cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.1594/pangaea.895685
title: CICE output from Global Ocean Forecast System (GOFS) 3.1 for 2018102012

description: INITIALIZATION: 2018102012FORECASTS:12-hrly out to 7.5 days (t180)GRIDS:ARCu0.08 -- poleward of 40NANTu0.08 -- poleward of 49.52SPARAMETERS:hi:standard_name = "sea_ice_thickness" ;hs:standard_name = "surface_snow_thickness" ;Tsfc:standard_name = "surface_temperature_where_sea_ice" ;aice:standard_name = "sea_ice_area_fraction" ;uvel:standard_name = "eastward_sea_ice_velocity" ;vvel:standard_name = "northward_sea_ice_velocity" ;sst:standard_name = "sea_water_temperature" ;uocn:standard_name = "eastward_sea_water_velocity" ;vocn:standard_name = "northward_sea_water_velocity" ;Tair:standard_name = "air_temperature" ;strength:standard_name = "compressive_strength_of_sea_ice" ;
DOI: 10.1594/pangaea.892967
title: List of number of microsatellite repeats for 23 fungus specific locus in stands of Usnea antarctica and U. aurantiacoatra

description: A dataset generated using 23 fungal-specific microsatellite markers published by Lagostina et al. (2017) to genotype our samples Markers were amplified in three different 10 μL multiplex reactions following the protocol by Lagostina et al. (2017). PCR amplicons were electrophoresed using an Applied Biosystems 3730 platform, with the LIZ 600 size standard (Applied Biosystems, Waltham, Mass., USA) and allele sizes were manually scored using the Geneious 10 microsatellites tool (Kearse et al., 2012). The dataset was used for discriminant analysis of principal components (DAPC), Bayesian clustering analysis and coalescent-based estimation of gene flow.
DOI: 10.1594/pangaea.892211
title: Microplankton fraction (Sfm) estimated form satellite output (OC-CCI), links to netCDF files

description: We provide satellite output that estimates phytoplankton size class as percent microplankton (Sfm, &gt; 20 μm). The calculation of Sfm requires satellite spectral remote sensing reflectance (Rrs(λ)), chlorophyll concentration ([Chl]), and absorption due to dissolved and detrital matter (adg(λ)). These are taken from 4km, monthly, Ocean Color Climate Change Initiative (OC-CCI, version 3.0, www.esa-oceancolour-cci.org) products which are globally merged Sea-Viewing Wide Field-of-View Sensor (SeaWiFS), Medium Resolution Imaging Spectrometer (MERIS), Moderate Resolution Imaging Spectroradiometer (MODIS-Aqua), and Visible Infrared Imaging Radiometer Suite (VIIRS) imagery for a continuous record from 1997 through 2015. This is an absorption-based approach from Mouw and Yoder (2010) (doi:10.1029/2010JC006337) where the chlorophyll-specific absorption spectra for phytoplankton size class extremes, pico- (0.2-2 μm) and microplankton (&gt; 20 μm), are weighted by Sfm. Sfm is estimated from a look-up table containing simulated [Chl], adg(443), Rrs(λ), and Sfm. For a given pixel, satellite-estimated [Chl] and adg(443), are used to narrow the search space within the look-up table. Of the remaining options, the closest simulated Rrs(λ) to the satellite-observed Rrs(λ) is selected and the associated Sfm is assigned.
DOI: 10.1594/pangaea.949598
title: High-resolution census data of Extinction Group species in the Cenozoic of ODP Site 113-690, Southern Ocean
DOI: 10.1594/pangaea.890334
title: CICE output from Navy Earth System Model (NESM) for 2018051412

description: INITIALIZATION: 2018051412FORECASTS:daily at 00Z out to 45 days (t1068)GRIDS:ARCu0.08 -- poleward of 40NANTu0.08 -- poleward of 49.52SPARAMETERS:hi:standard_name = "sea_ice_thickness" ;hs:standard_name = "surface_snow_thickness" ;Tsfc:standard_name = "surface_temperature_where_sea_ice" ;aice:standard_name = "sea_ice_area_fraction" ;uvel:standard_name = "eastward_sea_ice_velocity" ;vvel:standard_name = "northward_sea_ice_velocity" ;sst:standard_name = "sea_water_temperature" ;uocn:standard_name = "eastward_sea_water_velocity" ;vocn:standard_name = "northward_sea_water_velocity" ;Tair:standard_name = "air_temperature" ;strength:standard_name = "compressive_strength_of_sea_ice" ;
DOI: 10.1594/pangaea.949597
title: Low resolution census data of Extinction group species in the Cenozoic of ODP Site 113-689, Southern Ocean

description: Picked by Ellen Thomas.
DOI: 10.1594/pangaea.892973
title: Greenland geothermal heat flux distribution and estimated Curie Depths, links to gridded files

description: Curie depths beneath Greenland are revealed by spectral analysis of data from the World Digital Magnetic Anomaly Map2. A thermal model of the lithosphere then provides a corresponding geothermal heat flux map. This new map exhibits significantly higher frequency but lower amplitude variation than earlier heat flux maps, and provides an important boundary condition for numerical ice-sheet models and interpretation of borehole temperature profiles. In addition, it reveals new geologically significant features. Notably, we identify a prominent quasi-linear elevated geothermal heat flux anomaly running northwest-southeast across Greenland. We interpret this feature to be the relic of the passage of the Iceland hotspot from 80 to 50 Ma. The expected partial melting of the lithosphere and magmatic underplating or intrusion into the lower crust is compatible with models of observed satellite gravity data and recent seismic observations. Our geological interpretation has potentially significant implications for the geodynamic evolution of Greenland.
description: Gridded data at 15 km. X and Y geographic coordinates are in UTM23N projection.
description: Supplement to: Martos, Yasmina M; Jordan, Tom A; Catalán, Manuel; Jordan, Thomas M; Bamber, Jonathan L; Vaughan, David G (2018): Geothermal heat flux reveals the Iceland hotspot track underneath Greenland. Geophysical Research Letters, 45(16), 8214-8222
DOI: 10.1594/pangaea.823737
title: P-Wave velocity (PWL) from IODP Hole 320-U1333A

description: Geocode = Depth CSF-A (m)
DOI: 10.1594/pangaea.892319
title: Soil moisture and matric potential - An open field comparison of sensor systems

description: Soil water content and matric potential are central hydrological state variables. A large variety of automated probes and sensor systems for state monitoring exists and is frequently applied. Most studies solely rely on the calibration by the manufacturers. Until now, there is no commonly agreed calibration procedure. Moreover, several believes about the capabilities and reliabilities of specific sensing methods or sensor systems exist and compete.A consortium of several institutions conducted a comparison study of currently available sensor systems for soil moisture and matric potential under field conditions. All probes have been installed in 0.2 m depth under best practise procedure. We present the setup and the recorded data of 58 probes of 15 different systems measuring soil moisture and 50 probes of 14 different systems for matric potential, which have been used during the campaign in 2016. The data is extended by pedophysical analyses of the soil and laboratory reference measurements for calibration.
description: This repository holds the data and an exemplary python script.The Jupyter Notebook *Sensor_Comparision_EEMD.ipynb* reads data from a field comparison of numerous sensors for soil moisture and matric potential. It uses an Ensemble Empirical Mode Decomposition (EEMD) for spectral recomposition of the recorded signals in order to avoid any assumptions about offset or scaling between the individual time series.The notebook including the included python modules are given under GNU GPL3, the data under CreativeCommons BY-NC-SA 4.0 without any liability.
description: Supplement to: Jackisch, Conrad; Germer, Kai; Graeff, Thomas; Andrä, Ines; Schulz, Katrin; Schiedung, Marcus; Haller-Jans, Jaqueline; Schneider, Jonas; Jaquemotte, Julia; Helmer, Philipp; Lotz, Leander; Bauer, Andreas; Hahn, Irene; Sanda, Martin; Kumpan, Monika; Dorner, Johann; de Rooij, Gerrit; Wessel-Bothe, Stefan; Kottmann, Lorenz; Schittenhelm, Siegfried; Durner, Wolfgang (2020): Soil moisture and matric potential- an open field comparison of sensor systems. Earth System Science Data, 12(1), 683-697
DOI: 10.1594/pangaea.892940
title: Half-degree gridded manure and fertilizer nitrogen inputs in global grassland systems during 1860-2016

description: Production and application to soils of manure excreta from livestock production significantly perturb the global nutrient balance and result in significant greenhouse gas emissions that warm the earth's climate. Despite much attention paid to synthetic nitrogen (N) fertilizer and manure N applications to croplands, spatially-explicit, continuous time-series datasets of manure and fertilizer N inputs on pastures and rangelands are lacking. We developed three global gridded datasets at a resolution of 0.5 degree by 0.5 degree for the period 1860-2016 (i.e., annual manure N deposition (by grazing animals) rate, synthetic N fertilizer and N manure application rates), by combining annual and 5-arc minute spatial data on pastures and rangelands with country-level statistics on livestock manure, mineral and chemical fertilizers, and land use information for cropland and permanent meadows and pastures from the Food and Agricultural Organization database (FAOSTAT). Based on the new data products, we estimated that total N inputs, sum of manure N deposition, manure and fertilizer N application to pastures and rangelands increased globally from 15 to 101 Tg N yr-1 during 1860-2016. In particular during the period 2000-2016, livestock manure N deposition accounted for 83% of the total N inputs, whereas manure and fertilizer N application accounted 9% and 8%, respectively. At the regional scale, hotspots of manure N deposition remained largely similar during the period 1860-2016 (i.e., southern Asia, Africa, and South America), however hotspots of manure and fertilizer N application shifted from Europe to southern Asia in the early 21st century. The new three global datasets contribute to fill previous data gaps of global and regional N inputs in pastures and rangelands, improving the ability of ecosystem and biogeochemistry models to investigate the global impacts of N enrichment due to agriculture, in terms of associated greenhouse gas emissions and environmental sustainability issues.
description: Data are in ascii-format at a spatial resolution of 0.5 degree by 0.5 degree (latitude by longitude). Header for ascii-format files - ncols: 720 - nrows: 354 - xllcorner: -180 - yllcorner: -88.5 - cellsize: 0.5 - NODATA_value: -9999. The unit of these three datasets is kg N/km**2/yr.
description: Supplement to: Xu, Rongting; Tian, Hanqin; Pan, Shufen; Dangal, R S Shree; Chen, Jian; Chang, Jinfeng; Lu, Yonglong; Skiba, Ute Maria; Zhang, Bowen (2019): Increased nitrogen enrichment and shifted patterns in the world's grassland: 1860-2014. Earth System Science Data, 11(1), 175-187
DOI: 10.1594/pangaea.890178
title: CICE output from Navy Earth System Model (NESM) for 2018050712

description: INITIALIZATION: 2018050712FORECASTS:daily at 00Z out to 45 days (t1068)GRIDS:ARCu0.08 -- poleward of 40NANTu0.08 -- poleward of 49.52SPARAMETERS:hi:standard_name = "sea_ice_thickness" ;hs:standard_name = "surface_snow_thickness" ;Tsfc:standard_name = "surface_temperature_where_sea_ice" ;aice:standard_name = "sea_ice_area_fraction" ;uvel:standard_name = "eastward_sea_ice_velocity" ;vvel:standard_name = "northward_sea_ice_velocity" ;sst:standard_name = "sea_water_temperature" ;uocn:standard_name = "eastward_sea_water_velocity" ;vocn:standard_name = "northward_sea_water_velocity" ;Tair:standard_name = "air_temperature" ;strength:standard_name = "compressive_strength_of_sea_ice" ;
DOI: 10.1594/pangaea.893241
title: CICE output from Global Ocean Forecast System (GOFS) 3.1 for 2018081112

description: INITIALIZATION: 2018081112FORECASTS:12-hrly out to 7.5 days (t180)GRIDS:ARCu0.08 -- poleward of 40NANTu0.08 -- poleward of 49.52SPARAMETERS:hi:standard_name = "sea_ice_thickness" ;hs:standard_name = "surface_snow_thickness" ;Tsfc:standard_name = "surface_temperature_where_sea_ice" ;aice:standard_name = "sea_ice_area_fraction" ;uvel:standard_name = "eastward_sea_ice_velocity" ;vvel:standard_name = "northward_sea_ice_velocity" ;sst:standard_name = "sea_water_temperature" ;uocn:standard_name = "eastward_sea_water_velocity" ;vocn:standard_name = "northward_sea_water_velocity" ;Tair:standard_name = "air_temperature" ;strength:standard_name = "compressive_strength_of_sea_ice" ;
DOI: 10.1594/pangaea.769663
title: Basic measurements of radiation at station Carpentras (2011-06)
DOI: 10.1594/pangaea.713194
title: Smear slide analysis of sediment core GeoB6309-1
DOI: 10.1594/pangaea.892874
title: Extreme indices and return levels of daily maximum 10m wind speed in the Arctic and around Greenland

description: A polar-adjusted version of the regional climate model COSMO-CLM was used at a horizontal resolution of about 15km (0.125°; C15) to simulate and analyse extreme 10m wind speeds from 1979-2016 in winter (Nov to Apr) in the Arctic and around Greenland. Based on daily maximum 10m wind speeds, extreme indices (95% percentiles, average strong gale and hurricane days per winter) and return levels up to the 20year return period are calculated and compared with state-of-the-art reanalysis data sets (ERA-Interim, ASR version 1 and 2) and with the satellite product CCMP version 2. The return levels were calculated by the 'peaks-over-threshold' (POT) method which fits a General Pareto distribution (GPD) to extreme values exceeding a specified high threshold (for this study the local 95% and 99% percentiles). The model comparison was based on the overlapping winter period 2000-2012 (Nov to Apr). Before the analysis all data sets were interpolated onto the rotated model grid of C15 (450x350 grid boxes, with the rotated pole located at 100°W and 0°N).
DOI: 10.1594/pangaea.949581
title: High-resolution census data of Extinction Group species in the Late Pliocene-Pleistocene of DSDP Hole 90-594, Southwest Pacific
DOI: 10.1594/pangaea.749480
title: Meteorological observations during GREENE cruise from Texel to Kaap de Goede Hoop started at 1796-02-23
DOI: 10.1594/pangaea.708067
title: (Appendix A1) Stable carbon and oxygen isotope ratios of benthic foraminifera from ODP Site 177-1090

description: Sediment depth (m) is composite depth (mcd). Benthic foraminifera include Cibicidoides praemundulus, C. dickersoni, C. eocaenus, C. havanensis, C. mundulus, Oridorsalis umbonatus
DOI: 10.1594/pangaea.901553
title: Beach profile data for the Elwha River Delta, 2013-09-18

description: Data were collected using GNSS survey methods, with a differential GPS operating in Real Time Kinematic (RTK) mode. Data from prior to 2013 were typically collected with a Magellan ProMark 3 traditional RKT-DGPS system (i.e. local base station and rover), with the base station sited on survey control markers installed in 1996, with survey control coordinates referenced to NAD83(CORS91). Starting in 2013 survey data were typically collected with an AshTech ProMark 200 RTK-DGPS system connected to the Washington State Reference Network. Survey data collected between January and November 2013 are referenced to NAD83(CORS96), and after November 2013 to NAD83(2011). Vertical data for surveys in 2012 and 2013 are referenced to NAVD88, presumably using Geoid96 (the survey control documentation does not specific a geoid). For all subsequent surveys the vertical data are referenced to NAVD88(Geoid09). No conversion were applied to these data to account for variations in horizontal or vertical coordinate system adjustments through time, but an error analysis suggests a standard deviation for the elevation data of between 0.03 and 0.05 m across the entire sampling period (2011-2018). All survey data were collected with the GNSS system mounted on a 2.05 m rover pole, held level as a transect line was traced in a cross-shore orientation on the beach. The associated text files include the horizontal (HRMS) and vertical (VRMS) root-mean-square errors estimated by the GNSS system, as well as the RTK-DGPS status reported by the GNSS system at the time each point was collected. Times are referenced to local Pacific time (either PST or PDT).
description: Portions of these data have been published previously, including in Gelfenbaum et al. 2015.
DOI: 10.1594/pangaea.949639
title: High-resolution census data of Extinction Group species in the Late Pliocene-Pleistocene of ODP Hole 160-967A, Mediterranean Sea
DOI: 10.1594/pangaea.949641
title: High-resolution census data of Extinction Group species in the Late Pliocene-Pleistocene of ODP Hole 161-976C, Mediterranean Sea
DOI: 10.1594/pangaea.907222
title: Track of GPS very-near surface drifter ISMER_20141022_spot243
DOI: 10.1594/pangaea.907266
title: Track of GPS very-near surface drifter ISMER_20150619_spot032
DOI: 10.1594/pangaea.751221
title: Meteorological observations during PLANCIUS cruise from Nederland to Batavia started at 1842-09-25
DOI: 10.1594/pangaea.828624
title: Thermal conductivity of IODP Hole 323-U1343A

description: Geocode = Depth CSF-A (m)
DOI: 10.1594/pangaea.876535
title: Nematode communities in sediment transplantation experiments at Panarea shallow CO2 seeps during cruise ECO2-8
DOI: 10.1594/pangaea.893379
title: CICE output from Navy Earth System Model (NESM) for 2018022012

description: INITIALIZATION: 2018022012FORECASTS:daily at 00Z out to 45 days (t1068)GRIDS:ARCu0.08 -- poleward of 40NANTu0.08 -- poleward of 49.52SPARAMETERS:hi:standard_name = "sea_ice_thickness" ;hs:standard_name = "surface_snow_thickness" ;Tsfc:standard_name = "surface_temperature_where_sea_ice" ;aice:standard_name = "sea_ice_area_fraction" ;uvel:standard_name = "eastward_sea_ice_velocity" ;vvel:standard_name = "northward_sea_ice_velocity" ;sst:standard_name = "sea_water_temperature" ;uocn:standard_name = "eastward_sea_water_velocity" ;vocn:standard_name = "northward_sea_water_velocity" ;Tair:standard_name = "air_temperature" ;strength:standard_name = "compressive_strength_of_sea_ice" ;
DOI: 10.1594/pangaea.893242
title: CICE output from Global Ocean Forecast System (GOFS) 3.1 for 2018081212

description: INITIALIZATION: 2018081212FORECASTS:12-hrly out to 7.5 days (t180)GRIDS:ARCu0.08 -- poleward of 40NANTu0.08 -- poleward of 49.52SPARAMETERS:hi:standard_name = "sea_ice_thickness" ;hs:standard_name = "surface_snow_thickness" ;Tsfc:standard_name = "surface_temperature_where_sea_ice" ;aice:standard_name = "sea_ice_area_fraction" ;uvel:standard_name = "eastward_sea_ice_velocity" ;vvel:standard_name = "northward_sea_ice_velocity" ;sst:standard_name = "sea_water_temperature" ;uocn:standard_name = "eastward_sea_water_velocity" ;vocn:standard_name = "northward_sea_water_velocity" ;Tair:standard_name = "air_temperature" ;strength:standard_name = "compressive_strength_of_sea_ice" ;
DOI: 10.1594/pangaea.739420
title: Pollen profile LALAX, Lalaxkärret, Finland

description: Method: KOH, acetolysis.The EPD (http://www.europeanpollendatabase.net) accepted species name is given in the parameter comment. This dataset was archived on 2010-05-11 from the EPD database.
DOI: 10.1594/pangaea.893243
title: CICE output from Global Ocean Forecast System (GOFS) 3.1 for 2018081312

description: INITIALIZATION: 2018081312FORECASTS:12-hrly out to 7.5 days (t180)GRIDS:ARCu0.08 -- poleward of 40NANTu0.08 -- poleward of 49.52SPARAMETERS:hi:standard_name = "sea_ice_thickness" ;hs:standard_name = "surface_snow_thickness" ;Tsfc:standard_name = "surface_temperature_where_sea_ice" ;aice:standard_name = "sea_ice_area_fraction" ;uvel:standard_name = "eastward_sea_ice_velocity" ;vvel:standard_name = "northward_sea_ice_velocity" ;sst:standard_name = "sea_water_temperature" ;uocn:standard_name = "eastward_sea_water_velocity" ;vocn:standard_name = "northward_sea_water_velocity" ;Tair:standard_name = "air_temperature" ;strength:standard_name = "compressive_strength_of_sea_ice" ;
DOI: 10.1594/pangaea.893109
title: Water vapor database for atmospheric correction of Landsat imagery

description: Atmospheric correction is a crucial preprocessing step for the analysis of optical satellite imagery like Landsat. Among the radiance-modifying gases, atmospheric water vapor is spatially and temporally variable, and cannot be measured reliably from the Landsat sensors. As such, atmospheric correction of Landsat data requires spatially and temporally explicit auxiliary information about atmospheric water vapor content.We have compiled a water vapor dataset that can be readily used to perform atmospheric correction of Landsat images. The dataset was generated by a global processing of the MODIS MOD05/MYD05 collection 6.1 products (Gao, B., et al., 2015. MODIS Atmosphere L2 Water Vapor Product. NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA: doi:10.5067/MODIS/MOD05_L2.006, doi:10.5067/MODIS/MYD05_L2.006). The dataset is comprised of daily global water vapor data for February 2000 to July 2018 for each land-intersecting Worldwide Reference System 2 (WRS-2) scene, as well as a monthly climatology that can be used if no daily value is available.The dataset was generated by the Framework for Operational Radiometric Correction for Environmental monitoring (FORCE v. 2.0, http://force.feut.de), which is freely available software under the terms of the GNU General Public License v. &gt;= 3. The water vapor dataset can be readily ingested into the FORCE Level 2 Processing System (Frantz et al. 2016, doi:10.1109/TGRS.2016.2530856) to perform atmospheric correction of Landsat imagery.
description: Supplement to: Frantz, David; Röder, Achim; Stellmes, Marion; Hill, Joachim (2016): An operational radiometric Landsat preprocessing framework for large-area time series applications. IEEE Transactions on Geoscience and Remote Sensing, 54(7), 3928-3943
DOI: 10.1594/pangaea.892332
title: Data for Euryhalinity of Ponto-Caspian invaders in their native and introduced regions

description: In the past decades, Ponto-Caspian species established in freshwater and brackish habitats of the North and Baltic Sea and Great Lakes-St. Lawrence River region in much higher numbers than expected based on introduction effort (i.e. shipping frequency) and environmental conditions between these regions. Several studies suggested that Ponto-Caspian taxa are euryhaline and might be able to adapt rapidly to changing salinity conditions, and therefore might be more successful colonizers than species from other regions. To determine the realized niche in the native and introduced habitats of Ponto-Caspian invaders and to assess whether they expanded their salinity tolerance during the invasion process, we conducted a literature search to assess the salinity ranges of 55 Ponto-Caspian species in their native and introduced region. Our results confirmed that the majority of those species occupied a wide range of salinity in their native and introduced habitats. Approximately 50 % of the species were reported from both freshwater and brackish habitats (0-18 PSU) in their native region, occupying a salinity range of at least 10 PSU difference. In general, the number of species tended to decline as salinity increased in both native and introduced habitats. More than 90 % of the Ponto-Caspian invaders occupied freshwater (0-0.5 PSU) habitats, while 18 % did not occur above 18 PSU. Due to the limitation of our dataset, we were not able to confirm shifts in salinity tolerance during the invasion process. However, as our results suggest that the majority of the Ponto-Caspian invaders occupy freshwater and brackish habitats in their native region, the recent numerous invasions of freshwater and brackish areas by those species should not be a surprise. Therefore, managers and policy makers should take into account that the majority of Ponto-Caspian invaders originate from fresh water or low salinities and develop new regulations to prevent future invasions from the Ponto-Caspian region, as well as from areas highly invaded by Ponto-Caspian taxa such as Northern Europe.
description: Supplement to: Pauli, Nora-Charlotte; Briski, Elizabeta (2018): Euryhalinity of Ponto-Caspian invaders in their native and introduced regions. Aquatic Invasions, 13(4), 439-447