cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.26050/wdcc/lawr_uhh_hhg
title: Multi-year X-band weather radar observations in Hamburg (LAWR HHG)

description: Project: Hamburg Local Area Weather Radars - Knowledge of small-scale rainfall variability is needed for several meteorological and hydrological applications. For this purpose, the University of Hamburg operates two local area weather radars (LAWR) and five micro rain radars (MRR) in the area of Hamburg. The low-cost, operational, single-polarized X-band weather radars provide measurements with high temporal (30 s), range (60 m), and sampling (1°) resolution within the 20 km scan radius. Studies on short time periods (several months) proofs the performance of this low-cost local area weather radar. For example, a case study on a tornado in a rain event demonstrates its refined resolution compared to the German nationwide C-band radars. A similar observational network of LAWRs and MRRs was deployed in an rural area and proofed its performance in the past. This project covers data sets related to these radar measurements. Summary: An operational, single-polarized X-band weather radar (WRX) provides measurements in Hamburg’s city center since 2013. This local area weather radar (LAWR) is located on the rooftop of the high-rise building "Geomatikum" in Hamburg (HHG), which is the location of the Meteorological Institute of the Universität Hamburg. The radar operates at one beam elevation angle with a high temporal 30 s, range 60 m, and sampling 1° resolution refining observations of the German nationwide C-band radars within a 20 km scan radius. Several sources of radar-based errors were adjusted gradually improving the measurement variables, e.g. the radar calibration, alignment, attenuation, noise, non-meteorologial echoes. This experiment includes data sets of the equivalent radar reflectivity factor (dbz) in level 1 (without attenuation correction) and the rainfall rate (rr) in level 2 (applied attenuation correction). The WRX/LAWR HHG measurements were calibrated and evaluated with measurements of micro rain radars (MRR). With this high-quality and -resolution weather radar product, refined studies on the spatial and temporal scale of urban precipitation will be possible. For example, the data sets will be used for further hydrological research in an urban area within the project Sustainable Adaption Scenarios for Urban Areas – Water from Four Sides of the Cluster of Excellence Climate Climatic Change, and Society (CliCCS). This work was partly funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany‘s Excellence Strategy – EXC 2037 'CLICCS - Climate, Climatic Change, and Society' – Project Number: 390683824, contribution to the Center for Earth System Research and Sustainability (CEN) of Universität Hamburg.
DOI: 10.26207/mqke-k327
title: NaChem and WACCM data
DOI: 10.4121/769cc482-b104-4927-a94b-b16f6618c3b3.v1
title: Dataset of spectral reflectances and hypercubes of submerged plastic litter, including COVID-19 medical waste, pristine plastics, and ocean-harvested plastics

description: This dataset contains hyperspectral and hypercube measurements of several types of plastic debris as well as pristine plastics and COVID19 related medical PPE.<br>Contact: Robin de Vries, robin.devries@theoceancleanup.com<br>Hyperspectral measurements were collected with a Spectral Evolution SR-3501 spectroradiometer, in the filenames abbreviated as SE.Hypercube measurements were collected with a SPECIM IQ camera, abbreviated as SPECIM.<br>The measurements were illuminated by two ARRI Arrilite 750 Plus 575 W HPL halogen tungsten lamps.
DOI: 10.4121/7c53b72a-be97-478b-9288-ff9c850de64b.v1
title: Dataset of spectral reflectances and hypercubes of submerged biofouled, pristine, and ocean-harvested marine litter

description: This dataset contains hyperspectral and hypercube measurements of several types of plastic debris.Contact: Robin de Vries, robin.devries@theoceancleanup.comHyperspectral measurements were collected with a Spectral Evolution SR-3501 spectroradiometer, in the filenames abbreviated as SE.Hypercube measurements were collected with a SPECIM IQ camera, abbreviated as SPECIM.The measurements were illuminated by natural sunlight in an outdoor laboratory setup.<br>
DOI: 10.48529/94ds-8v54
title: Health Results Based Financing Impact Evaluation 2015, Health Facility Baseline Survey
title: COD_2015_HRBFIE-FBL_v01_M
DOI: 10.5067/atlas/atl08.003
title: ATLAS/ICESat-2 L3A Land and Vegetation Height, Version 3
DOI: 10.5281/zenodo.4009308
title: Full-coverage 1 km daily ambient PM2.5 and O3 concentrations of China in 2005-2017 based on multi-variable random forest model

description: The aim of our study was to construct random forest models with high-performance, and estimate daily average PM<sub>2.5</sub> concentration and O<sub>3</sub> daily maximum 8h average concentration (O<sub>3</sub>-8hmax) of China in 2005-2017 at a spatial resolution of 1km×1km. The model variables included meteorological variables, satellite data, chemical transport model output, geographic variables and socioeconomic variables. Random forest model based on ten-fold cross validation was established, and spatial and temporal validations were performed to evaluate the model performance. According to our sample-based division method, the daily, monthly and yearly simulations of PM<sub>2.5</sub> gave average model fitting R<sup>2</sup> values of 0.85, 0.88 and 0.90, respectively; these R<sup>2</sup> values were 0.77, 0.77, and 0.69 for O<sub>3</sub>-8hmax, respectively. The meteorological variables and their lagged values can significantly affect both PM<sub>2.5</sub> and O<sub>3</sub>-8hmax simulations. During 2005-2017, PM<sub>2.5</sub> exhibited an overall downward trend, while ambient O<sub>3</sub> experienced an upward trend. Whilst the spatial patterns of PM<sub>2.5</sub> and O<sub>3</sub>-8hmax barely changed between 2005 and 2017, the temporal trend had spatial characteristic. Each dataset is the annual mean concentration of PM<sub>2.5</sub> or O<sub>3</sub>-8hmax based on the standard grid (Grid.csv) for that year. The coordinate system of the grid is WGS-84.
DOI: 10.5281/zenodo.4579953
title: the ground observations for dust storm event in 2017 May in East Asia

description: This dataset covering the PM2.5, PM10 observations from May 1 to May 9 2017.
DOI: 10.5281/zenodo.4745479
title: Soil carbon loss in warmed subarctic grasslands is rapid and restricted to topsoil

description: This file includes the variable description of the data files published on Zenodo for the manuscript submitted to Biogeosciences titled 'Soil carbon loss in warmed subarctic grasslands is rapid and restricted to topsoil' 'stocks_data.csv'; includes the C stock data<br> grassland: medium-term warmed (MTW) or long-term warmed (LTW) grassland<br> sampling_year: year in which the soil samples were taken (2013 or 2018)<br> SOC_stock_corr: Mass-corrected soil organic carbon stock<br> SOC_stock: Uncorrected soil organic carbon stock<br> C_perc: soil C % of the soil sample<br> warming: degrees of soil warming (°C)<br> ID: plot soil ID<br> soil_layer: layer of soil sampled (0-10cm or 10-30cm)<br> BD: bulk density (g cm-3)<br> YOW: Years of warming; years the soil was warmed before sampling <br> 'C_input_data.csv'; includes the C input data<br> ID: plot soil ID<br> grassland: medium-term warmed (MTW) or long-term warmed (LTW) grassland<br> AMF_Cnew: C sequestered by AMF (ton C ha-1); data from Zhang et al., 2020<br> fine_root_C: fine root C in soil (ton C ha-1)<br> AGB_C: aboveground biomass C on top of soil (ton C ha-1)<br> warming: degrees of soil warming (°C) 'agg_data.csv'; includes the aggregate fractionation data<br> ID: plot soil ID<br> grassland: medium-term warmed (MTW) or long-term warmed (LTW) grassland<br> warming: degrees of soil warming (°C)<br> rel_mass: Relative aggregate fraction (%)<br> C_perc: C amount in the aggregate fraction (%)<br> abs_C_mass: absolute amount of C per fraction (g C 100 g-1 dw soil) 'DOC_data.csv'; includes the dissolved organic carbon leachate data (data from Edlinger, 2016)<br> year: sampling year of the leachates<br> grassland: medium-term warmed (MTW) or long-term warmed (LTW) grassland<br> ID: plot soil ID<br> warming: degrees of soil warming (°C)<br> DOC: dissolved organic carbon (ppm) 'T_profile_LTW.csv'; includes temperature profile data from the long-term warmed grassland<br> grassland: long-term warmed (LTW) grassland<br> ID: plot soil ID<br> depth: depth (cm) at which the the temperature was measured<br> T_diff_from_10cm: temperature difference compared to 10cm depth (°C) 'fine_root_LTW.csv'; includes fine root density data from the long-term warmed grassland<br> warming: degrees of soil warming (°C)<br> fine_root_density: fine root density (mg roots cm-3)<br> soil_layer: layer of soil sampled (0-10cm or 10-30cm)<br> grassland: long-term warmed (LTW) grassland<br> ID: plot soil ID
DOI: 10.5281/zenodo.5642505
title: Case simulation: LES RF20 composite case

description: This dataset contains the model configuration files and selected output data of the large-eddy simulation experiments as described in the publication: "Aerosol-cloud-turbulence interactions in well-coupled Arctic<br> boundary layers over open water"
description: We gratefully acknowledge the funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Projektnummer 268020496 – TRR 172, within the Transregional Collaborative Research Center "ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC) 3 ". We thank ECMWF for providing access to the large-scale model analyses and forecasts fields used to drive the LES experiments. We gratefully acknowledge the Regional Computing Centre of the University of Cologne (RRZK) for granting us access to the CHEOPS cluster. The Gauss Centre for Supercomputing e.V. (www.gauss-centre.eu) is acknowledged for providing computing time on the GCS Supercomputer JUWELS at the Jülich Supercomputing Centre (JSC) under projects CHKU28 and VIRTUALLAB. We further thank the Alfred Wegener Institute (AWI), the PS106/1 crew and the ACLOUD science teams for making the field campaign happen and for post-processing the observational data.
DOI: 10.5281/zenodo.5881876
title: Datasets supporting the paper 'Enhancing disaster risk resilience using greenspace in urbanising Quito, Ecuador'

description: Datasets supporting the paper 'Enhancing disaster risk resilience using greenspace in urbanising Quito, Ecuador' Contact: C. Scott Watson. c.s.watson@leeds.ac.uk DRR_greenspace<br> DRR_greenspace_polygon.shp - classified potential DRR greenspace (minimum 100 m2)<br> DRR_greenspace_zone_points.shp - classified potential DRR greenspace aggregated to zones<br> DRR_greenspace_zone_polygons_top10.shp - Top 10 maximum capacitated analysis of classified potential DRR greenspace aggregated to zones.<br> <br> Land_cover<br> rf_1986_mode_clipped.tif - 1986 land cover classification<br> rf_2020_mode_clipped.tif - 2020 land cover classification<br> landcover_classes.PNG - land cover classes<br> accuracy_assessment_points_1986 - 1986 land cover accuracy assessment points<br> accuracy_assessment_points_2020 - 2020 land cover accuracy assessment points<br> modified_urban_growth_scenario.shp - hazard-modified urban growth scenario
DOI: 10.5281/zenodo.6364705
title: Teaser Local Climate Zone maps extracted from the global map of Local Climate Zones.

description: Local Climate Zone teaser maps for the 15 largest functional urban areas stratified by urban ecoregion. The data is extracted from the global 100 m spatial resolution LCZ map, and is used to plot Figures 5, 6 and 7 of Demuzere et al. (2022a). The full global LCZ map is available via Demuzere et al. (2022b).<br> <br> See readme.txt for more details. <em>Demuzere, M., Kittner, J., Martilli, A., Mills, G., Moede, C., Stewart, I. D., Vliet, J. van, & Bechtel, B. (2022a). A global map of Local Climate Zones to support earth system modelling and urban scale environmental science. Earth Syst. Sci. Data Discuss.<br> Demuzere M, Kittner J, Martilli A, et al. Global map of Local Climate Zones. Zenodo. 2022b. doi:10.5281/zenodo.6364594</em>
description: See readme.txt for additional information.
DOI: 10.5281/zenodo.7349753
title: A global Lagrangian eddy dataset based on satellite altimetry (GLED v1.0)

description: Mesoscale eddies, defined as rotating structures ranging typically from tens to hundreds of kilometers and lasting for several weeks to months, are ubiquitous in the global ocean. Isolated mesoscale eddies are generally considered as coherent structures with a material barrier that can trap the fluid within the eddy interior. Methods employed to identify coherent eddies can be classified into Eulerian and Lagrangian frameworks. Eddy datasets based on Eulerian methods, especially the eddy census of Chelton et al. (2011), have been used in a huge range of applications, from physics to biology. However, recent works have shown that Eulerian eddies are not necessarily coherent because there is strong and persistent water exchange across the Eulerian eddy boundary. In this study, millions of Lagrangian particles are advected by satellite-derived surface geostrophic velocities over a period of 1993-2019. Using the method of Lagrangian-averaged vorticity deviation by Haller et al. (2016), we present a global Lagrangian eddies dataset (GLED v1.0). This open-source dataset contains not only general features (eddy center position, equivalent radius, rotation property, etc.) of eddies with lifespans of 30, 90, and 180 days, but also the trajectory of particles trapped by coherent eddy boundaries over the lifetime. The greatest strength of GLED v1.0 is that the identified eddies are all material objects by construction. Our eddy dataset provides an additional option for oceanographers in studying the interaction between coherent eddies and other physical or biochemical processes in the Earth system.
description: {"references": ["Chelton, D. B., Schlax, M. G., & Samelson, R. M. (2011). Global observations of nonlinear mesoscale eddies. Progress in oceanography, 91(2), 167-216.", "Haller, G., Hadjighasem, A., Farazmand, M., & Huhn, F. (2016). Defining coherent vortices objectively from the vorticity. Journal of Fluid Mechanics, 795, 136-173.", "Abernathey, R., & Haller, G. (2018). Transport by lagrangian vortices in the eastern pacific. Journal of Physical Oceanography, 48(3), 667-685.", "Liu, T., Abernathey, R., Sinha, A., & Chen, D. (2019). Quantifying Eulerian eddy leakiness in an idealized model. Journal of Geophysical Research: Oceans, 124(12), 8869-8886.", "Pegliasco, C., Delepoulle, A., Mason, E., Morrow, R., Faug\u00e8re, Y., & Dibarboure, G. (2022). META3. 1exp: a new global mesoscale eddy trajectory atlas derived from altimetry. Earth System Science Data, 14(3), 1087-1107."]}
DOI: 10.5281/zenodo.7745376
title: The second Met Office Unified Model-JULES Regional Atmosphere and Land configuration, RAL2

description: Supporting data for figures in GMD draft paper: The second Met Office Unified Model-JULES Regional Atmosphere and Land configuration, RAL2
DOI: 10.5439/1772490
title: KAZR Hydrometeor and Insect Masks

description: The Ka-band ARM zenith pointing radar (aka, KAZR) is so sensitive that it detects cloud particles and individual insects. While detecting insects with Ka-band radar is beneficial and desirable to advance radar entomology, this sensitivity can be detrimental to radar meteorology because insects could be interpreted as clouds or precipitation. For example, misclassifying insects as clouds has been a problem for the ARM Active Remote Sensing of Clouds (ARSCL) Value Added Product since its inception (Clothiaux et al. 2000). Based on cloud particle and insect radar scattering properties, an algorithm was developed that identifies clouds, raindrops, ice particles, and insects in KAZR co- and cross-polarimeteric Doppler velocity spectra. The algorithm produces affirmative masks in the KAZR native time and height resolution indicating time-height locations of hydrometeors and insects. The hydrometeor mask contains binary information (e.g., yes/no hydrometeor presence), and the insect mask includes a proxy for insect activity that increases when more insects are detected in the Doppler velocity spectra. The algorithm was developed using KAZR medium sensitivity mode (MD) observations and was applied to two summer seasons of KAZR observations at the Southern Great Plains (SGP) Central Facility: May-October 2018 and 2019. In the future, this data set will be expanded to include other KAZR operating modes and observations from other ARM field sites. Details of the algorithm and data set can be found in: Williams, C.R., K.L. Johnson, S.E. Giangrande, J. C. Hardin, R. Oktem, and D. M. Romps, 2021: Identifying Insects, Clouds, and Precipitation using Vertically Pointing Polarimetric Radar Doppler Velocity Spectra. Atmospheric Measurement Techniques, submitted 6-Feb-2021. https://amt.copernicus.org/preprints/amt-2021-27/#discussion.For more information on the ARSCL VAP, see Clothiaux, E. E., T. P. Ackerman, G. G. Mace, K. P. Moran, R. T. Marchand, M. A. Miller, and B. E. Martner, 2000; J. Appl. Meteor., 39, 645-665.
DOI: 10.6084/m9.figshare.14213909
title: 30-m sugarcane harvest maps in Brazil

description: This dataset provides 30-m spatial resolution sugarcane harvest maps (2016-2019) for fourteen states in Brazil (including São Paulo, Goiás, Minas Gerais, Mato Grosso do Sul, Paraná, Mato Grosso, Bahia, Rio de Janeiro, and Espírito Santo in south-central Brazil; and Alagoas, Pernambuco, Paraíba, Rio Grande do Norte, and Sergipe in northeast Brazil). The mapped areas constitute over 98% of the sugarcane cultivation area in Brazil. (1) Methodology and performance A phenology-based method was developed to produce the sugarcane distribution maps over the entire Brazil by incorporating the flexible phenology conditions of sugarcane into a time-weighted dynamic time warping method (TWDTW). Validations against field sample data and agricultural statistical data demonstrated the maps were in high accuracy. (2) Dataset information The dataset is provided in geotif (*.tif) format with pixel values of 1 for sugarcane and 0 for non-sugarcane. Data named "Brazil_sugarcane_2016_v2.tif" means sugarcane harvest map in 2016. Any questions about the dataset can be corresponded to Wenping Yuan (yuanwpcn@126.com).
DOI: 10.6084/m9.figshare.28239206
title: Supplementary Material for: Non-invasive Kupffer-CEUS Enhances the Accuracy of FLLs Diagnosis in Patients with Liver Cirrhosis or Fibrosis: A prospective multicenter study from China

description: Introduction: It is challenging to diagnose liver masses in the context of a rough liver background using CT and MRI. Perfluorobutane (PFB) CEUS microbubble, an ultrasound contrast agent, has a unique phase called the Kupffer phase. This study aimed to explore whether the diagnostic ability of Kupffer-CEUS is affected by the rough liver background.
Methods: A prospective analysis was conducted on patients with access to histological pathology of FLLs and liver parenchyma from 23 centers between August 2020 and March 2021. Kupffer-CEUS was performed on 552 patients, who were divided into two groups (normal and abnormal) based on the pathological results of liver parenchyma, and the abnormal group was further divided into four groups (Sight liver fibrosis, Serious liver fibrosis, Fatty liver, Mixed). Kupffer-CEUS was divided into vascular phase and vascular & Kupffer phase.
Results: In Kupffer-CEUS, differences in diagnostic efficiency of FLLs between normal and abnormal liver backgrounds were not statistically significant. However, in patients with abnormal liver backgrounds, the specificity (57.45% vs. 74.47%, P=0.008) and accuracy (89.81% vs. 96.92%, P&lt;0.001) of the vascular phase in distinguishing malignant from benign lesions were statistically lower than those of the vascular & Kupffer phase. Subgroup analysis revealed that the sensitivity, specificity, and accuracy of vascular & Kupffer phase in screening FLLs were all higher than those of vascular phase, except for the accuracy in patients with serious liver fibrosis (98.51% vs. 94.06, P&lt;0.001).
Conclusion: This study indicated that although there is no obvious restriction on the choice of Kupffer-CEUS methods when diagnosing liver masses in patients with normal or abnormal liver backgrounds, Kupffer phase CEUS can effectively reduce the misdiagnosis of FLLs. Particularly for patients with serious liver fibrosis, contrast-enhanced ultrasound combined with the Kupffer phase can provide a more accurate diagnosis than conventional contrast-enhanced ultrasonography.
DOI: 10.7265/n5w093vm
title: C-axis Fabric from Physical Properties Samples of the WAIS Divide Ice Core
DOI: 10.25824/redu/froese
title: Reference maps of soil phosphorus for the pan-Amazon region: code and data

description: This repository contains code and data employed to generate a set of reference maps of soil phosphorus (P) for the pan-Amazon region. The primary intent of these maps is to provide reference data for parametrization and benchmark of Land Surface/Terrestrial Ecosystem models. The maps created are the mean prediction of a set of random forest regression models fitted with available observed in situ data found in scientific literature. The model predictions are generated based on data from geographic datasets that have the same features utilized to fit the models.
DOI: 10.6084/m9.figshare.19536082.v1
title: Sources of organic aerosols in east China: A modeling study with high-resolution intermediate-volatility and semi-volatile organic compound emissions

description: Organic aerosol (OA) contributes a large fraction of atmospheric submicron aerosol and has negative impacts on air quality, climate, and human health. Sources of OA still remains unclear due to the inadequacy of emission inventory and modeling system. Herein, we established a high-resolution emission inventory of intermediate-volatility and semi-volatile organic compounds (I/SVOCs) and applied it into CMAQ to simulate POA and SOA from different sources in eastern China. Comprehensive observation data of organic carbon (OC), primary and secondary organic aerosol (POA, SOA), and precursors were used for the verification of model performance. With the addition of I/SVOC emissions, OA simulations in each season were substantially improved by increasing the modeled SOA by 1.2 times. I/SVOC emissions contributed 53.6% of SOA and 23.5% of total OA on average. Cooking emissions dominated the POA concentrations in most of the cities. I/SVOC emissions from industrial sources have become the predominant source of regional SOA, followed by those from mobile sources. The differences in OA source contributions between the cities implies that differentiated control measures shall be considered to OA pollution mitigation. Meanwhile, more localized I/SVOCs emission measurements and more sophisticated SOA simulation mechanisms are urgently needed to further improve the identification of OA sources in eastern China.
DOI: 10.15468/dl.9menwh
title: Occurrence Download

description: A dataset containing 46 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-96.21320 36.51472,-53.78680 36.51472,-53.78680 53.48528,-96.21320 53.48528,-96.21320 36.51472))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Scutellaria ×churchilliana Fernald"
 ]
}

 The dataset includes 46 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001796-250123221155621/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.