cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21978/p85d1v
title: ACE Linearly Interpolated 60 s Resolution SWEPAM data in GSE Coordinates
title: ACE SWEPAM data

description: ACE linearly interpolated to have the measurements on the minute at 60 s resolution SWEPAM data in GSE coordinates. This data set consists of processed solar wind data that has been linearly interpolated to 1 min resolution at the position of the spacecraft using the interp1.m function in MATLAB. This data set was originally constructed by Dr. J.M. Weygand for Prof. R.L. McPherron, who was the principle investigator of two National Science Foundation studies: GEM Grant ATM 02-1798 and a Space Weather Grant ATM 02-08501. These data were primarily used in superposed epoch studies and cross correlation studies on solar wind.
DOI: 10.21978/p8933r
title: ACE Weimer Propagated 60 s Resolution Tri-axial Fluxgate Magnetometer in GSM Coordinates
title: ACE MAG data

description: ACE Weimer propagated solar wind data and linearly interpolated to have the measurements on the minute at 60 s resolution tri-axial fluxgate magnetometer data in GSM coordinates. This data set consists of propagated solar wind data that has first been propagated to a position just outside of the nominal bow shock (about 17, 0, 0 Re) and then linearly interpolated to 1 min resolution using the interp1.m function in MATLAB. The input data for this data set is a 1 min resolution processed solar wind data constructed by Dr. J.M. Weygand. The method of propagation is similar to the minimum variance technique and is outlined in Dan Weimer et al. [2003; 2004]. The basic method is to find the minimum variance direction of the magnetic field in the plane orthogonal to the mean magnetic field direction. This minimum variance direction is then dotted with the difference between final position vector minus the original position vector and the quantity is divided by the minimum variance dotted with the solar wind velocity vector, which gives the propagation time. This method does not work well for shocks and minimum variance directions with tilts greater than 70 degrees of the sun-earth line. This data set was originally constructed by Dr. J.M. Weygand for Prof. R.L. McPherron, who was the principle investigator of two National Science Foundation studies: GEM Grant ATM 02-1798 and a Space Weather Grant ATM 02-08501. These data were primarily used in superposed epoch studies References: Weimer, D. R. (2004), Correction to ‘‘Predicting interplanetary magnetic field (IMF) propagation delay times using the minimum variance technique,’’ J. Geophys. Res., 109, A12104, doi:10.1029/2004JA010691. Weimer, D.R., D.M. Ober, N.C. Maynard, M.R. Collier, D.J. McComas, N.F. Ness, C. W. Smith, and J. Watermann (2003), Predicting interplanetary magnetic field (IMF) propagation delay times using the minimum variance technique, J. Geophys. Res., 108, 1026, doi:10.1029/2002JA009405.
DOI: 10.21978/p81k9c
title: ACE Linearly Interpolated 60 s Resolution SWEPAM data in GSM Coordinates
title: ACE SWEPAM data

description: ACE linearly interpolated to have the measurements on the minute at 60 s resolution SWEPAM data in GSM coordinates. This data set consists of processed solar wind data that has been linearly interpolated to 1 min resolution at the position of the spacecraft using the interp1.m function in MATLAB. This data set was originally constructed by Dr. J.M. Weygand for Prof. R.L. McPherron, who was the principle investigator of two National Science Foundation studies: GEM Grant ATM 02-1798 and a Space Weather Grant ATM 02-08501. These data were primarily used in superposed epoch studies and cross correlation studies on solar wind.
DOI: 10.21978/p8ww5q
title: ACE SWEPAM Solar Wind Weimer Propagated 60 s Resolution Data in GSE Coordinates
title: ACE SWEPAM data

description: ACE Weimer propagated solar wind data and linearly interpolated to have the measurements on the minute at 60 s resolution SWEPAM data in GSE coordinates. This data set consists of propagated solar wind data that has first been propagated to a position just outside of the nominal bow shock (about 17, 0, 0 Re) and then linearly interpolated to 1 min resolution using the interp1.m function in MATLAB. The input data for this data set is a 1 min resolution processed solar wind data constructed by Dr. J.M. Weygand. The method of propagation is similar to the minimum variance technique and is outlined in Dan Weimer et al. [2003; 2004]. The basic method is to find the minimum variance direction of the magnetic field in the plane orthogonal to the mean magnetic field direction. This minimum variance direction is then dotted with the difference between final position vector minus the original position vector and the quantity is divided by the minimum variance dotted with the solar wind velocity vector, which gives the propagation time. This method does not work well for shocks and minimum variance directions with tilts greater than 70 degrees of the sun-earth line. This data set was originally constructed by Dr. J.M. Weygand for Prof. R.L. McPherron, who was the principle investigator of two National Science Foundation studies: GEM Grant ATM 02-1798 and a Space Weather Grant ATM 02-08501. These data were primarily used in superposed epoch studies References: Weimer, D. R. (2004), Correction to Predicting interplanetary magnetic field (IMF) propagation delay times using the minimum variance technique, J. Geophys. Res., 109, A12104, doi:10.1029/2004JA010691. Weimer, D.R., D.M. Ober, N.C. Maynard, M.R. Collier, D.J. McComas, N.F. Ness, C. W. Smith, and J. Watermann (2003), Predicting interplanetary magnetic field (IMF) propagation delay times using the minimum variance technique, J. Geophys. Res., 108, 1026, doi:10.1029/2002JA009405.
DOI: 10.21978/p8hp70
title: ACE Solar Wind Weimer Propagation Details at 1 min Resolution

description: ACE Weimer propagated solar wind data and linearly interpolated time delay, cosine angle, and goodness information of propagated data at 1 min Resolution. This data set consists of propagated solar wind data that has first been propagated to a position just outside of the nominal bow shock (about 17, 0, 0 Re) and then linearly interpolated to 1 min resolution using the interp1.m function in MATLAB. The input data for this data set is a 1 min resolution processed solar wind data constructed by Dr. J.M. Weygand. The method of propagation is similar to the minimum variance technique and is outlined in Dan Weimer et al. [2003; 2004]. The basic method is to find the minimum variance direction of the magnetic field in the plane orthogonal to the mean magnetic field direction. This minimum variance direction is then dotted with the difference between final position vector minus the original position vector and the quantity is divided by the minimum variance dotted with the solar wind velocity vector, which gives the propagation time. This method does not work well for shocks and minimum variance directions with tilts greater than 70 degrees of the sun-earth line. This data set was originally constructed by Dr. J.M. Weygand for Prof. R.L. McPherron, who was the principle investigator of two National Science Foundation studies: GEM Grant ATM 02-1798 and a Space Weather Grant ATM 02-08501. These data were primarily used in superposed epoch studies References: Weimer, D. R. (2004), Correction to ‘‘Predicting interplanetary magnetic field (IMF) propagation delay times using the minimum variance technique,’’ J. Geophys. Res., 109, A12104, doi:10.1029/2004JA010691. Weimer, D.R., D.M. Ober, N.C. Maynard, M.R. Collier, D.J. McComas, N.F. Ness, C. W. Smith, and J. Watermann (2003), Predicting interplanetary magnetic field (IMF) propagation delay times using the minimum variance technique, J. Geophys. Res., 108, 1026, doi:10.1029/2002JA009405.
DOI: 10.21978/p8704g
title: Geotail Linearly Interpolated 60 s Resolution Coordinates Comprehensive Plasma Instrumentation (CPI) data in GSE
title: CPI data

description: Geotail linearly interpolated to have the measurements on the minute at 60 s resolution CPI data in GSE coordinates. This data set consists of processed solar wind data that has been linearly interpolated to 1 min resolution at the position of the spacecraft using the interp1.m function in MATLAB. This data set was originally constructed by Dr. J.M. Weygand for Prof. R.L. McPherron, who was the principle investigator of two National Science Foundation studies: GEM Grant ATM 02-1798 and a Space Weather Grant ATM 02-08501. These data were primarily used in superposed epoch studies and cross correlation studies on solar wind.
DOI: 10.21978/p8392k
title: Geotail Linearly Interpolated 60 s Resolution Coordinates Comprehensive Plasma Instrumentation (CPI) data in GSM
title: CPI data

description: Geotail linearly interpolated to have the measurements on the minute at 60 s resolution CPI data in GSM coordinates. This data set consists of processed solar wind data that has been linearly interpolated to 1 min resolution at the position of the spacecraft using the interp1.m function in MATLAB. This data set was originally constructed by Dr. J.M. Weygand for Prof. R.L. McPherron, who was the principle investigator of two National Science Foundation studies: GEM Grant ATM 02-1798 and a Space Weather Grant ATM 02-08501. These data were primarily used in superposed epoch studies and cross correlation studies on solar wind.
DOI: 10.21978/p8zh0n
title: Geotail Comprehensive Plasma Instrumentation (CPI) data Weimer Propagated 60 s Resolution in GSE Coordinates
title: CPI data

description: Geotail Weimer propagated solar wind data and linearly interpolated to have the measurements on the minute at 60 s resolution CPI data in GSE coordinates. This data set consists of propagated solar wind data that has first been propagated to a position just outside of the nominal bow shock (about 17, 0, 0 Re) and then linearly interpolated to 1 min resolution using the interp1.m function in MATLAB. The input data for this data set is a 1 min resolution processed solar wind data constructed by Dr. J.M. Weygand. The method of propagation is similar to the minimum variance technique and is outlined in Dan Weimer et al. [2003; 2004]. The basic method is to find the minimum variance direction of the magnetic field in the plane orthogonal to the mean magnetic field direction. This minimum variance direction is then dotted with the difference between final position vector minus the original position vector and the quantity is divided by the minimum variance dotted with the solar wind velocity vector, which gives the propagation time. This method does not work well for shocks and minimum variance directions with tilts greater than 70 degrees of the sun-earth line. This data set was originally constructed by Dr. J.M. Weygand for Prof. R.L. McPherron, who was the principle investigator of two National Science Foundation studies: GEM Grant ATM 02-1798 and a Space Weather Grant ATM 02-08501. These data were primarily used in superposed epoch studies References: Weimer, D. R. (2004), Correction to ‘‘Predicting interplanetary magnetic field (IMF) propagation delay times using the minimum variance technique,’’ J. Geophys. Res., 109, A12104, doi:10.1029/2004JA010691. Weimer, D.R., D.M. Ober, N.C. Maynard, M.R. Collier, D.J. McComas, N.F. Ness, C. W. Smith, and J. Watermann (2003), Predicting interplanetary magnetic field (IMF) propagation delay times using the minimum variance technique, J. Geophys. Res., 108, 1026, doi:10.1029/2002JA009405.
DOI: 10.21978/p8q33g
title: Geotail Linearly Interpolated 60 s Resolution Low Energy Particle (LEP) experiment data in GSE Coordinates
title: Geotail LEP data

description: Geotail linearly interpolated to have the measurements on the minute at 60 s resolution LEP data in GSE coordinates. This data set consists of processed solar wind data that has been linearly interpolated to 1 min resolution at the position of the spacecraft using the interp1.m function in MATLAB. This data set was originally constructed by Dr. J.M. Weygand for Prof. R.L. McPherron, who was the principle investigator of two National Science Foundation studies: GEM Grant ATM 02-1798 and a Space Weather Grant ATM 02-08501. These data were primarily used in superposed epoch studies and cross correlation studies on solar wind.
DOI: 10.21978/p8ts6f
title: Geotail Comprehensive Plasma Instrumentation (CPI) data Weimer Propagated 60 s Resolution in GSM Coordinates
title: CPI data

description: Geotail Weimer propagated solar wind data and linearly interpolated to have the measurements on the minute at 60 s resolution CPI data in GSM coordinates. This data set consists of propagated solar wind data that has first been propagated to a position just outside of the nominal bow shock (about 17, 0, 0 Re) and then linearly interpolated to 1 min resolution using the interp1.m function in MATLAB. The input data for this data set is a 1 min resolution processed solar wind data constructed by Dr. J.M. Weygand. The method of propagation is similar to the minimum variance technique and is outlined in Dan Weimer et al. [2003; 2004]. The basic method is to find the minimum variance direction of the magnetic field in the plane orthogonal to the mean magnetic field direction. This minimum variance direction is then dotted with the difference between final position vector minus the original position vector and the quantity is divided by the minimum variance dotted with the solar wind velocity vector, which gives the propagation time. This method does not work well for shocks and minimum variance directions with tilts greater than 70 degrees of the sun-earth line. This data set was originally constructed by Dr. J.M. Weygand for Prof. R.L. McPherron, who was the principle investigator of two National Science Foundation studies: GEM Grant ATM 02-1798 and a Space Weather Grant ATM 02-08501. These data were primarily used in superposed epoch studies References: Weimer, D. R. (2004), Correction to ‘‘Predicting interplanetary magnetic field (IMF) propagation delay times using the minimum variance technique,’’ J. Geophys. Res., 109, A12104, doi:10.1029/2004JA010691. Weimer, D.R., D.M. Ober, N.C. Maynard, M.R. Collier, D.J. McComas, N.F. Ness, C. W. Smith, and J. Watermann (2003), Predicting interplanetary magnetic field (IMF) propagation delay times using the minimum variance technique, J. Geophys. Res., 108, 1026, doi:10.1029/2002JA009405.
DOI: 10.21978/p8k91j
title: Geotail Linearly Interpolated 60 s Resolution Low Energy Particle (LEP) experiment data in GSM Coordinates
title: Geotail LEP data

description: Geotail linearly interpolated to have the measurements on the minute at 60 s resolution LEP data in GSM coordinates. This data set consists of processed solar wind data that has been linearly interpolated to 1 min resolution at the position of the spacecraft using the interp1.m function in MATLAB. This data set was originally constructed by Dr. J.M. Weygand for Prof. R.L. McPherron, who was the principle investigator of two National Science Foundation studies: GEM Grant ATM 02-1798 and a Space Weather Grant ATM 02-08501. These data were primarily used in superposed epoch studies and cross correlation studies on solar wind.
DOI: 10.21978/p89s5d
title: Geotail Low Energy Particle (LEP) experiment data Weimer Propagated 60 s Resolution in GSM Coordinates
title: Geotail LEP data

description: Geotail LEP Weimer propagated solar wind data and linearly interpolated to have the measurements on the minute at 60 s resolution data in GSM coordinates. This data set consists of propagated solar wind data that has first been propagated to a position just outside of the nominal bow shock (about 17, 0, 0 Re) and then linearly interpolated to 1 min resolution using the interp1.m function in MATLAB. The input data for this data set is a 1 min resolution processed solar wind data constructed by Dr. J.M. Weygand. The method of propagation is similar to the minimum variance technique and is outlined in Dan Weimer et al. [2003; 2004]. The basic method is to find the minimum variance direction of the magnetic field in the plane orthogonal to the mean magnetic field direction. This minimum variance direction is then dotted with the difference between final position vector minus the original position vector and the quantity is divided by the minimum variance dotted with the solar wind velocity vector, which gives the propagation time. This method does not work well for shocks and minimum variance directions with tilts greater than 70 degrees of the sun-earth line. This data set was originally constructed by Dr. J.M. Weygand for Prof. R.L. McPherron, who was the principle investigator of two National Science Foundation studies: GEM Grant ATM 02-1798 and a Space Weather Grant ATM 02-08501. These data were primarily used in superposed epoch studies References: Weimer, D. R. (2004), Correction to ‘‘Predicting interplanetary magnetic field (IMF) propagation delay times using the minimum variance technique,’’ J. Geophys. Res., 109, A12104, doi:10.1029/2004JA010691. Weimer, D.R., D.M. Ober, N.C. Maynard, M.R. Collier, D.J. McComas, N.F. Ness, C. W. Smith, and J. Watermann (2003), Predicting interplanetary magnetic field (IMF) propagation delay times using the minimum variance technique, J. Geophys. Res., 108, 1026, doi:10.1029/2002JA009405.
DOI: 10.21978/p8fk8q
title: Geotail Low Energy Particle (LEP) experiment data Weimer Propagated 60 s Resolution in GSE Coordinates
title: Geotail LEP data

description: Geotail LEP Weimer propagated solar wind data and linearly interpolated to have the measurements on the minute at 60 s resolution data in GSE coordinates. This data set consists of propagated solar wind data that has first been propagated to a position just outside of the nominal bow shock (about 17, 0, 0 Re) and then linearly interpolated to 1 min resolution using the interp1.m function in MATLAB. The input data for this data set is a 1 min resolution processed solar wind data constructed by Dr. J.M. Weygand. The method of propagation is similar to the minimum variance technique and is outlined in Dan Weimer et al. [2003; 2004]. The basic method is to find the minimum variance direction of the magnetic field in the plane orthogonal to the mean magnetic field direction. This minimum variance direction is then dotted with the difference between final position vector minus the original position vector and the quantity is divided by the minimum variance dotted with the solar wind velocity vector, which gives the propagation time. This method does not work well for shocks and minimum variance directions with tilts greater than 70 degrees of the sun-earth line. This data set was originally constructed by Dr. J.M. Weygand for Prof. R.L. McPherron, who was the principle investigator of two National Science Foundation studies: GEM Grant ATM 02-1798 and a Space Weather Grant ATM 02-08501. These data were primarily used in superposed epoch studies References: Weimer, D. R. (2004), Correction to ‘‘Predicting interplanetary magnetic field (IMF) propagation delay times using the minimum variance technique,’’ J. Geophys. Res., 109, A12104, doi:10.1029/2004JA010691. Weimer, D.R., D.M. Ober, N.C. Maynard, M.R. Collier, D.J. McComas, N.F. Ness, C. W. Smith, and J. Watermann (2003), Predicting interplanetary magnetic field (IMF) propagation delay times using the minimum variance technique, J. Geophys. Res., 108, 1026, doi:10.1029/2002JA009405.
DOI: 10.22008/fk2/ohi23z/a4iqah
title: MB_SMB_D_BMB.csv

description: MB CSV. Git hash: 20af941
DOI: 10.15468/dl.z7aduf
title: Occurrence Download

description: A dataset containing 40 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Gari pusilla Bertin, 1880"
 ]
}

 The dataset includes 40 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0106412-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22008/fk2/ohi23z/nvlvxz
title: MB_region.nc

description: MB region. Git hash: 20af941
DOI: 10.15468/dl.yahngs
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Paralatreutes bicornis Kemp, 1925"
 ]
}

 The dataset includes 3 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0127937-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22008/fk2/ohi23z/2szc6o
title: MB_sector.nc

description: MB by sector. Git hash: 20af941
DOI: 10.15468/dl.w5sau3
title: Occurrence Download

description: A dataset containing 35 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "OccurrenceStatus is Present",
 "TaxonKey is Castor canadensis Kuhl, 1820",
 "Year 2018-2023"
 ]
}

 The dataset includes 35 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0237662-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22008/fk2/ohi23z/zqygcz
title: MB_SMB_D_BMB_ann.csv

description: MB annual CSV. Git hash: 20af941
DOI: 10.22008/fk2/ohi23z/zx2w3i
title: MB_SMB_D_BMB.csv

description: MB CSV. Git hash: 20af941
DOI: 10.15468/dl.k994b3
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Material sample, Specimen, Fossil, Living Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is one of (Diplotaxis parvula Burmeister, 1855, Schrenkiella parvula (Schrenk) D.A.German & Al-Shehbaz, Sisymbrium parvulum (Schrenk) Lipsky, Stenophragma parvulum (Schrenk) B.Fedtsch., Thellungiella parvula (Schrenk) Al-Shehbaz & O'Kane, Eutrema parvulum (Schrenk) Al-Shehbaz & S.I.Warwick)"
 ]
}

 The dataset includes 5 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0106385-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22008/fk2/ohi23z/kz4d9o
title: MB_region.nc

description: MB region. Git hash: 20af941
DOI: 10.15468/dl.scxz9t
title: Occurrence Download

description: A dataset containing 5531567 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((26.7542939189847 1.2186193716968,36.9991642472184 13.6345880476356,41.544901412726 10.038706409249,37.5419388341447 2.16847489881781,35.84576825 -7.80500813595271,36.2528491901947 -16.0144737632128,34.2174444892211 -16.5572483501391,27.5006089760084 -8.95840413317107,26.7542939189847 1.2186193716968))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 5531567 records from 1065 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0237658-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ruuzej
title: Occurrence Download

description: A dataset containing 46 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Paralbunea dayriti (Serène & Umali, 1965)"
 ]
}

 The dataset includes 46 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0127938-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22008/fk2/ohi23z/8d0oyk
title: MB_sector.nc

description: MB by sector. Git hash: 20af941
DOI: 10.15468/dl.7xf9jw
title: Occurrence Download

description: A dataset containing 34 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Gari rasilis (Melvill & Standen, 1899)"
 ]
}

 The dataset includes 34 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0106413-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.