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108 results for “SPARC”
SPARC Data Initiative monthly zonal mean composition measurements from stratospheric limb sounders (1978-2018)
<p>The SPARC Data Initiative dataset is the most comprehensive compilation of vertically resolved stratospheric composition measurements to date and consists of four decades of monthly zonal mean climatologies (1978-2018) from a range of satellite limb sounders including LIMS, SAGE I/II/III, HALOE, UARS-MLS, POAMII/III, OSIRIS, SMR, MIPAS, GOMOS, SCIAMACHY, ACE-FTS, ACE-MAESTRO, Aura-MLS, HIRDLS, SMILES, OMPS-LP and SAGE III-ISS. The dataset includes most major long-lived trace gases (O<sub>3</sub>, H<sub>2</sub>O, N<sub>2</sub>O, CH<sub>4</sub>, CCl<sub>3</sub>F, and CCl<sub>2</sub>F<sub>2</sub>), transport tracers (HF, SF<sub>6</sub>, HCl, CO, HNO<sub>3</sub>, NOy), and shorter-lived trace gases important to stratospheric chemistry including nitrogens (NO, NO<sub>2</sub>, NOx, N<sub>2</sub>O<sub>5</sub>,and HNO<sub>4</sub>), halogens (BrO, ClO, ClONO<sub>2</sub> and HOCl), and other minor species (OH, HO<sub>2</sub>, CH<sub>2</sub>O, CH<sub>3</sub>CN). The observations considered have been compiled in units of volume mixing ratio (VMR) and on a common latitude-pressure grid, covering the region from the upper troposphere to the lower mesosphere (300-0.1 hPa) with a latitudinal resolution of 5 degrees.</p> <p> </p>
The SPARC water vapour assessment II: Comparison of annual, semi-annual and quasi-biennial variations in stratospheric and lower mesospheric water vapour observed from satellites
<p>Here we provide a NetCDF data set that contains the amplitudes and phases for the annual, semi-annual and quasi-biennial variations in stratospheric and lower mesospheric water vapour as observed by 30 satellite data sets. In addition, we combine the results from all data sets to provide average amplitudes and the corresponding standard deviations, among other.</p> <p>The content description of the NetCDF file looks as follows:</p> <p>netcdf results.amt-10-1111-2017 {<br> dimensions:<br> dataset = 30 ;<br> string_length = 60 ;<br> latitude = 37 ;<br> bands = 2 ;<br> altitude = 59 ;<br> variables:<br> char dataset_short(string_length, dataset) ;<br> dataset_short:standard_name = "data set" ;<br> dataset_short:long_name = "data set name" ;<br> dataset_short:description = "short label of data set" ;<br> char dataset_long(string_length, dataset) ;<br> dataset_long:standard_name = "data set" ;<br> dataset_long:long_name = "data set name" ;<br> dataset_long:description = "long label of data set" ;<br> double latitude(latitude) ;<br> latitude:standard_name = "latitude" ;<br> latitude:units = "degree_north" ;<br> latitude:minimum_value = "-90" ;<br> latitude:maximum_value = "90" ;<br> latitude:axis = "Y" ;<br> latitude:_CoordinateAxisType = "Lat" ;<br> double latitude_bands(bands, latitude) ;<br> latitude_bands:units = "degree_north" ;<br> double altitude(altitude) ;<br> altitude:standard_name = "altitude" ;<br> altitude:long_name = "pressure levels" ;<br> altitude:units = "hPa" ;<br> altitude:axis = "Z" ;<br> altitude:_CoordinateAxisType = "Alt" ;<br> double tropopause(latitude) ;<br> tropopause:standard_name = "tropopause" ;<br> tropopause:long_name = "tropopause pressure" ;<br> tropopause:description = "climatological tropopause pressure based on MERRA reanalysis data 2000 - 2014" ;<br> tropopause:units = "hPa" ;</p> <p>// global attributes:<br> :summary = "this file contains the results published in Lossow et al. (2017)" ;<br> :url = "https://www.atmos-meas-tech.net/10/1111/2017/amt-10-1111-2017.html" ;<br> :project = "second SPARC water vapour assessment (WAVAS-II)" ;<br> :creator_name = "Stefan Lossow & Farahnaz Khosrawi" ;<br> :creator_email = "stefan.lossow@kit.edu & farahnaz.khosrawi@kit.edu" ;<br> :creator_email_supplemental = "stefan.lossow@yahoo.se & f.khosrawi@gmail.com" ;<br> :value_for_nodata = "NaN" ;<br> :date_created = "20190105T112425Z" ;</p> <p>group: AO {<br> dimensions:<br> latitude = 37 ;<br> altitude = 59 ;<br> dataset = 30 ;<br> variables:<br> double amplitude(dataset, altitude, latitude) ;<br> amplitude:standard_name = "amplitude" ;<br> amplitude:long_name = "amplitude of the AO variation" ;<br> amplitude:description = "regression model is given by Eq. (1) in the manuscript; amplitude calculation based on Eq. (2)" ;<br> amplitude:units = "ppmv" ;<br> double phase(dataset, altitude, latitude) ;<br> phase:standard_name = "phase" ;<br> phase:long_name = "phase of the AO variation" ;<br> phase:description = "regression model is given by Eq. (1) in the manuscript; phase calculation based on Eq. (3)" ;<br> phase:units = "month" ;<br> double offset(dataset, altitude, latitude) ;<br> offset:standard_name = "offset" ;<br> offset:long_name = "offset component of the regression model" ;<br> offset:description = "regression model is given by Eq. (1) in the manuscript; meant for calculation of relative amplitudes" ;<br> offset:units = "ppmv" ;<br> double screening(dataset, altitude, latitude) ;<br> screening:standard_name = "screening" ;<br> screening:long_name = "screening for the amplitude and phase data" ;<br> screening:description = "screening matrix for the amplitude and phase data to calculate the standard deviations described in Sect. 3.3; 1 means screening; 0 means no screening" ;<br> screening:units = "" ;<br> double phase_difference(dataset, altitude, latitude) ;<br> phase_difference:standard_name = "phase difference" ;<br> phase_difference:long_name = "phase difference with respect to the reference data set" ;<br> phase_difference:reference_data_set_short = "MLS" ;<br> phase_difference:reference_data_set_long = "Aura/MLS v4.2" ;<br> phase_difference:description = "phase difference has been adapted so that it not exceeds the [-6,6] months interval by adding +/- 12 months; has been calculated after the screening" ;<br> phase_difference:units = "month" ;<br> double amplitude_standard_deviation(altitude, latitude) ;<br> amplitude_standard_deviation:standard_name = "standard deviation of amplitude" ;<br> amplitude_standard_deviation:long_name = "standard deviation of amplitude over all data sets" ;<br> amplitude_standard_deviation:description = "standard deviation calculation based on Eq. (6)" ;<br> amplitude_standard_deviation:units = "ppmv" ;<br> double amplitude_mean(altitude, latitude) ;<br> amplitude_mean:standard_name = "mean amplitude" ;<br> amplitude_mean:long_name = "mean amplitude over all data sets" ;<br> amplitude_mean:description = "mean calculation based on Eq. (6)" ;<br> amplitude_mean:units = "ppmv" ;<br> double amplitude_relative_standard_deviation(altitude, latitude) ;<br> amplitude_relative_standard_deviation:standard_name = "relative standard deviation of amplitude" ;<br> amplitude_relative_standard_deviation:long_name = "relatuve standard deviation of amplitude " ;<br> amplitude_relative_standard_deviation:description = "relavtive standard deviation calculation based on Eq. (6); uses \"amplitude_mean\" as reference" ;<br> amplitude_relative_standard_deviation:units = "ppmv" ;<br> double phase_difference_standard_deviation(altitude, latitude) ;<br> phase_difference_standard_deviation:standard_name = "standard deviation of phase difference" ;<br> phase_difference_standard_deviation:long_name = "standard deviation of phase difference over all data sets" ;<br> phase_difference_standard_deviation:description = "standard deviation calculation based on Eq. (7)" ;<br> phase_difference_standard_deviation:units = "month" ;<br> double phase_difference_mean(altitude, latitude) ;<br> phase_difference_mean:standard_name = "mean of phase difference" ;<br> phase_difference_mean:long_name = "mean of phase difference over all data sets" ;<br> phase_difference_mean:description = "mean calculation based on Eq. (7)" ;<br> phase_difference_mean:units = "month" ;<br> } // group AO</p> <p>group: SAO {<br> dimensions:<br> latitude = 37 ;<br> altitude = 59 ;<br> dataset = 30 ;<br> variables:<br> double amplitude(dataset, altitude, latitude) ;<br> amplitude:standard_name = "amplitude" ;<br> amplitude:long_name = "amplitude of the SAO variation" ;<br> amplitude:description = "regression model is given by Eq. (4) in the manuscript; amplitude calculation based on Eq. (2)" ;<br> amplitude:units = "ppmv" ;<br> double phase(dataset, altitude, latitude) ;<br> phase:standard_name = "phase" ;<br> phase:long_name = "phase of the SAO variation" ;<br> phase:description = "regression model is given by Eq. (4) in the manuscript; phase calculation based on Eq. (3)" ;<br> phase:units = "month" ;<br> double offset(dataset, altitude, latitude) ;<br> offset:standard_name = "offset" ;<br> offset:long_name = "offset component of the regression model" ;<br> offset:description = "regression model is given by Eq. (4) in the manuscript; meant for calculation of relative amplitudes" ;<br> offset:units = "ppmv" ;<br> double screening(dataset, altitude, latitude) ;<br> screening:standard_name = "screening" ;<br> screening:long_name = "screening for the amplitude and phase data" ;<br> screening:description = "screening matrix for the amplitude and phase data to calculate the standard deviations described in Sect. 3.3; 1 means screening; 0 means no screening" ;<br> screening:units = "" ;<br> double phase_difference(dataset, altitude, latitude) ;<br> phase_difference:standard_name = "phase difference" ;<br> phase_difference:long_name = "phase difference with respect to the reference data set" ;<br> phase_difference:reference_data_set_short = "MLS" ;<br> phase_difference:reference_data_set_long = "Aura/MLS v4.2" ;<br> phase_difference:description = "phase difference has been adapted so that it not exceeds the [-3,3] months interval by adding +/- 6 months; has been calculated after the screening" ;<br> phase_difference:units = "month" ;<br> double amplitude_standard_deviation(altitude, latitude) ;<br> amplitude_standard_deviation:standard_name = "standard deviation of amplitude" ;<br> amplitude_standard_deviation:long_name = "standard deviation of amplitude over all data sets" ;<br> amplitude_standard_deviation:description = "standard deviation calculation based on Eq. (6)" ;<br> amplitude_standard_deviation:units = "ppmv" ;<br> double amplitude_mean(altitude, latitude) ;<br> amplitude_mean:standard_name = "mean amplitude" ;<br> amplitude_mean:long_name = "mean amplitude over all data sets" ;<br> amplitude_mean:description = "mean calculation based on Eq. (6)" ;<br> amplitude_mean:units = "ppmv" ;<br> double amplitude_relative_standard_deviation(altitude, latitude) ;<br> amplitude_relative_standard_deviation:standard_name = "relative standard deviation of amplitude" ;<br> amplitude_relative_standard_deviation:long_name = "relatuve standard deviation of amplitude " ;<br> amplitude_relative_standard_deviation:description = "relavtive standard deviation calculation based on Eq. (6); uses \"amplitude_mean\" as reference" ;<br> amplitude_relative_standard_deviation:units = "ppmv" ;<br> double phase_difference_standard_deviation(altitude, latitude) ;<br> phase_difference_standard_deviation:standard_name = "standard deviation of phase difference" ;<br> phase_difference_standard_deviation:long_name = "standard deviation of phase difference over all data sets" ;<br> phase_difference_standard_deviation:description = "standard deviation calculation based on Eq. (7)" ;<br> phase_difference_standard_deviation:units = "month" ;<br> double phase_difference_mean(altitude, latitude) ;<br> phase_difference_mean:standard_name = "mean of phase difference" ;<br> phase_difference_mean:long_name = "mean of phase difference over all data sets" ;<br> phase_difference_mean:description = "mean calculation based on Eq. (7)" ;<br> phase_difference_mean:units = "month" ;<br> } // group SAO</p> <p>group: QBO {<br> dimensions:<br> latitude = 37 ;<br> altitude = 59 ;<br> dataset = 30 ;<br> variables:<br> double amplitude(dataset, altitude, latitude) ;<br> amplitude:standard_name = "amplitude" ;<br> amplitude:long_name = "amplitude of the QBO variation" ;<br> amplitude:description = "regression model is given by Eq. (5) in the manuscript; amplitude calculation based on Eq. (2)" ;<br> amplitude:units = "ppmv" ;<br> double phase(dataset, altitude, latitude) ;<br> phase:standard_name = "phase" ;<br> phase:long_name = "phase of the QBO variation" ;<br> phase:description = "regression model is given by Eq. (5) in the manuscript; phase is derived as the shift of the QBO regression fit for which the correlation with the Singapore (1N, 104E) winds at 50 hPa maximises" ;<br> phase:units = "month" ;<br> double offset(dataset, altitude, latitude) ;<br> offset:standard_name = "offset" ;<br> offset:long_name = "offset component of the regression model" ;<br> offset:description = "regression model is given by Eq. (5) in the manuscript; meant for calculation of relative amplitudes" ;<br> offset:units = "ppmv" ;<br> double screening(dataset, altitude, latitude) ;<br> screening:standard_name = "screening" ;<br> screening:long_name = "screening for the amplitude and phase data" ;<br> screening:description = "screening matrix for the amplitude and phase data to calculate the standard deviations described in Sect. 3.3; 1 means screening; 0 means no screening" ;<br> screening:units = "" ;<br> double phase_difference(dataset, altitude, latitude) ;<br> phase_difference:standard_name = "phase difference" ;<br> phase_difference:long_name = "phase difference with respect to the reference data set" ;<br> phase_difference:reference_data_set_short = "MLS" ;<br> phase_difference:reference_data_set_long = "Aura/MLS v4.2" ;<br> phase_difference:description = "phase difference has been adapted so that it not exceeds the [-14,14] months interval by adding +/- 28 months; has been calculated after the screening" ;<br> phase_difference:units = "month" ;<br> double amplitude_standard_deviation(altitude, latitude) ;<br> amplitude_standard_deviation:standard_name = "standard deviation of amplitude" ;<br> amplitude_standard_deviation:long_name = "standard deviation of amplitude over all data sets" ;<br> amplitude_standard_deviation:description = "standard deviation calculation based on Eq. (6)" ;<br> amplitude_standard_deviation:units = "ppmv" ;<br> double amplitude_mean(altitude, latitude) ;<br> amplitude_mean:standard_name = "mean amplitude" ;<br> amplitude_mean:long_name = "mean amplitude over all data sets" ;<br> amplitude_mean:description = "mean calculation based on Eq. (6)" ;<br> amplitude_mean:units = "ppmv" ;<br> double amplitude_relative_standard_deviation(altitude, latitude) ;<br> amplitude_relative_standard_deviation:standard_name = "relative standard deviation of amplitude" ;<br> amplitude_relative_standard_deviation:long_name = "relatuve standard deviation of amplitude " ;<br> amplitude_relative_standard_deviation:description = "relavtive standard deviation calculation based on Eq. (6); uses \"amplitude_mean\" as reference" ;<br> amplitude_relative_standard_deviation:units = "ppmv" ;<br> double phase_difference_standard_deviation(altitude, latitude) ;<br> phase_difference_standard_deviation:standard_name = "standard deviation of phase difference" ;<br> phase_difference_standard_deviation:long_name = "standard deviation of phase difference over all data sets" ;<br> phase_difference_standard_deviation:description = "standard deviation calculation based on Eq. (7)" ;<br> phase_difference_standard_deviation:units = "month" ;<br> double phase_difference_mean(altitude, latitude) ;<br> phase_difference_mean:standard_name = "mean of phase difference" ;<br> phase_difference_mean:long_name = "mean of phase difference over all data sets" ;<br> phase_difference_mean:description = "mean calculation based on Eq. (7)" ;<br> phase_difference_mean:units = "month" ;<br> } // group QBO<br> }</p> <p> </p>
SPARC Connectivity Knowledge base of the Autonomic Nervous System
<p>The SPARC Knowledge base of the Autonomic Nervous System (SCKAN) is an integrated graph database composed of three parts: the SPARC dataset metadata graph, ApiNATOMY and NPO models of connectivity, and the larger ontology used by SPARC which is a combination of the NIF-Ontology and community ontologies.</p> <p>The fastest way to get querying is to follow the instructions in the <a href="https://github.com/SciCrunch/sparc-curation/blob/master/docs/sckan/README.org#getting-started">SCKAN readme file</a>.</p> <p>For background information please see <a href="https://scicrunch.org/sawg/about/SCKAN">https://scicrunch.org/sawg/about/SCKAN</a> and <a href="https://sparc.science/resources/6eg3VpJbwQR4B84CjrvmyD">the SPARC portal resource page about SCKAN.</a></p> <p>This release contains the raw and compiled data for SCKAN. The release-*.zip contains raw data inputs along with the Blazegraph journal file, the sparc-sckan-graph-*.zip contains the SciGraph database, and sckan-data-*.tar.gz is a Docker image that contains the Blazegraph journal file and the SciGraph database along with the configuration files for running each of the servers. The image is intended to be used as a data volume with another Docker container that runs the SciGraph and Blazegraph server software.</p> <p>The Docker image containing this data is available live and is likely easier to use than the archived image included in this release. See the <a href="https://github.com/SciCrunch/sparc-curation/blob/master/docs/sckan/README.org#getting-started">SCKAN readme file</a> for the most up-to-date instructions.</p> <p>We would like to thank the members of the SAWG (SPARC Anatomy Working Group, RRID:SCR_018709) for their work on the various connectivity models included in this release.</p> <p>This work was funded by the NIH Common Fund under 3OT2OD030541-01S1.</p>
DATASET SPARC Europe Open Education in European Libraries of Higher Education Survey 2022
<p>This is the anonymised dataset for the 2022 edition of the SPARC Europe Open Education Survey amongst Higher Education libraries in Europe.</p>
SPARC_Landscape Research Centre Archive_2020
<p>The <a href="http://www.landscaperesearchcentre.org/html/lrc_home_page.html">Landscape Research Centre</a>, led by Dominic Powlesland, was registered as a charity in 1980 (Registered Charity number 326710 - Registered Company number 01852824) to promote research into the evolution of the landscape from the Palaeolithic to the present, and to publish the results. Most work so far has been under the banner of the <a href="http://www.landscaperesearchcentre.org/AA%20Tier%201%20Primary%20Headings/heslerton_parish_project.htm">Heslerton Parish Project</a>, a research framework established in 1980 to provide a research context for a series of large, seasonal, open-area rescue excavations undertaken ahead of mineral extraction in the Vale of Pickering in eastern Yorkshire. The LRC is undertaking remote-sensing projects employing established technologies that include air photography and ground-based geophysics, as well as new technologies such as thermal and multi-spectral surveys designed to identify the physical resources relating to human occupation of the landscape without physical intervention. In addition, the LRC carries out large scale rescue archaeology and smaller research projects, investigating sites threatened through mineral extraction, agriculture and drainage schemes which have a significant but less visible impact on the archaeological resource than, for instance, the redevelopment of our urban centres.</p> <p>The dataset published here (<a href="https://lrc.cast.uark.edu/map">and viewable online through the LRC's interactive map</a>) includes the magnetometry/gradiometry outputs in georeferenced tiff files, the inundation levels for the region in georeferenced tiff files, the extent of the sands and gravels in the region in georeferenced tiff files, and the polyline interpretation of the various datasets in geojson files. Though the original files were produced in OSGB-36, two projections have been archived for each file: OSGB-36 EPSG 27700 and WGS-84 EPSG 4326.</p> <p> </p>
Terms from the SPARC Term Request Pipeline (Oct 2019 - Aug 2021)
<p>Terms analyzed for the paper "Extending and using anatomical vocabularies in the Stimulating Peripheral Activity to Relieve Conditions (SPARC) project". These terms were submitted by SPARC investigators to the SPARC term request pipeline. The SPARC anatomical term request pipeline is an iterative curation process that consists of three main steps: term request, term review, and term engineering. <strong> </strong>This work was supported by NIH grant 3OT2OD030541 from the Office of the Director through the Stimulating Peripheral Activity to Relieve Conditions (SPARC) program.</p>
SPARCS_WP3_Espoo_City_SPARCS-WP3 participants in Smart Otaniemi events
<p>Number of participants in Smart Otaniemi, and other related, events completed during SPARCS Work Package 3 (WP3)</p>
SPARCS_WP3_Espoo_City_Electricity consumption in Espoo, Finland
<p>Electricity consumption in Espoo, Finland, divided by sector. Provided by the Helsinki Region Environmental Authority. 2000-2023</p>
SPARCS_WP3_Espoo_City_CO2 emissions in Espoo, Finland
<p>CO2 emissions in Espoo, Finland, divided by sector. Provided by the Helsinki Region Environmental Authority. 2000-2023</p>
SPARCS_WP3_Espoo_City_Energy consumption in Espoo, Finland
<p>Energy consumption in Espoo, Finland, divided by sector. Provided by the Helsinki Region Environmental Authority. 2000-2022</p>
SPARCS_WP3_Espoo_City_District heating production by fuel in Espoo, Finland
<p>District heat production in Espoo, Finland, divided by fuel. Provided by the Helsinki Region Environmental Authority. 2000-2023</p>
SPARCS_test_data_small_membrane
<p>Example images to run the SPARCS computation workflow on.</p>
SPARCS_WP4_Leipzig_City_Number of EV charging points
<p>Number of EV charging points in the city of Leipzig with annually captured data for the period between 2019 and 2024</p>
SPARCS_WP3_Espoo_City_SPARCS-WP3 number of promising solutions for PEDs identified in Espoo
<p>Number of promising solutions for PEDs identified during SPARCS Work Package 3 (WP3) work</p>
SPARCS-WP3_Espoo_City_Total number of vehicles in local transportation
<p>Number of vehicles registered in the Espoo area.</p>
SPARCS-WP3_Espoo_City_Number of electric cars registered in Espoo
<p>Number of fully electric cars that are registered in the Espoo area.</p>
The Effect of SPecialty cAre on Recovery From Cardiac Arrest Trial (the SPARC Trial)
ClinicalTrials.gov study NCT07002294. IPD Sharing: YES. Countries: 1. Publications: 62.
Dynamic Changes in the Levels of sCD62L and SPARC in Chronic Myeloid Leukemia Patients During Imatinib Treatment
ClinicalTrials.gov study NCT05387330. IPD Sharing: UNDECIDED. Countries: 1. Publications: 4.
SPARC Reanalysis Intercomparison Project (S-RIP) reanalysis common grid files
<p>This is the reanalysis common grid data set produced as part of the SPARC (Stratosphere-troposphere Processes and their Role in Climate) Reanalysis Intercomparison Project (<a href="https://s-rip.ees.hokudai.ac.jp/">S-RIP</a>). These data have been used in several chapters in the S-RIP report, including Chapter 4 (Overview of Ozone and Water Vapou<strong>r</strong> - See <a href="http://doi.org/10.5194/acp-17-12743-2017">Davis et al., ACP, 2017</a>) and Chapter 8 (Tropical Tropopause Layer - See <a href="https://www.atmos-chem-phys.net/20/753/2020/">Tegtmeier et al., ACP, 2020</a>).</p> <p>Notes about this data set:</p> <p> - Data set size: ~26 GB<br> - Reanalyses included are CFSR, ERA-I, JRA-25, JRA-55, MERRA, MERRA-2<br> - Variables include T (variable name ta), u (ua), v (va), O3 (tro3), WV (hus), and GPH (zg)<br> - Data are based off of the ana4mips data set<br> - Data are on a 2.5° x 2.5° grid<br> - All values are monthly means<br> - Pressure levels are (1000, 925, 850, 700, 600, 500, 400, 300, 250, 200, 150, 100, 70, 50, 30, 20, 10, 7, 5, 3, 2, 1, .7, .5, .3, .1 hPa)<br> - 3 time periods are provided:<br> - The “full” time period (different for each reanalysis)<br> - The “S-RIP base period” (i.e., 197901-201312)<br> - The “climatology” period (198101-201012)<br> - Both 3D (lon,lat,level) and zonal mean 2D (lat, level) files are provided<br> - Both timeseries and climatology data are provided. Files with “ltm” in the name are climatologies<br> - Reanalysis “Ensemble” files are located in the /ensemble directory (See note below*)</p> <p><br> *Regarding the “ensemble” data — I highly recommend using the “ensemble” files in the “ensemble” folder for climatological intercomparisons.<br> You can use a single file (e.g., hus_Amon_reanalysis_ENS_198101-201012.cg.ltm.nc for water vapor) that contains the climatologies for each reanalysis.<br> The data in these files are of dimension (lon, lat, level,time(==12 months ), “record”), where record 0 = CFSR, 1=ERA-I, 2=JRA-25, 3=JRA-55, 4=MERRA, 5=MERRA2.</p> <p>There is also a corresponding “ensemble mean” file (e.g., hus_Amon_reanalysis_ENS_198101-201012.cg.ltm.ensmean.nc) that is simply the ensemble mean climatology from the 4 core reanalyses (CFSR, ERA-I, JRA-55, MERRA — EXCLUDING JRA-25 & MERRA2).</p>
SPARCS_WP4_Leipzig_Baumwollspinnerei_Total Energy Generation
<p>Yearly energy generated (electricity and heating) by the PV plant and the two CHPs at the Baumwollspinnerei</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.