cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25573/data.25639560.v2
title: Wood density and bark thickness for 613 tree species from the 50-ha Forest Dynamics Plot at Yasuni, Ecuador

description: The data include wood density and bark thickness for 613 tree species from the Yasuni Biological Station focusing on species present in the Yasuni 50-ha Forest Dynamics Plot. The Yasuni Biological Station is in the Yasuni National Park and Biosphere Reserve, Ecuador. The Yasuni 50-ha plot is located at 0°41′ S latitude, 76°24′ W longitude. Elevation is approximately 300 m. Air temperatures average 24.8 °C, annual rainfall averages 3100 mm, and the minimum mean monthly rainfall is 152 mm (Hietz et al. 2013. Functional Ecology 27: 684–692). The Yasuni flora is hyper-diverse, with more than 1,100 tree species recorded from the western 25-ha of the 50-ha plot (Valencia et al. 2004. Journal of Ecology 92: 214–229).
DOI: 10.25966/9qgv-fe81
title: Chemical Reanalysis Products

description: The Tropospheric Chemistry Reanalysis version 2 (TCR-2) provides global data sets of atmospheric composition and emissions for the period 2005-2018 at 1.1° horizontal resolution obtained from the assimilation of multiple satellite measurements of ozone, CO, NO2, HNO3, and SO2 from the OMI, SCIAMACHY, GOME-2, TES, MLS, and MOPITT satellite instruments. The data sets can be used to improve understanding of the processes controlling variations in atmospheric composition, including long-term changes in air quality and emissions.
DOI: 10.3886/e192021
title: Data and Code for: Who Bears the Burden of Local Taxes?

description: We study the distributional effects of local taxes and find them to be strikingly progressive. We calibrate a structural model of a multi-municipality local labor market with new reduced-form elasticity estimates. Households with children are found to be considerably less mobile than households without children and to have moderately stronger preferences for locally provided public goods. Combined with capitalization of taxes into housing prices and non-homothetic housing demand, this implies that the incidence of local income taxes mainly falls on above-median income childless households. Local income taxes, even if flat-rate, turn out to be more progressive than property taxes.<br>
description: All households in Switzerland. All house price postings. .
DOI: 10.4121/uuid:44326654-8dae-42df-adbd-d0f145581353
title: Data underlying the figures presented in the paper: A global empirical GIA model based on GRACE data

description: Data used to generate the figures presented in the draft paper: A global empirical GIA model based on GRACE data by Yu Sun and Riccardo E. M. Riva.
DOI: 10.5067/1rjw1ymlw2f0
title: OCO-2 Level 1B calibrated, geolocated science spectra, Retrospective Processing V10r
DOI: 10.5067/22nfzl42rmuo
title: Snow Melt Onset Over Arctic Sea Ice from SMMR and SSM/I-SSMIS Brightness Temperatures, Version 3
DOI: 10.5067/aqua/modis/l3m/iop/2018
title: MODIS-Aqua Level 3 Mapped Inherent Optical Properties Data Version R2018.0
DOI: 10.5067/modis/cldmsk_l2_modis_aqua.001
title: MODIS/Aqua Cloud Mask and Spectral Test Results 5-Min L2 Swath 1km
DOI: 10.5067/pathf-mod50
title: AVHRR Pathfinder Level 3 Monthly Daytime SST Version 5
DOI: 10.5067/terra/modis/l3m/iop/2018
title: MODIS-TERRA Level 3 Mapped Inherent Optical Properties Data Version R2018.0
DOI: 10.5067/viirs/cldmsk_l2_viirs_snpp.001
title: VIIRS/SNPP Cloud Mask and Spectral Test Results 6-Min L2 Swath 750m
DOI: 10.5281/zenodo.14028867
title: StageIV-IRC – A High-resolution Dataset of Extreme Orographic Quantitative Precipitation Estimates (QPE) Constrained to Water Budget Closure for Historical Floods in the Appalachian Mountains

description: Quantitative Flood Estimation (QFE) in complex terrain remains a grand challenge in operational hydrology due to the lack of accurate high-resolution Quantitative Precipitation Estimates (QPE) at spatial and temporal resolutions needed to capture the variability of orographic precipitation, and where radar-based QPE are available there are significant biases due to the geometry and constraints of radar operations.  Here, we present a high-resolution (i.e. 250m, 5minute-hourly) QPE dataset for the most extreme (flood-producing) events from 2008 to 2024 for 26 gauged basins (in total 215 events) in the Appalachian mountains constrained to meet basin-scale water budget closure through inverse rainfall-runoff modeling to correct the Next Generation Weather Radar (NEXRAD) Stage IV analysis (4km resolution, hourly) using a fully-distributed uncalibrated hydrological model that leverages recent advances in hydrologic modeling in mountainous regions (e.g. improved river routing and initial soil moisture estimation) (Liao and Barros, 2024a and 2024b). The corrected Stage IV analysis is referred to as StageIV-IRC (Inverse Rainfall Correction).  Previously, a subset of this dataset informed the construction of a generalized QPE error model (Liao and Barros, 2023), supporting the development of water budget closure constrained QPE and providing physics insights into orographic QPE uncertainties for various radar-based products at high resolution in complex terrain. The unique advantage of the StageIV-IRC QPE is that it achieves water budget closure at the storm-flood event scale within observational uncertainty of streamflow observations, that is the golden standard in hydrological modeling.  The QPE dataset is publicly available at:  https://doi.org/10.5281/zenodo.14028867
DOI: 10.5281/zenodo.1403181
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: pDSSAT maize

description: This is model output from pDSSAT for maize as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1403189
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: pAPSIM maize

description: This is model output from pAPSIM for maize as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1405489
title: Two Multi-Temporal Datasets To Track The Enhanced Landsliding After The 2008 Wenchuan Earthquake

description: We release two datasets that track the enhanced landsliding induced by the 2008 M<sub>w</sub> 7.9 Wenchuan earthquake over a portion of the Longmen mountains, at the eastern margin of the Tibetan plateau (Sichuan, China). The first dataset is a geo-referenced multi-temporal polygon-based inventory of pre- and coseismic landslides, post-seismic remobilisations of coseismic landslide debris, and post-seismic landslides (new failures). It covers 471 km<sup>2</sup> in the earthquake’s epicentral area, from 2005 to 2018. The second dataset records the debris flows that occurred from 2008 to 2017 in a larger area (~17,000 km<sup>2</sup>), together with information on their triggering rainfall as recorded by a network of rain gauges. For some well-monitored events, we provide more detailed data on rainfall, discharge, flow depth and density. The datasets can be used to analyse, at various scales, the patterns of landsliding caused by the earthquake. They can be compared to inventories relative to past or new earthquakes or other triggers to reveal common or distinctive controlling factors. To our knowledge, no other inventories that track the temporal evolution of earthquake-induced mass wasting have been made freely available thus far. Our datasets can be accessed from https://doi.org/10.5281/zenodo.1405490. We also encourage other researchers to share their datasets to facilitate research on post-seismic geological hazards.
DOI: 10.5281/zenodo.1408571
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: GEPIC wheat

description: This is model output from GEPIC for wheat as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1408573
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: GEPIC soy

description: This is model output from GEPIC for soy as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.14175527
title: Dataset of bank soil parameters and stochastic modelling of bank erosion processes in the Middle Yangtze River

description: A probabilistic process-based model of bank erosion has proposed, embedding the probability distributions of different bank soil parameters.  The dataset includes the spatial distribution characteristics of critical shear stress, friction angle, and cohesion. The prediction results analyzed the effects of soil erosion resistance capacity and the variability of shear strength parameters in the simulation of bank erosion processes, obtaining the probability of mass failure and the distributions of bank erosion width. Additionally, the study investigated the effect of varying water content on bank erosion modeling and further analyzed how considering more influencing factors in the model affects prediction uncertainty and accuracy. Moreover, the relationship between the variability of these factors and river morphology was discussed. The dataset provides the aforementioned prediction results, and relevant plots were generated using MATLAB or Python, with the associated plotting code also uploaded.
DOI: 10.5281/zenodo.1485277
title: Magpie 4.0 Paper - Model Runs

description: Archive of runs produced for the MAgPIE 4 modeling framework paper.
DOI: 10.5281/zenodo.3250790
title: ­Calibrated data of stable water isotope measurements in water vapour at 13.5 m a.s.l., made in the austral summer of 2016/2017 around the Southern Ocean during the Antarctic Circumnavigation Expedition (ACE).

description: <strong>Dataset abstract</strong> This data set includes the calibrated data of stable water vapour isotope (δ<sup>18</sup>O, δ<sup>2</sup>H, deuterium excess) and water vapour mixing ratio measurements at approximately 13.5 m a.s.l. taken around the Southern Ocean during the Antarctic Circumnavigation Expedition (ACE) from November 2016 to April 2017 using a Picarro laser spectrometer L2130. The data provides continuous timelines of atmospheric water vapour properties in the marine boundary layer for studies of the atmospheric water cycle. The raw data from which this calibrated dataset originates has been published separately (Thurnherr and Aemisegger, 2019; DOI 10.5281/zenodo.3664177). Two other calibrated stable water isotope measurement datasets were also collected during ACE. They differ by the location of measurement on the ship: 8 m a.s.l on the starboard (DOI: 10.5281/zenodo.3739335) and port sides (DOI: 10.5281/zenodo.3739354). <strong>Dataset contents</strong> ACE_watervapour_isotopes_SWI13_1h.csv, data file, comma-separated values ACE_watervapour_isotopes_SWI13_5min.csv, data file, comma-separated values cal_runs_SWI13.csv, metadata, comma-separated values data_file_header.txt, metadata, text format README.txt, metadata, text format NaN values denote missing values which occur because of e.g., maintenance, instrument calibration, large cavity variations. <strong>Dataset license</strong> This calibrated stable water isotope measurements in water vapour is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/
description: The Antarctic Circumnavigation Expedition was made possible by funding from the Swiss Polar Institute and Ferring Pharmaceuticals.
description: {"references": ["Thurnherr, I., Kozachek, A., Graf, P., Weng, Y., Bolshiyanov, D., Landwehr, S. J., Pfahl, S., Schmale, J., Sodemann, H., Steen-Larsen, H. C., Toffoli, A., Wernli, H. and Aemisegger, F. (2020). Meridional and vertical variations of the marine boundary layer water vapour isotope composition in the Atlantic and the Southern Ocean. Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-782, accepted.", "IAEA: Reference Sheet for VSMOW2 and SLAP2 international measurement standards, International Atomic Energy Agency (IAEA), 2009", "David W H Walton, & Jenny Thomas. (2018, November 22). Cruise Report - Antarctic Circumnavigation Expedition (ACE) 20th December 2016 - 19th March 2017 (Version 1.0). Zenodo. http://doi.org/10.5281/zenodo.1443511"]}
DOI: 10.5281/zenodo.3337242
title: Mapping of the calving front of Eqip Sermia Glacier, West Greenland, by UAV photogrammetry

description: These data contain photogrammetrical data collected by unmanned aerial vehicle (UAV) in July 2018 at Eqip Sermia Glacier. The data include processed data (orthoimage and digital elevation models) with the Structure-fom-Motion photogrammetrical software Agisoft Photoscan. For each, processed and raw, data are organized by glacier surveys with the following convention GLACIER_YYYYMMDD_HHMM or GLACIER_YYYYMMDD_HHMM_N. For instance : eqip_20180708_1225 contains the Data of the LARGE-SCALE survey of Eqip glacier that started on July 8, 2018 at 12:25 UTC time. eqip_20180707_1245_1 contains the Data of the FIRST repeat survey of the calving front of Eqip glacier that started on July 7, 2018 at 12:45 UTC time, eqip_20180707_1245_2 is the second repeat survey, eqip_20180707_1245_3 is the third and eqip_20180707_1245_4 is the last. Coordinate system used is UTM Zone 22W based on WGS84 Take-off and landing site latitude and longitude was ( 69.757767 , - 50.228172 ) This dataset is related to the article "High-endurance UAV for monitoring calving glaciers: Application to the Inglefield Bredning and Eqip Sermia, Greenland", G. Jouvet, Y. Weidmann, E. van Dongen, M. Lüthi, A. Vieli, J. V. Ryan, Frontiers in Earth Sciences.
DOI: 10.5281/zenodo.3463003
title: ARTS Microwave Single Scattering Properties Database (Oriented Particles)

description: The database contains microwave and submillimeter wave single scattering data of azimuthally randomly oriented frozen hydrometeors. Main applications lie in polarized active/passive microwave and submillimeter wave remote sensing. This database is an independent add-on to the ARTS Microwave Single Scattering Properties Database. A description of the simulation methods and database is available in the following article. Please cite it if you use the database for a publication. Brath, M., Ekelund, R., Eriksson, P., Lemke, O., and Buehler, S. A.: Microwave and submillimeter wave scattering of oriented ice particles, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-382, in review, 2019. The dataset contains one aggregate habit and one pristine ice crystal habit. Furthermore, 35 frequencies from 1 to 886 GHz, and 3 temperatures, 190, 230 and 270 K, are included. The data were calculated using the discrete dipole approximation method (DDA) in combination with a self developed orientation averaging approach. Interfaces for easy user access is available under a separate upload, due to different licensing, under the title ARTS Microwave Single Scattering Properties Database Interfaces, in which only the Python3 interface can be used for browsing and importing of the single scattering data of azimuthally randomly oriented. The archive InputAzimuthallyRandom.tar.gz contains the shape files, which have be used as input for the DDA simulations. <strong>Unpacking</strong> The data files for the oriented particles follow the same directory structure as the ARTS Microwave Single Scattering Properties Database. Each tar file contains an SSD directory and the subdirectories for a specific particle orientation. Furthermore, it contains as a quick overview a report of the scattering properties for total random orientation. If the totally randomly oriented particle database is already present, these files should be unpacked in the same location that contains the SSD folder. In Unix, all files can be unpacked with: <pre><code class="language-bash">for ssdfile in SSD-AziRnd-ice*.tar; do tar -xvf $ssdfile done </code></pre>
DOI: 10.5281/zenodo.3475897
title: Supplement to "Microwave and submillimeter wave scattering of oriented ice particles"

description: This data set contains the simulated brightness temperatures and the corresponding atmospheric states for the radiative transfer simulations for the journal article "Microwave and submillimeter wave scattering of oriented ice particles", which is on Atmospheric Measurement Techniques (AMTD).
DOI: 10.5281/zenodo.3660488
title: Raw data for: Pressure and inertia sensing drifters for glacial hydrology flow path measurements

description: Raw data for paper Title: Pressure and inertia sensing drifters for glacial hydrology flow path measurements Authors: A.Alexander, M.Kruusmaa, J.A. Tuhtan, A.J. Hodson, T.V. Schuler, A. Kääb Journal: The Cryosphere Year, 2020