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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.

This Excel model encodes the analytical capability required to undertake an application of the adapted National Infrastructure Systems Modelling (NISMOD) capability, which has been developed by the Infrastructure Transitions Research Consortium (ITRC) - a UK based research consortium, led by the University of Oxford. Through a partnership between the United Nations Office for Project Service (UNOPS) and the ITRC, an initial national infrastructure assessment for Curaçao, known as Evidence-Based Infrastrastucture Assessment, has been performed. The focus of this model lies on one priority sector for the SIDS Curaçao: 'Waste Management'.

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.

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.

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

This Excel file contains two spread sheets. The first contains observed and projected climate data for Gavin Prairie, the site of the Cypripedium candidum and C. parviflorum populations, while the second contains observed and projected climate data for the Ophrys sphegodes site. Legends are included on each spreadsheet.

It shows point estimates for national GHG emissions (total emissions and seven agricultural activities) from 1978 to 2016 in China.

The Media and Climate Change Observatory Data monitors 74 sources (across newspapers, radio and TV) in 38 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://sciencepolicy.colorado.edu/icecaps/research/media_coverage/index.html. These data include Excel (.xlsx), CSV (.csv), and plain-text README files (.txt).

We include one dataset with demographic data for birds, called RCW_demo_data. Each row in this csv file represents an individual x year combination, and columns include information about individual and territory characteristics in that year, as well as various vital rates. For reproductive vital rates, we include these rates only for female breeders. Thus, reproductive vital rates such as “successfirstnest” will be NA (indicating missing data) for all males and for female non-breeders. Each row includes a climate reference number (“clim.group”) that allows the demographic data to be matched with the climate data in the climate files (see below for more description about these climate data). Below we list each column individually. Year: year in which data were collected Surtonext: did this individual survive to the next breeding season (1) or not (0)? Nohelp: how many helpers were present in this territory? Firstnestattempt_bin: did this breeding female initiate a nest in that year’s breeding season? 1 indicates yes, 0 indicates no. Morenestattempt_bin: did this breeding female initiate more than one nest in that years breeding season? 1 indicates yes, 0 no. Fledgedfirstnest: how many fledged from the first nest. Fledgedlaternest: how many fledged from any later nests. Eggsfirstattempt: how many eggs in the first nest. Eggslaterattempt: how many eggs in the first nest. Clim.group: a grouping variable that matches the clim.group variable in the climate datasets. Note that the demographic data contains a space, the climate datasets a period, but SH 146 is the same climate grouping as SH.146. Site: one of SH, EG, or CL, representing Sandhills, Eglin, or Camp Lejeune Numericage: age of the bird Binned status: one of Breeder, Helper or Floater (B, H, or F). Sex: F or M Numericmalemateage: age of the male breeder which which a female bred. Only recorde for breeding females. Successfirstnest_bin: was the first nest successful? 1 indicates yes, 0 no. Frsurvivingfirst: what fraction of eggs survived to fledging from the first nest?Successmorenest_bin: were any later (i.e., 2nd or later) nests successful? 1 indicates yes, 0 no. Frsurvivinglater: what fraction of eggs survived to fledging from all later nests? We have included five datasets corresponding to the five climate variables. The name of the csv file indicates the climate variable that the dataset contains. Each dataset contains information on the date, the climate group (clim.grp, corresponds to the climate groups in the demographic dataset), and the value of the climate signal for that date. Units are indicated in the main text for this paper.