cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14768/c2f7b2aa-8f6f-4718-8972-d9bc23f3c064
title: Projected changes in land carbon store simulated by ORCHIDEE v3 (r7267)

description: In Riano Sanchez et al. (2024), we quantify the projected change in land car- bon store (CLCS) over 2015-2100 for the different shared socioeconomic pathways (SSPs) from land-only simulations of the ORCHIDEE v3 land surface model (LSM) (Vuichard et al., 2019) driven by climate data from the IPSL- CM6 ESM (Boucher et al., 2020). In addition, through a set of crossed multi-factorial simulations, we also aim at estimating the CLCS dispersions associated specifically with climate and [CO2] (CCO2), land use change (LUC), and nitrogen input (NIN) trajectories.

The published dataset corresponds to the simulations performed with the ORCHIDEE v3 model (revision 7267), for the study published by Riano Sanchez et al. (2024) in Earth System Dynamics. They consist in 64 factorial simulations in which for a combination of 4 climate and atmospheric [CO2] trajectories, 4 land use change trajectories and 4 nitrogen input trajectories. 

The dataset contains a set of carbon-related variables at monthly time scales (see below) for the 64 sensitivity simulations.

Variable name Variable description Units Time frequency
cLand Carbon in Land kg m-2 monthly
cVeg Carbon in Vegetation kg m-2 monthly
cLitter Carbon in Litter Pool kg m-2 monthly
cSoil Carbon in Soil kg m-2 monthly
cProduct Carbon in Products of Land Use Change kg m-2 monthly
CONTFRAC Fractional continental cover - once
Areas Mesh area m-2 once

•Reference (article) : Riano Sanchez, J. A., Vuichard, N., and Peylin, P.: Projected changes in land carbon store over the 21st century: what contributions from land-use change and atmospheric nitrogen deposition?, Earth Syst. Dynam. Discuss. [preprint], https://doi.org/10.5194/esd-2023-31, in review, 2023.
DOI: 10.1594/pangaea.900204
title: Meteorological measurements by dropsondes released from POLAR 5 during ACLOUD 2017

description: Vertical profiles of air temperature, humidity, pressure, and the horizontal wind vector measured by dropsondes (type RS904) released from Polar 5 during ACLOUD 2017. The profiles cover altitudes between the flight level of Polar 5 (typically 3-4 km) and the surface. Observations during ACLOUD cover a range of cloud-free and cloud covered situations over open ocean and closed sea ice west and north of Svalbard. The ASPEN software package was used to correct the raw data for the slow time response of the temperature sensor and to remove the known humidity bias. Data close to the aircraft, where the sensors still did not adjust to the outside temperature, and invalid measurements were removed by the quality check of ASPEN. To resolve temperature and humidity changes at cloud top the time response of the sensors has been corrected by an alternative method following (Miloshevich et al. 2004)
description: *** PLEASE NOTE *** On 2019-11-07 a corrected version 2 was added to this dataset containing one flight more, please use V2.
DOI: 10.1594/pangaea.907818
title: Global soil and peat branched GDGT compilation dataset

description: Accurate temperature records for the deep geological past are a vital component of paleoclimate research. Distributional changes of branched glycerol dialkyl glycerol tetraether (brGDGT) lipids in geological archives including paleosoils are a promising indicators to infer past continental air temperatures. However, the 'orphan' status of the brGDGTs, the potential effect of temperature-independent parameters on their relative distribution, and the uneven geographical distribution of the soils used for calibration contribute to the high uncertainty of brGDGT-based transfer functions (root mean squared error, RMSE: ± 5 °C). Here, we expand the soil dataset from the previous calibration(s) with new and published soil data. We use Bayesian statistics to calibrate the relationship of the 5-methyl brGDGTs (MBT'5Me) and mean annual air temperature (MAAT). The addition of soils from warm (&gt;28 °C) environments from India substantially increases the upper limit of the Bayesian calibration (BayMBT) from 25 to 29 °C, aiding in the generation of temperature records for past greenhouse climates, such as the Eocene. The BayMBT model also effectively minimizes the structured MAAT residuals prevalent in previous calibrations, therefore giving the opportunity to explore confounding factors on the calibration. We formulate a set of alternative calibration models to test the effect of specific environmental parameters and show that soils at mid-latitudes with temperature seasonalities &gt;20 °C are not well described by the BayMBT model. We find that the MBT'5Me index is best correlated to the average temperature of all months &gt;0 °C, called the BayMBT0 model. This finding supports the hypothesis that brGDGT production ceases or slows down in the winter months. However, a persistent feature of the BayMBT model and previous calibrations is the significant scatter at mid-latitudes, which is speculatively linked with a possible increase in diversity of microbial brGDGT-producing communities in these locations.
description: Supplement to: Dearing Crampton-Flood, Emily; Tierney, Jessica E; Peterse, Francien; Kirkels, Frédérique M S A; Sinninghe Damsté, Jaap S (2020): BayMBT: A Bayesian calibration model for branched glycerol dialkyl glycerol tetraethers in soils and peats. Geochimica et Cosmochimica Acta, 268, 142-159
DOI: 10.1594/pangaea.923719
title: Total above-ground biomass of 39 vegetation sites of central Chukotka from 2018

description: Field investigations were performed in four areas: a treeless mountainous tundra (16-KP-04; Lake Rauchuagytgyn area), tundra-taiga transition zone (16-KP-01, Lake Ilirney area) and a northern taiga (18-BIL-01, 18-BIL-02). In total, 39 sites were investigated. The sites were placed to cover different vegetation communities that characterise central Chukotka.Fifteen-meter radius sample plots (sites) were demarcated in the most homogeneous locations. Heterogeneity was accommodated by roughly assorting vegetation into two to three vegetation types per sampling plot. Within each area of roughly estimated vegetation types we selected one 0.5 x 0.5 m subplot for representative ground-layer above-ground biomass (ABG) harvesting (major taxa and other). For moss and lichen AGB harvesting inside 0.5 x 0.5 m subplots representative 0.1 x 0.1 m subplots were chosen. All ground-layer vegetation AGB assessments were calculated for the fifteen-meter radius plot in g m^2 for each sample plot. Tree (Larix cajanderi) AGB was assessed using partial harvesting of three representative individual trees per sample plot, specifically developed for the study area allometric equations and measurements of all trees' heights on the fifteen-meter radius plot. AGB of tall shrubs (Alnus fruticosa, Pinus pumila and Salix spp. (non-creeping)) was assessed from harvested subsamples and projective cover on the fifteen-meter radius sample plot.All harvested AGB samples were weighed fresh in the field. In general, AGB samples with a weight of more than 15 g were subsampled. All samples were oven dried (60 °C, 24 h for ground-layer and moss and lichen samples, 48 h for shrub and tree branch samples, up to one week for tree stem discs) and weighed again.All data was collected by scientists from Alfred Wegener Institute (AWI), Helmholtz Centre for Polar and Marine Research and University of Potsdam, Germany, The Institute for Biological problems of the Cryolithozone, Russian Academy of Sciences, Siberian branch, and The Institute of Natural Sciences, North-Eastern Federal University of Yakutsk, Yakutsk, Russia.
DOI: 10.1594/pangaea.925621
title: Continuous meteorological observations at station Ny-Ålesund (2020-07)
DOI: 10.17592/001.2020112001
title: Black carbon mass concentrations and aerosol light absorption coefficients measured at Arctic sites

description: Black carbon mass concentrations and aerosol light absorption coefficients measured by filter-based absorption photometers at Alert in Canada, Ny-Alesund in Svalbard, Utqiagvik (NOAA Barrow Observatory) in Alaska, Pallastunturi in Finland, and Fukue in Japan.
DOI: 10.25326/221
title: JOANNE : Joint dropsonde Observations of the Atmosphere in tropical North atlaNtic meso-scale Environments

description: As part of the EUREC4A field campaign which took place over the tropical North Atlantic during January-February 2020, 1216 dropsondes from the HALO and WP-3D aircraft were deployed through 26 flights to improve the current understanding of the atmospheric environment in the trade-wind regions, complementing simultaneous measurements from a multitude of platforms. We present JOANNE, the dataset that contains these dropsonde measurements of temperature, pressure, relative humidity and horizontal winds, along with the products derived from them to characterize the dynamic and thermodynamic environment in the trade-wind regions. Together with the raw measurement profiles and basic post-processing, the dataset also includes a homogenized and gridded data set with 10 m vertical spacing (Level 3 product). The gridded data are used as a basis for deriving diagnostics of the area-averaged meso-scale circulation properties such as divergence, vorticity, vertical velocity and gradient terms (Level 4 product), making use of sondes dropped at regular intervals along a circular flight path. 85 such circles, 222 km in diameter, were flown during EUREC4A. The sampling strategy for dropsonde measurements during EUREC4A, the quality control for the data, the methods of estimation of additional products from the measurements and the different post-processed levels of the dataset are explained in the JOANNE publication on ESSD.
DOI: 10.25966/3d2p-f515
title: IceCube Level 1 Radiance Data and Codes

description: This zipped meta data file can be expanded into two folders. One folder contains the daily calibrated Level 1 radiance and geolocation data in HDF5 format, and the other folder contains the main IDL codes that process the data and make plots (mainly for generating plots for the paper Gong et al. 2021 that is under review for Earth Science System Data journal). Both folders contain a README file in each to guide readers through the file name, variable namelist, quality flag, code's usage, etc.
DOI: 10.26050/wdcc/sawam_d01_seas5_bcsd
title: Seasonal Water Resources Management for Semiarid Areas: Bias-corrected and spatially disaggregated seasonal forecasts for the Karun Basin (Iran)

description: Project: Seasonal Water Resources Management for Semiarid Areas: Regionalized Global Data and Transfer to Practise - GRoW-SaWaM (BMBF): The SaWaM-Project, which is funded by the German Federal Ministry of Education and Research (BMBF) within the "Water as a global Resource (GRoW)“ initiative, aims at the development of methods and products for improving the water management in semi-arid regions. The methodological core of the project is a model chain, where global hydrometeorological information is first adapted towards five different study regions in Brazil (Rio São Francisco Basin), Iran (Karun Basin), Sudan and Ethiopia (Tekeze-Atbara and Blue Nile Basins), Ecuador and Peru (Catamayo-Chira Basin) and West-Africa (Niger and Volta Basins). Special focus is put on the application of seasonal hydrometeorological forecasts, which give information about the precipitation or temperature to be expected during the coming months. The regionalized information is then used as driving data for hydrological and ecosystem models, which allow for the description of water-management-related parameters and aspects both in the past, but also for the coming months. Further information can be found at http://grow-sawam.org/. Summary: This dataset group contains the regionalised seasonal forecasts for the SaWaM study domain D01 (Karun Basin, Iran). The data is based on the latest seasonal forecast product SEAS5 from the European Centre for Medium Range Weather Forecast (ECMWF), which has been Bias-Corrected and Spatially Disaggregated (BCSD) towards the ERA5-Land high-resolution replay of the land component of ECMWF's ERA5 climate reanalysis. It hence provides a temporally and spatially consistent set of land surface variables for driving e.g. hydrological models or assessing the regional forecast skill of seasonal forecasts. Currently, the dataset group contains daily and monthly ensemble (re)forecasts during the period 1981 to 2019. In particular, each forecast with 25 (before 2017) and 51 (since 2017) ensemble members contains daily and monthly forecasts for precipitation, maximum, minimum, and average temperature as well as radiation from the issue date for the next 215 days.
DOI: 10.26050/wdcc/sawam_d02_seas5_bcsd
title: Seasonal Water Resources Management for Semiarid Areas: Bias-corrected and spatially disaggregated seasonal forecasts for the Rio São Francisco Basin (Brazil)

description: Project: Seasonal Water Resources Management for Semiarid Areas: Regionalized Global Data and Transfer to Practise - GRoW-SaWaM (BMBF): The SaWaM-Project, which is funded by the German Federal Ministry of Education and Research (BMBF) within the "Water as a global Resource (GRoW)“ initiative, aims at the development of methods and products for improving the water management in semi-arid regions. The methodological core of the project is a model chain, where global hydrometeorological information is first adapted towards five different study regions in Brazil (Rio São Francisco Basin), Iran (Karun Basin), Sudan and Ethiopia (Tekeze-Atbara and Blue Nile Basins), Ecuador and Peru (Catamayo-Chira Basin) and West-Africa (Niger and Volta Basins). Special focus is put on the application of seasonal hydrometeorological forecasts, which give information about the precipitation or temperature to be expected during the coming months. The regionalized information is then used as driving data for hydrological and ecosystem models, which allow for the description of water-management-related parameters and aspects both in the past, but also for the coming months. Further information can be found at http://grow-sawam.org/. Summary: This dataset group contains the regionalised seasonal forecasts for the SaWaM study domain D02 (Rio São Francisco, Brazil). The data is based on the latest seasonal forecast product SEAS5 from the European Centre for Medium Range Weather Forecast (ECMWF), which has been Bias-Corrected and Spatially Disaggregated (BCSD) towards the ERA5-Land high-resolution replay of the land component of ECMWF's ERA5 climate reanalysis. It hence provides a temporally and spatially consistent set of land surface variables for driving e.g. hydrological models or assessing the regional forecast skill of seasonal forecasts. Currently, the dataset group contains daily and monthly ensemble (re)forecasts during the period 1981 to 2019. In particular, each forecast with 25 (before 2017) and 51 (since 2017) ensemble members contains daily and monthly forecasts for precipitation, maximum, minimum, and average temperature as well as radiation from the issue date for the next 215 days.
DOI: 10.26050/wdcc/sawam_d04_seas5_bcsd
title: Seasonal Water Resources Management for Semiarid Areas: Bias-corrected and spatially disaggregated seasonal forecasts for the Catamayo-Chira Basin (Ecuador/Peru)

description: Project: Seasonal Water Resources Management for Semiarid Areas: Regionalized Global Data and Transfer to Practise - GRoW-SaWaM (BMBF): The SaWaM-Project, which is funded by the German Federal Ministry of Education and Research (BMBF) within the "Water as a global Resource (GRoW)“ initiative, aims at the development of methods and products for improving the water management in semi-arid regions. The methodological core of the project is a model chain, where global hydrometeorological information is first adapted towards five different study regions in Brazil (Rio São Francisco Basin), Iran (Karun Basin), Sudan and Ethiopia (Tekeze-Atbara and Blue Nile Basins), Ecuador and Peru (Catamayo-Chira Basin) and West-Africa (Niger and Volta Basins). Special focus is put on the application of seasonal hydrometeorological forecasts, which give information about the precipitation or temperature to be expected during the coming months. The regionalized information is then used as driving data for hydrological and ecosystem models, which allow for the description of water-management-related parameters and aspects both in the past, but also for the coming months. Further information can be found at http://grow-sawam.org/. Summary: This dataset group contains the regionalised seasonal forecasts for the SaWaM study domain D04 (Catamayo-Chira Basin, Ecuador and Peru). The data is based on the latest seasonal forecast product SEAS5 from the European Centre for Medium Range Weather Forecast (ECMWF), which has been Bias-Corrected and Spatially Disaggregated (BCSD) towards the ERA5-Land high-resolution replay of the land component of ECMWF's ERA5 climate reanalysis. It hence provides a temporally and spatially consistent set of land surface variables for driving e.g. hydrological models or assessing the regional forecast skill of seasonal forecasts. Currently, the dataset group contains daily and monthly ensemble (re)forecasts during the period 1981 to 2019. In particular, each forecast with 25 (before 2017) and 51 (since 2017) ensemble members contains daily and monthly forecasts for precipitation, maximum, minimum, and average temperature as well as radiation from the issue date for the next 215 days.
DOI: 10.34740/kaggle/dsv/7548853
title: arXiv Dataset
DOI: 10.5067/e9e9qsrnlytk
title: IceBridge LVIS L2 Geolocated Surface Elevation Product, Version 2
DOI: 10.5067/lis/isslis/data107
title: Non-Quality Controlled Lightning Imaging Sensor (LIS) on International Space Station (ISS) Science Data
DOI: 10.5067/oc7b04zm9g6q
title: MEaSUREs Greenland Ice Sheet Velocity Map from InSAR Data, Version 2
DOI: 10.5067/telnd-3ac63
title: CSR TELLUS GRACE Level-3 Monthly Land Water-Equivalent-Thickness Surface Mass Anomaly Release 6.0 version 03 in netCDF/ASCII/GeoTIFF Formats
DOI: 10.5281/zenodo.13356055
title: Proteomic changes upon treatment with semaglutide in individuals with obesity

description: Proteomic changes upon treatment with semaglutide in individuals with obesity
DOI: 10.5281/zenodo.3906170
title: PALM_ERP_Inputdata

description: <strong>Input data for performing a simulation of the Ernst-Reuter-Platz in Berlin, including the "building indoor model" embedded to PALM model system 6.0</strong> This dataset includes the input information applied to perform a simulation for a winter and a summer scenario of the Ernst-Reuter-Platz in Berlin including the "building indoor model" . The content: <em>ERP_&lt;simulation scenario&gt;_static</em>: The static input file contains all static information, such as topography, geographical latitude and longitude, surface property and vegetation information. ERP_&lt;<em>simulation scenario&gt;_dynamic:</em> The dynamic input file contains dynamic information on the initial state of the atmosphere or time-dependent boundary conditions. ERP_&lt;<em>simulation scenario&gt;_p3d:</em> Parameterfile for model steering. ERP_&lt;<em>simulation scenario&gt;_rlw: </em>Input dataset for longwave radiation. ERP_&lt;<em>simulation scenario&gt;_rsw: </em>Input dataset for shortwave radiation. See the model documentation https://palm.muk.uni-hannover.de/trac/wiki/doc for further details.
DOI: 10.5281/zenodo.3958826
title: Vertical cloud radiative heating from the EC-Earth3 PRIMAVERA high-resolution model part 1 (of 2)

description: The h5 files contain variables used for the article “Vertical structure of cloud radiative heating in the tropics: confronting the EC-Earth v3.3.1/3P model with satellite observations”. The experiment was done with the EC-Earth3 model (https://portal.enes.org/models/earthsystem-models/ec-earth/ec-earth). The model run was done in atmosphere-only mode with prescribed SST for the years 2005 - 2010. Year 2005 and 2006 are considered as spin-up time and are therefore not included. The experiment is described in more detail in the article. The files are named as follows: model-version_resolution_year_month_variable..h5<br> The following variables (named after ECMWF Parameter database) from the model output are included in the dataset:<br> - 107: Top of the atmosphere (TOA) SW radiation (all sky)<br> - 108: TOA SW radiation (clear sky)<br> - 109: TOA SW radiation (cloudy sky)<br> - 110: TOA LW radiation (all sky)<br> - 130: Temperature<br> - 133: Specific humidity<br> - 246: Specific cloud liquid water content<br> - 247: Specific cloud ice water content<br> - 248: Fraction of cloud cover<br> - 54: Pressure The latlon.h5 file contains the latitude and longitude for the dataset. <br> <br> To get the complete dataset for the experiment, see:<br> DOI: 10.5281/zenodo.3958826 for the radiation part of the PRIMAVERA high-resolution data.<br> DOI: 10.5281/zenodo.3960087 for the humidity part of the PRIMAVERA high-resolution data.<br> DOI: 10.5281/zenodo.3947700 for the PRIMAVERA standard-resolution data.<br> DOI: 10.5281/zenodo.3981154 for the V3.3.1 standard-resolution data.<br> DOI: 10.5281/zenodo.4734468 for the python code.
DOI: 10.5281/zenodo.3960087
title: Vertical cloud radiative heating from the EC-Earth3 PRIMAVERA high-resolution model part 2 (of 2)

description: The h5 files contain variables used for the article “Vertical structure of cloud radiative heating in the tropics: confronting the EC-Earth v3.3.1/3P model with satellite observations”. The experiment was done with the EC-Earth3 model (https://portal.enes.org/models/earthsystem-models/ec-earth/ec-earth). The model run was done in atmosphere-only mode with prescribed SST for the years 2005 - 2010. Year 2005 and 2006 are considered as spin-up time and are therefore not included. The experiment is described in more detail in the article. The files are named as follows: model-version_resolution_year_month_variable..h5<br> The following variables (named after ECMWF Parameter database) from the model output are included in the dataset:<br> - 107: Top of the atmosphere (TOA) SW radiation (all sky)<br> - 108: TOA SW radiation (clear sky)<br> - 109: TOA SW radiation (cloudy sky)<br> - 110: TOA LW radiation (all sky)<br> - 130: Temperature<br> - 133: Specific humidity<br> - 246: Specific cloud liquid water content<br> - 247: Specific cloud ice water content<br> - 248: Fraction of cloud cover<br> - 54: Pressure The latlon.h5 file contains the latitude and longitude for the dataset. <br> <br> To get the complete dataset for the experiment, see:<br> DOI: 10.5281/zenodo.3958826 for the radiation part of the PRIMAVERA high-resolution data.<br> DOI: 10.5281/zenodo.3960087 for the humidity part of the PRIMAVERA high-resolution data.<br> DOI: 10.5281/zenodo.3947700 for the PRIMAVERA standard-resolution data.<br> DOI: 10.5281/zenodo.3981154 for the V3.3.1 standard-resolution data.<br> DOI: 10.5281/zenodo.4734468 for the python code.