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Research data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors:Schupfner, Martin;
Schupfner, Martin
Schupfner, Martin in OpenAIREWieners, Karl-Hermann;
Wachsmann, Fabian;Wieners, Karl-Hermann
Wieners, Karl-Hermann in OpenAIRESteger, Christian;
+47 AuthorsSteger, Christian
Steger, Christian in OpenAIRESchupfner, Martin;
Schupfner, Martin
Schupfner, Martin in OpenAIREWieners, Karl-Hermann;
Wachsmann, Fabian;Wieners, Karl-Hermann
Wieners, Karl-Hermann in OpenAIRESteger, Christian;
Steger, Christian
Steger, Christian in OpenAIREBittner, Matthias;
Bittner, Matthias
Bittner, Matthias in OpenAIREJungclaus, Johann;
Früh, Barbara; Pankatz, Klaus; Giorgetta, Marco; Reick, Christian; Legutke, Stephanie; Esch, Monika; Gayler, Veronika;Jungclaus, Johann
Jungclaus, Johann in OpenAIREHaak, Helmuth;
de Vrese, Philipp; Raddatz, Thomas;Haak, Helmuth
Haak, Helmuth in OpenAIREMauritsen, Thorsten;
Mauritsen, Thorsten
Mauritsen, Thorsten in OpenAIREvon Storch, Jin-Song;
Behrens, Jörg;von Storch, Jin-Song
von Storch, Jin-Song in OpenAIREBrovkin, Victor;
Claussen, Martin; Crueger, Traute; Fast, Irina;Brovkin, Victor
Brovkin, Victor in OpenAIREFiedler, Stephanie;
Fiedler, Stephanie
Fiedler, Stephanie in OpenAIREHagemann, Stefan;
Hohenegger, Cathy; Jahns, Thomas; Kloster, Silvia; Kinne, Stefan;Hagemann, Stefan
Hagemann, Stefan in OpenAIRELasslop, Gitta;
Kornblueh, Luis;Lasslop, Gitta
Lasslop, Gitta in OpenAIREMarotzke, Jochem;
Marotzke, Jochem
Marotzke, Jochem in OpenAIREMatei, Daniela;
Meraner, Katharina; Mikolajewicz, Uwe; Modali, Kameswarrao; Müller, Wolfgang; Nabel, Julia;Matei, Daniela
Matei, Daniela in OpenAIRENotz, Dirk;
Notz, Dirk
Notz, Dirk in OpenAIREPeters-von Gehlen, Karsten;
Peters-von Gehlen, Karsten
Peters-von Gehlen, Karsten in OpenAIREPincus, Robert;
Pincus, Robert
Pincus, Robert in OpenAIREPohlmann, Holger;
Pohlmann, Holger
Pohlmann, Holger in OpenAIREPongratz, Julia;
Rast, Sebastian; Schmidt, Hauke; Schnur, Reiner; Schulzweida, Uwe; Six, Katharina;Pongratz, Julia
Pongratz, Julia in OpenAIREStevens, Bjorn;
Voigt, Aiko; Roeckner, Erich;Stevens, Bjorn
Stevens, Bjorn in OpenAIREProject: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.DKRZ.MPI-ESM1-2-HR.ssp126' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The MPI-ESM1.2-HR climate model, released in 2017, includes the following components: aerosol: none, prescribed MACv2-SP, atmos: ECHAM6.3 (spectral T127; 384 x 192 longitude/latitude; 95 levels; top level 0.01 hPa), land: JSBACH3.20, landIce: none/prescribed, ocean: MPIOM1.63 (tripolar TP04, approximately 0.4deg; 802 x 404 longitude/latitude; 40 levels; top grid cell 0-12 m), ocnBgchem: HAMOCC6, seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model). The model was run by the Deutsches Klimarechenzentrum, Hamburg 20146, Germany (DKRZ) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, landIce: none, ocean: 50 km, ocnBgchem: 50 km, seaIce: 50 km.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:Zenodo Authors: Idiano D'Adamo; Gastaldi, Massimo; Ioppolo, Giuseppe; Morone, Piergiuseppe;The aggregation of data concerned 103 Italian cities and for each city 45 indicators were considered
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2022Publisher:Zenodo Authors:Negri, Valentina;
Negri, Valentina
Negri, Valentina in OpenAIREVázquez, Daniel;
Sales-Pardo, Marta; Guimerà, Roger; +1 AuthorsVázquez, Daniel
Vázquez, Daniel in OpenAIRENegri, Valentina;
Negri, Valentina
Negri, Valentina in OpenAIREVázquez, Daniel;
Sales-Pardo, Marta; Guimerà, Roger;Vázquez, Daniel
Vázquez, Daniel in OpenAIREGuillén-Gosálbez, Gonzalo;
Guillén-Gosálbez, Gonzalo
Guillén-Gosálbez, Gonzalo in OpenAIREDataset of process simulations results of the natural gas sweetening and flue gas treatment (first and second sheet, respectively as indicated by the sheet name in the .xlsx file). The dataset refers to the publication Bayesian Symbolic Learning to Build Analytical Correlations from Rigorous Process Simulations: Application to CO2 Capture Technologies by V. Negri, Vàzquey D., Sales-Pardo, Marta, Guimerà, R. and Guillén-Gosàlbez, G. The training and testing dataset are used to generate the figures in the main manuscript and supplementary information.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:Zenodo Authors:Minx, Jan C.;
Minx, Jan C.
Minx, Jan C. in OpenAIRELamb, William F.;
Lamb, William F.
Lamb, William F. in OpenAIREAndrew, Robbie M.;
Andrew, Robbie M.
Andrew, Robbie M. in OpenAIRECanadell, Josep G.;
+13 AuthorsCanadell, Josep G.
Canadell, Josep G. in OpenAIREMinx, Jan C.;
Minx, Jan C.
Minx, Jan C. in OpenAIRELamb, William F.;
Lamb, William F.
Lamb, William F. in OpenAIREAndrew, Robbie M.;
Andrew, Robbie M.
Andrew, Robbie M. in OpenAIRECanadell, Josep G.;
Crippa, Monica;Canadell, Josep G.
Canadell, Josep G. in OpenAIREDöbbeling, Niklas;
Döbbeling, Niklas
Döbbeling, Niklas in OpenAIREForster, Piers;
Guizzardi, Diego;Forster, Piers
Forster, Piers in OpenAIREOlivier, Jos;
Olivier, Jos
Olivier, Jos in OpenAIREPongratz, Julia;
Pongratz, Julia
Pongratz, Julia in OpenAIREReisinger, Andy;
Reisinger, Andy
Reisinger, Andy in OpenAIRERigby, Matthew;
Rigby, Matthew
Rigby, Matthew in OpenAIREPeters, Glen;
Peters, Glen
Peters, Glen in OpenAIRESaunois, Marielle;
Saunois, Marielle
Saunois, Marielle in OpenAIRESmith, Steven J.;
Smith, Steven J.
Smith, Steven J. in OpenAIRESolazzo, Efisio;
Solazzo, Efisio
Solazzo, Efisio in OpenAIRETian, Hanqin;
Tian, Hanqin
Tian, Hanqin in OpenAIREComprehensive and reliable information on anthropogenic sources of greenhouse gas emissions is required to track progress towards keeping warming well below 2°C as agreed upon in the Paris Agreement. Here we provide a dataset on anthropogenic GHG emissions 1970-2019 with a broad country and sector coverage. We build the dataset from recent releases from the “Emissions Database for Global Atmospheric Research” (EDGAR) for CO2 emissions from fossil fuel combustion and industry (FFI), CH4 emissions, N2O emissions, and fluorinated gases and use a well-established fast-track method to extend this dataset from 2018 to 2019. We complement this with information on net CO2 emissions from land use, land-use change and forestry (LULUCF) from three available bookkeeping models.
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visibility 3Kvisibility views 3,130 download downloads 1,221 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2015Embargo end date: 04 Jun 2015Publisher:Dryad Piper, Adam T.; Manes, Costantino; Siniscalchi, Fabio; Marion, Andrea; Wright, Rosalind M.; Kemp, Paul S.;doi: 10.5061/dryad.c77jn
Anthropogenic structures (e.g. weirs and dams) fragment river networks and restrict the movement of migratory fish. Poor understanding of behavioural response to hydrodynamic cues at structures currently limits the development of effective barrier mitigation measures. This study aimed to assess the effect of flow constriction and associated flow patterns on eel behaviour during downstream migration. In a field experiment, we tracked the movements of 40 tagged adult European eels (Anguilla anguilla) through the forebay of a redundant hydropower intake under two manipulated hydrodynamic treatments. Interrogation of fish trajectories in relation to measured and modelled water velocities provided new insights into behaviour, fundamental for developing passage technologies for this endangered species. Eels rarely followed direct routes through the site. Initially, fish aligned with streamlines near the channel banks and approached the intake semi-passively. A switch to more energetically costly avoidance behaviours occurred on encountering constricted flow, prior to physical contact with structures. Under high water velocity gradients, fish then tended to escape rapidly back upstream, whereas exploratory ‘search’ behaviour was common when acceleration was low. This study highlights the importance of hydrodynamics in informing eel behaviour. This offers potential to develop behavioural guidance, improve fish passage solutions and enhance traditional physical screening. Fish_detections_UL_CHFish positions derived from acoustic telemetry contained within excel file with 5 columns. 'Record' denotes tag detection numbered consecutively in sequence; 'tag_number' denotes the fish identification number; ‘PosX’ denotes fish x coordinate in UTM; ‘PosY’ denotes fish y coordinate in UTM, ‘Treatment’ denotes experimental treatment
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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visibility 25visibility views 25 download downloads 3 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:Zenodo Funded by:EC | HELIXEC| HELIXAuthors:Thiery, Wim;
Lange, Stefan; Rogelj, Joeri; Schleussner, Carl-Friedrich; +33 AuthorsThiery, Wim
Thiery, Wim in OpenAIREThiery, Wim;
Lange, Stefan; Rogelj, Joeri; Schleussner, Carl-Friedrich; Gudmundsson, Lukas; Seneviratne, Sonia I.; Andrijevic, Marina; Frieler, Katja; Emanuel, Kerry; Geiger, Tobias; Bresch, David N.; Zhao, Fang; Willner, Sven N.; Büchner, Matthias; Volkholz, Jan; Bauer, Nico; Chang, Jinfeng; Ciais, Philippe; Dury, Marie; François, Louis; Grillakis, Manolis; Gosling, Simon N.; Hanasaki, Naota; Hickler, Thomas; Huber, Veronika; Ito, Akihiko; Jägermeyr, Jonas; Khabarov, Nikolay; Koutroulis, Aristeidis; Liu, Wenfeng; Lutz, Wolfgang; Mengel, Matthias; Müller, Christoph; Ostberg, Sebastian; Reyer, Christopher P. O.; Stacke, Tobias; Wada, Yoshihide;Thiery, Wim
Thiery, Wim in OpenAIREThis data set contains the essential files used as input for the analysis, intermediate files produced during the analysis, and the key output fields. The code of the analysis is available here: https://github.com/VUB-HYDR/2021_Thiery_etal_Science Input fields: - isimip.zip: Postprocessed ISIMIP2b simulation output. This data set is very similar to the data presented in Lange et al. (2020 Earth's Future) but includes selected additional impact models and scenarios (notably RCP8.5). This data set also includes the gridded population data. - GMT_50pc_manualoutput_4pathways.xlsx: Global mean temperature anomaly trajectories from the IPCC SR15 - wcde_data.xlsx: postprocessed cohort size data originally obtained from the Wittgenstein Centre Human Capital Data Explorer. - WPP2019_MORT_F16_1_LIFE_EXPECTANCY_BY_AGE_BOTH_SEXES.xlsx: Postprocessed life expectancy data originally obtained from the UNited Nations World Population Programme Intermediate files *only use if you're interested in reproducing the results*: - workspaces.zip: Postprocessed ISIMIP2b simulation output. These matlab workspaces contain data on land area annually exposed to extreme events which is stored in a format designed to speed up the analysis. - mw_isimip.mat: ISIMIP2 simulations metadata (e.g. model, gcm and rcp name per simulation) - mw_countries.mat: information on the countries used in the analysis (e.g. border polygon coordinates) - mw_exposure.mat: age-dependent exposure computed from the ISIMIP and population data - mw_exposure_pic.mat: pre-industrial control age-dependent exposure computed from the ISIMIP and population data - mw_exposure_pic_coldwaves.mat: pre-industrial control age-dependent exposure to coldwaves computed from the ISIMIP and population data Output of the analysis: - mw_output.mat: Matlab workspace containing all variables produced during the analysis presented in thepaper. Use this file if you wish to look up certain numbers or want to use the study results for further analysis.
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visibility 317visibility views 317 download downloads 197 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2024Publisher:Zenodo Authors:Figgener, Jan;
Figgener, Jan
Figgener, Jan in OpenAIREHaberschusz, David;
Haberschusz, David
Haberschusz, David in OpenAIREWessels, Oliver;
Wessels, Oliver
Wessels, Oliver in OpenAIREKairies, Kai-Philipp;
+3 AuthorsKairies, Kai-Philipp
Kairies, Kai-Philipp in OpenAIREFiggener, Jan;
Figgener, Jan
Figgener, Jan in OpenAIREHaberschusz, David;
Haberschusz, David
Haberschusz, David in OpenAIREWessels, Oliver;
Wessels, Oliver
Wessels, Oliver in OpenAIREKairies, Kai-Philipp;
Kairies, Kai-Philipp
Kairies, Kai-Philipp in OpenAIREBors, Jakob;
Bors, Jakob
Bors, Jakob in OpenAIREvan Ouwerkerk, Jonas;
van Ouwerkerk, Jonas
van Ouwerkerk, Jonas in OpenAIRESauer, Dirk Uwe;
Sauer, Dirk Uwe
Sauer, Dirk Uwe in OpenAIREThe dataset accompanies the Nature Energy publication by Figgener et al. (2024), Multi-year field measurements of home storage systems and their use in capacity estimation, DOI 10.1038/s41560-024-01620-9. In addition, we use the dataset in Figgener et al. (2024), Degradation mode estimation using reconstructed open circuit voltage curves from multi-year home storage field data, DOI 10.48550/arXiv.2411.08025 The ISEA / CARL of RWTH Aachen University measured 21 private home storage systems in Germany over up to eight years from 2015 to 2022. All these storage systems are combined with residential photovoltaic systems to increase self-consumption. The measured quantities published are system-level battery current, voltage, power, battery pack housing temperature, and room temperature. The sample rate is one second. The dataset consists of 106 system years, 14 billion data points, and 1,270 monthly files stored in 21 system folders. Use the data as follows:1. Download the data (Data_ID_01.zip to Data_ID_21.zip) and the belonging repository (Metadata_and_Code.zip) 2. Uncompress the files so that the uncompressed folders have the same name as the .zip files. 3. Copy all data folders in folder "Metadata_and_Code/00_Data/01_Operational_Data". Read and execute the file "StartUp_Read_and_Execute.m" and stay in this folder for any script you execute. In addition, a detailed description of the dataset and how to use it can be found in the supplementary information of the publication.
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For further information contact us at helpdesk@openaire.eu1 citations 1 popularity Average influence Average impulse Average Powered by BIP!
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Collection , Dataset 2023Publisher:PANGAEA Authors:Ausems, Anne;
Kuepper, Nadja; Archuby, Diego; Braun, Christina; +15 AuthorsAusems, Anne
Ausems, Anne in OpenAIREAusems, Anne;
Kuepper, Nadja; Archuby, Diego; Braun, Christina; Gębczyński, Andrzej; Gladbach, Anja; Hahn, Steffen;Ausems, Anne
Ausems, Anne in OpenAIREJadwiszczak, Piotr;
Krämer, Philipp; Libertelli, Marcela; Lorenz, Stefan; Richter, Benjamin; Ruß, Anja; Schmoll, Tim; Thorn, Simon; Turner, John;Jadwiszczak, Piotr
Jadwiszczak, Piotr in OpenAIREWojczulanis-Jakubas, Katarzyna;
Wojczulanis-Jakubas, Katarzyna
Wojczulanis-Jakubas, Katarzyna in OpenAIREJakubas, Dariusz;
Jakubas, Dariusz
Jakubas, Dariusz in OpenAIREQuillfeldt, Petra;
Quillfeldt, Petra
Quillfeldt, Petra in OpenAIREThis data set describes the population dynamics of Wilson's Storm Petrels (Oceanites oceanicus) at King George Island (Isla 25 de Mayo, Antarctica) over a forty year period (1978 – 2020). It includes all available data on Wilson's Storm Petrels from two colonies: around the Argentinian Base Carlini (62°14′S, 58°40′W; CA, formerly called Base Jubany) and the Henryk Arctowski Polish Antarctic Station (62°09′S, 58°27′W; HA). Data on population productivity (number of nests, eggs, chicks and fledglings) was collected by regular visits to the colonies and searching for nest burrows, or monitoring of the egg or chick if found. Data on adult abundance and estimated age categories (i.e., presence of foot spots; Quillfeldt et al. (2000, doi:10.1007/s003000000167) were collected at CA by using the same size mistnet every study year in the same location within the breeding colony. Chicks were measured regularly (varying intervals depending on the study) at both CA and HA. Chick tarsus was measured using callipers (vernier or digital depending on the study year) to the nearest 0.1 mm, chick wing length was measured using wing rulers to the nearest 1 mm, and chick body mass was measured using mechanical or digital scales depending on the study year to the nearest 0.1 g. Chick growth rates were calculated based on the linear growth period following Ausems et al. (2020, doi:10.1016/j.scitotenv.2020.138768). Chick food loads (g) were recorded at CA and determined based on changes in chick body mass on consecutive days (Gladbach et al. (2009, doi:10.1007/s00300-009-0628-z); Kuepper et al. (2018, doi:10.1016/j.cbpa.2018.06.018). This study was further supported by the Erasmus+ programm and thee German Academic Exchange Service (DAAD)
PANGAEA arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceCollection . 2023License: CC BY SAData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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more_vert PANGAEA arrow_drop_down PANGAEA - Data Publisher for Earth and Environmental ScienceCollection . 2023License: CC BY SAData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2023Publisher:World Data Center for Climate (WDCC) at DKRZ Authors:Neubauer, David;
Neubauer, David
Neubauer, David in OpenAIREFerrachat, Sylvaine;
Siegenthaler-Le Drian, Colombe; Stoll, Jens; +18 AuthorsFerrachat, Sylvaine
Ferrachat, Sylvaine in OpenAIRENeubauer, David;
Neubauer, David
Neubauer, David in OpenAIREFerrachat, Sylvaine;
Siegenthaler-Le Drian, Colombe; Stoll, Jens; Folini, Doris Sylvia;Ferrachat, Sylvaine
Ferrachat, Sylvaine in OpenAIRETegen, Ina;
Tegen, Ina
Tegen, Ina in OpenAIREWieners, Karl-Hermann;
Wieners, Karl-Hermann
Wieners, Karl-Hermann in OpenAIREMauritsen, Thorsten;
Stemmler, Irene; Barthel, Stefan; Bey, Isabelle;Mauritsen, Thorsten
Mauritsen, Thorsten in OpenAIREDaskalakis, Nikos;
Heinold, Bernd;Daskalakis, Nikos
Daskalakis, Nikos in OpenAIREKokkola, Harri;
Kokkola, Harri
Kokkola, Harri in OpenAIREPartridge, Daniel;
Rast, Sebastian; Schmidt, Hauke;Partridge, Daniel
Partridge, Daniel in OpenAIRESchutgens, Nick;
Stanelle, Tanja;Schutgens, Nick
Schutgens, Nick in OpenAIREStier, Philip;
Stier, Philip
Stier, Philip in OpenAIREWatson-Parris, Duncan;
Watson-Parris, Duncan
Watson-Parris, Duncan in OpenAIRELohmann, Ulrike;
Lohmann, Ulrike
Lohmann, Ulrike in OpenAIREProject: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.AerChemMIP.HAMMOZ-Consortium.MPI-ESM-1-2-HAM' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The MPI-ESM1.2-HAM climate model, released in 2017, includes the following components: aerosol: HAM2.3, atmos: ECHAM6.3 (spectral T63; 192 x 96 longitude/latitude; 47 levels; top level 0.01 hPa), atmosChem: sulfur chemistry (unnamed), land: JSBACH 3.20, ocean: MPIOM1.63 (bipolar GR1.5, approximately 1.5deg; 256 x 220 longitude/latitude; 40 levels; top grid cell 0-12 m), ocnBgchem: HAMOCC6, seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model). The model was run by the ETH Zurich, Switzerland; Max Planck Institut fur Meteorologie, Germany; Forschungszentrum Julich, Germany; University of Oxford, UK; Finnish Meteorological Institute, Finland; Leibniz Institute for Tropospheric Research, Germany; Center for Climate Systems Modeling (C2SM) at ETH Zurich, Switzerland (HAMMOZ-Consortium) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 250 km, ocnBgchem: 250 km, seaIce: 250 km.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
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For further information contact us at helpdesk@openaire.euResearch data keyboard_double_arrow_right Dataset 2021Publisher:Zenodo Authors:S��sser, Diana;
al Rakouki, Housam;S��sser, Diana
S��sser, Diana in OpenAIRELilliestam, Johan;
Lilliestam, Johan
Lilliestam, Johan in OpenAIREQTDIAN - Quantification of Technological DIffusion and sociAl constraiNts - is a toolbox of qualitative and quantitative descriptions of socio-technical and political aspects of the energy transition that influence the overall potential, the rate of energy-related technology and service diffusion and the design of the future energy system. The output of QTIDIAN is empirically founded datasets of social and political drivers and barriers of the transition, both in the form of raw data describing past and current developments and manipulated to constitute consistent quantifications of the storylines. Here you can download the data for six QTDIAN themes: Socially feasible scaling of energy technologies Policy preferences & dynamics Barriers to infrastructural development (wind energy, grid development) Citizen energy Private energy demand Further information on the QTDIAN modelling toolbox and the data can be found in the SENTINEL Deliverable 2.3 and Deliverable 2.4: S��sser, D., al Rakouki, H., & Lilliestam, J.(2021). The QTDIAN modelling toolbox���Quantification of social drivers and constraints of the diffusion of energy technologies. Deliverable 2.3. Sustainable Energy Transitions Laboratory (SENTINEL) project. Potsdam: Institute for Advanced Sustainability Studies (IASS). S��sser, D., Pickering, B., Chatterjee, S., Oreggioni, G., Stavrakas, V., & Lilliestam, J.(2021). Integration of socio-technological transition constraints into energy demand and systems models. Deliverable 2.5. Sustainable Energy Transitions Laboratory (SENTINEL) project. Potsdam: Institute for Advanced Sustainability Studies (IASS).
ZENODO arrow_drop_down Smithsonian figshareDataset . 2021License: CC BYData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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visibility 252visibility views 252 download downloads 85 Powered bymore_vert ZENODO arrow_drop_down Smithsonian figshareDataset . 2021License: CC BYData sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
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