cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.1594/pangaea.937649
title: Sun Photometer Data (AOD) 2015 from Zeppelin Station, Ny-Ålesund, Svalbard (AWIPEV)

description: Aerosol optical depth (AOD) is measured by a sun photometer, type SP1a by Dr. Schulz & Partner GmbH in 17 wavelengths between λ = 369nm to 1023nm with a field of view of 1° × 1° and a time resolution of 1 minute. In winter 2012/13 a new sun photometer was installed and just 10 of 17 wavelengths remained in the same wavelength range. With the nine out of ten wavelengths optical parameters like the AOD are computed. The one, which is devoted to water vapor is omitted. The instrument is calibrated regularly in pristine conditions at Izaña, Tenerife, via Langley method. A cloud screening based on short scale fluctuations of the AOD is used. The uncertainty for the AOD is generally said to be around 0.01. However, this is the maximum error of the instrument because the fluctuations are much smaller by comparing data minute by minute under low or constant aerosol conditions.The number of individual measurements differs between a few hundreds, especially in March and September, to up to 12,000 in early summer. No trend in each month can be seen comparing the amount of cloud-free measurements over the years. Only an annual cycle due to polar day and night is included in the data. Due to the instrument data is only available in clear sky conditions. In this regard the data should represent the real aerosol conditions. Only aerosols that are advected and processed within clouds or hygroscopic growth cannot be measured by this instrument.In this data set AOD, Angstrom-Exponent and modified Angstrom-Exponent (Graßl, Ritter 2019, Remote Sensing, https://doi.org/10.3390/rs11111362) are given for the sun photometer at Zeppelin Station, operated by AWIPEV, for the time 19. March 2015 until 30. September 2015. The variables are in netcdf format for each measurement day. The used instrument for the measurement period was SP1A34.
description: Each measurement day contains in netcdf format the following variables:Time (minutes after midnight UTC)wavelengths (nm lambda)AODModified Angstrom parameters (3 values!)traditional Angstrom parameters (2 values)
DOI: 10.1594/pangaea.937657
title: ADCP current measurements (38 and 75 kHz) during METEOR cruise M148

description: Two Teledyne RDI Ocean Surveyor systems with 38 and 75 kHz transmission frequency were used. Data was processed with a software package developed at GEOMAR following the GO-SHIP standards (Firing and Hummon, 2010). The data was subsequently averaged over one minute intervals and converted to a NetCDF based format.
DOI: 10.15468/dl.3wby4t
title: Occurrence Download

description: A dataset containing 1128 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Liolaemus bibronii (Bell, 1843)"
 ]
}

 The dataset includes 1128 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0284196-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.937675
title: Sun Photometer Data (AOD) 2016 from Zeppelin Station, Ny-Ålesund, Svalbard (AWIPEV)

description: Aerosol optical depth (AOD) is measured by a sun photometer, type SP1a by Dr. Schulz & Partner GmbH in 17 wavelengths between λ = 369nm to 1023nm with a field of view of 1° × 1° and a time resolution of 1 minute. In winter 2012/13 a new sun photometer was installed and just 10 of 17 wavelengths remained in the same wavelength range. With the nine out of ten wavelengths optical parameters like the AOD are computed. The one, which is devoted to water vapor is omitted. The instrument is calibrated regularly in pristine conditions at Izaña, Tenerife, via Langley method. A cloud screening based on short scale fluctuations of the AOD is used. The uncertainty for the AOD is generally said to be around 0.01. However, this is the maximum error of the instrument because the fluctuations are much smaller by comparing data minute by minute under low or constant aerosol conditions.The number of individual measurements differs between a few hundreds, especially in March and September, to up to 12,000 in early summer. No trend in each month can be seen comparing the amount of cloud-free measurements over the years. Only an annual cycle due to polar day and night is included in the data. Due to the instrument data is only available in clear sky conditions. In this regard the data should represent the real aerosol conditions. Only aerosols that are advected and processed within clouds or hygroscopic growth cannot be measured by this instrument.In this data set AOD, Angstrom-Exponent and modified Angstrom-Exponent (Graßl, Ritter 2019, Remote Sensing, https://doi.org/10.3390/rs11111362) are given for the sun photometer at Zeppelin Station, operated by AWIPEV, for the time 8. March 2016 until 30. September 2016. The variables are in netcdf format for each measurement day. The used instrument for the measurement period was SP1A34.
description: Each measurement day contains in netcdf format the following variables:Time (minutes after midnight UTC)wavelengths (nm lambda)AODModified Angstrom parameters (3 values!)traditional Angstrom parameters (2 values)
DOI: 10.15468/dl.dmpdxv
title: Occurrence Download

description: A dataset containing 151 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tofieldia glabra Nutt."
 ]
}

 The dataset includes 151 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017244-230810091245214/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.937677
title: Landsat image time series (1988-2020) of the Modified Soil Adjusted Vegetation Index (MSAVI) for change detection in the eastern Hindu Kush

description: Based on Landsat satellite imagery we set up a 32-year raster image time series. Due to the arid environment soil noise is an issue therefore we calculated the MSAVI. We carried out the following steps: 1. Data was pre-processed for clouds removal using quality assessment bands, 2. Valleys were extracted using buffers along the river network while non-vegetated areas such as glaciers and mountain slopes were masked out, 3. Breaks for Additive Season and Trend (BFAST) was applied to detect timing, magnitude, and number of breakpoints in the trend component of the time series. The dataset is suitable to analyze land cover change and detect the impacts of disasters in the eastern Hindu Kush region.
DOI: 10.1594/pangaea.937680
title: ADCP current measurements (38 and 75 kHz) during METEOR cruise M159

description: Two Teledyne RDI Ocean Surveyor systems with 38 and 75 kHz transmission frequency were used. Data was processed with a software package developed at GEOMAR following the GO-SHIP standards (Firing and Hummon, 2010). The data was subsequently averaged over one minute intervals and converted to a NetCDF based format.
DOI: 10.1594/pangaea.939108
title: Side scan sonar and swath bathymetry collected along OFOBS profiles PS124_78-8 during POLARSTERN cruise PS124, stave
DOI: 10.1594/pangaea.939114
title: Idealised steady-state and transient simulations of Miocene Antarctic ice-sheet variability using 3D thermodynamical ice-sheet model IMAU-ICE

description: We present results from simulations of the Miocene Antarctic ice sheet, that were performed using the 3D thermodynamical ice-sheet model IMAU-ICE (v1.1.1-MIO). Five steady-state present-day simulations were conducted for reference (PI_ref), and 12 experiments using Miocene settings. Each Miocene experiment comprises 11 steady-state and 4 transient simulations. In the README file, the experiments and simulations are listed.IMAU-ICE was run using a 40x40km grid covering the Antarctic continent. Initial conditions were obtained from reconstructions of the Antarctic bathymetry and bedrock topography pertaining to 23 to 24 million years (Myr) ago (dataset doi:10.1594/PANGAEA.923109). The simulations were forced by climate input data obtained from GENESIS simulations with varying CO2 levels (280 to 840 ppm) and Antarctic ice sheet cover (no ice to a large East-Antarctic ice sheet), and with present-day insolation. We utilized a matrix interpolation method to construct the time-varying climate forcing, based on the prescribed CO2 levels and ice cover simulated by IMAU-ICE.For each simulation, we provide the run script, 1D output variables including CO2 level and the sea level contribution of the Antarctic ice sheet, and 3D output variables including ice thickness, bedrock and surface height, surface mass balance, basal mass balance, ice velocities, and ice temperatures. For more information, please contact L.B. Stap at l.b.stap@uu.nl.
description: ZIP-file containing all the data. Data is structured in separate folders for the different experiments, with subfolders for the different simulations. A list of all the experiments and simulations is given in the README file.
DOI: 10.1594/pangaea.939121
title: Benchmark dataset for 24-hour stratospheric ozone tendencies (SWIFT-AI-DS)

description: SWIFT-AI-DS is a benchmark dataset that consists of samples that have been derived from two simulation runs (each 2.5 years long) of the chemistry and transport model ATLAS (Wohltmann and Rex, 2009; Wohltmann et al., 2010). This data set of nearly 200 million samples meets the requirements of a labelled data set and is ideally suited for training and testing of a machine learning based surrogate model.Two time periods were considered in the simulation runs: first from November 1998 to March 2001 and the second from November 2004 to March 2007.The dataset covers the entire Earth geographically, but is vertically restricted to the altitudes of the lower to middle stratosphere, for which the SWIFT (Rex et al., 2014; Kreyling et. al, 2017; Wohltmann et al., 2017) approach of 24-hour ozone tendencies can be applied. Applicability was determined in terms of the chemical lifetime of stratospheric ozone, which is a function of solar irradiance and altitude. It can be described by a dynamic upper bound [Kreyling et. Al, 2017]. Within the range where the chemical lifetime is longer than 14 days, ozone is not in quasi-chemical equilibrium. Moreover, this data set focuses on the region of the lower to middle stratosphere because it is the region with the largest contribution to the total ozone column.State-of-the-art physical process models for stratospheric chemistry require enormous computational time. Our research is focused on developing much faster, yet accurate, surrogate models for computing the 24-hour tendencies of stratospheric ozone. Much faster models of stratospheric ozone provide a new application area such as for climate models. These surrogate models benefit greatly from the methodological and hardware improvements of the last decade.Each simulation run uses the full stratospheric chemistry model to solve a system of differential equations involving 47 chemical species and 171 chemical reactions at a very high (&lt;&lt; seconds) and variable temporal resolution. The ATLAS model is driven by ECMWF reanalysis data (either ERA-I or ERA5). The air parcel state has been sampled at a 24-hour time step (00:00 UTC model time). During postprocessing some variables are stored as 24-hour averages, as 24-hour tendencies or as the state at the beginning of the 24-hour time step. The dataset is stored in 12 monthly netCDF-files.
description: The benchmark-dataset consists of training- and test-data.Variables are being described in the document Description_variables.pdf.Training-Data:The training data consists of files that include ca. 100 million data samples. Each data sample consists of the input and output features that can be used to train a data-driven model on a regression taskInput X: choice of variables (see document Description_variables.pdf)Output y: 24-hour tendency of stratospheric ozoneTest-Data:Similar to the training data, but this test-data includes ca. 100 million data samples that have not been used for training. It can be used to assess model performance.
DOI: 10.15468/dl.45uf2b
title: Occurrence Download

description: A dataset containing 26 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pristimantis petrobardus (Duellman, 1991)"
 ]
}

 The dataset includes 26 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0299230-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gvc212
title: Occurrence Download

description: A dataset containing 439 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Atlas de la Biodiversité Communal sur la commune de Saint-Geyrac-Inventaire Oiseaux"
 ]
}

 The dataset includes 439 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024890-200221144449610/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.938173
title: Figure 1 to 9 from Lago Formoso sediments in Maranhão State, northeastern Brazil
DOI: 10.1594/pangaea.939125
title: Spatial Data Identifying Strategic Forest Reserves that can Protect Biodiversity in the Western United States and Mitigate Climate Change

description: To support local to international actions on climate change mitigation and biodiversity conservation, this spatial dataset prioritizes forestlands for preservation in the Western United States. The need for joint climate change mitigation and biodiversity conservation has led to efforts to protect 30% of land area by 2030 (30x30) and 50% by 2050 (50x50). A crucial aspects of these efforts is prioritizing lands for new protection so they best achieve climate and biodiversity goals. We developed and applied a quantitative forest preservation priority ranking (PPR) system that incorporated existing geospatial datasets related to forest carbon, biodiversity, and future vulnerabilities to climate change across the Western United States. Specifically, the forest PPR system incorporated estimates of (1) current forest carbon stocks, (2) near-term forest carbon accumulation, (3) terrestrial vertebrate species richness by taxa, (4) tree species richness, and (5) near-term forest vulnerability to increasing mortality rates from drought or fire. Input datasets were re-gridded to a common 1 x 1 km (1 km2) spatial resolution and reflect contemporary (2000-2020) and near-future (2020-2050) forest conditions, with near-future conditions derived using land surface simulations from the Community Land Model (CLM 4.5). We applied the forest PPR system such that each patch of forest (i.e., a 1 km2 grid cell) was ranked relative to others in its ecoregion based on metrics of carbon and/or biodiversity both with and without considering future vulnerabilities (i.e., six scenarios). We assessed the extent of forestlands that are currently protected (GAP 1 or 2; IUCN Ia-VI) and then identified the highest-ranked unprotected forestlands that could be preserved to meet the 30x30 and 50x50 targets using each prioritization scenario. This spatial dataset thus includes the locations of forestlands that could be strategically preserved to meet the 30x30 and 50x50 targets as prioritized using six scenarios. Each raster is provided at 1 km2 resolution in an Albers Equal Area Projection (EPSG 9822) and covers forestlands that occur across the 11 contiguous western states (i.e., Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming). Raster files are in GeoTiff format. These spatial data were produced as part of Law et al. (2021) and support cross-scale efforts to preserve forests for climate change mitigation and biodiversity conservation.
DOI: 10.15468/dl.vabrha
title: Occurrence Download

description: A dataset containing 35 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lepidocentridae",
 "Continent is one of (North America, South America)"
 ]
}

 The dataset includes 35 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017234-230810091245214/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.938751
title: Radiosonde measurements from Neumayer Station (2020-02)

description: The meteorological observatory Neumayer typically launches one radiosonde per day around 12UTC. At least weekly the sonde has an ozone sensor attached. Sondes are released from the roof of the station building. The measurement interval of the raw data is typically 1s. Data is quality controlled: Erroneous data is removed (technical issues). Partial pressure ozone is manually validated for plausibility.
description: Station altitude is 43 m, the launch site is located 25 m higher at 68 m above sea level. The first row of each sounding holds surface data for TTT, RH, ff and dd, which is not acquired by the radiosonde. The measuring height of TTT and RH is 2m, and 10m for dd and ff.
DOI: 10.15468/dl.6dymm8
title: Occurrence Download

description: A dataset containing 8064 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "Country is one of (United States of America, Mexico, Canada)",
 "Year is greater than 1978",
 "Year is less than 2014",
 "HasGeospatialIssue is false",
 "TaxonKey is Paralabrax clathratus (Girard, 1854)"
 ]
}

 The dataset includes 8064 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0113808-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.suaaof
title: Occurrence Download

description: A dataset containing 3403810 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is A global database for the distributions of crop wild relatives"
 ]
}

 The dataset includes 3403810 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027137-200221144449610/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.938754
title: Radiosonde measurements from Neumayer Station (2020-03)

description: The meteorological observatory Neumayer typically launches one radiosonde per day around 12UTC. At least weekly the sonde has an ozone sensor attached. Sondes are released from the roof of the station building. The measurement interval of the raw data is typically 1s. Data is quality controlled: Erroneous data is removed (technical issues). Partial pressure ozone is manually validated for plausibility.
description: Station altitude is 43 m, the launch site is located 25 m higher at 68 m above sea level. The first row of each sounding holds surface data for TTT, RH, ff and dd, which is not acquired by the radiosonde. The measuring height of TTT and RH is 2m, and 10m for dd and ff.
DOI: 10.15468/dl.jbq6u6
title: Occurrence Download

description: A dataset containing 510 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "BasisOfRecord is Living Specimen",
 "BasisOfRecord is Human Observation"
 ]
 },
 "Continent is South America",
 "Geometry POLYGON((-75.73535 12.26074,-80.16064 -0.1626,-70.8794 -4.59229,-66.03223 -5.45801,-67.11767 5.95459,-70.11035 12.26074,-71.89892 13.02099,-75.73535 12.26074))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Iguana iguana (Linnaeus, 1758)",
 "Year 1991-2022"
 ]
}

 The dataset includes 510 records from 65 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0309671-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.938757
title: Radiosonde measurements from Neumayer Station (2020-04)

description: The meteorological observatory Neumayer typically launches one radiosonde per day around 12UTC. At least weekly the sonde has an ozone sensor attached. Sondes are released from the roof of the station building. The measurement interval of the raw data is typically 1s. Data is quality controlled: Erroneous data is removed (technical issues). Partial pressure ozone is manually validated for plausibility.
description: Station altitude is 43 m, the launch site is located 25 m higher at 68 m above sea level. The first row of each sounding holds surface data for TTT, RH, ff and dd, which is not acquired by the radiosonde. The measuring height of TTT and RH is 2m, and 10m for dd and ff.
DOI: 10.1594/pangaea.938761
title: Radiosonde measurements from Neumayer Station (2020-05)

description: The meteorological observatory Neumayer typically launches one radiosonde per day around 12UTC. At least weekly the sonde has an ozone sensor attached. Sondes are released from the roof of the station building. The measurement interval of the raw data is typically 1s. Data is quality controlled: Erroneous data is removed (technical issues). Partial pressure ozone is manually validated for plausibility.
description: Station altitude is 43 m, the launch site is located 25 m higher at 68 m above sea level. The first row of each sounding holds surface data for TTT, RH, ff and dd, which is not acquired by the radiosonde. The measuring height of TTT and RH is 2m, and 10m for dd and ff.
DOI: 10.1594/pangaea.938762
title: Radiosonde measurements from Neumayer Station (2020-06)

description: The meteorological observatory Neumayer typically launches one radiosonde per day around 12UTC. At least weekly the sonde has an ozone sensor attached. Sondes are released from the roof of the station building. The measurement interval of the raw data is typically 1s. Data is quality controlled: Erroneous data is removed (technical issues). Partial pressure ozone is manually validated for plausibility.
description: Station altitude is 43 m, the launch site is located 25 m higher at 68 m above sea level. The first row of each sounding holds surface data for TTT, RH, ff and dd, which is not acquired by the radiosonde. The measuring height of TTT and RH is 2m, and 10m for dd and ff. Sounding was performed using a different method (Radiosonde, Vaisala, RS92-SGP) on 2020-06-20T12:00.
DOI: 10.1594/pangaea.938764
title: Radiosonde measurements from Neumayer Station (2020-07)

description: The meteorological observatory Neumayer typically launches one radiosonde per day around 12UTC. At least weekly the sonde has an ozone sensor attached. Sondes are released from the roof of the station building. The measurement interval of the raw data is typically 1s. Data is quality controlled: Erroneous data is removed (technical issues). Partial pressure ozone is manually validated for plausibility.
description: Station altitude is 43 m, the launch site is located 25 m higher at 68 m above sea level. The first row of each sounding holds surface data for TTT, RH, ff and dd, which is not acquired by the radiosonde. The measuring height of TTT and RH is 2m, and 10m for dd and ff.