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edi60/100

Lake ice clearance and formation data for Green Lakes Valley, 1968 - ongoing.

Records were based on intermittent observation of the extent of ice cover on Silver Lake, Lake Albion, and Green Lakes 1-5, dependent on observers present for other reasons (or in some cases from photos or satellite data). Dates of freeze-up (formation), breakup (first melt or open water), and lake-ice clearance were recorded, along with visual estimates of percent ice cover at various dates prior to complete meltout in spring. The latter estimates are only included starting in 2019.

openCC (other)Sep 2025View details →
zenodo52/100

Cirrus formation regimes - Data driven identification and quantification of mineral dust effect

<p>This repository contains the data for the paper:&nbsp;</p> <p>Authors: Kai Jeggle , David Neubauer , Hanin Binder and Ulrike Lohmann<br>Titel: Cirrus formation regimes - Data driven identification and quantification of mineral dust effect<br>Date: 2024</p> <p>Note that the scripts can be found in the accompanying code repository (https://github.com/tabularaza27/cloud_clustering)<br><br>Contents:<br><br>├── cirrus_cloud_trajectories.ftr<br>├── cluster_input_data.ftr<br>├── cluster_models<br>│ &nbsp; &nbsp; &nbsp; └── temperature_clustering_k4_12<br>│ &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; ├── cloud_ids.npy<br>│ &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; ├── model_params.json<br>│ &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; └── trained_model.hdf5</p> <p>│ &nbsp; &nbsp; &nbsp; └── temperature_clustering_k4_24<br>│ &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; ├── cloud_ids.npy<br>│ &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; ├── model_params.json<br>│ &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; └── trained_model.hdf5</p> <p>├── cluster_predictions.ftr<br>└── readme.txt<br><br>For more info, please have a look at the&nbsp;<em>readme.txt</em><br><br>This is an updated version of the data, containing updated models and predictions based on the Journal revisions</p>

opencc-by-4.0Aug 2024View details →
zenodo52/100

CMS 2011A Open Data | Jet Primary Dataset | pT > 375 GeV | MOD HDF5 Format

<p>A dataset of 1,785,625 jets from the <a href="http://doi.org/10.7483/OPENDATA.CMS.UP77.P6PQ">Jet Primary Dataset of the CMS 2011A&nbsp;Open Data</a>&nbsp;reprocessed into the MOD HDF5 format. Jets are selected from the hardest two anti-kT R=0.5 jets in events passing the Jet300 High Level Trigger and are required to have <span class="math-tex">\(p_T^\text{jet}&gt;375\)</span>&nbsp;GeV, where&nbsp;<span class="math-tex">\(p_T^\text{jet}\)</span> includes a jet energy correction factor. Particle Flow Candidates (PFCs) for each jet are provided and include information about the PFC kinematics, PDG ID, and vertex. Additionally, jets have metadata describing their kinematics and provenance in the original CMS AOD files.</p> <p>For additional details about the dataset, please see the accompanying paper,&nbsp;Exploring the Space of Jets with CMS Open Data. There, jets were further restricted to have&nbsp;<span class="math-tex">\(|\eta^\text{jet}|&lt;1.9\)</span> to ensure tracking coverage&nbsp;and have &quot;medium&quot; quality to reject fake jets.</p> <p>The supported method for downloading, reading, and using this dataset is through the <a href="https://energyflow.network">EnergyFlow Python package</a>, which has additional documentation about how to read and use this and related datasets. Should any problems be encountered, please <a href="https://github.com/pkomiske/EnergyFlow/issues">submit an issue on GitHub</a>.</p> <p>There are corresponding datasets of simulated jets organized by hard parton&nbsp;<span class="math-tex">\(\hat p_T\)</span>&nbsp;also available on Zenodo:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.3341500">SIM/GEN QCD Jets&nbsp;170-300 GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341498">SIM/GEN QCD Jets 300-470&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341419">SIM/GEN QCD Jets 470-600&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3364139">SIM/GEN QCD Jets 600-800&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341413">SIM/GEN QCD Jets 800-1000&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341502">SIM/GEN QCD Jets 1000-1400&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341770">SIM/GEN QCD Jets 1400-1800&nbsp;GeV</a></li> <li><a href="https://doi.org/10.5281/zenodo.3341772">SIM/GEN QCD Jets 1800-<span class="math-tex">\(\infty\)</span>&nbsp;GeV</a></li> </ul>

opencc-by-4.0Aug 2019View details →
zenodo52/100

Data for: Diminutive temnospondyls from the lower and middle Fremouw Formation (Lower Triassic) of Antarctica

<p>This dataset contains the supporting data for the journal article, "Diminutive temnospondyls from the lower and middle Fremouw Formation (Lower Triassic) of Antarctica." Included are the phylogenetic character matrix (in .nex and .tnt formats) that was analyzed in TNT, the resultant 18 MPTs (.tre) recovered by the analysis, the skull length measurement data sourced from the literature for capitosaurs (.csv), a list of references used to source this measurement data (.pdf), and a README file with more metadata and details (.txt).&nbsp;</p>

opencc-zeroOct 2024View details →
zenodo52/100

Spectral reflectance data of Mercury's surface collected by the Mercury Atmospheric and Surface Composition Spectrometer (MASCS) instrument during orbital observations of the NASA MESSENGER mission between 2011 and 2015 resampled to a [55399 × 396] tabular data format.

<p>MASCS is a three sensor point spectrometer with a spectral coverage from 200 nm to 1450 nm.<br> Single spectra are resamples in to steps to a format useful for our ML application : a datacube with ~400 spectral channel covering the whole surface of Mercury.<br> The final dataset has dimension [N&times;M] where N is the number of grid cells (360 &times; 180 = 64, 800) and M is the number of spectral features (396).<br> Due to the incomplete coverage and data filtering, some grid cells are empty.<br> After removing these empty cells, the size of the dataset is [55399 &times; 396].</p> <p>This specific product is stored as a gzip compressed json, where each element is a grid cell.<br> We are in the process to publish a complete pipeline to produce this product from RAW data on https://github.com/epn-ml/MESSENGER-Mercury-Surface-Cassification-Unsupervised_DLR/ .</p> <p>Spectral reflectance data of Mercury&rsquo;s surface collected by the Mercury Atmospheric and Surface Composition Spectrometer (MASCS) instrument during orbital observations of the NASA MESSENGER mission between 2011 and 2015.<br> MASCS is a three sensor point spectrometer with a spectral coverage from 200 nm to 1450 nm.<br> Single spectra are resamples in to steps to a format useful for our ML application : a datacube with ~400 spectral channel covering the whole surface of Mercury.<br> The final dataset has dimension [N&times;M] where N is the number of grid cells (360 &times; 180 = 64, 800) and M is the number of spectral features (396).<br> Due to the incomplete coverage and data filtering, some grid cells are empty.<br> After removing these empty cells, the size of the dataset is [55399 &times; 396].</p> <p>0. Pre-filtering<br> We used the most recent dataset that had large-scale photometric corrections and thus was almost free from observation geometry effects.<br> However, extreme geometry are still present and are typically associated with high noise and some residual instrumental effects.<br> Based on our empirical tests, we filtered out observations with an emission/incidence angle &ge;80∘.<br> We also calculated the median value per wavelength and per cell grid when constructing the global hyperspectral data cube and filtered out observations falling under the 2nd percentile and above 99.9th percentile to clean some residual geometry effects.<br> With this approach we create an effective noise filter while retaining enough observations to be able to analyse the entirety of the surface of the planet.</p> <p>1. Spectral resmpling<br> Unprocessed MASCS spectra could have 512 or 256 channes, depending on binning.<br> We resampled the data in the spectral dimension to a common wavelength range from 260 nm to 1052 nm with a&nbsp; 4 nm resolution (2 nm spectral sampling), resulting in 396 spectral channels.<br> This approach slightly oversamples the original 4.77 nm spectral resolution and removes some points from the original 200-1050 nm range.<br> The resulting data matrix is expressed in tabular form, with each row representing a single grid cell or pixel on the surface.<br> The elements of each row are the spectral reflectance values from the VIS instrument at 396 (resampled) wavelengths.</p> <p>2. Spatial resmpling<br> The whole dataset of &sim; 5 million spectra is resampled to a planet-wide rectangular grid of 1&times;1deg in the latitudinal band between &plusmn; 80.<br> The cell longitudinal size varies between &sim; 40 km at the equator to a minimum of &sim; 10 km at &plusmn;80∘.<br> Thus, the area spanned by each grid cell depends on the latitude. However, the same is true for the acquisition process, where higher spatial resolution is reached near the equator and lower resolution at the poles.</p>

opencc-by-4.0Dec 2022View details →
zenodo52/100

Simulated galaxy cluster data at z=0 demonstrating the entropy core problem with the SWIFT-EAGLE galaxy formation model

<p>Cluster simulated with the SWIFT hydrodynamic code with the Ref SWIFT-EAGLE model. This dataset contains the redshift 0 snapshot and the VELOCIraptor halo catalogue.</p> <p>Paper reference:&nbsp;https://arxiv.org/abs/2210.09978</p>

opencc-by-4.0Oct 2023View details →
zenodo48/100

Silva SSU taxonomic training data formatted for DADA2 (Silva version 138)

<p>These DADA2-formatted training fasta files were derived from the Silva Project&#39;s version 138 release. See https://www.arb-silva.de/documentation/release-138/ for database and citation information. The Silva 138 database is licensed under Creative Commons Attribution 4.0 (CC-BY 4.0); see file &quot;SILVA_LICENSE.txt&quot;. The fasta files were generated and checked for consistency with version 132 using the R code in the R-markdown document &quot;silva-v138.Rmd&quot;.</p> <p>Version 2 removes the dependence on preprocessed files from mothur, which results in a greater number of bacterial and archeal sequences. It also includes&nbsp;a new version of the assignTaxonomy training set&nbsp;that goes through the species level for use with longer amplicons obtained from long-read amplicon sequencing.</p> <p>If you use these files, please cite one or both of the Silva references below (or at the above link) and the DADA2 paper (reference below). I also recommend&nbsp;citing or linking to the Zenodo record for this specific version in your Methods or published source code to record&nbsp;the specific taxonomic database files used in your analysis.</p> <p><strong>NOTE:</strong><strong> </strong>These Version 2 files are intended for use in classifying prokaryotic 16S sequencing data and are not appropriate for classifying eukaryotic ASVs. The new method implemented within DADA2 for constructing these files only includes 100 eukaryotic sequences for use as an outgroup.</p> <p><strong>NOTE:</strong>&nbsp;These Version 2 files have a known problem in 10/883 families and 114/3838 genera. See https://github.com/mikemc/dada2-reference-databases/blob/main/silva-138/v2/bad-taxa.csv for a list of affected taxa and https://github.com/benjjneb/dada2/issues/1293 for more information.</p>

opencc-by-4.0Mar 2020View details →
zenodo48/100

IPBES Data Management Tutorials - Session 3.4: Data management report details: File formats

<p>The&nbsp;<em>IPBES data management tutorials</em>&nbsp;are short videos to help experts implement the IPBES data management Policy. They cover topics ranging from data management policy, reports, active research data, tools, and examples.</p> <p>The&nbsp;<em>IPBES data management reports&nbsp;</em>chapter&nbsp;provides an overview and discussion of specific elements of IPBES data management reports.</p> <p>This session,&nbsp;<em>Data management report details: File formats</em>, focuses on specific recommended file formats for text, tabular data, images, sound, and geospatial data.&nbsp;</p>

opencc-by-4.0Nov 2020View details →
zenodo48/100

Formatting hemiclone Drosophila melanogaster genotype data for GWAS

<p>Data and code for generating filtering and formatting of Drosophila melanogaster genotype data, from the Sussex LHM hemiclone population sample.</p>

opencc-by-4.0Jun 2017View details →
zenodo48/100

Dataset to "Persistent Identifiers for File Formats: enabling preservation and re-use of research data"

<p>This fileset includes a &quot;preprint&quot; and the main dataset <em>fileformatRecognizer</em> (as .xlsx and .csv) to the paper &quot;Persistent identifiers for file formats: enabling preservation and re-use of research data&quot; submitted to iPRES 2019, but subsequently rejected after peer review.&nbsp; For the sake of transparency, permission to make available here the anonymous reviews motivating the rejection (<em>ReviewsPIDs4fileFormats.odt</em>) was asked, but was left without response. Some images (screendumps) and text result files from file identification tools tested are included. Further, a simple xquery command file (BaseX) for <em>fetch:content-type</em>()<em>, </em>used for getting MIME-types for files, is also provided.</p>

opencc-by-4.0Apr 2019View details →
zenodo48/100

Data for the 'Evaluation of global simulations of aerosol particle and cloud condensation nuclei number, with implications for cloud droplet formation'

<p>All numerical data used in the manuscript <strong>&ldquo;Evaluation of global simulations of aerosol particle number and cloud condensation nuclei, and implications for cloud droplet formation&rdquo; </strong>by G. S. Fanourgakis et al. ACP (2019) are categorized and provided in a number of files. All files are in the hdf format. A readme file is also provided.</p> <p>These data files have been created by G. S. Fanourgakis (fanourg@uoc.gr)</p> <p>Details on the data are provided in Fanourgakis et al. Atmos. Chem. Phys. 2019 https://doi.org/10.5194/acp-2018-1340 &nbsp;(e-mail to <a href="mailto:mariak@uoc.gr">mariak@uoc.gr</a> ; <a href="mailto:athanasios.nenes@epfl.ch">athanasios.nenes@epfl.ch</a> )</p> <p>For an in-depth understanding of the description below, a study of the above mentioned manuscript is required.</p> <p>(A) Station model results</p> <p>The station results can be found in files with filenames of the form:</p> <p>station $MODEL.nc</p> <p>The &ldquo;$MODEL&rdquo; (as well as all names starting with &ldquo;$&rdquo;) indicates a variable, and more specifically one of the models participated in the present study. The values of this variable are tabulated in Table 1 in the readme file.</p> <p>In each file a number of computational results are provided by the specified model for all nine (9) stations that provided observational data. The name of the variable is formed as:</p> <p>st $STATION $FIELDhour st $STATION $FIELD month</p> <p>where all possible values of the variables $STATION and $FIELD are tabulated in Tables 2 and 3 in the readme file, respectively. The extension _hour denotes that hourly values for the field are provided, while the extension _month the monthly average of this quantity. For example, the variable</p> <p>st Finokalia CCN02 hour</p> <p>found in the file station_TM4-ECPL.nc, contains the hourly values of the CCN<sub>0<em>.</em>2 </sub>at the Finokalia station as computed by the TM4-ECPL model. In a similar way, in the file station_EMAC.nc, the variable below gives the monthly values of dust at Vavihill as computed with the EMAC model.</p> <p>st Vavihill DU month</p> <p>Notice also that in all files hourly and monthly data are provided for the time period from 1-1-2011 up to 31-12-2015 (60 months and 43,824 hours)</p> <p>(B) Station observational results</p> <p>There is one file that contains all observational data from Schmale et al., SCIENTIFIC DATA | 4:170003 | DOI: 10.1038/sdata.2017.3, 2017 (<a href="mailto:julia.schmale@psi.ch">julia.schmale@psi.ch</a>) and the data that were computed based on the observations (i.e. number of cloud droplets) (contact person: athanasios.nenes@epfl.ch). The file is</p> <p>station observations.nc</p> <p>while the following fields are contained in there:</p> <p>st $STATION $FIELDhour</p> <p>st $STATION $FIELD month</p> <p>The values of variables are given in the Tables 2 and 3 in the readme file. The time period covered is from 1-1-2011 up to 31-12-2015. Notice that due to the lack of observations a lot of data are missing. For missing observational data the value -9999.999 is given. Contact person for the observational data is Julia Schmale (julia.schmale@psi.ch).</p> <p>(C) Station Multi-model Median</p> <p>Monthly averages of the models can be found in the file</p> <p>station MMM.nc</p> <p>The following fields can be found in the file</p> <p>st $STATION $FIELD month median</p> <p>st $STATION$FIELD month quart25</p> <p>st $STATION$FIELD month quart75</p> <p>where the values of the variables $STATION and $FIELD can be found in Tables 2 and 3, respectively. The extension median corresponds to the multi-model median, while the quart25 and quart75 to the 25 % and 75 % quartiles, respectively.</p> <p>(D) Global model results</p> <p>In the following single file can be found for each of the models the surface distribution of various fields.</p> <p>results global models year2011.nc</p> <p>They correspond to the annual mean of the year 2011. The resolution of the grid is 1<sup>◦ </sup>&times; 1<sup>◦</sup>. The file contains the following variables:</p> <p>$FIELD $MODEL</p> <p>The $FIELD and $MODEL can be found in Tables 3 and 1, respectively.</p> <p>(E) Global average results</p> <p>In the file</p> <p>surface_ global_average_year2011.nc</p> <p>can be found in 5<sup>◦</sup>&times;5<sup>◦ </sup>resolution, the Multi-model median of surface distribution of the various fields denoted in Table 3 and their corresponding diversity. The names of the variables are formed as:</p> <p>med $FIELD</p> <p>div $FIELD</p> <p>where, &lsquo;med&rsquo; stands for median and &lsquo;div&rsquo; for diversity calculated as standard deviation divided by the mean of the model results.</p> <p>Tables and details on the fields provided are given in the readme file.</p>

opencc-by-4.0Jul 2019View details →
zenodo48/100

SAMI3 data in netCDF format (2019-Mar-28)

<p>SAMI3 (Sami3 is Also a Model of the Ionosphere) is a seamless, three-dimensional, physics-based model of the ionosphere (Huba et al, 2008). It is based on SAMI2, a two-dimensional model of the ionosphere (Huba et al., 2000). <br><br>SAMI3 models the plasma and chemical evolution of seven ion species (H⁺, He⁺, N⁺, O⁺, N⁺₂, NO⁺ and O⁺₂). The temperature equation is solved for three ion species (H⁺, He⁺ and O⁺) and for the electrons. Ion inertia is included in the ion momentum equation for motion along the geomagnetic field. This is important in modeling the topside ionosphere and plasmasphere where the plasma becomes collisionless. <br><br>SAMI3 includes 21 chemical reactions and radiative recombination, and uses a nonorthogonal, nonuniform, fixed grid for the magnetic latitude range +/- 89 degrees.. <br><br><b>Drivers</b><br>Neutral composition, temperature, and winds: NRLMSISE00 (Picone et al., 2002) and HWM14 (Drob et al., 2015). <br>Solar radiation: Flare Irradiance Spectral Model version 2 (FISM v2)<br>Magnetic field: Richmond apex model [Richmond, 1995]. <br>Neutral wind dynamo electric field: Determined from the solution of a 2D potential equation [Huba et at., 2008]. <br>For the SAMI3/Weimer configuration: High latitude electric field: calculated from the empirical Weimer model for the potential. <br>For the SAMI3/AMPERE configuration: High latitude electric field: calculated using the Magnetosphere-Ionosphere Coupling solver (MIX) developed by Merkin and Lyon (2010). The inputs to MIX are SAMI3's internal conductances, plus field-aligned current observations from Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE), derived from the 66+ satellite Iridium NEXT constellation's engineering magnetometer data. This potential calculation is described in Chartier et al (2022). <br><br>For ease of use, SAMI3 output is remapped to a regular grid using the Earth System Modeling Framework by Hill et al (2004)</p>

opencc-zeroApr 2023View details →
zenodo48/100

SAMI3 data in netCDF format (2019-Mar-29)

<p>SAMI3 (Sami3 is Also a Model of the Ionosphere) is a seamless, three-dimensional, physics-based model of the ionosphere (Huba et al, 2008). It is based on SAMI2, a two-dimensional model of the ionosphere (Huba et al., 2000). <br><br>SAMI3 models the plasma and chemical evolution of seven ion species (H⁺, He⁺, N⁺, O⁺, N⁺₂, NO⁺ and O⁺₂). The temperature equation is solved for three ion species (H⁺, He⁺ and O⁺) and for the electrons. Ion inertia is included in the ion momentum equation for motion along the geomagnetic field. This is important in modeling the topside ionosphere and plasmasphere where the plasma becomes collisionless. <br><br>SAMI3 includes 21 chemical reactions and radiative recombination, and uses a nonorthogonal, nonuniform, fixed grid for the magnetic latitude range +/- 89 degrees.. <br><br><b>Drivers</b><br>Neutral composition, temperature, and winds: NRLMSISE00 (Picone et al., 2002) and HWM14 (Drob et al., 2015). <br>Solar radiation: Flare Irradiance Spectral Model version 2 (FISM v2)<br>Magnetic field: Richmond apex model [Richmond, 1995]. <br>Neutral wind dynamo electric field: Determined from the solution of a 2D potential equation [Huba et at., 2008]. <br>For the SAMI3/Weimer configuration: High latitude electric field: calculated from the empirical Weimer model for the potential. <br>For the SAMI3/AMPERE configuration: High latitude electric field: calculated using the Magnetosphere-Ionosphere Coupling solver (MIX) developed by Merkin and Lyon (2010). The inputs to MIX are SAMI3's internal conductances, plus field-aligned current observations from Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE), derived from the 66+ satellite Iridium NEXT constellation's engineering magnetometer data. This potential calculation is described in Chartier et al (2022). <br><br>For ease of use, SAMI3 output is remapped to a regular grid using the Earth System Modeling Framework by Hill et al (2004)</p>

opencc-zeroApr 2023View details →
zenodo48/100

SAMI3 data in netCDF format (2019-Mar-25)

<p>SAMI3 (Sami3 is Also a Model of the Ionosphere) is a seamless, three-dimensional, physics-based model of the ionosphere (Huba et al, 2008). It is based on SAMI2, a two-dimensional model of the ionosphere (Huba et al., 2000). <br><br>SAMI3 models the plasma and chemical evolution of seven ion species (H⁺, He⁺, N⁺, O⁺, N⁺₂, NO⁺ and O⁺₂). The temperature equation is solved for three ion species (H⁺, He⁺ and O⁺) and for the electrons. Ion inertia is included in the ion momentum equation for motion along the geomagnetic field. This is important in modeling the topside ionosphere and plasmasphere where the plasma becomes collisionless. <br><br>SAMI3 includes 21 chemical reactions and radiative recombination, and uses a nonorthogonal, nonuniform, fixed grid for the magnetic latitude range +/- 89 degrees.. <br><br><b>Drivers</b><br>Neutral composition, temperature, and winds: NRLMSISE00 (Picone et al., 2002) and HWM14 (Drob et al., 2015). <br>Solar radiation: Flare Irradiance Spectral Model version 2 (FISM v2)<br>Magnetic field: Richmond apex model [Richmond, 1995]. <br>Neutral wind dynamo electric field: Determined from the solution of a 2D potential equation [Huba et at., 2008]. <br>For the SAMI3/Weimer configuration: High latitude electric field: calculated from the empirical Weimer model for the potential. <br>For the SAMI3/AMPERE configuration: High latitude electric field: calculated using the Magnetosphere-Ionosphere Coupling solver (MIX) developed by Merkin and Lyon (2010). The inputs to MIX are SAMI3's internal conductances, plus field-aligned current observations from Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE), derived from the 66+ satellite Iridium NEXT constellation's engineering magnetometer data. This potential calculation is described in Chartier et al (2022). <br><br>For ease of use, SAMI3 output is remapped to a regular grid using the Earth System Modeling Framework by Hill et al (2004)</p>

opencc-zeroApr 2023View details →
zenodo48/100

SAMI3 data in netCDF format (2019-Mar-23)

<p>SAMI3 (Sami3 is Also a Model of the Ionosphere) is a seamless, three-dimensional, physics-based model of the ionosphere (Huba et al, 2008). It is based on SAMI2, a two-dimensional model of the ionosphere (Huba et al., 2000). <br><br>SAMI3 models the plasma and chemical evolution of seven ion species (H⁺, He⁺, N⁺, O⁺, N⁺₂, NO⁺ and O⁺₂). The temperature equation is solved for three ion species (H⁺, He⁺ and O⁺) and for the electrons. Ion inertia is included in the ion momentum equation for motion along the geomagnetic field. This is important in modeling the topside ionosphere and plasmasphere where the plasma becomes collisionless. <br><br>SAMI3 includes 21 chemical reactions and radiative recombination, and uses a nonorthogonal, nonuniform, fixed grid for the magnetic latitude range +/- 89 degrees.. <br><br><b>Drivers</b><br>Neutral composition, temperature, and winds: NRLMSISE00 (Picone et al., 2002) and HWM14 (Drob et al., 2015). <br>Solar radiation: Flare Irradiance Spectral Model version 2 (FISM v2)<br>Magnetic field: Richmond apex model [Richmond, 1995]. <br>Neutral wind dynamo electric field: Determined from the solution of a 2D potential equation [Huba et at., 2008]. <br>For the SAMI3/Weimer configuration: High latitude electric field: calculated from the empirical Weimer model for the potential. <br>For the SAMI3/AMPERE configuration: High latitude electric field: calculated using the Magnetosphere-Ionosphere Coupling solver (MIX) developed by Merkin and Lyon (2010). The inputs to MIX are SAMI3's internal conductances, plus field-aligned current observations from Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE), derived from the 66+ satellite Iridium NEXT constellation's engineering magnetometer data. This potential calculation is described in Chartier et al (2022). <br><br>For ease of use, SAMI3 output is remapped to a regular grid using the Earth System Modeling Framework by Hill et al (2004)</p>

opencc-zeroApr 2023View details →
zenodo48/100

SAMI3 data in netCDF format (2019-Mar-24)

<p>SAMI3 (Sami3 is Also a Model of the Ionosphere) is a seamless, three-dimensional, physics-based model of the ionosphere (Huba et al, 2008). It is based on SAMI2, a two-dimensional model of the ionosphere (Huba et al., 2000). <br><br>SAMI3 models the plasma and chemical evolution of seven ion species (H⁺, He⁺, N⁺, O⁺, N⁺₂, NO⁺ and O⁺₂). The temperature equation is solved for three ion species (H⁺, He⁺ and O⁺) and for the electrons. Ion inertia is included in the ion momentum equation for motion along the geomagnetic field. This is important in modeling the topside ionosphere and plasmasphere where the plasma becomes collisionless. <br><br>SAMI3 includes 21 chemical reactions and radiative recombination, and uses a nonorthogonal, nonuniform, fixed grid for the magnetic latitude range +/- 89 degrees.. <br><br><b>Drivers</b><br>Neutral composition, temperature, and winds: NRLMSISE00 (Picone et al., 2002) and HWM14 (Drob et al., 2015). <br>Solar radiation: Flare Irradiance Spectral Model version 2 (FISM v2)<br>Magnetic field: Richmond apex model [Richmond, 1995]. <br>Neutral wind dynamo electric field: Determined from the solution of a 2D potential equation [Huba et at., 2008]. <br>For the SAMI3/Weimer configuration: High latitude electric field: calculated from the empirical Weimer model for the potential. <br>For the SAMI3/AMPERE configuration: High latitude electric field: calculated using the Magnetosphere-Ionosphere Coupling solver (MIX) developed by Merkin and Lyon (2010). The inputs to MIX are SAMI3's internal conductances, plus field-aligned current observations from Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE), derived from the 66+ satellite Iridium NEXT constellation's engineering magnetometer data. This potential calculation is described in Chartier et al (2022). <br><br>For ease of use, SAMI3 output is remapped to a regular grid using the Earth System Modeling Framework by Hill et al (2004)</p>

opencc-zeroApr 2023View details →
zenodo48/100

SAMI3 data in netCDF format (2019-Mar-22)

<p>SAMI3 (Sami3 is Also a Model of the Ionosphere) is a seamless, three-dimensional, physics-based model of the ionosphere (Huba et al, 2008). It is based on SAMI2, a two-dimensional model of the ionosphere (Huba et al., 2000). <br><br>SAMI3 models the plasma and chemical evolution of seven ion species (H⁺, He⁺, N⁺, O⁺, N⁺₂, NO⁺ and O⁺₂). The temperature equation is solved for three ion species (H⁺, He⁺ and O⁺) and for the electrons. Ion inertia is included in the ion momentum equation for motion along the geomagnetic field. This is important in modeling the topside ionosphere and plasmasphere where the plasma becomes collisionless. <br><br>SAMI3 includes 21 chemical reactions and radiative recombination, and uses a nonorthogonal, nonuniform, fixed grid for the magnetic latitude range +/- 89 degrees.. <br><br><b>Drivers</b><br>Neutral composition, temperature, and winds: NRLMSISE00 (Picone et al., 2002) and HWM14 (Drob et al., 2015). <br>Solar radiation: Flare Irradiance Spectral Model version 2 (FISM v2)<br>Magnetic field: Richmond apex model [Richmond, 1995]. <br>Neutral wind dynamo electric field: Determined from the solution of a 2D potential equation [Huba et at., 2008]. <br>For the SAMI3/Weimer configuration: High latitude electric field: calculated from the empirical Weimer model for the potential. <br>For the SAMI3/AMPERE configuration: High latitude electric field: calculated using the Magnetosphere-Ionosphere Coupling solver (MIX) developed by Merkin and Lyon (2010). The inputs to MIX are SAMI3's internal conductances, plus field-aligned current observations from Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE), derived from the 66+ satellite Iridium NEXT constellation's engineering magnetometer data. This potential calculation is described in Chartier et al (2022). <br><br>For ease of use, SAMI3 output is remapped to a regular grid using the Earth System Modeling Framework by Hill et al (2004)</p>

opencc-zeroApr 2023View details →
zenodo48/100

SAMI3 data in netCDF format (2019-Mar-27)

<p>SAMI3 (Sami3 is Also a Model of the Ionosphere) is a seamless, three-dimensional, physics-based model of the ionosphere (Huba et al, 2008). It is based on SAMI2, a two-dimensional model of the ionosphere (Huba et al., 2000). <br><br>SAMI3 models the plasma and chemical evolution of seven ion species (H⁺, He⁺, N⁺, O⁺, N⁺₂, NO⁺ and O⁺₂). The temperature equation is solved for three ion species (H⁺, He⁺ and O⁺) and for the electrons. Ion inertia is included in the ion momentum equation for motion along the geomagnetic field. This is important in modeling the topside ionosphere and plasmasphere where the plasma becomes collisionless. <br><br>SAMI3 includes 21 chemical reactions and radiative recombination, and uses a nonorthogonal, nonuniform, fixed grid for the magnetic latitude range +/- 89 degrees.. <br><br><b>Drivers</b><br>Neutral composition, temperature, and winds: NRLMSISE00 (Picone et al., 2002) and HWM14 (Drob et al., 2015). <br>Solar radiation: Flare Irradiance Spectral Model version 2 (FISM v2)<br>Magnetic field: Richmond apex model [Richmond, 1995]. <br>Neutral wind dynamo electric field: Determined from the solution of a 2D potential equation [Huba et at., 2008]. <br>For the SAMI3/Weimer configuration: High latitude electric field: calculated from the empirical Weimer model for the potential. <br>For the SAMI3/AMPERE configuration: High latitude electric field: calculated using the Magnetosphere-Ionosphere Coupling solver (MIX) developed by Merkin and Lyon (2010). The inputs to MIX are SAMI3's internal conductances, plus field-aligned current observations from Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE), derived from the 66+ satellite Iridium NEXT constellation's engineering magnetometer data. This potential calculation is described in Chartier et al (2022). <br><br>For ease of use, SAMI3 output is remapped to a regular grid using the Earth System Modeling Framework by Hill et al (2004)</p>

opencc-zeroApr 2023View details →
zenodo48/100

SAMI3 data in netCDF format (2019-Mar-20)

<p>SAMI3 (Sami3 is Also a Model of the Ionosphere) is a seamless, three-dimensional, physics-based model of the ionosphere (Huba et al, 2008). It is based on SAMI2, a two-dimensional model of the ionosphere (Huba et al., 2000). <br><br>SAMI3 models the plasma and chemical evolution of seven ion species (H⁺, He⁺, N⁺, O⁺, N⁺₂, NO⁺ and O⁺₂). The temperature equation is solved for three ion species (H⁺, He⁺ and O⁺) and for the electrons. Ion inertia is included in the ion momentum equation for motion along the geomagnetic field. This is important in modeling the topside ionosphere and plasmasphere where the plasma becomes collisionless. <br><br>SAMI3 includes 21 chemical reactions and radiative recombination, and uses a nonorthogonal, nonuniform, fixed grid for the magnetic latitude range +/- 89 degrees.. <br><br><b>Drivers</b><br>Neutral composition, temperature, and winds: NRLMSISE00 (Picone et al., 2002) and HWM14 (Drob et al., 2015). <br>Solar radiation: Flare Irradiance Spectral Model version 2 (FISM v2)<br>Magnetic field: Richmond apex model [Richmond, 1995]. <br>Neutral wind dynamo electric field: Determined from the solution of a 2D potential equation [Huba et at., 2008]. <br>For the SAMI3/Weimer configuration: High latitude electric field: calculated from the empirical Weimer model for the potential. <br>For the SAMI3/AMPERE configuration: High latitude electric field: calculated using the Magnetosphere-Ionosphere Coupling solver (MIX) developed by Merkin and Lyon (2010). The inputs to MIX are SAMI3's internal conductances, plus field-aligned current observations from Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE), derived from the 66+ satellite Iridium NEXT constellation's engineering magnetometer data. This potential calculation is described in Chartier et al (2022). <br><br>For ease of use, SAMI3 output is remapped to a regular grid using the Earth System Modeling Framework by Hill et al (2004)</p>

opencc-zeroApr 2023View details →
zenodo48/100

SAMI3 data in netCDF format (2019-Mar-19)

<p>SAMI3 (Sami3 is Also a Model of the Ionosphere) is a seamless, three-dimensional, physics-based model of the ionosphere (Huba et al, 2008). It is based on SAMI2, a two-dimensional model of the ionosphere (Huba et al., 2000). <br><br>SAMI3 models the plasma and chemical evolution of seven ion species (H⁺, He⁺, N⁺, O⁺, N⁺₂, NO⁺ and O⁺₂). The temperature equation is solved for three ion species (H⁺, He⁺ and O⁺) and for the electrons. Ion inertia is included in the ion momentum equation for motion along the geomagnetic field. This is important in modeling the topside ionosphere and plasmasphere where the plasma becomes collisionless. <br><br>SAMI3 includes 21 chemical reactions and radiative recombination, and uses a nonorthogonal, nonuniform, fixed grid for the magnetic latitude range +/- 89 degrees.. <br><br><b>Drivers</b><br>Neutral composition, temperature, and winds: NRLMSISE00 (Picone et al., 2002) and HWM14 (Drob et al., 2015). <br>Solar radiation: Flare Irradiance Spectral Model version 2 (FISM v2)<br>Magnetic field: Richmond apex model [Richmond, 1995]. <br>Neutral wind dynamo electric field: Determined from the solution of a 2D potential equation [Huba et at., 2008]. <br>For the SAMI3/Weimer configuration: High latitude electric field: calculated from the empirical Weimer model for the potential. <br>For the SAMI3/AMPERE configuration: High latitude electric field: calculated using the Magnetosphere-Ionosphere Coupling solver (MIX) developed by Merkin and Lyon (2010). The inputs to MIX are SAMI3's internal conductances, plus field-aligned current observations from Active Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE), derived from the 66+ satellite Iridium NEXT constellation's engineering magnetometer data. This potential calculation is described in Chartier et al (2022). <br><br>For ease of use, SAMI3 output is remapped to a regular grid using the Earth System Modeling Framework by Hill et al (2004)</p>

opencc-zeroApr 2023View details →

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

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behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record

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