accompanies the previous version of this living data.
Published: 2014

23. Instrumental pressure observations and atmospheric circulation from the 17th and 18th centuries: London and Paris

Author: V.C. Slonosky, Trevor Davies, Philip Jones, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Extrèmes : Statistiques, Impacts et Régionalisation (ESTIMR), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Climatic Research Unit [Norwich] (CRU), University of East Anglia [Norwich] (UEA), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, 010506 paleontology, Atmospheric Science, Historical climatology, 010504 meteorology & atmospheric sciences, Atmospheric circulation, Climate change, Weather and climate, Surface pressure, 01 natural sciences, Proxy (climate), Geography, 13. Climate action, North Atlantic oscillation, Climatology, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, ComputingMilieux_MISCELLANEOUS, Pressure gradient, 0105 earth and related environmental sciences
Abstract: Daily pressure observations recorded by William Derham (1657‐1735) at Upminster, Essex (near London), from 1697 to 1706 and 1708 have been corrected, converted to modern units and the Gregorian calendar, and adjusted for homogeneity. These pressure readings have been compared with previously published contemporary observations from Paris, and the two sets of early instrumental data used to calculate a daily series of the pressure difference between Paris and London. Frequency analysis of the daily series reveals that reversals of the south‐north pressure gradient and easterly winds were more common from 1697 to 1708 than during the 1990s. Monthly mean values of Paris‐London pressure differences have been compared with previously published monthly mean reconstructed surface pressure maps and to a reconstructed North Atlantic Oscillation (NAO) index. There is a good agreement between the strength and direction of monthly mean flow between London and Paris estimated from the circulation maps and the sign and magnitude of the Paris‐London westerly flow index, but the correlation between the Paris‐London index, known to be a good proxy for European zonal circulation, and the reconstructed NAO index, is low (0.2). Correlations between the monthly mean Paris‐London zonal circulation index and central England temperatures suggest a strong relationship during winter and late summer from 1697 to 1708. The meticulous daily instrumental observations and the monthly and seasonal climate descriptions of Derham, his collection of instrumental observations and climatic descriptions from contemporary observers throughout Europe, and his early theories on the causes of climate change make his publications a valuable source of information for studies on climate during the early instrumental period. It is hoped that more of Derham’s papers related to weather and climate may eventually come to light. Copyright © 2001 Royal Meteorological Society.
Published: 2001

24. UK Climate Projections Briefing Report

Author: Jenkins, Geoff J, Murphy, James M, Sexton, David M, Lowe, Jason A, Jones, Phil, Kilsby, Chris G, Met Office Hadley Centre, Climatic Research Unit, University of East Anglia, and University of Newcastle
Abstract: This report provides a summary of the 2009 UK Climate Projections (UKCP09), consolidating for the general reader the scientific reports describing the methodology and some key projections of future climate change for the UK over the 21st century. The UKCP09 Projections provide a basis for studies of impacts and vulnerability and decisions on adaptation to climate change in the UK over the 21st century. Projections are given of changes to climate, and of changes in the marine and coastal environment; recent trends in observed climate are also discussed. Each will be treated separately in this summary., Previously curated at: http://cedadocs.ceda.ac.uk/1321/ Main files in this record: breifing_report_full.pdf Item originally deposited with Centre for Environmental Data Analysis (CEDA) document repository by Miss Kate Winfield. Transferred to CEDA document repository community on Zenodo on 2022-11-24
Published: 2010
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25. UK Climate Projections science report: Projections of future daily climate for the UK from the Weather Generator

Author: Jones, Phil, Harpham, Colin, Kilsby, Chris, Glenis, Vassilis, Burton, Aidan, Bowyer, Paul, Steynor, Anna, Street, Roger, Capon, Rachel, Crisp, Vic, Hardy, Karl, Humphrey, Kathryn, Maresh, Jenny, Jenkins, Geoff, Mitchell, John, Stephens, Ag, Wade, Steven, Wilby, Rob, Barrow, Elaine, Carter, Tim, Montanari, Alberto, Climatic Research Unit, University of East Anglia, Newcastle University, and UK Climate Projections 2009
Abstract: In this report the UK Climate Projections (UKCP09) Weather Generator (WG) is introduced. This report covers the needs and principles and how it can be used to assess changes in extremes at spatial and temporal scales finer than the UKCP09 probability distribution functions (PDFs) can provide. Further, an illustration in the way the WG is perturbed to account for future climate change works and some illustrative maps of changes in extremes across the UK are also provided, Previously curated at: http://cedadocs.ceda.ac.uk/1335/ Main files in this record: weather_generator_full_report.pdf Item originally deposited with Centre for Environmental Data Analysis (CEDA) document repository by Miss Kate Winfield. Transferred to CEDA document repository community on Zenodo on 2022-11-24
Published: 2010
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26. Millennial temperature reconstruction intercomparison and evaluation

Author: S. L. Weber, Myles R. Allen, Jan Esper, Timothy J. Osborn, Gabriele C. Hegerl, Keith R. Briffa, Anders Moberg, Martin Juckes, STFC Rutherford Appleton Laboratory (RAL), Science and Technology Facilities Council (STFC), University of Oxford [Oxford], Climatic Research Unit [Norwich], School of Environmental Sciences [Norwich], University of East Anglia [Norwich] (UEA)-University of East Anglia [Norwich] (UEA), Swiss Federal Research Institute WSL, SWISS FEDERAL RESEARCH INSTITUTE WSL, Earth and Ocean Sciences Division, Nicholas School of the Environment, Duke University [Durham]-Duke University [Durham], Department of Meteorology and Department of Physical Geography and Quaternary Geology, Royal Netherlands Meteorological Institute (KNMI), Agency, N, Union, European Geosciences, and EGU, Publication
Subjects: 010506 paleontology, 010504 meteorology & atmospheric sciences, Stratigraphy, lcsh:Environmental protection, Inverse, Atmospheric,Oceanic,and Planetary physics, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, Residual, 01 natural sciences, Standard deviation, Proxy (climate), lcsh:Environmental pollution, lcsh:TD169-171.8, Climate systems and policy, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, lcsh:Environmental sciences, 0105 earth and related environmental sciences, Mathematics, lcsh:GE1-350, Global and Planetary Change, Small number, Physics, Paleontology, Regression, [SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces, environment, Weighting, Earth sciences, Standard error, 13. Climate action, Climatology, lcsh:TD172-193.5, [SDU.STU] Sciences of the Universe [physics]/Earth Sciences
Abstract: There has been considerable recent interest in paleoclimate reconstructions of the temperature history of the last millennium. A wide variety of techniques have been used. The interrelation among the techniques is sometimes unclear, as different studies often use distinct data sources as well as distinct methodologies. Here recent work is reviewed and some new calculations performed with an aim to clarifying the consequences of the different approaches used. A range of proxy data collections introduced by different authors is used to estimate Northern Hemispheric annual mean temperatures with two reconstruction algorithms: (1) inverse regression and, (2) compositing followed by variance matching (CVM). It is found that inverse regression tends to give large weighting to a small number of proxies and that the second approach (CVM) is more robust to varying proxy input. The choice of proxy records is one reason why different reconstructions show different ranges. A reconstruction using 13 proxy records extending back to AD 1000 shows a maximum pre-industrial temperature of 0.25 K (relative to the 1866 to 1970 mean). The standard error on this estimate, based on the residual in the calibration period, is 0.14 K. Instrumental temperatures for two recent years (1998 and 2005) have exceeded the pre-industrial estimated maximum by more than 4 standard deviations of the calibration period residual.
Published: 2007

27. Millennial temperature reconstruction intercomparison and evaluation

Author: Juckes, M. N., Allen, M. R., Briffa, K. R., Esper, J., Hegerl, G. C., Moberg, A., Osborn, T. J., Weber, S. L., Zorita, E., British Atmospheric Data Centre, STFC Rutherford Appleton Laboratory (RAL), Science and Technology Facilities Council (STFC)-Science and Technology Facilities Council (STFC), Department of Atmospheric, Oceanic and Planetary Physics [Oxford] (AOPP), University of Oxford [Oxford], Climatic Research Unit [Norwich] (CRU), University of East Anglia [Norwich] (UEA), Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Department of Earth and Ocean Sciences [Durham] (EOS), Duke University [Durham], Department of Meteorology [Stockholm] (MISU), Stockholm University, Royal Netherlands Meteorological Institute (KNMI), GKSS Research Centre, and Union, European Geosciences
Subjects: 010506 paleontology, 010504 meteorology & atmospheric sciences, 13. Climate action, Physics, Atmospheric,Oceanic,and Planetary physics, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, Climate systems and policy, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, 01 natural sciences, 0105 earth and related environmental sciences
Abstract: There has been considerable recent interest in paleoclimate reconstructions of the temperature history of the last millennium. A wide variety of techniques have been used. The interrelation between the techniques is sometimes unclear, as different studies often use distinct data sources as well as distinct methodologies. Recent work is reviewed with an aim to clarifying the import of the different approaches. A range of proxy data collections used by different authors are passed through two reconstruction algorithms: firstly, inverse regression and, secondly, compositing followed by variance matching. It is found that the first method tends to give large weighting to a small number of proxies and that the second approach is more robust to varying proxy input. A reconstruction using 18 proxy records extending back to AD 1000 shows a maximum pre-industrial temperature of 0.25 K (relative to the 1866 to 1970 mean). The standard error on this estimate, based on the residual in the calibration period is 0.149 K. Two recent years (1998 and 2005) have exceeded the estimated pre-industrial maximum by more than 4 standard errors.
Published: 2006

28. Climate Change Scenarios for the United Kingdom Scientific Report 1998

Author: Hulme, M, Jenkins, G, The Met Office, UK Climate Impacts Programme, and Climatic Research Unit (CRU)
Subjects: data and information
Abstract: This report describes how the climate of the UK has changed in the recent past and presents out understanding of how it may change through the next century in response to the build-up in atmospheric greenhouse gases. The predictions are based on the best information available in 1998. The scenarios of greenhouse gas emissions and concentrations are based on the work of the Intergovernmental Panel on Climate Change and the scenarios of climate change which may follow are based on climate modelling experiments performed by the Hadley Centre. The purpose of producing this report is to enable assessments to be made of the possible impacts of climate change in the UK. When and where damaging effects occur - or what opportunities may be presented that could be exploited? Specifically, the report was commissioned as an essential first step for the UK Climate Change Impacts Programme. This programme exists to help stakeholders in the public and private sectors assess their vulnerability to climate change, recognising that some effects are felt indirectly so that an integrated approach is required. The scenarios defined here are those that UKCIP recommend be used in such integrated studies. Overall the report represents a balanced account of the best information currently available on the future climate of the UK., Previously curated at: http://cedadocs.ceda.ac.uk/1130/ The publish date on this item was its original published date. Main files in this record: Climate_Change_Scenarios_for_the_United_Kingdom_Scientific_Report_1998.pdf Item originally deposited with Centre for Environmental Data Analysis (CEDA) document repository by Miss Poppy Townsend. Transferred to CEDA document repository community on Zenodo on 2022-11-24
Published: 1998
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29. Response to Comments on 'Saturation of the Southern Ocean CO 2 Sink Due to Recent Climate Change'

Author: Casper Labuschagne, Erik T. Buitenhuis, Thomas J. Conway, Michel Ramonet, Takakiyo Nakazawa, Corinne Le Quéré, Nicolas Metzl, Christian Rödenbeck, Nathan P. Gillett, Martin Heimann, Ray L. Langenfelds, Antony Gomez, University of East Anglia [Norwich] (UEA), School of Environmental Sciences [Norwich], Max-Planck-Institut für Biogeochemie (MPI-BGC), NOAA Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA), CSIRO Marine and Atmospheric Research (CSIRO-MAR), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), South African Weather Service (SAWS), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ICOS-RAMCES (ICOS-RAMCES), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Center for Atmospheric and Oceanic Studies [Sendai], Tohoku University [Sendai], Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Climatic Research Unit [Norwich] (CRU), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Muséum national d'Histoire naturelle (MNHN)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris)
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, geography, Multidisciplinary, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, [SDU.STU]Sciences of the Universe [physics]/Earth Sciences, Climate change, 010501 environmental sciences, Atmospheric sciences, 01 natural sciences, Sink (geography), chemistry.chemical_compound, Oceanography, chemistry, 13. Climate action, Carbon dioxide, Environmental science, 14. Life underwater, Saturation (chemistry), 0105 earth and related environmental sciences
Abstract: We estimated a weakening of the Southern Ocean carbon dioxide (CO 2 ) sink since 1981 relative to the trend expected from the large increase in atmospheric CO 2 . We agree with Law et al . that network choice increases the uncertainty of trend estimates but argue that their network of five locations is too small to be reliable. A future reversal of Southern Ocean CO 2 saturation as suggested by Zickfeld et al . is possible, but only at high atmospheric CO 2 concentrations, and the effect would be temporary.
Published: 2008

30. Etsushi Kato 29 , Markus Kautz 30 , Ralph F. Keeling 31

Author: Nicolas Vuichard, Markus Kautz, Atul K. Jain, Richard A. Houghton, Anthony P. Walker, Bronte Tilbrook, Glen P. Peters, Christian Rödenbeck, Christopher W. Hunt, Nicolas Metzl, Andy Wiltshire, Dan Zhu, Sebastian Lienert, Ingrid T. van der Laan-Luijkx, Benjamin Poulter, Judith Hauck, Frédéric Chevallier, Philippe Ciais, Benjamin D. Stocker, Thomas Gasser, Ralph F. Keeling, Vivek K. Arora, Etsushi Kato, Gregor Rehder, Andrew C. Manning, X. Antonio Padin, Ivan D. Lima, Andrew Lenton, Steven van Heuven, Jessica N. Cross, Leticia Barbero, Robbie M. Andrew, Nathalie Lefèvre, Denis Pierrot, Roland Séférian, Yukihiro Nojiri, Ingunn Skjelvan, Meike Becker, Guido R. van der Werf, George C. Hurtt, Kees Klein Goldewijk, Stephen Sitch, Julia E. M. S. Nabel, Ian Harris, Pieter P. Tans, Robert B. Jackson, Andrew J. Watson, Jan Ivar Korsbakken, Hanqin Tian, Francesco N. Tubiello, Thomas A. Boden, Arne Körtzinger, Frank J. Millero, Benjamin Pfeil, Oliver Andrews, Corinne Le Quéré, Shin-Ichiro Nakaoka, Nicolas Viovy, Anna Peregon, Catherine E Cosca, Vanessa Haverd, Richard Betts, Josep G. Canadell, Janet J. Reimer, Louise Chini, Kim I. Currie, Jörg Schwinger, Laurent Bopp, Tatiana Ilyina, Peter Landschützer, Dorothee C. E. Bakker, Pierre Friedlingstein, Julia Pongratz, David R. Munro, Danica Lombardozzi, Pedro M. S. Monteiro, Sönke Zaehle, Tyndall Centre for Climate Change Research, University of East Anglia [Norwich] (UEA), Center for International Climate and Environmental Research [Oslo] (CICERO), University of Oslo (UiO), College of Engineering, Mathematics and Physical Sciences, University of Exeter, College of Life and Environmental Sciences, University of Exeter, Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Global Carbon Project, CSIRO Marine and Atmospheric Research, Department of Earth System Science [Stanford] (ESS), Stanford EARTH, Stanford University-Stanford University, Climate Change Science Institute [Oak Ridge] (CCSI), Oak Ridge National Laboratory [Oak Ridge] (ORNL), UT-Battelle, LLC-UT-Battelle, LLC, ESRL Chemical Sciences Division [Boulder] (CSD), NOAA Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA)-National Oceanic and Atmospheric Administration (NOAA), Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, Cooperative Institute for Marine and Atmospheric Studies, Rosenstiel School for Marine and Atmospheric Science (CIMAS), Rosenstiel School of Marine and Atmospheric Science (RSMAS), University of Miami [Coral Gables]-University of Miami [Coral Gables], NOAA Atlantic Oceanographic and Meteorological Laboratory (AOML), National Oceanic and Atmospheric Administration (NOAA), Bjerknes Centre for Climate Research (BCCR), Department of Biological Sciences [Bergen] (BIO / UiB), University of Bergen (UiB)-University of Bergen (UiB), Geophysical Institute [Bergen] (GFI / BiU), University of Bergen (UiB), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Department of Geographical Sciences, University of Maryland [College Park], University of Maryland System-University of Maryland System, ICOS-ATC (ICOS-ATC), NOAA Pacific Marine Environmental Laboratory [Seattle] (PMEL), National Institute of Water and Atmospheric Research [Wellington] (NIWA), International Institute for Applied Systems Analysis [Laxenburg] (IIASA), Climatic Research Unit, Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), Commonwealth Scientific and Industrial Research Organisation (CSIRO), Woods Hole Oceanographic Institution (WHOI), Ocean Process Analysis Laboratory, University of New Hampshire (UNH), Department of Atmospheric Sciences [Urbana], University of Illinois at Urbana-Champaign [Urbana], University of Illinois System-University of Illinois System, The Institute of Applied Energy (IAE), Karlsruher Institut für Technologie (KIT), University of California [San Diego] (UC San Diego), University of California, PBL Netherlands Environmental Assessment Agency, Christian-Albrechts-Universität zu Kiel (CAU), Austral, Boréal et Carbone (ABC), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU), CISRO Oceans and Atmosphere, Antarctic Climate & Ecosystem Cooperative Research Centre, University of Tasmania [Hobart, Australia] (UTAS), Climate and Environmental Physics [Bern] (CEP), Physikalisches Institut [Bern], Universität Bern [Bern]-Universität Bern [Bern], Oeschger Centre for Climate Change Research (OCCR), University of Bern, National Center for Atmospheric Research [Boulder] (NCAR), Cycles biogéochimiques marins : processus et perturbations (CYBIOM), Department of Ocean Sciences, University of Miami [Coral Gables], Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento em Lisboa (INESC-ID), Instituto Superior Técnico, Universidade Técnica de Lisboa (IST)-Instituto de Engenharia de Sistemas e Computadores (INESC), University of Wisconsin Whitewater, National Institute for Environmental Studies (NIES), Montana State University (MSU), Max-Planck-Institut für Biogeochemie (MPI-BGC), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Shandong Agricultural University (SDAU), Antarctic Climate and Ecosystems Cooperative Research Centre (ACE-CRC), Wageningen University and Research [Wageningen] (WUR), Faculty of Earth and Life Sciences [Amsterdam] (FALW), Vrije Universiteit Amsterdam [Amsterdam] (VU), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), NASA Ames Research Center (ARC), Biogeochemical Systems Department [Jena], Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft-Max-Planck-Gesellschaft, Huazhong University of Science and Technology [Wuhan] (HUST), Environmental Sciences, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), University of California (UC), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Universität Bern [Bern] (UNIBE)-Universität Bern [Bern] (UNIBE), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), and Earth and Climate
Subjects: Meteorologie en Luchtkwaliteit, ENVIRONMENT SIMULATOR JULES, 010504 meteorology & atmospheric sciences, Epidemiology, Earth science, 010501 environmental sciences, Atmospheric sciences, 01 natural sciences, 7. Clean energy, FOSSIL-FUEL COMBUSTION, chemistry.chemical_compound, 11. Sustainability, ddc:550, Energy statistics, DIOXIDE EMISSIONS, lcsh:Environmental sciences, lcsh:GE1-350, EARTH SYSTEM MODEL, lcsh:QE1-996.5, VEGETATION MODEL, Biosphere, Carbon dioxide, Meteorology and Air Quality, Bioinformatica & Diermodellen, 530 Physics, MIXED-LAYER SCHEME, Earth and Planetary Sciences(all), chemistry.chemical_element, [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], INTERNATIONAL-TRADE, 12. Responsible consumption, Carbon cycle, ANTHROPOGENIC CO2 UPTAKE, Deforestation, Bio-informatics & Animal models, Life Science, Epidemiology, Bio-informatics & Animal models, SDG 14 - Life Below Water, ATMOSPHERIC CO2, 0105 earth and related environmental sciences, Epidemiologie, LAND-COVER CHANGE, WIMEK, business.industry, Fossil fuel, 15. Life on land, Earth system science, lcsh:Geology, Earth sciences, chemistry, 13. Climate action, Epidemiologie, Bioinformatica & Diermodellen, General Earth and Planetary Sciences, Environmental science, Physical geography, Sink (computing), business, Carbon
Abstract: 44 pages, 9 tables, 9 figures.-- Corinne Le Quéré ... et al.-- This work is distributed under the Creative Commons Attribution 4.0 License, 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 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 high fossil emissions and the small SLAND consistent with El Niño conditions. The global atmospheric CO2 concentration reached 402.8 ± 0.1 ppm averaged over 2016. For 2017, preliminary data for the first 6–9 months 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 (GDP) corrected for recent changes in the carbon intensity of the economy for the rest of the world. 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, a, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017 (GCP, 2017)
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31. Comparing monthly statistical distributions of wind speed measured at wind towers and estimated from ERA-Interim

Author: Colin Harpham, Alberto Troccoli, Philip Jones, Thierry Ranchin, Lucien Wald, Climatic Research Unit, University of East Anglia [Norwich] (UEA), Centre Observation, Impacts, Énergie (O.I.E.), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), and European Meteorological Society
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, [SPI.NRJ]Engineering Sciences [physics]/Electric power
Abstract: International audience; The energy sector is undergoing a major transformation with an increasing share of power supply from variable renewable energy sources and an increasing variability in energy demand in a variable and changing climate. The European Climatic Energy Mixes (ECEM) project will develop a demonstrator to assess how well different energy supply mixes in Europe will meet demand, over seasonal to long-term decadal time horizons, focusing on the role climate has on the mixes. ECEM is funded under the Copernicus Climate Change Service, operated by ECMWF on behalf of the European Union. Many surface climate variables needed to develop energy profiles are provided by the ERA-Interim Reanalysis. Among these profiles, are wind power supply with wind speed at different heights as main inputs to determine periods when the wind power plants are expected to produce more or less than expected. In this view, a preliminary assessment of the monthly statistical distribution of wind speed at the standard height for wind power plants (80 m) has been performed. Time series of wind speed were obtained for the towers at Cabauw in The Netherlands and offshore at Docking Shoal in the North Sea. Reference statistical distributions were built for each month. Similarly, estimated statistical distributions were built using ERA-Interim estimates of wind speed at different levels. One series was built with a power approach and a second with a log approach. The estimated statistical distributions are then compared to the reference for each month. The log approach produces stronger winds than the power approach for both sites. At Cabauw, both approaches do not produce enough large wind speed for all months. At Docking Shoal, the power approach exhibits statistical distributions very close to the reference ones. Those from the log approach are biased towards higher wind speeds.

32. Novel datasets of energy-relevant climate variables based on ERA-Interim reanalysis

Author: Philip Jones, Colin Harpham, Alberto Troccoli, Benoît Gschwind, Thierry Ranchin, Lucien Wald, Clare Goodess, Stephen Dorling, Climatic Research Unit, University of East Anglia [Norwich] (UEA), Centre Observation, Impacts, Énergie (O.I.E.), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), School of Environmental Sciences, University of East Anglia, and University of East Anglia
Subjects: [SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, [SPI.NRJ]Engineering Sciences [physics]/Electric power
Abstract: International audience; Meteorological reanalysis datasets are being widely used in a number of studies relating to the climate impact on energy. Reanalyses have the specific advantage of being complete through the process of physical/dynamic representation of the climate system which provides internally consistent fields across most surface atmospheric variables as well as in the atmospheric column up to the stratosphere. The present communication deals with the use of the ERA-Interim reanalysis for the production of datasets of climate variables relevant to energy. The work took place within the European Climatic Energy Mixes (ECEM) project in the framework of the Copernicus Climate Change Service (C3S) Sectoral Information Service (SIS). ECEM is primarily focused on users in the energy sector who are interested in sub-daily and daily variability for the following variables at the near surface: air temperature, dewpoint temperature, precipitation, solar radiation, wind speed and relative humidity. There are differences between estimates from the reanalysis and station observations. Bias adjustment is a process to adjust the reanalysis onto observational distributions. The aim of this communication is to present the construction of novel bias-adjusted datasets of the climate variables listed above.ERA-Interim was compared against observations. The bias was computed as the mean of the differences (model minus observations). As the users in energy sector are much more interested in the extremes of the distribution, our approach is based on the adjustment of the whole ERA-Interim distribution, using a different statistical distribution for each variable. In other words, we have modified the parameters of different distributions (depending on the variable), altering those calculated from ERA-Interim to those based on gridded station or direct station observations. For wind speed, the two-parameter Weibull distribution computed from ERA-Interim was adjusted to that computed for each station contained in the HadISD dataset. The scale and shape parameters computed at stations were bi-linearly interpolated to each ERA-Interim grid box. A similar approach but with adjustment of means and standard deviations was used for the dewpoint contained in the HadISD dataset and for air temperature but with the E-OBS datasets. The relative humidity is computed from these two variables. For precipitation daily totals, E-OBS and gamma distribution were used. For surface solar irradiance, the statistical distribution of ERA-Interim is adjusted to that of the satellite-derived HelioClim-3v5 dataset. This is done on a so-called clearness index, which is the ratio of the irradiation at ground level to that at the top of atmosphere. Once the clearness index adjusted, the adjusted irradiation is computed.The comparison between initial and bias-adjusted data against station observations and gridded observation products has demonstrated the benefit of performing bias-adjustment and has provided an assessment of the quality of the novel datasets. These datasets are available to anyone this ftp site: ftp://ecem.climate.copernicus.eu.

33. A comprehensive review on agricultural waste utilization through sustainable conversion techniques, with a focus on the additives effect on the fate of phosphorus and toxic elements during composting process.

Author: Xu Q, Zhang T, Niu Y, Mukherjee S, Abou-Elwafa SF, Nguyen NSH, Al Aboud NM, Wang Y, Pu M, Zhang Y, Tran HT, Almazroui M, Hooda PS, Bolan NS, Rinklebe J, and Shaheen SM
Subjects: Waste Management methods, Phosphorus analysis, Agriculture methods, Composting methods
Abstract: The increasing trend of using agricultural wastes follows the concept of "waste to wealth" and is closely related to the themes of sustainable development goals (SDGs). Carbon-neutral technologies for waste management have not been critically reviewed yet. This paper reviews the technological trend of agricultural waste utilization, including composting, thermal conversion, and anaerobic digestion. Specifically, the effects of exogenous additives on the contents, fractionation, and fate of phosphorus (P) and potentially toxic elements (PTEs) during the composting process have been comprehensively reviewed in this article. The composting process can transform biomass-P and additive-born P into plant available forms. PTEs can be passivated during the composting process. Biochar can accelerate the passivation of PTEs in the composting process through different physiochemical interactions such as surface adsorption, precipitation, and cation exchange reactions. The addition of exogenous calcium, magnesium and phosphate in the compost can reduce the mobility of PTEs such as copper, cadmium, and zinc. Based on critical analysis, this paper recommends an eco-innovative perspective for the improvement and practical application of composting technology for the utilization of agricultural biowastes to meet the circular economy approach and achieve the SDGs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)
Published: 2024
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34. Long-term PM 2.5 pollution over China: Identification of PM 2.5 pollution hotspots and source contributions.

Author: Ali MA, Huang Z, Bilal M, Assiri ME, Mhawish A, Nichol JE, de Leeuw G, Almazroui M, Wang Y, and Alsubhi Y
Abstract: Fine particulate matter, with an aerodynamic diameter ≤ 2.5 μm (PM 2.5 ), is a severe problem in China. The lack of ground-based measurements and its sparse distribution obstruct long-term air pollution impact studies over China. Therefore, the present study used newly updated Global Estimates (V5. GL.02) of monthly PM 2.5 data from 2001 to 2020 based on Geographically Weighted Regression (GWR) by Washington University. The GWR PM 2.5 data were validated against ground-based measurements from 2014 to 2020, and the validation results demonstrated a good agreement between GWR and ground-based PM 2.5 with a higher correlation (r = 0.95), lower error (8.14), and lower bias (-3.10 %). The long-term (2001-2020) PM 2.5 data were used to identify pollution hotspots and sources across China using the potential source contribution function (PSCF). The results showed highly significant PM 2.5 pollution hotspots in central (Henan, Hubei), North China Plain (NCP), northwest (Taklimakan), and Sichuan Basin (Chongqing, Sichuan) in China, with the most severe pollution occurring in winter compared to other seasons. During the winter, PM 2.5 was in the range from 6.08 to 93.05 μg/m 3 in 33 provinces, which is 1.22 to 18.61 times higher than the World Health Organization (WHO) Air Quality Guidelines (AQG-2021; annual mean: 5 μg/m 3 ). In 26 provinces, the reported PM 2.5 was 1.07 to 2.66 times higher than the Chinese Ambient Air Quality Standard (AAQS; annual mean: 35 μg/m 3 ). Furthermore, provincial-level trend analysis shows that in most Chinese provinces, PM 2.5 increased significantly (3-43 %) from 2001 to 2012, whereas it decreased by 12-94 % from 2013 to 2020 due to the implementation of air pollution control policies. Finally, the PSCF analysis demonstrates that China's air quality is mainly affected by local PM 2.5 sources rather than by pollutants imported from outside China., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier B.V.)
Published: 2023
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35. The global historical climate database HCLIM.

Author: Lundstad E, Brugnara Y, Pappert D, Kopp J, Samakinwa E, Hürzeler A, Andersson A, Chimani B, Cornes R, Demarée G, Filipiak J, Gates L, Ives GL, Jones JM, Jourdain S, Kiss A, Nicholson SE, Przybylak R, Jones P, Rousseau D, Tinz B, Rodrigo FS, Grab S, Domínguez-Castro F, Slonosky V, Cooper J, Brunet M, and Brönnimann S
Abstract: There is a growing need for past weather and climate data to support science and decision-making. This paper describes the compilation and construction of a global multivariable (air temperature, pressure, precipitation sum, number of precipitation days) monthly instrumental climate database that encompasses a substantial body of the known early instrumental time series. The dataset contains series compiled from existing databases that start before 1890 (though continuing to the present) as well as a large amount of newly rescued data. All series underwent a quality control procedure and subdaily series were processed to monthly mean values. An inventory was compiled, and the collection was deduplicated based on coordinates and mutual correlations. The data are provided in a common format accompanied by the inventory. The collection totals 12452 meteorological records in 118 countries. The data can be used for climate reconstructions and analyses. It is the most comprehensive global monthly climate dataset for the preindustrial period so far., (© 2023. The Author(s).)
Published: 2023
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36. Response of stratospheric water vapour to warming constrained by satellite observations.

Author: Nowack P, Ceppi P, Davis SM, Chiodo G, Ball W, Diallo MA, Hassler B, Jia Y, Keeble J, and Joshi M
Abstract: Future increases in stratospheric water vapour risk amplifying climate change and slowing down the recovery of the ozone layer. However, state-of-the-art climate models strongly disagree on the magnitude of these increases under global warming. Uncertainty primarily arises from the complex processes leading to dehydration of air during its tropical ascent into the stratosphere. Here we derive an observational constraint on this longstanding uncertainty. We use a statistical-learning approach to infer historical co-variations between the atmospheric temperature structure and tropical lower stratospheric water vapour concentrations. For climate models, we demonstrate that these historically constrained relationships are highly predictive of the water vapour response to increased atmospheric carbon dioxide. We obtain an observationally constrained range for stratospheric water vapour changes per degree of global warming of 0.31 ± 0.39 ppmv K -1 . Across 61 climate models, we find that a large fraction of future model projections are inconsistent with observational evidence. In particular, frequently projected strong increases (>1 ppmv K -1 ) are highly unlikely. Our constraint represents a 50% decrease in the 95th percentile of the climate model uncertainty distribution, which has implications for surface warming, ozone recovery and the tropospheric circulation response under climate change., Competing Interests: Competing interestsThe authors declare no competing interests., (© The Author(s) 2023.)
Published: 2023
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37. Spatiotemporal drought analysis in Bangladesh using the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI).

Author: Kamruzzaman M, Almazroui M, Salam MA, Mondol MAH, Rahman MM, Deb L, Kundu PK, Zaman MAU, and Islam ARMT
Subjects: Bangladesh, Spatio-Temporal Analysis, Climate Change, Droughts, Meteorology
Abstract: Countries depending on small-scale agriculture, such as Bangladesh, are susceptible to climate change and variability. Changes in the frequency and intensity of drought are a crucial aspect of this issue and the focus of this research. The goal of this work is to use SPI (standardized precipitation index) and SPEI (standardized precipitation evapotranspiration index) to investigate the differences in drought characteristics across different physiognomy types in Bangladesh and to highlight how drought characteristics change over time and spatial scales when considering different geomorphologies. This study used monthly precipitation and temperature data from 29 metrological stations for 39 years (1980-2018) for calculating SPI and SPEI values. To determine the significance of drought characteristic trends over different temporal and spatial scales, the modified Mann-Kendall trend test and multivariable linear regression (MLR) techniques were used. The results are as follows: (1) Overall, decreasing dry trend was found in Eastern hill regions, whereas an increasing drought trends were found in the in the rest of the regions in all time scaless (range is from - 0.08 decade -1 to - 0.15 decade -1 for 3-month time scale). However, except for the one-month time scale, the statistically significant trend was identified mostly in the north-central and northeast regions, indicating that drought patterns migrate from the northwest to the center region. (2) SPEI is anticipated to be better at capturing dry/wet cycles in more complex regions than SPI. (3) According to the MLR, longitude and maximum temperature can both influence precipitation. (4) Drought intensity increased gradually from the southern to the northern regions (1.26-1.56), and drought events occurred predominantly in the northwestern regions (27-30 times), indicating that drought meteorological hotspots were primarily concentrated in the Barind Tract and Tista River basin over time. Findings can be used to improve drought evaluation, hazard management, and application policymaking in Bangladesh. This has implications for agricultural catastrophe prevention and mitigation., (© 2022. The Author(s).)
Published: 2022
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38. Current Siberian heating is unprecedented during the past seven millennia.

Author: Hantemirov RM, Corona C, Guillet S, Shiyatov SG, Stoffel M, Osborn TJ, Melvin TM, Gorlanova LA, Kukarskih VV, Surkov AY, von Arx G, and Fonti P
Subjects: Arctic Regions, Humans, Seasons, Temperature, Heating, Trees
Abstract: The Arctic is warming faster than any other region on Earth. Putting this rapid warming into perspective is challenging because instrumental records are often short or incomplete in polar regions and precisely-dated temperature proxies with high temporal resolution are largely lacking. Here, we provide this long-term perspective by reconstructing past summer temperature variability at Yamal Peninsula - a hotspot of recent warming - over the past 7638 years using annually resolved tree-ring records. We demonstrate that the recent anthropogenic warming interrupted a multi-millennial cooling trend. We find the industrial-era warming to be unprecedented in rate and to have elevated the summer temperature to levels above those reconstructed for the past seven millennia (in both 30-year mean and the frequency of extreme summers). This is undoubtedly of concern for the natural and human systems that are being impacted by climatic changes that lie outside the envelope of natural climatic variations for this region., (© 2022. The Author(s).)
Published: 2022
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39. Spatiotemporal changes in aerosols over Bangladesh using 18 years of MODIS and reanalysis data.

Author: Ali MA, Bilal M, Wang Y, Qiu Z, Nichol JE, Mhawish A, de Leeuw G, Zhang Y, Shahid S, Almazroui M, Islam MN, Rahman MA, Mondol SK, Tiwari P, and Khedher KM
Subjects: Aerosols analysis, Bangladesh, Carbon, Environmental Monitoring methods, Retrospective Studies, Sulfates, Air Pollutants analysis, Satellite Imagery
Abstract: In this study, combined Dark Target and Deep Blue (DTB) aerosol optical depth at 550 nm (AOD 550 nm ) data the Moderate Resolution Imaging Spectroradiometer (MODIS) flying on the Terra and Aqua satellites during the years 2003-2020 are used as a reference to assess the performance of the Copernicus Atmosphere Monitoring Services (CAMS) and the second version of Modern-Era Retrospective analysis for Research and Applications (MERRA-2) AOD over Bangladesh. The study also investigates long-term spatiotemporal variations and trends in AOD, and determines the relative contributions from different aerosol species (black carbon: BC, dust, organic carbon: OC, sea salt: SS, and sulfate) and anthropogenic emissions to the total AOD. As the evaluations suggest higher accuracy for CAMS than for MERRA-2, CAMS is used for further analysis of AOD over Bangladesh. The annual mean AOD from both CAMS and MODIS DTB is high (>0.60) over most parts of Bangladesh except for the eastern areas of Chattogram and Sylhet. Higher AOD is observed in spring and winter than in summer and autumn, which is mainly due to higher local anthropogenic emissions during the winter to spring season. Annual trends from 2003-2020 show a significant increase in AOD (by 0.006-0.014 year -1 ) over Bangladesh, and this increase in AOD was more evident in winter and spring than in summer and autumn. The increasing total AOD is caused by rising anthropogenic emissions and accompanied by changes in aerosol species (with increased OC, sulfate, and BC). Overall, this study improves understanding of aerosol pollution in Bangladesh and can be considered as a supportive document for Bangladesh to improve air quality by reducing anthropogenic emissions., (Copyright © 2022 Elsevier Ltd. All rights reserved.)
Published: 2022
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40. Meteorological data rescue: Citizen science lessons learned from Southern Weather Discovery.

Author: Lorrey AM, Pearce PR, Allan R, Wilkinson C, Woolley JM, Judd E, Mackay S, Rawhat S, Slivinski L, Wilkinson S, Hawkins E, Quesnel P, and Compo GP
Abstract: Daily weather reconstructions (called "reanalyses") can help improve our understanding of meteorology and long-term climate changes. Adding undigitized historical weather observations to the datasets that underpin reanalyses is desirable; however, time requirements to capture those data from a range of archives is usually limited. Southern Weather Discovery is a citizen science data rescue project that recovered tabulated handwritten meteorological observations from ship log books and land-based stations spanning New Zealand, the Southern Ocean, and Antarctica. We describe the Zooniverse-hosted Southern Weather Discovery campaign, highlight promotion tactics, and replicate keying levels needed to obtain 100% complete transcribed datasets with minimal type 1 and type 2 transcription errors. Rescued weather observations can augment optical character recognition (OCR) text recognition libraries. Closer links between citizen science data rescue and OCR-based scientific data capture will accelerate weather reconstruction improvements, which can be harnessed to mitigate impacts on communities and infrastructure from weather extremes., Competing Interests: The authors declare no competing interests., (© 2022 The Authors.)
Published: 2022
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41. Reply to Weiss: Tree-ring stable oxygen isotopes suggest an increase in Asian monsoon rainfall at 4.2 ka BP.

Author: Yang B, Qin C, Bräuning A, Osborn TJ, Trouet V, Ljungqvist FC, Esper J, Schneider L, Grießinger J, Büntgen U, Rossi S, Dong G, Yan M, Ning L, Wang J, Wang X, Fan B, Wang S, Luterbacher J, Cook ER, and Stenseth NC
Subjects: Climate, Oxygen Isotopes analysis, Rain, Trees
Published: 2022
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42. Removal of potentially toxic elements from contaminated soil and water using bone char compared to plant- and bone-derived biochars: A review.

Author: Azeem M, Shaheen SM, Ali A, Jeyasundar PGSA, Latif A, Abdelrahman H, Li R, Almazroui M, Niazi NK, Sarmah AK, Li G, Rinklebe J, Zhu YG, and Zhang Z
Subjects: Charcoal, Soil, Water, Soil Pollutants analysis
Abstract: Conversion of hazardous waste materials to value-added products is of great interest from both agro-environmental and economic points of view. Bone char (BC) has been used for the removal of potentially toxic elements (PTEs) from contaminated water, however, its potential BC for the immobilization of PTEs in contaminated water and soil compared to bone (BBC)- and plant (PBC)-derived biochars has not been reviewed yet. This review presents an elaboration for the potentials of BC for the remediation of PTEs-contaminated water and soil in comparison with PBC and BBC. This work critically reviews the preparation and characterization of BC, BBC, and PBC and their PTEs removal efficiency from water and soils. The mechanisms of PTE removal by BC, BBC, and PBC are also discussed in relation to their physicochemical characteristics. The review demonstrates the key opportunities for using bone waste as feedstock for producing BC and BBC as promising low-cost and effective materials for the remediation of PTEs-contaminated water and soils and also elucidates the possible combinations of BC and BBC aiming to effectively immobilize PTEs in water and soils., (Copyright © 2022 Elsevier B.V. All rights reserved.)
Published: 2022
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43. Contamination of the marine environment in Egypt and Saudi Arabia with personal protective equipment during COVID-19 pandemic: A short focus.

Author: Hassan IA, Younis A, Al Ghamdi MA, Almazroui M, Basahi JM, El-Sheekh MM, Abouelkhair EK, Haiba NS, Alhussaini MS, Hajjar D, Abdel Wahab MM, and El Maghraby DM
Subjects: Ecosystem, Egypt epidemiology, Humans, Pandemics, Plastics, SARS-CoV-2, Saudi Arabia epidemiology, COVID-19, Personal Protective Equipment
Abstract: Plastic pollution and its impact on marine ecosystems are major concerns globally, and the situation was exacerbated after the outbreak of COVID-19. Clean-up campaigns took place during the summer season (June-August 2020) in two coastal cities in Egypt (Alexandria and Hurghada) and Jeddah, Saudi Arabia to document the abundance of beach debris through public involvement, and then remove it. A total of 3673, 255, and 848 items were collected from Alexandria, Hurghada, and Jeddah daily, respectively. Gloves and face masks (personal protective equipment "PPE") represent represented 40-60% of the total plastic items collected from each of the three cities, while plastic bags represented 7-20% of the total plastics litter collected from the same cities. The results indicated the presence of 2.79, 0.29, and 0.86 PPE item m -2 in Alexandria, Hurghada and Jeddah, respectively. This short focus provides an assessment of the environmental impacts of single-use gloves and masks used for COVID-19 protection from June to August 2020. To the best of our knowledge, this study presents the first such information from the Middle East, specifically Egypt and Saudi Arabia. It highlights the need for further knowledge and action, such as safe, sustainable, and transparent waste management processes related to COVID-19 to reduce the negative impacts now, as well as in future events. Furthermore, this study helps in achieving key components of the United Nation's Sustainable Development Goals (SDGs). This short focus can serve as a multipurpose document, not only for scientists of different disciplines but for social media and citizens in general., Competing Interests: Declaration of competing interest We believe this subject is interesting and no data were published from Egypt or Saudi Arabia. We have the pleasure to submit this paper as a short communication. Having said that, I could not find a short communication option regarding the submission, so I have selected the nearest option. The authors declare no potential conflicts of interest concerning the research, authorship, and/or publication of this article., (Copyright © 2021 Elsevier B.V. All rights reserved.)
Published: 2022
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44. Does anthropogenic upstream water withdrawal impact on downstream land use and livelihood changes of Teesta transboundary river basin in Bangladesh?

Author: Ahmed Z, Alam R, Ahmed MNQ, Ambinakudige S, Almazroui M, Islam MN, Chowdhury P, Kabir MN, and Mahmud S
Subjects: Bangladesh, Environmental Monitoring, Humans, Rivers, Hunting, Water
Abstract: This article evaluates the impact of upstream water withdrawal on downstream land use and livelihood changes in the Teesta River basin, using a combination of geospatial and social data. Results show that water bodies gradually decreased, indicating a low volume of water discharge from upstream of the Teesta River basin due to the construction of several barrages. During the study period, a significant change in the area of water bodies was observed between 2012 and 2016, from 881 to 1123 Ha, respectively. The cropland area increased because farmers changed their cropping practice due to water scarcity and floods. Trend analyses of riverbank erosion and accretion patterns suggest an increase in accretion rates compared to the rate of riverbank erosion. A household survey was conducted using a self-administered questionnaire where 450 respondents have participated (farmers: 200 and fishermen: 250). Survey results show that most of the farmers (65.5%) and fishermen (76.8%) think that the construction of upstream barrages caused harm to them. The majority of farmers and fishermen feel water scarcity, mainly in the dry season. We found that a large number of participants in the study area are willing to change their occupations. Furthermore, participants observed that many local people are migrating or willing to migrate to other places nowadays. Our study also found that farmers who face water scarcity in their area are more likely to change their location than their counterparts, while those who face problems in their cultivation are less likely to move. On the other hand, upstream barrages, fishing effects, and getting support in crisis significantly predict fishermen's occupation changes. We believe our results provide essential information on the significance of transboundary water-sharing treaties, sustainable water resource management, and planning., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)
Published: 2022
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45. The COVID-19 Pandemic: Quantification of Temporal Variations in Air Pollutants Before, During and Post the Lockdown in Jeddah City, Saudi Arabia.

Author: Hammam EE, Al Ghamdi MA, Almazroui M, and Hassan IA
Abstract: The government of Saudi Arabia imposed a strict lockdown between March and July 2020 to stop the spread of the coronavirus disease (COVID-19), which has led to a sharp decline in economic activities. The daily temporal variations of PM 10 , PM 2.5 , carbon monoxide (CO), nitrogen dioxide (NO 2 ), and ozone (O 3 ) were used to investigate the changes in air quality in response to COVID-19 lockdown control measures from January to December 2020 in Jeddah, Saudi Arabia. Meteorological parameters (wind speed, direction, temperature, relative humidity) were also analyzed to understand the changes during the pandemic. As a result, significant reductions in the concentrations of NO 2 (- 44.5%), CO (- 41.5%), and PM 2.5 , PM 10 (- 29.5%, each) were measured in the capital city of Jeddah during the quarantine compared to the pre-lockdown average. In contrast, the lockdown caused a significant increase in O 3 by 41%. The changes in air quality during the COVID-19 outbreak by comparing the average pollutant concentration before lockdown (January 1-March 21, 2020) and the following 12 weeks during the partial lockdown (March 22-July 28, 2020), reveal a very significant decrease in pollutants, and consequently a significant improvement in air quality. Observed differences are attributable to changes in point source emissions associated with changes in localized activities, possibly related to decreased economic and industrial activity in response to the lockdown. The results of the present study show during the study period indicated a positive response to lockdown during the COVID-19 pandemic. Furthermore, the results can be used to establish future control measures and strategies to improve air quality., Competing Interests: Conflict of interestAuthors declare that there is no conflict of interest., (© King Abdulaziz University and Springer Nature Switzerland AG 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)
Published: 2022
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46. Climate change projections for sustainable and healthy cities.

Author: Goodess C, Berk S, Ratna SB, Brousse O, Davies M, Heaviside C, Moore G, and Pineo H
Abstract: The ambition to develop sustainable and healthy cities requires city-specific policy and practice founded on a multidisciplinary evidence base, including projections of human-induced climate change. A cascade of climate models of increasing complexity and resolution is reviewed, which provides the basis for constructing climate projections-from global climate models with a typical horizontal resolution of a few hundred kilometres, through regional climate models at 12-50 km to convection-permitting models at 1 km resolution that permit the representation of urban induced climates. Different approaches to modelling the urban heat island (UHI) are also reviewed-focusing on how climate model outputs can be adjusted and coupled with urban canopy models to better represent UHI intensity, its impacts and variability. The latter can be due to changes induced by urbanisation or to climate change itself. City interventions such as greater use of green infrastructure also have an effect on the UHI and can help to reduce adverse health impacts such as heat stress and the mortality associated with increasing heat. Examples for the Complex Urban Systems for Sustainability and Health (CUSSH) partner cities of London, Rennes, Kisumu, Nairobi, Beijing and Ningbo illustrate how cities could potentially make use of more detailed models and projections to develop and evaluate policies and practices targeted at their specific environmental and health priorities., Practice Relevance: Large-scale climate projections for the coming decades show robust trends in rising air temperatures, including more warm days and nights, and longer/more intense warm spells and heatwaves. This paper describes how more complex and higher resolution regional climate and urban canopy models can be combined with the aim of better understanding and quantifying how these larger scale patterns of change may be modified at the city or finer scale. These modifications may arise due to urbanisation and effects such as the UHI, as well as city interventions such as the greater use of grey and green infrastructures.There is potential danger in generalising from one city to another-under certain conditions some cities may experience an urban cool island, or little future intensification of the UHI, for example. City-specific, tailored climate projections combined with tailored health impact models contribute to an evidence base that supports built environment professionals, urban planners and policymakers to ensure designs for buildings and urban areas are fit for future climates., Competing Interests: Competing Interests The authors have no competing interests to declare.
Published: 2021
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47. Long-term decrease in Asian monsoon rainfall and abrupt climate change events over the past 6,700 years.

Author: Yang B, Qin C, Bräuning A, Osborn TJ, Trouet V, Ljungqvist FC, Esper J, Schneider L, Grießinger J, Büntgen U, Rossi S, Dong G, Yan M, Ning L, Wang J, Wang X, Wang S, Luterbacher J, Cook ER, and Stenseth NC
Abstract: Asian summer monsoon (ASM) variability and its long-term ecological and societal impacts extending back to Neolithic times are poorly understood due to a lack of high-resolution climate proxy data. Here, we present a precisely dated and well-calibrated tree-ring stable isotope chronology from the Tibetan Plateau with 1- to 5-y resolution that reflects high- to low-frequency ASM variability from 4680 BCE to 2011 CE. Superimposed on a persistent drying trend since the mid-Holocene, a rapid decrease in moisture availability between ∼2000 and ∼1500 BCE caused a dry hydroclimatic regime from ∼1675 to ∼1185 BCE, with mean precipitation estimated at 42 ± 4% and 5 ± 2% lower than during the mid-Holocene and the instrumental period, respectively. This second-millennium-BCE megadrought marks the mid-to late Holocene transition, during which regional forests declined and enhanced aeolian activity affected northern Chinese ecosystems. We argue that this abrupt aridification starting ∼2000 BCE contributed to the shift of Neolithic cultures in northern China and likely triggered human migration and societal transformation., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)
Published: 2021
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48. Observational evidence that cloud feedback amplifies global warming.

Author: Ceppi P and Nowack P
Abstract: Global warming drives changes in Earth's cloud cover, which, in turn, may amplify or dampen climate change. This "cloud feedback" is the single most important cause of uncertainty in Equilibrium Climate Sensitivity (ECS)-the equilibrium global warming following a doubling of atmospheric carbon dioxide. Using data from Earth observations and climate model simulations, we here develop a statistical learning analysis of how clouds respond to changes in the environment. We show that global cloud feedback is dominated by the sensitivity of clouds to surface temperature and tropospheric stability. Considering changes in just these two factors, we are able to constrain global cloud feedback to 0.43 ± 0.35 W⋅m -2 ⋅K -1 (90% confidence), implying a robustly amplifying effect of clouds on global warming and only a 0.5% chance of ECS below 2 K. We thus anticipate that our approach will enable tighter constraints on climate change projections, including its manifold socioeconomic and ecological impacts., Competing Interests: The authors declare no competing interest.
Published: 2021
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49. Recurrent transitions to Little Ice Age-like climatic regimes over the Holocene.

Author: Helama S, Stoffel M, Hall RJ, Jones PD, Arppe L, Matskovsky VV, Timonen M, Nöjd P, Mielikäinen K, and Oinonen M
Abstract: Holocene climate variability is punctuated by episodic climatic events such as the Little Ice Age (LIA) predating the industrial-era warming. Their dating and forcing mechanisms have however remained controversial. Even more crucially, it is uncertain whether earlier events represent climatic regimes similar to the LIA. Here we produce and analyse a new 7500-year long palaeoclimate record tailored to detect LIA-like climatic regimes from northern European tree-ring data. In addition to the actual LIA, we identify LIA-like ca. 100-800 year periods with cold temperatures combined with clear sky conditions from 540 CE, 1670 BCE, 3240 BCE and 5450 BCE onwards, these LIA-like regimes covering 20% of the study period. Consistent with climate modelling, the LIA-like regimes originate from a coupled atmosphere-ocean-sea ice North Atlantic-Arctic system and were amplified by volcanic activity (multiple eruptions closely spaced in time), tree-ring evidence pointing to similarly enhanced LIA-like regimes starting after the eruptions recorded in 1627 BCE, 536/540 CE and 1809/1815 CE. Conversely, the ongoing decline in Arctic sea-ice extent is mirrored in our data which shows reversal of the LIA-like conditions since the late nineteenth century, our record also correlating highly with the instrumentally recorded Northern Hemisphere and global temperatures over the same period. Our results bridge the gaps between low- and high-resolution, precisely dated proxies and demonstrate the efficacy of slow and fast components of the climate system to generate LIA-like climate regimes., Supplementary Information: The online version contains supplementary material available at 10.1007/s00382-021-05669-0., (© The Author(s) 2021.)
Published: 2021
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50. Consistency of global warming trends strengthened since 1880s.

Author: Li Q, Sun W, Huang B, Dong W, Wang X, Zhai P, and Jones P
Abstract: Competing Interests: Conflict of interest The authors declare that they have no conflict of interest.
Published: 2020
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