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This is the pentad mean soil moisture (SM) for three land surface models as well as ensemble SM pertaining to the following research paper: "More rapid intensification of flash droughts with shorter onset timescales" . It includes the GLDAS-2 datasets (https://disc.sci.gsfc.nasa.gov/datasets?keywords=GLDAS) for gridded three-hours surface air temperature (T), precipitation (P), evapotranspiration (ET), and SM (2000-2019).

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.C4MIP.E3SM-Project.E3SM-1-1' 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 E3SM 1.1 (Energy Exascale Earth System Model) climate model, released in 2019, includes the following components: aerosol: MAM4 with resuspension, marine organics, and secondary organics (same grid as atmos), atmos: EAM (v1.1, cubed sphere spectral-element grid; 5400 elements with p=3; 1 deg average grid spacing; 90 x 90 x 6 longitude/latitude/cubeface; 72 levels; top level 0.1 hPa), atmosChem: Troposphere specified oxidants for aerosols. Stratosphere linearized interactive ozone (LINOZ v2) (same grid as atmos), land: ELM (v1.1, same grid as atmos; active biogeochemistry using the Converging Trophic Cascade plant and soil carbon and nutrient mechanisms to represent carbon, nitrogen and phosphorus cycles), MOSART (v1.1, 0.5 degree latitude/longitude grid), ocean: MPAS-Ocean (v6.0, oEC60to30 unstructured SVTs mesh with 235160 cells and 714274 edges, variable resolution 60 km to 30 km; 60 levels; top grid cell 0-10 m), ocnBgchem: BEC (Biogeochemical Elemental Cycling model, NPZD-type with C/N/P/Fe/Si/O; same grid as ocean), seaIce: MPAS-Seaice (v6.0; same grid as ocean). The model was run by the LLNL (Lawrence Livermore National Laboratory, Livermore, CA 94550, USA); ANL (Argonne National Laboratory, Argonne, IL 60439, USA); BNL (Brookhaven National Laboratory, Upton, NY 11973, USA); LANL (Los Alamos National Laboratory, Los Alamos, NM 87545, USA); LBNL (Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA); ORNL (Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA); PNNL (Pacific Northwest National Laboratory, Richland, WA 99352, USA); SNL (Sandia National Laboratories, Albuquerque, NM 87185, USA). Mailing address: LLNL Climate Program, c/o David C. Bader, Principal Investigator, L-103, 7000 East Avenue, Livermore, CA 94550, USA (E3SM-Project) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, ocean: 50 km, ocnBgchem: 50 km, seaIce: 50 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.ScenarioMIP.CNRM-CERFACS.CNRM-CM6-1-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 CNRM-CM6-1-HR climate model, released in 2017, includes the following components: aerosol: prescribed monthly fields computed by TACTIC_v2 scheme, atmos: Arpege 6.3 (T359; Gaussian Reduced with 181724 grid points in total distributed over 360 latitude circles (with 720 grid points per latitude circle between 32.2degN and 32.2degS reducing to 18 grid points per latitude circle at 89.6degN and 89.6degS); 91 levels; top level 78.4 km), atmosChem: OZL_v2, land: Surfex 8.0c, ocean: Nemo 3.6 (eORCA025, tripolar primarily 1/4deg; 1442 x 1050 longitude/latitude; 75 levels; top grid cell 0-1 m), seaIce: Gelato 6.1. The model was run by the CNRM (Centre National de Recherches Meteorologiques, Toulouse 31057, France), CERFACS (Centre Europeen de Recherche et de Formation Avancee en Calcul Scientifique, Toulouse 31057, France) (CNRM-CERFACS) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, ocean: 25 km, seaIce: 25 km.

We present a comprehensive inventory of thaw slumps (landslides developed in the Arctic and sub-Arctic areas) in Nordenskiöld Land (Svalbard Archipelago). We used the most recent orthophotos (5 x 5 m pixel size) acquired in 2009-2011 from the Web Map Services (WMS) of the Norwegian Polar Institute. The thaw slumps were identified and digitised on-screen as polygons in the WGS_1984_UTM_Zone_33N coordinate reference system. We identified a number of 562 thaw slumps, that will be used along with the thermo-erosion gullies inventory to provide the first multi-hazard predictive model in the Arctic. * Project: GEOCULT - Monitoring Geohazards Affecting Cultural Heritage Sites at Svalbard, Award: 369913 and 369924* File descriptions: Vector format: ESRI shapefileProjection: WGS_1984_UTM_Zone_33NVector type: polygon

Greenhouse gas (GHG) additions to Earth’s atmosphere initially reduce global outgoing longwave radiation (OLR), thereby warming the planet. In select environments with temperature inversions, however, increased GHG concentrations can actually increase local OLR. Negative top-of-atmosphere and effective radiative forcing (ERF) from this situation give the impression that local surface temperatures could cool in response to GHG increases. Here we consider an extreme scenario in which GHG concentrations are increased only within the warmest layers of winter near-surface inversions of the Arctic and Antarctic. We find, using a fully coupled Earth system model, that the underlying surface warms despite the GHG addition exerting negative ERF and cooling the troposphere in the vicinity of the GHG increase. This unique radiative forcing and thermal response is facilitated by the high stability of the polar winter atmosphere, which inhibits thermal mixing and amplifies the impact of surface radiative forcing on surface temperature. These findings also suggest that strategies to exploit negative ERF via injections of short-lived GHGs into inversion layers would likely be unsuccessful in cooling the planetary surface.;Note: A revised data description file was added to this work on April 11, 2018 containing additional information about the data set than was provided in the original description. Additional keywords and a full citation to the related article were added as well. The data are model output from climate simulations conducted with the Community Earth System Model (CESM) version 1.0.6

This dataset contains two metrics for climate change exposure using downscaled climate projections with the SRES A2 emissions scenario (Tabor and Williams, 2007).The metrics represent dissimilarity measurements of the squared Euclidean distance between seasonal (June–August and December–February) temperature and precipitation variables in the 20th century climate and mid-21st century climate. (1) disappearing climate risk - measure of dissimilarity between a pixel’s late 20th century climate and its closest matching pixel in the global set of 21st-century climates (2) novel climate risk - measure of dissimilarity between a pixel’s future climate and its closest matching pixel in the global set of late 20th-century climates. The data are in arcASCII format. All data are in units of standard Euclidean distance and multiplied by 1000. This is the original data. To scale the data similar to Tabor et al. (2018), remove outliers above the 99th percentile distribution before rescaling from 0-1. Unprojected number of columns 2160 number of rows 857 Lower Left X Center -179.917 Lower Left Y Center -59.084 Cell size 0.166667 decimal degrees (10 minutes or ~17 km) {"references": ["Tabor, K. et al. (2018). Tropical Protected Areas Under Increasing Threats from Climate Change and Deforestation: https://doi.org/10.3390/land7030090", "Tabor and Williams (2010). Globally downscaled climate projections for assessing the conservation impacts of climate change. https://doi.org/10.1890/09-0173.1", "Williams, J.W. et al. (2007). Projected distributions of novel and disappearing climates by 20100 AD. https://doi.org/10.1073/pnas.0606292104"]} Support for this project was provided by Conservation International, the Land Tenure Center at the University of Wisconsin, the Center for Climatic Research at the University of Wisconsin, and the Environment Program at the University of Wisconsin–Madison. This research has been funded in part by the Walton Family Foundation, the Gordon and Betty Moore Foundation, and a gift from Betty and Gordon Moore.

Forest aboveground carbon density (ACD) for the main eight Hawaiian Islands in 2015-2016. The data are in 30 meter resolution format with the units of Mg C per hectare. The file is a standard GeoTIFF. Use of these data requires citation of this dataset plus citation of the source study as follows: Asner, G.P., S. Sousan, D.E. Knapp, P.C. Selmants, R.E. Martin, R.F. Hughes, and C.P. Giardina. 2016. Rapid forest carbon assessments of oceanic islands: a case study of the Hawaiian archipelago. Carbon Balance and Management 11, doi:10.1186/s13021-015-0043-4

Changes in late rice phenology during 1981–2009 were investigated using observed phenological data from agro-meteorological stations across China. This dataset contains 1) details of late rice agrometeorological experiment stations; 2) mean date of late rice phenology date and trend in phenology date during the period of 1981–2009; 3) trends in length of late rice growing period during the period of 1981-2009. Changes in late rice phenology during 1981–2009 were investigated using observed phenological data from agro-meteorological stations across China. This dataset contains 1) details of late rice agrometeorological experiment stations; 2) mean date of late rice phenology date and trend in phenology date during the period of 1981–2009; 3) trends in length of late rice growing period during the period of 1981-2009.

Digital Annex for the following thesis: Vila-Viçosa, C. (2023). Natural History, Biogeography and Evolution of the Iberian white oak syngameon (Quercus L. Sect. Quercus). Ph.D. Thesis, Faculdade de Ciências da Universidade do Porto, Portugal Abstract: The genus Quercus L. is one of the most diverse and important group of woody plants, particularly when considering that they are the trees that rule the Northern Hemisphere forests. Oaks have an intricate Biogeography that criss-crosses diverse climatic and edaphic gradients, encompassing a huge ambiguity in terms of species delimitation. Frequently, the taxonomic proposals brought by traditional Linnaean Botany are either insufficient or rather inflate the number of species and nomenclatural assignments, which are further diluted into inconsistent taxonomic ranks, varying from species to subspecies and varieties. The supremacy given to morphological characters that are inherently fragile and plastic, spread across the distribution areas of distinct lineages, may carry ambiguity on the identification and proper species delimitation. From the oaks that are distributed across the Western Palearctic region, the ones that are deciduous or brevi-deciduous present higher levels of ambiguity in terms of species number and their delimitation. This ambiguity is particularly strong in the circummediterranean region and in the transitional areas between the two major biogeographic Regions of the western Palearctic region, the Euro-Siberian and Mediterranean. This degree of uncertainty, which increases towards the Southern European Peninsulas, is amplified by the ease that the different species of oaks tend to hybridize among them. The present work provides a holistic framework that covers multiple areas, from the taxonomic and evolutive study of this genus, to biogeography and molecular characterization. Its major objective was to resolve the species delimitation of the Iberian deciduous and marcescent oaks and putative introgression among them, enhancing the available knowledge about species diversity, which can foster suitable species and forest conservation. A specific objective was to cross-reference the natural history revision and the different taxonomic treatments brought by distinct authors, with personal observations. These data were then incorporated into ecological modelling and molecular characterization, which in the end fed a newly updated taxonomic proposal. In Section A we obtained results from extensive field, herbaria, and literature review, updating the nomenclature of the Portuguese and western Mediterranean oaks. Section B was supported by Section A’s in-depth review and enabled finer species distribution models, nurturing both hindcast (since ca. 20 Kyr) and forecast (2070-2100) exercises of the range dynamics of Mediterranean oaks species. The study of past and future range shifts solved important pending biogeographic questions, especially related to past range-shifts. Such past-range shifts improved our knowledge on species responses to climate dynamics and allowed a better anticipation of future responses of range shifts driven by climate change. Section C encompassed the molecular characterization of Iberian white oak species and their hybrids, whose delimitation is often faltering when one intends to infer about species rank, or hypothesize about the participation of parent taxon in natural hybrid swarms. This work allowed us to solve the phylogenetic backbone of western Palearctic white oaks, suggesting a significant segregation of the Iberian pedunculate oaks and unveiling two subsections inside Section Quercus. These subsections are biogeographically well-segregated and present diverse levels of introgression among species. Results demonstrated the efficiency of RADSeq for rebuilding the reticulate phylogeny of the Eurasian white oaks, showcasing the significance of the Iberian Peninsula as a major hotspot for oak diversity. We implemented a circular approach to these methods, which retro-fed themselves in terms of insight generation, enabling a powerful strategy to solve the evolutionary history of this difficult groups of plants. We estimate that the reticulate historical biogeography of the western Palearctic white oaks deserves further scrutiny by adding vicariant oak populations from northern Africa, the Near East and southern European Peninsulas. Methods should again follow this similar additive and sequential process of adjoining deep Natural History examination, with extensive fieldwork in type populations and genome-wide molecular surveys, in order to solve this group of plants. With the present work, we were able to significantly improve on the depiction of the basic unit of Biodiversity (the Species), in the complex Quercus genus. We provided tools to enable further efforts for the conservation of the Mediterranean oak forests, which overwhelm one of the most important (and one of the most threatened) Biomes for plant conservation at the global scale.