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  • Meteo measurements at the Sand Motor. Air temperature, humidity, pressure, solar radiation, precipitation, wind speed and wind direction are measured. Contributor: Verheijen, A.H. (Anne) [orcid:0000-0002-2131-7619]

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    Authors: Nardone, Jessica A; Patel, Shrey; Siegel, Kyle R; Tedesco, Dana; +7 Authors

    Barnacles are dominant members of marine intertidal communities. Their success depends on firm attachment provided by their proteinaceous adhesive and protection imparted by their calcified shell plates. Little is known about how variations in the environment affect adhesion and shell formation processes in barnacles. Increased levels of atmospheric CO2 have led to a reduction in the pH of ocean waters (i.e., ocean acidification), a trend that is expected to continue into the future. Here, we assessed if a reduction in seawater pH, at levels predicted within the next 200 years, would alter physiology, adhesion, and shell formation in the cosmopolitan barnacle Amphibalanus (=Balanus) amphitrite. Juvenile barnacles, settled on silicone substrates, were exposed to one of three static levels of pHT, 8.01, 7.78, or 7.50, for 13 weeks. We found that barnacles were robust to reduced pH, with no effect of pH on physiological metrics (mortality, tissue mass, and presence of eggs). Likewise, adhesive properties (adhesion strength and adhesive plaque gross morphology) were not affected by reduced pH. Shell formation, however, was affected by seawater pH. Shell mass and base plate area were higher in barnacles exposed to reduced pH; barnacles grown at pHT 8.01 exhibited approximately 30% lower shell mass and 20% smaller base plate area as compared to those at pHT 7.50 or 7.78. Enhanced growth at reduced pH appears to be driven by the increased size of the calcite crystals that comprise the shell. Despite enhanced growth, mechanical properties of the base plate (but not the parietal plates) were compromised at the lowest pH level. Barnacle base plates at pHT 7.50 broke more easily and crack propagation, measured through microhardness testing, was significantly affected by seawater pH. Other shell metrics (plate thickness, relative crystallinity, and atomic disorder) were not affected by seawater pH. Hence, a reduction in pH resulted in larger barnacles but with base plates that would crack more readily. It is yet to be determined if such changes would alter the survival of A. amphitrite in the field, but changes in the abundance of this ecologically dominant species would undoubtedly affect the composition of biofouling communities. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2019) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2020-09-18.

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    B2FIND
    Dataset . 2018
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2018
    License: CC BY
    Data sources: PANGAEA
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    PANGAEA
    Dataset . 2018
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2018
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2018
      License: CC BY
      Data sources: PANGAEA
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      PANGAEA
      Dataset . 2018
      Data sources: PANGAEA
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    Authors: Lucas Moreau (11607577); Evelyne Thiffault (10700505); Dominic Cyr (4836624); Yan Boulanger (2909306);

    Dataset for the article: How can the forest sector maintain its mitigation potential in a changing climate ? Case studies of boreal and northern temperate forests in eastern Canada.

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    figshare
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    figshare
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    Smithsonian figshare
    Dataset . 2021
    License: CC BY
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      figshare
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      figshare
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      Smithsonian figshare
      Dataset . 2021
      License: CC BY
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  • Authors: GULLO, P.; CORTELLA, G.; POLZOT, A.;

    Carbon dioxide (CO2, R744) is an environmentally friendly refrigerant, which is widely used in supermarket refrigeration systems located in cold weather sites. Its use at high outdoor temperatures still requires some additional investigations to accomplish performance similar to the one obtained by employing the conventional working fluids. This paper deals with the theoretical comparison in terms of both annual energy consumption and Total Equivalent Warming Impact (TEWI) of different commercial R744 refrigeration cycles operating in five different warm climates. An innovative CO2 direct expansion (DX) configuration, which serves both the medium temperature (MT) load and the low temperature (LT) one, is also considered. Taking into account the running modes of a typical European supermarket and a R404A multiplex configuration as the baseline, the results showed that enhanced R744 refrigeration technologies are capable of dropping the energy consumption and the TEWI by at least 2.8% and 31.1%, respectively.

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    Authors: Hysa, Artan;

    The data shared in this package delivers the wildfire ignition probability and spreading capacity of vegetated surfaces in Romania following the method developed by Hysa and Baskaya (2019, https://doi.org/10.1007/s40808-018-0519-9). The model relies on remotely sensed free data that covers the time-lapse between 2015-2020. Geospatial information about sixteen criteria about anthropogenic, hydro-meteorological, geophysical, and fuel properties of Romanian territory are considered here. Raw data regarding each criterion is acquired for free from different online databases. The attribute table of the shared shapefile includes all inventory measurements per each criterion. It consist of 70410 point geometries in total representing 1km2 each, covering all vegetated surfaces of Romania. This data consist of a geospatial points layer (shp file), which deliver both the multi-criteria inventory records and the calculated wildfire ignition probability and wildfire spreading capacity (WIPI/WSCI) of the Romanian vegetated surfaces. The distance between points is 1km. The file consists of 70410 points in total, that overlap with the vegetated surfaces as derived from CORINE Land Cover data of 2018.

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    B2FIND
    Dataset . 2021
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2021
    License: CC BY
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2021
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2021
      License: CC BY
      Data sources: PANGAEA
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    Author: Daniel Vázquez Pombo (dvapo@elektro.dtu.dk) ------------------------------------------------------------------------------- This dataset corresponds to the results of the paper titled: "Multi-Horizon Data-Driven Wind Power Forecast: From Nowcast to 2 Days-Ahead" 4th International Conference on Smart Energy Systems and Technologies (SEST) - 2021 -> https://sites.univaasa.fi/sest2021/ Submmited: Dec 2020 Accepted: Feb 2021 Published: Sep 2021 ------------------------------------------------------------------------------- The folder contains all the results presented in the paper, for clarity. Additional resources might be supplied under request. -------------------------------------------------------------------------------

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    Smithsonian figshare
    Dataset . 2021
    License: CC BY SA
    https://dx.doi.org/10.11583/dt...
    Dataset . 2021
    License: CC BY SA
    Data sources: Datacite
    https://dx.doi.org/10.11583/dt...
    Dataset . 2021
    License: CC BY SA
    Data sources: Datacite
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      Smithsonian figshare
      Dataset . 2021
      License: CC BY SA
      https://dx.doi.org/10.11583/dt...
      Dataset . 2021
      License: CC BY SA
      Data sources: Datacite
      https://dx.doi.org/10.11583/dt...
      Dataset . 2021
      License: CC BY SA
      Data sources: Datacite
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    Authors: John, Jasmin G; Blanton, Chris; McHugh, Colleen; Radhakrishnan, Aparna; +17 Authors

    Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.NOAA-GFDL.GFDL-ESM4.ssp245' 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 GFDL-ESM4 climate model, released in 2018, includes the following components: aerosol: interactive, atmos: GFDL-AM4.1 (Cubed-sphere (c96) - 1 degree nominal horizontal resolution; 360 x 180 longitude/latitude; 49 levels; top level 1 Pa), atmosChem: GFDL-ATMCHEM4.1 (full atmospheric chemistry), land: GFDL-LM4.1, landIce: GFDL-LM4.1, ocean: GFDL-OM4p5 (GFDL-MOM6, tripolar - nominal 0.5 deg; 720 x 576 longitude/latitude; 75 levels; top grid cell 0-2 m), ocnBgchem: GFDL-COBALTv2, seaIce: GFDL-SIM4p5 (GFDL-SIS2.0, tripolar - nominal 0.5 deg; 720 x 576 longitude/latitude; 5 layers; 5 thickness categories). The model was run by the National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory, Princeton, NJ 08540, USA (NOAA-GFDL) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, landIce: 100 km, ocean: 50 km, ocnBgchem: 50 km, seaIce: 50 km.

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    World Data Center for Climate
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      World Data Center for Climate
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Jiang, Hou; Lu, Ning;

    Surface solar radiation drives the water cycle and energy exchange on the earth's surface, and its diffuse component can promote carbon uptake in ecosystems by increasing the plant productivity. The accurate knowledge of their spatial distribution is of great importance to many studies and applications, such as the estimation of agricultural yield, carbon dynamics of terrestrial systems, site selection of solar power plants, as well as trends of regional climate changes. Therefore, we produce the hourly surface radiation datasets based on the hourly Multi-functional Transport Satellite (MTSAT) satellite imagery and the ground observations from the China Meteorology Administration (CMA) through deep learning techniques. The deep network is trained using training samples in 2008, and then utilized to generate the hourly radiation for other years. This dataset provides the gridded surface global and diffuse solar radiation in 2015 within 71.025°E - 141.025°E and 14.975°N - 59.975°N with an increment of 0.05°. Both the direct predicted hourly values and the integrated daily and monthly total values are available. The dataset should be useful for the analysis of the regional differences and temporal cycles of solar radiation in fine scales, and the impact of diffuse radiation on plant growth etc.

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    B2FIND
    Dataset . 2019
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2019
    License: CC BY NC SA
    Data sources: PANGAEA
    PANGAEA - Data Publisher for Earth and Environmental Science
    Dataset . 2019
    License: CC BY NC SA
    Data sources: Datacite
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      B2FIND
      Dataset . 2019
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2019
      License: CC BY NC SA
      Data sources: PANGAEA
      PANGAEA - Data Publisher for Earth and Environmental Science
      Dataset . 2019
      License: CC BY NC SA
      Data sources: Datacite
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    Authors: Lefevre, Dominique; Libes, Maurice; Mallarino, Didier; Bernardet, Karim; +4 Authors

    The European Multidisciplinary Seafloor and water column Observatory (EMSO-ERIC, https://emso.eu/) is a research infrastructure distributed throughout Europe for seabed and water column observatories. It aims to further explore the oceans, better understand the phenomena that occur on the seabed, and elucidate the critical role that these phenomena play in global Earth systems. This observatory is based on observation sites (or nodes) that have been deployed in strategic locations in European seas, from the Arctic to the Atlantic, from the Mediterranean to the Black Sea. There are currently eleven deepwater nodes plus four shallow water test nodes. EMSO-Western Ligurian Sea Node (https://www.emso-fr.org/fr) is a second generation permanent submarine observatory deployed offshore of Toulon, France, as a follow up of the pioneering ANTARES neutrino telescope. This submarine network, deployed at a depth of 2450m, is part of KM3NeT (https://www.km3net.org/) which has a modular topology designed to connect up to 120 neutrino detection units, i.e. ten times more than ANTARES. The Earth and Sea Science (ESS) instrumentation connected to KM3NeT is based on two complementary components: an Instrumented Interface Module (MII) and an autonomous mooring line (ALBATROSS). The ALBATROSS line is an inductive instrumented mooring line (2000 m) composed of an acoustic communication system, two inductive cables equipped with CTD-O2 sensors, current meters and two instrumented buoys. The MII and the ALMBATROSS mooring line communicate through an acoustic link. The MII is connected to an electro-optical cable via the KM3NeT node allowing the data transfer from and to the land based controlled room.

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    https://dx.doi.org/10.17882/95...
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    SEANOE
    Dataset . 2023
    License: CC BY
    Data sources: SEANOE
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      https://dx.doi.org/10.17882/95...
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      SEANOE
      Dataset . 2023
      License: CC BY
      Data sources: SEANOE
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    Authors: National Inventory Submissions 2019 to the United Nations Framework Convention on Climate Change;

    This dataset presents trends in man-made emissions of major greenhouse gases and emissions by gas.

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    https://stats.oecd.org/Index.a...
    Dataset . 2019
    License: See "Other relevant information"
    Data sources: EnerMaps
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      https://stats.oecd.org/Index.a...
      Dataset . 2019
      License: See "Other relevant information"
      Data sources: EnerMaps
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  • Meteo measurements at the Sand Motor. Air temperature, humidity, pressure, solar radiation, precipitation, wind speed and wind direction are measured. Contributor: Verheijen, A.H. (Anne) [orcid:0000-0002-2131-7619]

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    Authors: Nardone, Jessica A; Patel, Shrey; Siegel, Kyle R; Tedesco, Dana; +7 Authors

    Barnacles are dominant members of marine intertidal communities. Their success depends on firm attachment provided by their proteinaceous adhesive and protection imparted by their calcified shell plates. Little is known about how variations in the environment affect adhesion and shell formation processes in barnacles. Increased levels of atmospheric CO2 have led to a reduction in the pH of ocean waters (i.e., ocean acidification), a trend that is expected to continue into the future. Here, we assessed if a reduction in seawater pH, at levels predicted within the next 200 years, would alter physiology, adhesion, and shell formation in the cosmopolitan barnacle Amphibalanus (=Balanus) amphitrite. Juvenile barnacles, settled on silicone substrates, were exposed to one of three static levels of pHT, 8.01, 7.78, or 7.50, for 13 weeks. We found that barnacles were robust to reduced pH, with no effect of pH on physiological metrics (mortality, tissue mass, and presence of eggs). Likewise, adhesive properties (adhesion strength and adhesive plaque gross morphology) were not affected by reduced pH. Shell formation, however, was affected by seawater pH. Shell mass and base plate area were higher in barnacles exposed to reduced pH; barnacles grown at pHT 8.01 exhibited approximately 30% lower shell mass and 20% smaller base plate area as compared to those at pHT 7.50 or 7.78. Enhanced growth at reduced pH appears to be driven by the increased size of the calcite crystals that comprise the shell. Despite enhanced growth, mechanical properties of the base plate (but not the parietal plates) were compromised at the lowest pH level. Barnacle base plates at pHT 7.50 broke more easily and crack propagation, measured through microhardness testing, was significantly affected by seawater pH. Other shell metrics (plate thickness, relative crystallinity, and atomic disorder) were not affected by seawater pH. Hence, a reduction in pH resulted in larger barnacles but with base plates that would crack more readily. It is yet to be determined if such changes would alter the survival of A. amphitrite in the field, but changes in the abundance of this ecologically dominant species would undoubtedly affect the composition of biofouling communities. In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2019) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2020-09-18.

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    B2FIND
    Dataset . 2018
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2018
    License: CC BY
    Data sources: PANGAEA
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    PANGAEA
    Dataset . 2018
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2018
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2018
      License: CC BY
      Data sources: PANGAEA
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      PANGAEA
      Dataset . 2018
      Data sources: PANGAEA
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Lucas Moreau (11607577); Evelyne Thiffault (10700505); Dominic Cyr (4836624); Yan Boulanger (2909306);

    Dataset for the article: How can the forest sector maintain its mitigation potential in a changing climate ? Case studies of boreal and northern temperate forests in eastern Canada.

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    figshare
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    figshare
    Dataset . 2021
    License: CC BY
    Data sources: Datacite
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    Smithsonian figshare
    Dataset . 2021
    License: CC BY
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      figshare
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      figshare
      Dataset . 2021
      License: CC BY
      Data sources: Datacite
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      Smithsonian figshare
      Dataset . 2021
      License: CC BY
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  • Authors: GULLO, P.; CORTELLA, G.; POLZOT, A.;

    Carbon dioxide (CO2, R744) is an environmentally friendly refrigerant, which is widely used in supermarket refrigeration systems located in cold weather sites. Its use at high outdoor temperatures still requires some additional investigations to accomplish performance similar to the one obtained by employing the conventional working fluids. This paper deals with the theoretical comparison in terms of both annual energy consumption and Total Equivalent Warming Impact (TEWI) of different commercial R744 refrigeration cycles operating in five different warm climates. An innovative CO2 direct expansion (DX) configuration, which serves both the medium temperature (MT) load and the low temperature (LT) one, is also considered. Taking into account the running modes of a typical European supermarket and a R404A multiplex configuration as the baseline, the results showed that enhanced R744 refrigeration technologies are capable of dropping the energy consumption and the TEWI by at least 2.8% and 31.1%, respectively.

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    Authors: Hysa, Artan;

    The data shared in this package delivers the wildfire ignition probability and spreading capacity of vegetated surfaces in Romania following the method developed by Hysa and Baskaya (2019, https://doi.org/10.1007/s40808-018-0519-9). The model relies on remotely sensed free data that covers the time-lapse between 2015-2020. Geospatial information about sixteen criteria about anthropogenic, hydro-meteorological, geophysical, and fuel properties of Romanian territory are considered here. Raw data regarding each criterion is acquired for free from different online databases. The attribute table of the shared shapefile includes all inventory measurements per each criterion. It consist of 70410 point geometries in total representing 1km2 each, covering all vegetated surfaces of Romania. This data consist of a geospatial points layer (shp file), which deliver both the multi-criteria inventory records and the calculated wildfire ignition probability and wildfire spreading capacity (WIPI/WSCI) of the Romanian vegetated surfaces. The distance between points is 1km. The file consists of 70410 points in total, that overlap with the vegetated surfaces as derived from CORINE Land Cover data of 2018.

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    B2FIND
    Dataset . 2021
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2021
    License: CC BY
    Data sources: PANGAEA
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      B2FIND
      Dataset . 2021
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2021
      License: CC BY
      Data sources: PANGAEA
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    Author: Daniel Vázquez Pombo (dvapo@elektro.dtu.dk) ------------------------------------------------------------------------------- This dataset corresponds to the results of the paper titled: "Multi-Horizon Data-Driven Wind Power Forecast: From Nowcast to 2 Days-Ahead" 4th International Conference on Smart Energy Systems and Technologies (SEST) - 2021 -> https://sites.univaasa.fi/sest2021/ Submmited: Dec 2020 Accepted: Feb 2021 Published: Sep 2021 ------------------------------------------------------------------------------- The folder contains all the results presented in the paper, for clarity. Additional resources might be supplied under request. -------------------------------------------------------------------------------

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    Smithsonian figshare
    Dataset . 2021
    License: CC BY SA
    https://dx.doi.org/10.11583/dt...
    Dataset . 2021
    License: CC BY SA
    Data sources: Datacite
    https://dx.doi.org/10.11583/dt...
    Dataset . 2021
    License: CC BY SA
    Data sources: Datacite
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      Smithsonian figshare
      Dataset . 2021
      License: CC BY SA
      https://dx.doi.org/10.11583/dt...
      Dataset . 2021
      License: CC BY SA
      Data sources: Datacite
      https://dx.doi.org/10.11583/dt...
      Dataset . 2021
      License: CC BY SA
      Data sources: Datacite
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    Authors: John, Jasmin G; Blanton, Chris; McHugh, Colleen; Radhakrishnan, Aparna; +17 Authors

    Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.ScenarioMIP.NOAA-GFDL.GFDL-ESM4.ssp245' 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 GFDL-ESM4 climate model, released in 2018, includes the following components: aerosol: interactive, atmos: GFDL-AM4.1 (Cubed-sphere (c96) - 1 degree nominal horizontal resolution; 360 x 180 longitude/latitude; 49 levels; top level 1 Pa), atmosChem: GFDL-ATMCHEM4.1 (full atmospheric chemistry), land: GFDL-LM4.1, landIce: GFDL-LM4.1, ocean: GFDL-OM4p5 (GFDL-MOM6, tripolar - nominal 0.5 deg; 720 x 576 longitude/latitude; 75 levels; top grid cell 0-2 m), ocnBgchem: GFDL-COBALTv2, seaIce: GFDL-SIM4p5 (GFDL-SIS2.0, tripolar - nominal 0.5 deg; 720 x 576 longitude/latitude; 5 layers; 5 thickness categories). The model was run by the National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory, Princeton, NJ 08540, USA (NOAA-GFDL) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, landIce: 100 km, ocean: 50 km, ocnBgchem: 50 km, seaIce: 50 km.

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    World Data Center for Climate
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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      World Data Center for Climate
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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    Authors: Jiang, Hou; Lu, Ning;

    Surface solar radiation drives the water cycle and energy exchange on the earth's surface, and its diffuse component can promote carbon uptake in ecosystems by increasing the plant productivity. The accurate knowledge of their spatial distribution is of great importance to many studies and applications, such as the estimation of agricultural yield, carbon dynamics of terrestrial systems, site selection of solar power plants, as well as trends of regional climate changes. Therefore, we produce the hourly surface radiation datasets based on the hourly Multi-functional Transport Satellite (MTSAT) satellite imagery and the ground observations from the China Meteorology Administration (CMA) through deep learning techniques. The deep network is trained using training samples in 2008, and then utilized to generate the hourly radiation for other years. This dataset provides the gridded surface global and diffuse solar radiation in 2015 within 71.025°E - 141.025°E and 14.975°N - 59.975°N with an increment of 0.05°. Both the direct predicted hourly values and the integrated daily and monthly total values are available. The dataset should be useful for the analysis of the regional differences and temporal cycles of solar radiation in fine scales, and the impact of diffuse radiation on plant growth etc.

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    B2FIND
    Dataset . 2019
    Data sources: B2FIND
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    PANGAEA
    Dataset . 2019
    License: CC BY NC SA
    Data sources: PANGAEA
    PANGAEA - Data Publisher for Earth and Environmental Science
    Dataset . 2019
    License: CC BY NC SA
    Data sources: Datacite
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      B2FIND
      Dataset . 2019
      Data sources: B2FIND
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      PANGAEA
      Dataset . 2019
      License: CC BY NC SA
      Data sources: PANGAEA
      PANGAEA - Data Publisher for Earth and Environmental Science
      Dataset . 2019
      License: CC BY NC SA
      Data sources: Datacite
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    Authors: Lefevre, Dominique; Libes, Maurice; Mallarino, Didier; Bernardet, Karim; +4 Authors

    The European Multidisciplinary Seafloor and water column Observatory (EMSO-ERIC, https://emso.eu/) is a research infrastructure distributed throughout Europe for seabed and water column observatories. It aims to further explore the oceans, better understand the phenomena that occur on the seabed, and elucidate the critical role that these phenomena play in global Earth systems. This observatory is based on observation sites (or nodes) that have been deployed in strategic locations in European seas, from the Arctic to the Atlantic, from the Mediterranean to the Black Sea. There are currently eleven deepwater nodes plus four shallow water test nodes. EMSO-Western Ligurian Sea Node (https://www.emso-fr.org/fr) is a second generation permanent submarine observatory deployed offshore of Toulon, France, as a follow up of the pioneering ANTARES neutrino telescope. This submarine network, deployed at a depth of 2450m, is part of KM3NeT (https://www.km3net.org/) which has a modular topology designed to connect up to 120 neutrino detection units, i.e. ten times more than ANTARES. The Earth and Sea Science (ESS) instrumentation connected to KM3NeT is based on two complementary components: an Instrumented Interface Module (MII) and an autonomous mooring line (ALBATROSS). The ALBATROSS line is an inductive instrumented mooring line (2000 m) composed of an acoustic communication system, two inductive cables equipped with CTD-O2 sensors, current meters and two instrumented buoys. The MII and the ALMBATROSS mooring line communicate through an acoustic link. The MII is connected to an electro-optical cable via the KM3NeT node allowing the data transfer from and to the land based controlled room.

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    https://dx.doi.org/10.17882/95...
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    SEANOE
    Dataset . 2023
    License: CC BY
    Data sources: SEANOE
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      https://dx.doi.org/10.17882/95...
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      SEANOE
      Dataset . 2023
      License: CC BY
      Data sources: SEANOE
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    Authors: National Inventory Submissions 2019 to the United Nations Framework Convention on Climate Change;

    This dataset presents trends in man-made emissions of major greenhouse gases and emissions by gas.

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    https://stats.oecd.org/Index.a...
    Dataset . 2019
    License: See "Other relevant information"
    Data sources: EnerMaps
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      https://stats.oecd.org/Index.a...
      Dataset . 2019
      License: See "Other relevant information"
      Data sources: EnerMaps
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