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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.HighResMIP.MOHC.HadGEM3-GC31-HH' 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 HadGEM3-GC3.1-N512ORCA12 climate model, released in 2016, includes the following components: aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N512; 1024 x 768 longitude/latitude; 85 levels; top level 85 km), land: JULES-HadGEM3-GL7.1, ocean: NEMO-HadGEM3-GO6.0 (eORCA12 tripolar primarily 1/12 deg; 4320 x 3604 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: CICE-HadGEM3-GSI8 (eORCA12 tripolar primarily 1/12 deg; 4320 x 3604 longitude/latitude). The model was run by the Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, EX1 3PB, UK (MOHC) in native nominal resolutions: aerosol: 50 km, atmos: 50 km, land: 50 km, ocean: 10 km, seaIce: 10 km.

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.CMIP.CMCC.CMCC-CM2-SR5.historical' 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 CMCC-CM2-SR5 climate model, released in 2016, includes the following components: aerosol: MAM3, atmos: CAM5.3 (1deg; 288 x 192 longitude/latitude; 30 levels; top at ~2 hPa), land: CLM4.5 (BGC mode), ocean: NEMO3.6 (ORCA1 tripolar primarly 1 deg lat/lon with meridional refinement down to 1/3 degree in the tropics; 362 x 292 longitude/latitude; 50 vertical levels; top grid cell 0-1 m), seaIce: CICE4.0. The model was run by the Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Lecce 73100, Italy (CMCC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.

Suitability maps (raster format: geotiff) of Fraxinus excelsior, computed using the ForestFocus European dataset of species presence/absence. The adopted suitability model estimates the optimal environmental conditions for European tree species under present and future climates. Available years: 2000, 2020, 2050, 2080. For year 2000 the observed (WorldClim) climate conditions have been used. For years 2020, 2050, 2080 the climate conditions simulated for the climate change scenarios A2 and B2 have been used (by means of the climate models CCCMA, CSIRO, HANDCM3 and of an ensemble model of them).

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.CMIP.MOHC.HadGEM3-GC31-MM.piControl' 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 HadGEM3-GC3.1-N216ORCA025 climate model, released in 2016, includes the following components: aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N216; 432 x 324 longitude/latitude; 85 levels; top level 85 km), land: JULES-HadGEM3-GL7.1, ocean: NEMO-HadGEM3-GO6.0 (eORCA025 tripolar primarily 0.25 deg; 1440 x 1205 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: CICE-HadGEM3-GSI8 (eORCA025 tripolar primarily 0.25 deg; 1440 x 1205 longitude/latitude). The model was run by the Met Office Hadley Centre, Fitzroy Road, Exeter, Devon, EX1 3PB, UK (MOHC) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 25 km, seaIce: 25 km.

Research data and scientific software related to spatio-temporal estimations of ecological soil moisture with available data covering the whole territory of Germany and the Kellerwald National Park (Hesse). Temporal trends of modelled soil moisture for the time period 1961–2070 were statistically analyzed. Soil moisture changes (drying-out) at both national and regional levels were mapped. {"references": ["Nickel S, Schr\u00f6der W 2017. Fuzzy modelling and mapping soil moisture for observed and future periods. An alternative for dynamic modelling at the national and regional scale? Annals of Forest Science 74:71"]}

The Intergovernmental Panel on Climate Change (IPCC) report that to limit warming to 1.5 °C, Bioenergy with Carbon Capture and Storage (BECCS) is required. Integrated assessment models (IAMS) predict that a land area between the size of Argentina and Australia is required for bioenergy crops, a 3–7 time increase in the current bioenergy planting area globally. The authors pose the question of whether vertical farming (VF) technology can enable BECCS deployment, either via land sparing or supply. VF involves indoor controlled environment cultivation, and can increase productivity per unit land area by 5–10 times. VF is predominantly being used to grow small, high value leafy greens with rapid growth cycles. Capital expenditure, operational expenditure, and sustainability are challenges in current VF industries, and will affect the ability to utilise this technology for other crops. The authors argue that, whilst challenging, VF could help reach wider climate goals. Application of VF for bioenergy crops could be a game changer in delivering BECCS technologies and may reduce the land footprint required as well as the subsequent associated negative environmental impacts. VF bioenergy could allow us to cultivate the future demand for bioenergy for BECCS on the same, or less, land area than is currently used globally.

Upwelling processes bring nutrient-rich waters from the deep ocean to the surface. Areas of upwelling are often associated with high productivity, offering great economic value in terms of fisheries. The sensitivity of spring/summer-time coastal upwelling systems to climate change has recently received a lot of attention. Several studies have suggested that their intensity may increase in the future while other authors have shown decreasing intensity in their equatorward portions. Yet, recent observations do not show robust evidence of this intensification. The Senegalo-Mauritanian upwelling system (SMUS) located at the southern edge of the north Atlantic system (12°N–20°N) and most active in winter/spring has been largely excluded from these studies. Here, the seasonal cycle of the SMUS and its response to climate change is investigated in the database of the Coupled Models Inter comparison Project Phase 5 (CMIP5). Upwelling magnitude and surface signature are characterized by several sea surface temperature and wind stress indices. We highlight the ability of the climate models to reproduce the system, as well as their biases. The simulations suggest that the intensity of the SMUS winter/spring upwelling will moderately decrease in the future, primarily because of a reduction of the wind forcing linked to a northward shift of Azores anticyclone and a more regional modulation of the low pressures found over Northwest Africa. The implications of such an upwelling reduction on the ecosystems and local communities exploiting them remains very uncertain.

Climate change, environmental degradation, and limited resources are motivations for sustainable forest management. Forests, the most abundant renewable resource on earth, used to make a wide variety of forest-based products for human consumption. To provide a scientific measure of a product’s sustainability and environmental performance, the life cycle assessment (LCA) method is used. This article provides a comprehensive review of environmental performances of forest-based products including traditional building products, emerging (mass-timber) building products and nanomaterials using attributional LCA. Across the supply chain, the product manufacturing life-cycle stage tends to have the largest environmental impacts. However, forest management activities and logistics tend to have the greatest economic impact. In addition, environmental trade-offs exist when regulating emissions as indicated by the latest traditional wood building product LCAs. Interpretation of these LCA results can guide new product development using biomaterials, future (mass) building systems and policy-making on mitigating climate change. Key challenges include handling of uncertainties in the supply chain and complex interactions of environment, material conversion, resource use for product production and quantifying the emissions released.