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This dataset contains spatial predictions of the potential environmental spaces for pingos, ice-wedge polygons and rock glaciers across the Northern Hemisphere permafrost areas. The potential environmental spaces, i.e. conditions where climate, topography and soil properties are suitable for landform presence, were predicted with statistical ensemble modelling employing geospatial data on environmental conditions at 30 arc-second resolution (~1 km). In addition to the baseline period (1950-2000), the predictions are provided for 2041-2060 and 2061-2080 using climate-forcing scenarios (Representative Concentration Pathways 4.5 and 8.5). The resulting dataset consists of five spatial predictions for each landform in GeoTIFF format.The data provide new information on 1) the fine-scale spatial distribution of permafrost landforms in the Northern Hemisphere, 2) the potential future alterations in the environmental suitability for permafrost landforms due to climate change, and 3) the circumpolar distribution of various ground ice types, and can 4) facilitate efforts to inventory permafrost landforms in incompletely mapped areas.

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.DAMIP.MPI-M.MPI-ESM1-2-LR' 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-LR climate model, released in 2017, includes the following components: aerosol: none, prescribed MACv2-SP, atmos: ECHAM6.3 (spectral T63; 192 x 96 longitude/latitude; 47 levels; top level 0.01 hPa), land: JSBACH3.20, landIce: none/prescribed, 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 Max Planck Institute for Meteorology, Hamburg 20146, Germany (MPI-M) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, landIce: none, ocean: 250 km, ocnBgchem: 250 km, seaIce: 250 km.

Search and location of the remains of the submarine in the area using side-scan sonar and visual identification with a mini submarine. ARM-REC Cruise (29SG20220502) carried out on the Research Vessel Sarmiento de Gamboa in 2022.

Data reported by companies on the production, import, export, destruction and feedstock use of fluorinated greenhouse gases in the European Union during the years 2007-2019. The primary data is synthesised and aggregated at EU level and used to assess the progress on HFC phase-down made under both EU legislation and the UN framework as part of the Kigali Amendment to the Montreal Protocol. The data also details the amount of F-gases supplied to various industrial applications.

The CARBO-ACID research cruise (EUROFLEETS+ SEA02_10) was carried out on the RV Ramón Margalef between August 2nd and August 11st, with departing from Vigo – Spain and ending in Lisbon – Portugal. The main objective of this cruise was to collect data and samples to study the potential effects of ocean acidification on carbonate marine organisms (coccolithophores, pteropods, planktonic and benthic foraminifera, and corals) along the Iberian margin. With this objective, oceanographic data and water samples, plankton, cold-water corals and sediment samples were collected during an upwelling season, along two transects coinciding with the two persistent upwelling filaments off the Iberia Margin: the Cape Finisterra and the Cape Roca. In this dataset is guiven all the acquired data recollected onboad. During the CARBO-ACID cruise we did a total of 7 stations, 4 stations along the Cape Finisterra transect (from W to E: CA3, CA2, CA7, CA8) and 3 stations at the Cape Roca (from W to E: CA6, CA5, CA4) transect (Fig). At each station we usually started with a multibeam survey, a CTD and Rosette cast. These initial operations allowed to identify the different water masses present in this area, characterize their physical properties and to recover seawater samples at specific depth levels. The seawater samples were onboard subsampled, preserved in cold conditions or with chemicals and/ or filtered for several further analysis in the shore-based laboratories: DNA, chlorophyll, fitoplankton, coccolithophores, pH, alkalinity, stable isotopic composition, trace elements concentration and Suspend Particulate Matter. Subsequently to these operations, at each station, two vertical tows with a plankton multinet (with 5 nets) were done on the top 700 m of the water column to sample the planktonic communities of the different water depths. After this, sediment samples were recovered with a box-corer to study the past oceanographic conditions, between the pre-industrial Era and the Present, with multi-proxies used in paleoceanography and sedimentology. A total of 10 box-cores were recollected and each of them was onboard sub-sampled for eDNA, enzymes and benthic foraminifera. Fifteen shipek grab samples were recollected at the Fontanelas seamount (Estremadura Spur), station CA6, to characterize the sedimentary cover and to evaluate the presence of deep cold-water corals. Preliminary results show that the stations CA7, CA8 and CA4, located close to the coast, as expected, are the most influenced by the coastal upwelling, exhibiting colder surface water, higher values of fluorescence, and more zooplankton content reflecting higher phyto-zooplankton concentrations, as typical of the upwelling waters. At station CA4 temperature was higher and fluorescence showed lower values, indicative of less phytoplankton, and interpreted as indicating a different upwelling source water from that upwelled further north. Based on the CTD data, the Cape Roca transect is more influenced by the subtropical East North Atlantic Central Water (ENACWst), while the Cape Finisterra transect is more under the influence of the subpolar branch (ENACWsp). Seafloor sediment samples showed significant differences between the stations. Along the northern transect (Cape Finisterra) the seafloor sediments show an increase in grain size from the offshore to the coast. The offshore stations CA3 and CA2 revealed finer grained sediments, CA8 were composed of coarser sand and the station CA7, the shallowest station 77 m, presented the sediment composed mainly of shell fragments and coarse grain sand. Along the southern transect (Cape Roca), the offshore station CA6 (Fontanelas seamount) has coarser sandy sediments with rock clasts and cold-water coral fragments, and the stations CA5 and CA4 with fine sand to muddy sediments. The detailed CA6 bathymetry allowed to verify the existence of small plateaus on the slope of the Fontanelas seamount, where the fossil cold-water corals fragments were found, suggesting that this area is a very interesting system deserving further study with a ROV, and to characterize the corals fields and verify if there are live corals. These recollected data and samples will allow not only to reconstruct the pH variability under different environmental conditions, but also to estimate the biogeochemical changes along the coastal ocean waters as the anthropogenic influence increases. These results will contribute to better understand and model the effects on the biota under the future expected oceans pH changes.

EXport Processes in the Ocean from Remote Sensing (EXPORTS) is a large-scale NASA-led field campaign that will provide critical information for quantifying the export and fate of upper ocean net primary production (NPP) using satellite observations and state of the art ocean technologies. The goal of EXPORTS is to understand how the organic carbon makes it to the twilight zone and deep ocean interior, and how lon it stays there, which is vital to understanding present and future ocean ecosystems and global climate. Oceanographic data acquired during the EXPORTS Cruise (29SG20210503) on board the Research Vessel Sarmiento de Gamboa in 2021.

This data release contains the boundaries of assessment units and input data for the assessment of undiscovered Deep Tuscaloosa Group sandstones conventional gas resources in the U.S. Gulf Coast in Louisiana and Mississippi. The Assessment Unit is the fundamental unit used in the National Assessment Project for the assessment of undiscovered oil and gas resources. The Assessment Unit is defined within the context of the higher-level Total Petroleum System. The Assessment Unit is shown herein as a geographic boundary interpreted, defined, and mapped by the geologist responsible for the province and incorporates a set of known or postulated oil and (or) gas accumulations sharing similar geologic, geographic, and temporal properties within the Total Petroleum System, such as source rock, timing, migration pathways, trapping mechanism, and hydrocarbon type. The Assessment Unit boundary is defined geologically as the limits of the geologic elements that define the Assessment Unit, such as limits of reservoir rock, geologic structures, source rock, and seal lithologies. The only exceptions to this are Assessment Units that border the Federal-State water boundary. In these cases, the Federal-State water boundary forms part of the Assessment Unit boundary. In addition to the shapefile, for U.S. assessments, allocation tables are provided that enumerate percentages assigned to various land categories. Machine-readable tables are also provided that contain the input and results for each assessment unit summarized in the USGS Fact Sheet. Methodology of assessments are documented in USGS Data Series 547 for continuous assessments (https://pubs.usgs.gov/ds/547) and USGS DDS69-D, Chapter 21 for conventional assessments (https://pubs.usgs.gov/dds/dds-069/dds-069-d/REPORTS/69_D_CH_21.pdf). See supplemental information for a detailed list of files included this data release.

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-CM4.ssp585' 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-CM4 climate model, released in 2018, includes the following components: aerosol: interactive, atmos: GFDL-AM4.0.1 (Cubed-sphere (c96) - 1 degree nominal horizontal resolution; 360 x 180 longitude/latitude; 33 levels; top level 1 hPa), atmosChem: fast chemistry, aerosol only, land: GFDL-LM4.0.1 (1 degree nominal horizontal resolution; 360 x 180 longitude/latitude; 20 levels; bottom level 10m); land-Veg:unnamed (dynamic vegetation, dynamic land use); land-Hydro:unnamed (soil water and ice, multi-layer snow, rivers and lakes), landIce: GFDL-LM4.0.1, ocean: GFDL-OM4p25 (GFDL-MOM6, tripolar - nominal 0.25 deg; 1440 x 1080 longitude/latitude; 75 levels; top grid cell 0-2 m), ocnBgchem: GFDL-BLINGv2, seaIce: GFDL-SIM4p25 (GFDL-SIS2.0, tripolar - nominal 0.25 deg; 1440 x 1080 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: 25 km, ocnBgchem: 25 km, seaIce: 25 km.

Salmonids are of immense socio-economic importance in much of the world but are threatened by climate change. This has generated a substantial literature documenting effects of climate variation on salmonid productivity in freshwater ecosystems, but there has been no global quantitative synthesis across studies. We conducted a systematic review and meta-analysis to gain quantitative insight into key factors shaping the effects of climate on salmonid productivity, ultimately collecting 1,321 correlations from 156 studies, representing 23 species across 24 countries. Fisher’s Z was used as the standardized effect size, and a series of weighted mixed-effects models were compared to identify covariates that best explained variation in effects. Patterns in climate effects were complex, and were driven by spatial (latitude, elevation), temporal (time-period, age-class), and biological (range, habitat type, anadromy) variation within and among study populations. These trends were often consistent with predictions based on salmonid thermal tolerances. Namely, warming and decreased precipitation tended to reduce productivity when high temperatures challenged upper thermal limits, while opposite patterns were common when cold temperatures limited productivity. Overall, variable climate impacts on salmonids suggest that future declines in some locations may be counterbalanced by gains in others. In particular, we suggest that future warming should (1) increase salmonid productivity at high latitudes and elevations (especially >60° and >1,500m), (2) reduce productivity in populations experiencing hotter and dryer growing season conditions, (3) favor non-native over native salmonids, and (4) impact lentic populations less negatively than lotic ones. These patterns should help conservation and management organizations identify populations most vulnerable to climate change, which can then be prioritized for protective measures. Our framework enables broad inferences about future productivity that can inform decision-making under climate change for salmonids and other taxa, but more widespread, standardized, and hypothesis-driven research is needed to expand current knowledge. See README document and R code. See README document.