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2,152 results for “outputs”
Convective systems associated with Amazon coastal squall lines using ForTraCC outputs
<p>List of convective systems tracked with ForTraCC that are associated with Amazon coastal squall lines during the period between July and October 2020. Contains information on the date, duration, displacement inland, maximum size, classification according to ForTraCC criteria and according to Cohen et al. (1995).</p> <p> </p>
Figure 1 in Exposure of the snail Potamopyrgus antipodarum to herbicide boosts output and survival of parasite infective stages
Figure 1. Mean (±SE) number of cercariae emerging per day from individual snails, P. antipodarum, exposed to either control water, low, medium or high concentrations of the herbicide glyphosate. Data are shown separately for the trematodes C. parvum (N = 6 snails for each treatment), Apatemon sp. (N = 3), and an undescribed renicolid species from two localities (Tomahawk Lagoon, N = 12; Lake Waihola, N = 9). In each case, different letters on the bars indicate mean values that are significantly different (Tukey–Kramer tests, P <0.05).
F I G U R E 4 in Toward optimising reproductive output of Eristalis tenax (Diptera: Syrphidae) for commercial mass rearing systems
F I G U R E 4 Time to first hatch (hours) and number of hatched larvae per egg cluster (mean ± SE) for Eristalis tenax egg clusters reared at 12 (n = 6), 16.5 (n = 5), 21.5 (n = 6), 25.5 (n = 5), 30 C (n = 6). Letters indicate significant differences in time to first hatch (bold) and hatched larval output at each temperature (p <0.05).
T A B L E 1 in Toward optimising reproductive output of Eristalis tenax (Diptera: Syrphidae) for commercial mass rearing systems
T A B L E 1 Summary of percentage of females mated, observed total egg cluster count and expected total egg cluster count proportionate to the number of females per cage, and differences between observed and expected egg cluster counts (% of expected) for Eristalis tenax at three different sex ratio treatments: 20:40, 30:30 and 40:20 female to male.
F I G U R E 3 in Toward optimising reproductive output of Eristalis tenax (Diptera: Syrphidae) for commercial mass rearing systems
F I G U R E 3 Percentage of total Eristalis tenax egg cluster output per week from eclosion, from four cages in the 30:30 sex ratio treatment (n = 196) and three cages in the 60 fly per cage stocking density treatment with a 1:1 sex ratio (n = 62).
F I G U R E 2 Survival curves for female Eristalis tenax flies observed for 11 in Toward optimising reproductive output of Eristalis tenax (Diptera: Syrphidae) for commercial mass rearing systems
F I G U R E 2 Survival curves for female Eristalis tenax flies observed for 11 weeks in four adult density treatments; 15:15 (n = 45), 30:30 (n = 90), 60:60 (n = 180), 120:120 (n = 360). Letters indicate significant differences (p <0.05) between survival curves of treatments.
METIS case study PSHA: openquake hdf5 output files for Conditional Spectra
<p>This dataset (V2) contains the disaggregation results, the hdf5 files for the Conditional Spectra are in V1</p>
F I G U R E 1 in Toward optimising reproductive output of Eristalis tenax (Diptera: Syrphidae) for commercial mass rearing systems
F I G U R E 1 Percentage of mated Eristalis tenax females in a captive population over time following eclosion (mean ± SE); 2 weeks (n = 15), 4 weeks (n = 29), 5 weeks (n = 15), 7 weeks (n = 4), 9 weeks (n = 16).
Tremor catalogs produced (output data) in the paper "Dynamics of the 2021 Fagradalsfjall eruption (Iceland) revealed by volcanic tremor patterns"
<p>This repository contains tremor catalogs produced as output data in the paper "Dynamics of the 2021 Fagradalsfjall eruption (Iceland) revealed by volcanic tremor patterns" submitted to Journal of Geophysical Research - Solid Earth by Soubestre J., Caudron C., Melnik O., Lecocq T., Jaupart C., Shapiro N.M., Journeau C., Çubuk-Sabuncu Y., and Jónsdóttir K.</p> <p>In particular, it contains three catalogs :<br>+ time and 3-D location of <strong>tremor sources</strong> shown in Figure 5 ;<br>+ time and duration of <strong>tremor bursts</strong> associated with pulsating lava fountains shown in Figure 6 ;<br>+ time and duration of <strong>repose times</strong> associated with pulsating lava fountains shown in Figure 6 ;</p>
Output of Optimized gross primary productivity over the croplands within the BEPS particle filtering data assimilation system (BEPS_PF v1.0)
<p>Output of Optimized gross primary productivity over the croplands within the BEPS particle filtering data assimilation system (BEPS_PF v1.0)</p>
Output from ICON v2.6.2.2 cloud locking simulations: 3D radiative fluxes and additional atmospheric variables
<p>Simulation output from a cloud locking experiment carried out by A. Voigt with ICON version 2.6.2.2, originally for use in M. Huber’s PhD thesis (<a href="https://utheses.univie.ac.at/detail/63548/">https://utheses.univie.ac.at/detail/63548/</a>) and described therein. This subset was processed by E.K. Van de Koot for use in a study by McGraw et al (submitted 2024). Vertically-resolved radiative flux output is in the ‘phy_3d’ files, while ‘atm_2d’ and ‘atm_3d’ include additional atmospheric quantities, such as temperatures, specific humidity, and 2D radiative fluxes at the top-of-atmosphere and surface. Each file name is prefaced with the name of the relevant simulation (e.g. ‘amip_T1C1W1’), which follows nomenclature described in the Huber thesis.</p> <p>*Updated Dec 4, 2024 to fix a very small issue on vertical levels in the 'phy' files.</p>
Model output from 'Modelling the circular economy potential of micromobility: A Finnish case study for e-scooters and e-bikes'
<p>These two files include the results for e-scooters and e-bikes. The dynamics of the BAU scenario is shown in the first few columns, then follow the sensitivity analyses. The column names should be self-explanatory, subject to reading the paper.</p>
Output of simulations for "Atmosphere Response to an Oceanic Sub-mesoscale SST Front: A Coherent Structure Analysis": Part 1
<p>This dataset contains the output of the simulations for the paper "Atmosphere Response to an Oceanic Sub-mesoscale SST Front: A Coherent Structure Analysis" doi: [TO BE COMPLETED]. This is part 1. It contains data for the S1 simulation.</p>
Output of simulations for "Atmosphere Response to an Oceanic Sub-mesoscale SST Front: A Coherent Structure Analysis": Part 2
<p>This dataset contains the output of the simulations for the paper "Atmosphere Response to an Oceanic Sub-mesoscale SST Front: A Coherent Structure Analysis" doi: [TO BE COMPLETED]. This is part 2. It contains the remaining of data for the S1 simulation, the data of the reference simulations RefC and RefW, and the data for the sensitivity analysis of the supplementary material.</p>
Data, code, and outputs for the paper "Can Place-Based Crime Prevention Impacts be Sustained Over Long Durations? 11-Year Follow-Up of a Quasi-Experimental Evaluation of a CCTV Project"
<p>**********<br>Can Place-Based Crime Prevention Impacts be Sustained Over Long Durations? 11-Year Follow-Up of a Quasi-Experimental Evaluation of a CCTV Project<br>**********</p> <p>The phase-specific datasets for the main and displacement analyses are contained in the “1.datasets” folder. </p> <p>The scripts used to conduct the microsynthetic control matching analyses are contained in the “2.Rscripts” folder. The subfolders “3.outputs_main” and "4.outputs_displacement" contains all graphs and tables generated by the microsynth package. Please note that running the analysis will take several hours on most computer systems.</p> <p>The Microsoft Excel file displays the results of all models conducted for this analysis. Yellow tabs contain the WDD results presented in the text of the article. Red tabs are the per-capita (quarter-year) microsynth results used to calculate WDD values. All other tabs contain the raw microsynth outputs used to calculate the per-capita results. </p>
Conservation outcomes of dietary transitions across different values of nature - model outputs
<p>Archive of output reports produced for the MAgPIE v4.8.2 paper <strong>Conservation outcomes of dietary transitions across different values of nature</strong>.</p> <p><strong>Data</strong></p> <p>The data contain the MAgPIE model and post-processing outputs for all assessed scenarios, including the sensitivity test across the SSP1 and SSP3 scenarios.</p> <ul> <li>The file <em>rev9_healthyLscps_AOH_full_report.Rds </em>contains the outputs of our Area of Habitat (AOH) assessment for all assessed species and across all scenarios. The summary statistics shown in Figure 2 and Figure 3 have been derived from this data set. The data has also been used to create Extended Data Figures<span lang="EN-GB"> 5-</span>7<span lang="EN-GB"> and is shown in the Supplementary Information. </span>However, for Extended Data Figure<span lang="EN-GB"> 7</span> the data was <span lang="EN-GB">used in combination</span> with <span lang="EN-GB">rasterized </span>range polygons obtained from the <span lang="EN-GB">IUCN Red List Database (IUCN 2020).</span></li> <li><span lang="EN-GB">The file <em>rev9_healthyLscps_pollSuff_report_all.Rds </em>reports the global and regional cropland area (Mha) that is subject to insufficient and sufficient pollination supply. This is specified in the column ‘poll_class’, where 1 is insufficient and 2 is sufficient pollination supply. The data is shown in Figure 4, Extended Data Figure 8 and the Supplementary Information.</span></li> <li><span lang="EN-GB">The file <em>rev9_healthyLscps_RUSLE_report_all.Rds</em> reports estimated global and regional soil loss in Pg per year across all modelled scenarios. The data is displayed in Figure 4, Extended Data Figure 9 and the Supplementary Information.</span></li> <li><span lang="EN-GB">The file <em>rev9_healthyLscps_allSSP_report.rds </em>contains regional and global output variables from the MAgPIE model used in this study. The data is shown in Figure 1 and 5, as well as in Extended Data Figures 2-4 and the Supplementary Information.</span></li> <li><span lang="EN-GB">The file <em>rev9_healthyLscps_validation.rds </em>contains validation data for the MAgPIE model output variables.</span></li> </ul> <p> </p> <p><strong><span lang="EN-GB">Model code</span></strong></p> <p>The model code of the MAgPIE and SEALS models can be accessed via:</p> <p><em>MAgPIE model code</em><em>:</em></p> <ul> <li><a href="https://doi.org/10.5281/zenodo.13833444">https://doi.org/10.5281/zenodo.13833444</a> and <a href="https://github.com/magpiemodel/magpie">https://github.com/magpiemodel/magpie</a></li> </ul> <p><em>MAgPIE model documentation</em><em>:</em></p> <ul> <li><a href="https://rse.pik-potsdam.de/doc/magpie/4.3.5/">https://rse.pik-potsdam.de/doc/magpie/4.8.2/</a></li> </ul> <p><em>SEALS model code</em><em>:</em></p> <ul> <li><a href="https://github.com/jandrewjohnson/seals_dev/releases/tag/v1.0.0">https://github.com/jandrewjohnson/seals_dev/releases/tag/v1.0.0</a></li> </ul> <p><em>SEALS mode documentation:</em></p> <ul> <li><a href="https://justinandrewjohnson.com/earth_economy_devstack/seals_overview.html">https://justinandrewjohnson.com/earth_economy_devstack/seals_overview.html</a></li> </ul> <p> </p> <p><strong><span lang="EN-GB">Cited references</span></strong></p> <p><span>IUCN. (2020). <em>The IUCN Red List of Threatened Species. Version 2020-2</em>. https://www.iucnredlist.org.</span><em><span> </span></em><span>Downloaded on 25 November 2020</span></p>
Database of PV output forecast errors
<p>This database is extracted from 180 studies on PV output forecasting and is used for the research paper "What drives the accuracy of PV output forecasts?". The data of 21 key variables including the publishing year of the papers, the error values, data processing techniques used by the models, the length of the test sets, the forecast resolution, the country and region of the studies, the methodology of the forecast models, the forecast horizon, and the error metrics are included. Besides, other information such as the weather condition of the forecasts, the number of power plants, the installed capacity... is also included. </p>
Two Source Energy Balance Model Inputs and Outputs from Drone Surveys at Majadas de Tietar in May 2021
<p><strong>MONSOON PROJECT SURVEY DATA OUTPUTS: Majadas de Tietar Tree-Grass Savanna Ecosystem 05/05/2021-20/05/2021</strong></p> <p>Here we make available high resolution (0.82 cm) energy and water flux maps from unmanned aerial system (UAS) data collected using a Micasense Altum in May 2021. We use the Two Source Energy Balance Model (via pyTSEB) and include model inputs and outputs. We use the Priestley Taylor (TSEB hereafter) and Dual Time Difference (DTD hereafter) methods in pyTSEB, the details of which can be found here pyTSEB https://pytseb.readthedocs.io/en/latest/index.html. The data collection method largely follows https://www.mdpi.com/2072-4292/13/7/1286, however a new paper detailing these surveys in Majadas is under review (as of November 2021). </p> <p>This upload includes the following gridded datasets:</p> <p><strong>Model inputs</strong></p> <p>Zipfiles are named according to their collection date (<strong>DDMMYYYY.7z</strong>). Within each zipfile are the datasets corresponding to different flight times UTC +2 (<strong>hhmm_DDMMYY</strong>). Within each survey folder are rasters with descriptive filenames using the following format:</p> <p><em>Product type_Resolution_survey area_date_flight time.tif</em></p> <p>The following prefixes denote the Product types:</p> <ul> <li>CHM_... = Canopy Height Model (m)</li> <li>GFrac2_... = Green Fraction (0-1)</li> <li>MSpec_... = Raw multispectral dataset from Altum (Blue, Green, Red, NIR, Rededge, LWIR)</li> <li>TEmpK_... = Radiometric Surface Temperature (empirical calibration, K)</li> <li>TRawK_... = Radiometric Surface Temperature (no calibration, K)</li> <li>LST2_... = Radiometric Surface Temperature (calibrated using methods outlined here https://www.mdpi.com/2072-4292/12/7/1075, K)</li> <li>Grass_... = grass vegetation mask</li> <li>Tree_... = tree vegetation mask</li> </ul> <p>We also supply the config files used to generate TSEB and DTD. To run these you will need to edit the filepaths according to your own system. </p> <p><strong>Model Outputs</strong></p> <p><strong>Majadas_TSEB_EMP_outputs.7z</strong> = Two Source Energy Balance (pyTSEB) model outputs (using the Priestley-Taylor method), using radiometric temperature datasets calibrated empirically. </p> <p><strong>Majadas_DTD_EMP_outputs.7z</strong> = TSEB Dual Time Difference model outputs (from pyTSEB) using radiometric temperature datasets calibrated empirically. </p> <p><strong>DTD_ET.7z</strong> = Evapotranspiration rasters (calculated using DTD latent heat data) in g m<sup>-2</sup> s<sup>-1</sup></p> <p><strong>File names are descriptive</strong>:</p> <p><em>Model type_radiometric temperature method_vegetation type_survey area_date_flighttime.tif</em></p> <p>Model type = DTD or TSEB</p> <ul> <li>Radiometric temperature method = always empirical calibration here</li> <li>vegetation type = grass, tree, or merge (which is both tree and grass)</li> <li>Survey area = N (north, or Nitrogen fertiliser treatment), C (central, or Control fertiliser treatment), S (south, or Nitrogen and Phosphorus fertiliser treatment)</li> <li>date = in DDMMYY format</li> <li>flight time = takeoff time for the drone (hhmm) (UTC+2)</li> </ul> <p>To find the exact local time of survey times, please see the table in flight_data3.csv</p>
NOAA-GFDL GFDL-ESM4 CMIP6 ScenarioMIP additional model output
<p>This repository contains annual 3D sea water age since surface contact files from the ScenarioMIP ssp585 simulation conducted with GFDL's ESM4.1 climate model (Dunne et al., 2020) that was contributed to the 6th Coupled Model Intercomparison Project (CMIP6).</p> <p>Both the ocean model native grid and the regridded output can be found in this repository. For the regridded output, the files have been regridded from MOM6 native grid to standard World Ocean Atlas 1x1 horizontal grid, and they have been remapped from the lagrangian vertical coordinate used by GFDL's MOM6 ocean model (Adcroft et al., 2019) to standard World Ocean Atlas depths.</p> <p>Files have undergone QA/QC. All data files are NetCDF.</p> <p>Enquiries should be directed to Jasmin.John (Jasmin.John@noaa.gov) or John Dunne (John.Dunne@noaa.gov)</p> <p>Anyone using these data should cite Dunne et al. (2020) and Adcroft et al. (2019). See references below.</p> <p>Other variables associated with these simulations, along with assigned DOI's, are available through the ESGF CMIP6 portal:</p> <p>https://esgf-node.llnl.gov/projects/cmip6/ </p> <p>______________________________________________________________________</p> <p>The organization of this repository is as follows:</p> <p>Experiments:</p> <p>The tar files in the repository follow this naming convention: <model>_<activity>_<MIP>_<experiment>_<component_and_grid>_<variable>.tar.gz</p> <p> </p> <p>E.g. </p> <p> </p> <p>GFDL_ESM4_CMIP6_ScenarioMIP_ssp585_ocean_annual_z_1x1deg_agessc.tar.gz (regridded)</p> <p>GFDL_ESM4_CMIP6_ScenarioMIP_ssp585_ocean_annual_z_agessc.tar.gz (native grid)</p> <p>The organization of above repository is as follows:</p> <p>Experiment: ssp585</p> <p>NOAA-GFDL/CMIP6/ScenarioMIP/GFDL-ESM4/ESM4_ssp585_D1/</p> <p>For each experiment, 3D annual sea water age data can be found in the sub-directory:</p> <p>/ocean_annual_z_1x1deg (for regridded output)</p> <p>/ocean_annual_z (for native grid output)</p> <p>_________________________________________________________________________</p> <p>NOTES:</p> <p>Provenance:</p> <p>The data provided here do not have metadata that can be used for provenance and traceability back to NOAA/GFDL. The data DOI assigned should be used when sharing and citing these data.</p> <p>_________________________________________________________________________</p>
PACT-1D model version including polar halogen emissions - output files
<p>This dataset includes all output files created from the PACT-1D model (v1.0) developed with Arctic chlorine and bromine emission parameterizations. The PACT-1D source code used to create these output files is available at: https://doi.org/10.5281/zenodo.5654589.</p> <p> </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.