cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3941973
title: FAOSTAT Forest Land Emissions

description: The Forest Land dataset disseminates information on emissions and area change due to gain and losses of carbon stocks in living (aboveground and belowground) tree biomass. Estimates are computed following land Approach 1 and Tier 3 ( stock difference method) of the 2006 IPCC Guidelines for National GHG Inventories (IPCC, 2006). Data on carbon stocks and forest area used as input are those of the Forest Resources Assessment 2020 (FAO, 2020). Data are available by country, with global coverage and relative to the period 1990-2020. This domain contains data on net CO<sub>2</sub> emissions/removals, associated implied emission factors and underlying activity data. The FAOSTAT Emissions data are estimated by FAO and do not coincide with GHG data reported by Parties to UNFCCC. FAOSTAT data and estimates support member countries to assess and report their emissions and removals. FAOSTAT emissions data are a global knowledge product.
description: README. Data for forest land (GF) are organizes by Area Code and Area Name --corresponding to FAOSTAT (M49) codes, with official names of FAO member countries and territories. Item/elements combinations are those available at the parent FAOSTAT domain (see FAOSTAT definitions and standards within http://www.fao.org/faostat/en/#data/GF). Items include forest land total (6749), forest land (6646) and net forest conversion (6650), For each of these, information is provided on carbon stocks (72151), carbon stock density (72152), net emissions/removals is CO2 (72332) and implied emissions factors (71952).
description: {"references": ["Federici. S., Tubiello, F.N., Salvatore, M., Jacobs, H. and Schmidhuber, J., 2015. New estimates of CO2 forest emissions and removals: 1990-2015. Forest Ecol Manag. 352:89-98."]}
DOI: 10.5281/zenodo.4011629
title: LiDAR dataset

description: These are the modified LiDAR data used in Bernard et al. (2020). Original pre-earthquake LiDAR can be found at: http://dx.doi.org/10.5069/G9G44N75 Original post-earthquake data can be accessible on request.
DOI: 10.5281/zenodo.4399453
title: An All-sky 1 km Daily Surface Air Temperature Product over Mainland China

description: An all-sky daily mean surface air temperature (T<sub>a</sub>) product at 1 km spatial resolution over mainland China for 2003–2019 has been generated mainly from the Moderate Resolution Imaging Spectroradiometer (MODIS) products and the Global Land Data Assimilation System (GLDAS) dataset. Three T<sub>a</sub> estimation models based on random forest were trained using ground measurements from 2384 stations for three different clear-sky and cloudy-sky conditions. The validation results showed that R<sup>2</sup> and root mean square error (RMSE) values of the three models ranged from 0.984 to 0.986 and 1.342 K to 1.440 K, respectively, indicating that this high-resolution product has satisfactory accuracy. The format of the data is tif and a sample data is provided in example.zip. The dataset is stored by year, with 6 *.zip files per year. There is also an all-sky 0.01° daily surface air temperature product over Beijing for 2003–2019 (http://doi.org/10.5281/zenodo.4405123), which is a sub-dataset generated from this dataset for easy and convenient understanding of this dataset. And the sub-dataset has a data volume of only 264MB after compressed.
description: The dataset is also available at the University of Maryland (http://glass.umd.edu/Ta_China/). Due to the upload size restrictions, only the dataset for 2003–2008 is included on this site, and the complete dataset can be freely downloaded at http://glass.umd.edu/Ta_China/.
DOI: 10.5281/zenodo.4405123
title: An All-sky 0.01° Daily Surface Air Temperature Product over Beijing (2003-2019)

description: This dataset is a provincial sub-dataset generated from the all-sky 1 km daily surface air temperature product over mainland China (http://doi.org/10.5281/zenodo.4399453) after resampling and clipping. The raw dataset was developed mainly from the Moderate Resolution Imaging Spectroradiometer (MODIS) products and the Global Land Data Assimilation System (GLDAS) dataset. The sub-dataset has a total data volume of only 264MB after compressed, making data download and understanding easier, and it also presents the characteristics of the raw dataset well. People who are interested in that big dataset can download the provincial sub-dataset first. This sub-dataset was validated using ground measurements from 20 meteorological stations, with R<sup>2</sup> and root mean square error (RMSE) values of 0.987 and 1.295 K, respectively, which proved reliability of this high-resolution dataset. In order to make this big dataset easier to understand and use, we made a provincial sub-dataset with a smaller geographic coverage.
description: The format of the data is tif and a sample data is provided in sample.zip. The dataset is stored by year and compressed into zipped files. More details about this dataset are given in the readme.pdf.
DOI: 10.5281/zenodo.4415788
title: WRF-Chem Volcano output - Etna Summer 2012

description: Output from a model run of a modified version of WRF-Chem, which we refer to as WRF-Chem Volcano (WCV). At the time of submission of this dataset, these data were the basis of the modelling part of a paper submitted imminently to [Atmospheric Chemistry and Physics Discussions (ACPD)]: "Observation and modelling of ozone-destructive chemistry in a quiescent degassing volcanic plume". The code of WCV is maintained here. Development of this code will continue after the submission of this repository, This branch is a permanent record of the code as used to create this dataset.<br> This is a simulation of the chemistry of the degassing plume of Etna in July/August 2012. This simulation includes bromine, chlorine and mercury chemistry. The time period modelled for the main and novolc runs is the 29 July - 01 August, however the first 24 hours of simulation are considered to be "spin up" and these data are not uploaded here. Other runs were begun from the state of the <em>main</em> model run at 2012-08-01 00:00 and therefore only output for this one day exists. All data here relates to domain "d04", which is the innermost nest (see Figure 3 of paper). Data from multiple runs is uploaded here, see Table 2 of paper. <strong>Overview of files</strong> <strong><em>Output files: RUNNAME_wrfout_d04_YYYY-MM-DD_HH:MM:SS</em></strong> Output data is contained in NetCDF files. Each file contains hourly snapshots of the 3D simulation with fields for various parameters. Most of the 4D (three spatial dimensions and time) variables record modelled mixing ratios of various gaseous species (in units ppm) and aerosol species (separated by species and size bin, in units ug/kg-dry-air). Many other variables are standard WRF-Chem output variables; please see WRF-Chem's documentation. If the meaning of a variable is unclear, please contact the author. Each file covers a period of 24 hours. Runs <em>main</em>, <em>novolc</em> and <em>hal00</em> were run for the full model period. The other runs were run for 2012-08-01 only, beginning with the model state of <em>main</em> at 2012-08-01 00:00:00 <em><strong>WRF-Chem namelist files</strong></em> <em>namelist.wps</em> is the input file used for the WPS pre-processor (common to all runs). <em>namelist.input</em> is the input file used for WRF, this file is common to all runs with volcanic emissions. <em>namelist.input_novolc </em>is the input file used for the novolc run <strong><em>PREP-CHEM SRC input files: prep_chem_sources_RUNNAME.inp</em></strong> Input files for PrepChem for each run with volcanic emissions.
DOI: 10.5281/zenodo.4974826
title: Last Interglacial Sea Levels within the Korean Peninsula

description: This file contains a table of the data input into the standardized database entitled World Atlas of Last Interglacial Shorelines (WALIS) database by Ryang and Simms for the Korean Peninsula. The data contains age and elevations obtained from Last Interglacial Shoreline across the Korean Peninsula.
DOI: 10.5281/zenodo.5025802
title: Datasets for "A holistic framework to estimate the origins of atmospheric moisture and heat using a Lagrangian model"

description: This repository contains the post-processed model outputs from HAMSTER as used in the publication "A holistic framework to estimate the origins of atmospheric moisture and heat using a Lagrangian model" by Jessica Keune, Dominik L. Schumacher, and Diego G. Miralles.<br> <br> The data set contains (1) global validation statistics for the three fluxes (evaporation, precipitation, sensible heat), and (2) the climatological source regions of precipitation and heat for Denver, Beijing and Windhoek. The former are found in the directory 'validation/global', and the latter are found in the directories '1001' (Denver), '3001' (Beijing) and '5002' (Windhoek). Multiple experiments were performed to assess the uncertainty of the source regions. Thus, multiple files exist, that show the same variables but for multiple experiments (indicated by the names "ALLPBL", "RH-10-20", "SOD08-SCH19", "SCH20", "FAS19" in the file name). For the source regions, the uncertainty of the attribution methodology was assessed; these are indicated by the different folders, i.e. 'linear', 'linear_upscaled', 'random' and 'random_upscaled'. For each city and each experiment, the climatologically averaged source regions ('_mean.nc') and the climatologically averaged individual backward day contributions ('_bwmean.nc') are provided. Data sets are in the netCDF format and contain metadata following the CF convention.<br>
description: {"references": ["Keune, J., D. L. Schumacher, D. G. Miralles (2021, June 1). h-cel/hamster: Public release of HAMSTER (Version v1.0.0). Zenodo. http://doi.org/10.5281/zenodo.4889311", "Keune, J., D. L. Schumacher, D. G. Miralles (manuscript submitted): A holistic framework to estimate the origins of atmospheric moisture and heat using a Lagrangian model."]}
DOI: 10.5281/zenodo.5745363
title: Rotterdam EyePACS AIROGS train set

description: The Rotterdam EyePACS AIROGS train set contains 101,442 color fundus images from 54,274 subjects and approximately 500 different sites with a heterogeneous ethnicity. All images were assigned by human experts with the labels referable glaucoma, no referable glaucoma, or ungradable. This dataset contains the data for training data of the AIROGS challenge, which is held as part of ISBI 2022. See https://airogs.grand-challenge.org/ for more information on the still ongoing challenge. The paper that summarizes the AIROGS challenge is available on ArXiv here: https://arxiv.org/abs/2302.01738. Please cite as follows: <pre>@article{devente23airogs, title={AIROGS: Artificial Intelligence for RObust Glaucoma Screening Challenge}, author={de Vente, Coen and Vermeer, Koenraad A. and Jaccard, Nicolas and Wang, He and Sun, Hongyi and Khader, Firas and Truhn, Daniel and Aimyshev, Temirgali and Zhanibekuly, Yerkebulan and Le, Tien-Dung and Galdran, Adrian and González Ballester, Miguel Ángel and Carneiro, Gustavo and G, Devika R and S, Hrishikesh P and Puthussery, Densen and Liu, Hong and Yang, Zekang and Kondo, Satoshi and Kasai, Satoshi and Wang, Edward and Durvasula, Ashritha and Heras, Jónathan and Zapata, Miguel Ángel and Araújo, Teresa and Aresta, Guilherme and Bogunović, Hrvoje and Arikan, Mustafa and Lee, Yeong Chan and Cho, Hyun Bin and Choi, Yoon Ho and Qayyum, Abdul and Razzak, Imran and van Ginneken, Bram and Lemij, Hans G. and Sánchez, Clara I.}, journal={arXiv preprint arXiv:2302.01738}, year={2023} }</pre>
description: The previous version was split into two records. This new version contains all data and the second record is deprecated.
DOI: 10.5281/zenodo.7576413
title: VOCdata_O3_Na2S2O3scrubber

description: contact: Lisa Ernle (lisa.ernle@mpic.de), M. Akima Ringsdorf (a.ringsdorf@mpic.de), Jonathan Williams (jonathan.williams@mpic.de) instruments: fast GC-MS SOFIA (MPIC), PTR-ToF-MS 4000 (Ionicon) merged dataset calibrated with VOC standard gas mix (Apel-Riemer Environmental Inc., Colorado, USA) all values are parts per billion (ppb) for information concerning updated versions, please see ReadMe.txt
DOI: 10.5683/sp2/wrwjaz
title: MATLAB code for firn thermodynamic and hydrological modelling

description: This repository contains MATLAB source code for a model of glacier surface energy balance, coupled with a subsurface (snow and firn) thermodynamic and hydrological evolution. The default configuration of the subsurface model is for a 35-m firn column, with 0.1-m thick layers from 0-0.6 m, 0.2-m thick layers from 0.6-2 m, 0.4-m thick layers from 2-10 m, and 1-m thick layers below that. The model requires forcing from mean daily automatic weather station, climate model, or climate reanalysis data, with the default inputs being: minimum, mean, and maximum daily air temperature, mean daily relative or specific humidity, wind speed, air pressure, and longwave radiation, and mean and maximum daily incoming incoming shortwave. The model internally calculates snow albedo and snow surface temperature (hence, outgoing longwave radiation), as well as conductive heat flux to the snow surface, based on temperature gradients in the top three layers of the subsurface snow/firn model. See the referenced papers for further details on the model physics and parameterizations. The readme file with the code repository includes additional details and references.
DOI: 10.1594/pangaea.905498
title: Code for ancient ocean 5 box model on euxinic/ferruginous balance and the nitrogen cycle

description: Code for ancient ocean 5 box model on euxinic/ferruginous balance and the Nitrogen cycle, by Richard Boyle 2018 .This paper was a deep-time adaptation of a contemporary ocean box model: Canfield, D. E. Models of oxic respiration, denitrification and sulphate reduction in zones of coastal upwelling. Geochim. Cosmochim. Act 70, 5753-5765 (2006). The main difference is the inclusion of direct limitation of export production by reduced nitrogen. This is only a semi-quantitative box model and the results discussed in the paper are parameter sensitive.
DOI: 10.25919/ezp0-em87
title: MARCUS ARM CN and CCN data reprocessed to remove ship exhaust influence

description: The MARCUS (Measurements of Aerosols, Radiation and CloUds over the Southern Oceans) campaign occurred between October 2017 and March 2018 aboard RSV Aurora Australis during its summer season resupplying Australia’s Antarctic research stations from its port in Hobart, Australia. The campaign involved deploying the ARM Mobile Facility (https://www.arm.gov/capabilities/observatories/amf) aboard the Aurora Australis in order to collect data in sea-ice locations inaccessible to platforms without ice-breaking capability. The data set presented in this collection are the cloud condensation nuclei (CCN) and condensation nuclei (CN) data set with contamination by ship exhaust removed.
DOI: 10.5281/zenodo.5733402
title: The effects of surface roughness on the spectral (300-1400 nm) bidirectional reflectance distribution function (BRDF) of sea ice

description: Please cite the following publication when using the data: <br> Lamare, M. L., Hedley, J. D., and King, M. D.: The effects of surface roughness on the calculated, spectral, conical–conical reflectance factor as an alternative to the bidirectional reflectance distribution function of bare sea ice, The Cryosphere, 17, 737–751, https://doi.org/10.5194/tc-17-737-2023, 2023. "BRF_results" contains BRDF output files from the radiative-transfer model PlanarRad. BDRF was computed for three different types of sea ice with varying roughness parameters and <br> thicknesses. The folder tree is constructed with the following structure: BRF_results<br> - Solar Zenith angles<br> - Roughness parameters<br> - Sea ice thicknesses<br> - Wavelengths<br> - Sea ice types
DOI: 10.15468/dl.475f7c
title: Occurrence Download

description: A dataset containing 5504208 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "OccurrenceStatus is Present",
 "TaxonKey is Parus major Linnaeus, 1758",
 "Year 2010-2020"
 ]
}

 The dataset includes 5504208 records from 4022 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004551-250123221155621/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w9ujk2
title: Occurrence Download

description: A dataset containing 70 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((2.456998761619918 5.040497240777794,6.456998761619918 5.040497240777794,6.456998761619918 9.040497240777794,2.456998761619918 9.040497240777794,2.456998761619918 5.040497240777794))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Lophira lanceolata Tiegh. ex Keay"
 ]
}

 The dataset includes 70 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0324906-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8htwbw
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cryptanthus colnagoi Rauh & Leme"
 ]
}

 The dataset includes 10 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0154381-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zjx6t3
title: Occurrence Download

description: A dataset containing 1083 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Kunzea muelleri Benth."
 ]
}

 The dataset includes 1083 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080881-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dem7j6
title: Occurrence Download

description: A dataset containing 51 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Peru",
 "TaxonKey is Opuntia ficus-indica (L.) Mill."
 ]
}

 The dataset includes 51 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008664-190813142620410/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ce4rbr
title: Occurrence Download

description: A dataset containing 373966 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is National Finnish butterfly monitoring scheme (NAFI)"
 ]
}

 The dataset includes 373966 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008705-210819072339941/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e7v5ya
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Asparagus yanyuanensis S.C.Chen"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017251-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tnlinz
title: Occurrence Download

description: A dataset containing 41 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Rhinoplax vigil (Pennant, 1781)",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 41 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009539-190813142620410/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pxfcl4
title: Occurrence Download

description: A dataset containing 56 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Gehyra papuana Meyer, 1874"
 ]
}

 The dataset includes 56 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003035-180412121330197/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sqxpyb
title: Occurrence Download

description: A dataset containing 11094 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Trogon citreolus Gould, 1835"
 ]
}

 The dataset includes 11094 records from 59 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006291-190813142620410/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jebvxe
title: Occurrence Download

description: A dataset containing 311 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Plantae",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Country is Germany",
 "DecimalLongitude is greater than or equal to 14.7512724474825",
 "DecimalLongitude is less than 14.7543320006669",
 "DecimalLatitude is greater than or equal to 47.27011",
 "DecimalLatitude is less than or equal to 55.05864"
 ]
}

 The dataset includes 311 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017266-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v5uagi
title: Occurrence Download

description: A dataset containing 191 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is New Zealand",
 {
 "or" : [
 "PublishingOrg is 6b2f029b-7823-4b84-9c30-31ff364238fe",
 "PublishingOrg is 28eb1a3f-1c15-4a95-931a-4af90ecb574d",
 "PublishingOrg is 32e82a64-c9b4-4b2f-9fbd-d446309b973f"
 ]
 },
 "HasCoordinate is true",
 "TaxonKey is Pinus contorta Douglas ex Loudon",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 191 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009542-190813142620410/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cjedns
title: Occurrence Download

description: A dataset containing 1206 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Sturnornis albofrontatus (E.L.Layard, 1854)"
 ]
}

 The dataset includes 1206 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010374-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cnpqe3
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tarsopterus trachystomus Reinhardt & Lütken, 1862"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010672-190813142620410/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.