Find research datasets worth reusing

opencc-by-4.0May 2022View details →

The datasets used in the manuscript named "Fidelity of Global Tropical Cyclone Activity in a High-Resolution Reanalysis Dataset CRA40 in Comparison with Multiple Other Reanalysis Datasets"

The datasets after tracking the TC events in five reanalyses: ERA5, JRA55, CFSR, MERRA2, CRA40.

opencc-by-sa-4.0Feb 2022View details →

ERA5-Land weekly: Total precipitation, weekly time series for Europe at 1 km resolution (2016 - 2020)

Overview: ERA5-Land is a reanalysis dataset providing a consistent view of the evolution of land variables over several decades at an enhanced resolution compared to ERA5. ERA5-Land has been produced by replaying the land component of the ECMWF ERA5 climate reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. Reanalysis produces data that goes several decades back in time, providing an accurate description of the climate of the past. Total precipitation: Accumulated liquid and frozen water, including rain and snow, that falls to the Earth's surface. It is the sum of large-scale precipitation (that precipitation which is generated by large-scale weather patterns, such as troughs and cold fronts) and convective precipitation (generated by convection which occurs when air at lower levels in the atmosphere is warmer and less dense than the air above, so it rises). Precipitation variables do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth. This variable is accumulated from the beginning of the forecast time to the end of the forecast step. The units of precipitation are depth in metres. It is the depth the water would have if it were spread evenly over the grid box. Care should be taken when comparing model variables with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step. Processing steps: The original hourly ERA5-Land data has been spatially enhanced from 0.1 degree to 30 arc seconds (approx. 1000 m) spatial resolution by image fusion with CHELSA data (V1.2) (https://chelsa-climate.org/). For each day we used the corresponding monthly long-term average of CHELSA. The aim was to use the fine spatial detail of CHELSA and at the same time preserve the general regional pattern and fine temporal detail of ERA5-Land. The steps included aggregation and enhancement, specifically: 1. spatially aggregate CHELSA to the resolution of ERA5-Land 2. calculate proportion of ERA5-Land / aggregated CHELSA 3. interpolate proportion with a Gaussian filter to 30 arc seconds 4. multiply the interpolated proportions with CHELSA Using proportions ensures that areas without precipitation remain areas without precipitation. Only if there was actual precipitation in a given area, precipitation was redistributed according to the spatial detail of CHELSA. The spatially enhanced daily ERA5-Land data has been aggregated on a weekly basis starting from Saturday for the time period 2016 - 2020. Data available is the weekly average of daily sums and the weekly sum of daily sums of total precipitation. File naming: Average of daily sum: <code>era5_land_prectot_avg_weekly_YYYY_MM_DD.tif</code> Sum of daily sum: <code>era5_land_prectot_sum_weekly_YYYY_MM_DD.tif</code> The date in the file name determines the start day of the week (Saturday). Pixel values: mm * 10 Example: Value 218 = 21.8 mm Coordinate reference system: ETRS89 / LAEA Europe (EPSG:3035) (EPSG:3035) Spatial extent: north: 82:00:30N south: 18N west: 32:00:30W east: 70E Spatial resolution: 1km Temporal resolution: weekly Period: 01/01/2016 - 12/31/2020 Lineage: Dataset has been processed from original Copernicus Climate Data Store (ERA5-Land) data sources. As auxiliary data CHELSA climate data has been used. Software used: GDAL 3.2.2 and GRASS GIS 8.0.0 (r.resamp.stats -w; r.relief) Original ERA5-Land dataset license: <a href="https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf">https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf</a> CHELSA climatologies (V1.2): Data used: Karger D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E, Linder, H.P., Kessler, M. (2018): Data from: Climatologies at high resolution for the earth's land surface areas. Dryad digital repository. <a href="http://dx.doi.org/doi:10.5061/dryad.kd1d4">http://dx.doi.org/doi:10.5061/dryad.kd1d4</a> Original peer-reviewed publication: Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, P., Kessler, M. (2017): Climatologies at high resolution for the Earth land surface areas. Scientific Data. 4 170122. <a href="https://doi.org/10.1038/sdata.2017.122">https://doi.org/10.1038/sdata.2017.122</a> Other resources: <a href="https://data.mundialis.de/geonetwork/srv/eng/catalog.search#/metadata/601ea08c-0768-4af3-a8fa-7da25fb9125b">https://data.mundialis.de/geonetwork/srv/eng/catalog.search#/metadata/601ea08c-0768-4af3-a8fa-7da25fb9125b</a> Format: GeoTIFF Representation type: Grid Processed by: mundialis GmbH & Co. KG, Germany (<a href="https://www.mundialis.de/">https://www.mundialis.de/</a>) Contact: mundialis GmbH & Co. KG, info@mundialis.de

opencc-by-4.0May 2022View details →

High resolution opacities for H2/He atmospheres

This set of molecular and atomic opacities has been built based on the same opacity sources used for calculating the correlated-k coefficients in the following repositories: 10.5281/zenodo.5590997 (11 windows) 10.5281/zenodo.5590995 (30 windows) 10.5281/zenodo.5590986 (180 windows) 10.5281/zenodo.5590989 (196 windows) These opacities can be used to generate high resolution spectra for the atmospheric structures computed with the correlated-k coefficients above. The set includes C2H2, C2H4, C2H6, CH4, CO, CO2, CrH, Fe, FeH, H2, H3+, H2O, H2S, HCN, LiCl, LiF, LiH, MgH, N2, NH3, OCS, PH3, SiO, TiO, and VO, in addition to alkali metals (Li, Na, K, Rb, Cs). The opacities are calculated for a grid of 1460 pressure-temperature points, from10^−6 to 3000 bar and from 75 to 4000 K, listed in the file 1460_layer_list. Each *.zip file contains one opacity file for each pressure-temperature layer, with the species’ name, the pressure, and the temperature given in the filename. The opacity is given in units of cm^2/molecule. For completeness, each *.zip file also contains a file named wavelengths.txt, listing the wavelengths corresponding to each opacity point, in units of microns. All the opacities are calculated on the same wavelength grid.  The references for the line lists used in these opacity calculations can be found in the file Opacity_references_2021.pdf. Please include these references, as well as the reference to this Zenodo repository when publishing your paper.  Resources supporting this work were provided by the NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center.

Supplementary Material for "High spatial resolution photogrammetry and LiDAR in the Cádiz Bay (SW, Spain): optimizing the application of UAV-techniques to salt marshes" article.

Data presented in the study "High spatial resolution photogrammetry and LiDAR in the Cádiz Bay (SW, Spain): optimizing the application of UAV-techniques to salt marshes"

High-Resolution TURBINE fMRI Dataset 1

Isotropic 0.67 mm visual cortex-slab TURBINE raw dataset 1 (in ISMRMRD format) for "Ultra-High Resolution fMRI at 7T using Radial-Cartesian TURBINE sampling" published in Magnetic Resonance in Medicine.

High-Resolution TURBINE fMRI Dataset 2

Isotropic 0.67 mm visual cortex-slab TURBINE raw dataset 2 (in ISMRMRD format) for "Ultra-High Resolution fMRI at 7T using Radial-Cartesian TURBINE sampling" published in Magnetic Resonance in Medicine.

Characterisation and calibration of PM sensors at high temporal resolution

This repository contains the data used for the Chapter 7 of my PhD thesis: <blockquote> Bulot, Florentin (2022) Systematic studies of commodity particulate matter air pollution sensors. University of Southampton, Doctoral Thesis, 272pp.  http://eprints.soton.ac.uk/id/eprint/458166 </blockquote> It contains three files: <ul> <li>fidas_10s.csv - contains the PM concentration data from the Fidas 200S</li> <li>rh_temperature.csv - contains the relative humidity and temperature data recorded by each of the SHT35 sensors in each air quality monitor</li> <li>sensors_10s_avg.zip -  a zip file containing sensors_10s_avg.csv which contains the PM concentration data measured by the commodity PM sensors from Plantower PMS5003 and Sensirion SPS30 models</li> </ul>

opencc-by-4.0Apr 2022View details →

Dataset presented in the recently submitted AGU manuscript "A multi-resolution finite-element approach for global electromagnetic induction modeling with application to southeast China coastal geomagnetic observatory studies"

Dataset presented in the recently submitted AGU paper "A multi-resolution finite-element approach for global electromagnetic induction modeling with application to southeast China coastal geomagnetic observatory studies"

dryad32/100

Data from: Phylogenomic resolution of the cetacean tree of life using target sequence capture

The evolution of the cetaceans, from their early transition to an aquatic lifestyle to their subsequent diversification, has been the subject of numerous studies. However, while the higher-level relationships among cetacean families have been largely settled, several aspects of the systematics within these groups remain unresolved. Problematic clades include the oceanic dolphins (37 spp.), which have experienced a recent rapid radiation, and the beaked whales (22 spp.), which have not been investigated in detail using nuclear loci. The combined application of high-throughput sequencing with techniques that target specific genomic sequences provide a powerful means of rapidly generating large volumes of orthologous sequence data for use in phylogenomic studies. To elucidate the phylogenetic relationships within the Cetacea, we combined sequence capture with Illumina sequencing to generate data for ~3200 protein-coding genes for 68 cetacean species and their close relatives including the pygmy hippopotamus. By combining data from >38,000 exons with existing sequences from 11 cetaceans and seven outgroup taxa, we produced the first comprehensive comparative genomic dataset for cetaceans, spanning 6,527,596 aligned base pairs and 89 taxa. Phylogenetic trees reconstructed with maximum likelihood and Bayesian inference of concatenated loci, as well as with coalescence analyses of individual gene trees, produced mostly concordant and well-supported trees. Our results completely resolve the relationships among beaked whales as well as the contentious relationships among ocean dolphins, especially the problematic subfamily Delphininae, which includes the common and bottlenose dolphins. We performed Bayesian estimation of species divergence times using MCMCtree, integrating recently described fossils as calibration points (e.g., Mystacodon selenensis) that have not been used before. Integration of new fossil dates in the context of autocorrelated rates indicate that the diversification of Crown Cetacea began before the Late Eocene and the divergence of Crown Delphinidae as early as the Middle Miocene.

opencc-zeroOct 2019View details →

opencc-by-4.0Feb 2022View details →

High-resolution (250 m) dataset for drought assessment in India

#################Summary######################################## We downscaled MODIS (MOD11A2) LST 1000 m to 250 m using the co-kriging method (Pardo-Igúzquiza et al., 2006),  and calculated various agriculture drought indices from the downscaled LST and EVI at 250 m. The downscaled LST was then combined with EVI to evaluate various drought indices over India.  ################################################################# ################Various Abbreviation ############################## Land Surface Temperature                    - LST Enhanced Vegetation Index                    - EVI Soil Moisture Agriculture Drought Index        - SMADI Normalized Vegetation Supply Water Index        - NVSWI Vegetation Health Index                          - VHI Vegetation Condition Index                    - VCI Temperature Condition Index                    - TCI Moderate Resolution Imaging Spectroradiometer - MODIS ################################################################# ################################################################# Downscaled LST at 250m The "Downscaled_method" folder consist of original 1000 m MODIS (LST_1000m_MODIS.nc) and downscaled 250 m LST (LST_250m_Downscale.nc) data. ################################################################# ################################################################# Various Drought Indices for India during 2002 drought (Folder: Drought_Indices) Here all the data names are represented as Julian day with corresponding year and Drought Index.  Example:- File name: NVSWI02033.nc; Drought Index - "NVSWI"; year - "02"; Julian day- "033" For VHI, VCI, TCI, and NVSWI, values closer to 100 represent very healthy and value close to zero represent extreme stress For SMADI, values closer to 5 represent very healthy and value close to zero represent extreme stress. ################################################################## ################################################################## Time series of NVSWI between 2000 and 2017 (Folder: NVSWI) Here all the data names are represented as Julian day with corresponding year and Drought Index.  Example:- File name: NVSWI02033.nc; Drought Index - "NVSWI"; year - "02"; Julian day- "033" ################################################################## ################################################################## ##################################################################

Dataset with square plots across Sierra Nevada (Spain) where the contours of all juniper shrubs were annotated as polygons using centimetric GPS and very high resolution aerial and satellite RGB images

This dataset is a shapefile of 767 polygons describing the contours of Juniperus communis L. and Juniperus sabina L. shrubs for the year 2021 in rectangular plots across Sierra Nevada. The coordinates of the polygons were obtained from a field work campaign with a differential centimetric GPS, and their contours were drawn manually in QGIS using the Google Earth satellite image for 2020 and the PNOA aerial image for the 2020.  This dataset also contains an excel file describing the features of each polygon: the polygon centroid coordinates, the type of species, the sexgender, the morphotype, the damage in the vegetation cover estimated in the field and telematically, certainty of the digitalization with QGIS and also if the differential centimetric GPS used belongs to the University of Granada or the University of Almeria.

Study on the Evolution Characteristics of the Return Stroke Spectra and Channel Temperatures by Using Two Spectrographs with Different Time Resolution

Temperature is one of the crucial parameters reflecting the energy and current transfer characteristics in the lightning discharge channel. According to the spectra of six lightning return strokes recorded simultaneously by two high-speed slit-less spectrographs with different time resolutions, the spectral intensity and temperature evolution of the return stroke channels over time was quantitatively analyzed. The spectral characteristics show that the ionic line intensity decayed rapidly with time as the current declined, while the atomic line intensity decreased more slowly. Additionally, it is found that ionic lines existed in the spectra of continuing current process for up to hundreds of microseconds. It further indicates that the ionic line intensities are  associated with the discharge currents and that their radiation mechanism is closely related to the collision excitation under the action of strong currents. The temperature calculated by the ionic lines can reflect the thermodynamic properties of the current-carrying channel. The temperature calculated using atomic lines is significantly lower than that calculated by the ionic lines in the same spectrum. The radiation mechanism for majority of the atomic lines differs from that of the ionic lines. During the continuing current, the channel temperatures calculated by both ionic lines and atomic lines showed a similar evolution feature which declined slowly or even basically unchanged. This property reflects the persistent heating effect of the current.

Supplementary material for "Evaluating the Performance of High Spatial Resolution UAV-photogrammetry and UAV-LiDAR for Salt Marshes: the Cádiz Bay Study Case" article

Data presented in the study "Evaluating the Performance of High Spatial Resolution UAV-photogrammetry and UAV-LiDAR for Salt Marshes: the Cádiz Bay Study Case".

GULF18, a high-resolution NEMO-based tidal ocean model of the Arabian/Persian Gulf

Supporting data for the GMD draft paper "GULF18, a high-resolution NEMO-based tidal ocean model of the Arabian/Persian Gulf" (© Crown copyright Met Office): 1) input_geometry_gulf_models: bathymetry, horizontal grid and domain (in the case of GULF18-4.0) files needed to run the three Gulf models and analyse their results. 2) analysis_gulf_models: data for figures and analysis.

Data for "Dependence of Convective Cloud Properties and Their Transport on Cloud Fraction and GCM Resolution Diagnosed from a Cloud-Resolving Model Simulation"

The datasets for the manuscript "Dependence of Convective Cloud Properties and Their Transport on Cloud Fraction and GCM Resolution Diagnosed from a Cloud-Resolving Model Simulation". model: WRF3.1.1 location: Southern Great Plains time: from 2100 UTC 23 May to 0600 UTC 24 May time interval: 6 minutes domain size: 512km x 512km vertical layer: 500hpa variables: P, PB, PH, PHB, U, V, W, T, QCLOUD, QICE, QVAPOR calculated data: mse, up_only(only consider updraft), up_down(consider both updrafts and downdrafts)

openAug 2022View details →

Cell Atlas at Single-Nuclei Resolution of the Adult Human Adrenal Gland and Adrenocortical Adenomas

Abstract The human adrenal glands are highly dynamic endocrine organs that are involved in the secretion of various hormones such as steroids and catecholamines. Here we present a single-nuclei and spatial transcriptomic analysis of healthy adult human adrenal glands to provide a complete adrenal gland atlas. With this, we show how such an atlas can be taken advantage when studying adrenocortical diseases, such as adrenocortical adenomas (ACA). Using nornal adrenal as reference, we showed a high intra-tumoural heterogeneity in the single-nuclei transcriptome of ACA, revealing the presence of specific cell populations associated with cortisol secretion and genetic background.   Data content This dataset contains the two Visium replicates (NAG-7A and NAG-7B) processed using Space Ranger (spaceranger-1.0.0).

opencc-by-4.0Aug 2022View details →

SimuShips - A High Resolution Simulation Dataset for Ship Detection with Precise Annotations

SimuShips - A High Resolution Simulation Dataset for Ship Detection with Precise Annotations Availability of domain-specific datasets is a challenge for object detection. In particular, conducting onsite experiments is risky and time-consuming for the maritime domain. It is not always possible to capture challenging situations and incorporate variations in the environment. Therefore, we present a simulation-based dataset for maritime environments consisting of 9471 high-resolution (1920x1080) images resembling the real world with precise annotations. The dataset was acquired using a simulation tool, AILiveSim [17]. AILiveSim is a 3D simulation platform for targeted scalable development and integration of autonomous systems through digital twins. The tool provides a realistic 3D model of the route of the watercraft extended from the city of Turku to Ruisalo in South-West Finland. Our dataset incorporates diversity of objects, weather, illumination, visible proportion and scale in images that resemble the real world.  Please cite the following publication when using the dataset: M. Raza, H. Prokopova, S. Huseynzade, S. Azimi and S. Lafond, "SimuShips - A High Resolution Simulation Dataset for Ship Detection with Precise Annotations," OCEANS 2022, Hampton Roads, Hampton Roads, VA, USA, 2022, pp. 1-5, doi: 10.1109/OCEANS47191.2022.9977182. The publication is available at: <a href="https://doi.org/10.1109/OCEANS47191.2022.9977182">https://doi.org/10.1109/OCEANS47191.2022.9977182</a> A preprint version of the publication is available at <a href="https://arxiv.org/abs/2211.05237">https://arxiv.org/abs/2211.05237</a>

opencc-by-4.0Jan 2021View details →

Supporting Information: Vortex streets to the lee of Madeira in a km-resolution regional climate model

This is the Supporting Information for the manuscript Vortex streets to the lee of Madeira in a km-resolution regional climate model. It is posted as a preprint on EGUsphere for the journal Weather and Climate Dynamics: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-965/.