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SuperMAG Web Service API

You can also download magnetometer data directly into your application using the SuperMAG Web Service API (IDL, Python, Matlab, and R clients are available). Gridded solutions and High Fidelity one second data are not yet available via Web Services.

Rules of the Road

SuperMAG is made possible by the generous contribution of data by numerous collaborators. To ensure their continued operation the user must follow the below rules-of-the-road. Data, plots or derived data products are provided under the limitations of "fair use" and cannot be redistributed. Contact the individual instrument PI and the SuperMAG PI for requests that are in conflict with these restrictions.

The user is requested to acknowledge individual collaborators and SuperMAG when original data, derived data, movies, or data products are used in publications and/or presentations.

When Using Data

In all cases:

  • Include acknowledgement as listed on the SuperMAG website.
  • Include references to a technical papers for stations used (see list below).
  • Include SuperMAG reference: Gjerloev, J. W. (2012), The SuperMAG data processing technique, J. Geophys. Res., 117, A09213, doi:10.1029/2012JA017683.

In cases that only a few stations play a key role and their data are central to the scientific conclusion of the paper:

  • Offer of co-authorship to the PI (or PIs) of those stations and reference the appropriate paper (see list below).
When Using Indices
  • Include the text: “We gratefully acknowledge the SuperMAG collaborators (https://supermag.jhuapl.edu/info/?page=acknowledgement)”
  • Include appropriate reference for indices used (see list below).
  • Include SuperMAG reference: Gjerloev, J. W. (2012), The SuperMAG data processing technique, J. Geophys. Res., 117, A09213, doi:10.1029/2012JA017683.
When Using Substorm Lists
  • If the substorm onset list is central to your study please offer co-authorship to the authors of the technique you use.
  • When using substorm lists please include acknowledgements found here.
  • Include appropriate reference (see list below)
  • For details please see https://supermag.jhuapl.edu/substorms.
When Using OMNI When Using Imaging When using INTERMAGNET Data

References

Collaborator EMMA

Lichtenberger J., M. Clilverd, B. Heilig, M. Vellante, J. Manninen, C. Rodger, A. Collier, A. Jørgensen, J. Reda, R. Holzworth, and R. Friedel (2013), The plasmasphere during a space weather event: first results from the PLASMON project, J. Space Weather Space Clim., 3, A23 (www.swsc-journal.org/articles/swsc/pdf/2013/01/swsc120062.pdf).

Collaborator IMAGE Chain

Tanskanen, E.I. (2009), A comprehensive high-throughput analysis of substorms observed by IMAGE magnetometer network: Years 1993-2003 examined, 114, A05204, doi:10.1029/2008JA013682.

Collaborator MACCS

Engebretson, M. J., W. J. Hughes, J. L. Alford, E. Zesta, L. J. Cahill, Jr., R. L. Arnoldy, and G. D. Reeves (1995), Magnetometer array for cusp and cleft studies observations of the spatial extent of broadband ULF magnetic pulsations at cusp/cleft latitudes , J. Geophys. Res., 100, 19371-19386, doi:10.1029/95JA00768.

Collaborator McMAC Chain

Chi, P. J., M. J. Engebretson, M. B. Moldwin, C. T. Russell, I. R. Mann, M. R. Hairston, M. Reno, J. Goldstein, L. I. Winkler, J. L. Cruz-Abeyro, D.-H. Lee, K.Yumoto, R. Dalrymple, B. Chen, and J. P. Gibson (2013), Sounding of the plasmasphere by Mid-continent MAgnetoseismic Chain magnetometers, J. Geophys. Res. Space Physics, 118, doi:10.1002/jgra.50274.

Collaborator MAGDAS / 210 Chain

Yumoto, K,. and the CPMN Group (2001), Characteristics of Pi 2 magnetic pulsations observed at the CPMN stations: A review of the STEP results, Earth Planets Space, 53, 981-992.

Collaborator CARISMA

Mann, I. R., et al. (2008), The upgraded CARISMA magnetometer array in the THEMIS era, Space Sci. Rev., 141, 413–451, doi:10.1007/s11214-008-9457-6.

Collaborator AALPIP

Clauer, C. R., et al. (2014), An autonomous adaptive low-power instrument platform (AAL-PIP) for remote high-latitude geospace data collection, Geosci. Instrum. Methods Data Syst., 3, 211–227, doi:10.5194/gi-3-211-2014

Collaborator INTERMAGNET

Love, J. J., Chulliat, A., (2013), An international network of magnetic observatories, Eos, 94(42), 373-374, doi:10.1002/2013EO420001

SuperMAG

Gjerloev, J. W. (2012), The SuperMAG data processing technique, J. Geophys. Res., 117 , A09213, doi:10.1029/2012JA017683.

Indices SML, SMU, SME

Newell, P. T., and J. W. Gjerloev (2011), Evaluation of SuperMAG auroral electrojet indices as indicators of substorms and auroral power, J. Geophys. Res., 116, A12211, doi:10.1029/2011JA016779.

Indices SMLs, SMLd, SMUs, SMUd

Gjerloev, J. W., R. A. Hoffman, S. Ohtani, J. Weygand, and R. Barnes, Response of the Auroral Electrojet Indices to Abrupt Southward IMF Turnings (2010), Annales Geophysicae, 28, 1167-1182.

Indices SME-LT, SMU-LT, SML-LT

Newell, P. T., and J. W. Gjerloev (2014), Local geomagnetic indices and the prediction of auroral power, J. Geophys. Res. Space Physics, 119, doi:10.1002/2014JA020524.

Indices SMR, SMR-LT

Newell, P. T. and J. W. Gjerloev (2012), SuperMAG-Based Partial Ring Current Indices, J. Geophys. Res., 117, doi:10.1029/2012JA017586.

Substorm List

Forsyth, C., Rae, I. J., Coxon, J. C., Freeman, M. P., Jackman, C. M., Gjerloev, J., and Fazakerley, A. N. ( 2015), A new technique for determining Substorm Onsets and Phases from Indices of the Electrojet (SOPHIE), J. Geophys. Res. Space Physics, 120, 10,592– 10,606, doi:10.1002/2015JA021343.

Frey, H. U., Mende, S. B., Angelopoulos, V., and Donovan, E. F. (2004), Substorm onset observations by IMAGE‐FUV, J. Geophys. Res., 109, A10304, doi:10.1029/2004JA010607.

Gjerloev, J. W. (2012), The SuperMAG data processing technique, J. Geophys. Res., 117, A09213,  doi:10.1029/2012JA017683.

Liou, K. (2010),  Polar Ultraviolet Imager observation of auroral breakup, J. Geophys. Res.,  115, A12219, doi:10.1029/2010JA015578.

Newell, P. T., and J. W. Gjerloev (2011), Evaluation of SuperMAG auroral electrojet indices as indicators of substorms and auroral power, J. Geophys. Res., 116, A12211, doi:10.1029/2011JA016779.

Newell, P. T., and J. W. Gjerloev (2011), Substorm and magnetosphere characteristic scales inferred from the SuperMAG auroral electrojet indices, J. Geophys. Res., 116, A12232, doi:10.1029/2011JA016936.

Ohtani, S., and J. Gjerloev, Is the Substorm Current Wedge an Ensemble of Wedgelets?: Revisit to Midlatitude Positive Bays, accepted, J. Geophys. Res, 2020.

Custom Download of Data

Download custom generated data files for the selected station(s), time intervals, duration, baseline solution, and other options. SuperMAG custom data files are distributed in ASCII, CSV, or NetCDF format.

Please be considerate when generating custom data files. If you need a large amount of data then please use the Large Downloads tab.

By downloading data from SuperMAG you agree to follow the Rules of the Road.

[green]Selected Station [red]Available Station (Data Present) [grey]Available Station (No Data Present)

Custom Download Options

Rules of the Road

SuperMAG is made possible by the generous contribution of data by numerous collaborators. To ensure their continued operation the user must follow the below rules-of-the-road. Data, plots or derived data products are provided under the limitations of "fair use" and cannot be redistributed. Contact the individual instrument PI and the SuperMAG PI for requests that are in conflict with these restrictions.

The user is requested to acknowledge individual collaborators and SuperMAG when original data, derived data, movies, or data products are used in publications and/or presentations.

When Using Data

In all cases:

  • Include acknowledgement as listed on the SuperMAG website.
  • Include references to a technical papers for stations used (see list below).
  • Include SuperMAG reference: Gjerloev, J. W. (2012), The SuperMAG data processing technique, J. Geophys. Res., 117, A09213, doi:10.1029/2012JA017683.

In cases that only a few stations play a key role and their data are central to the scientific conclusion of the paper:

  • Offer of co-authorship to the PI (or PIs) of those stations and reference the appropriate paper (see list below).
When Using Indices
  • Include the text: “We gratefully acknowledge the SuperMAG collaborators (https://supermag.jhuapl.edu/info/?page=acknowledgement)”
  • Include appropriate reference for indices used (see list below).
  • Include SuperMAG reference: Gjerloev, J. W. (2012), The SuperMAG data processing technique, J. Geophys. Res., 117, A09213, doi:10.1029/2012JA017683.
When Using Substorm Lists
  • If the substorm onset list is central to your study please offer co-authorship to the authors of the technique you use.
  • When using substorm lists please include acknowledgements found here.
  • Include appropriate reference (see list below)
  • For details please see https://supermag.jhuapl.edu/substorms.
When Using OMNI When Using Imaging When using INTERMAGNET Data

References

Collaborator EMMA

Lichtenberger J., M. Clilverd, B. Heilig, M. Vellante, J. Manninen, C. Rodger, A. Collier, A. Jørgensen, J. Reda, R. Holzworth, and R. Friedel (2013), The plasmasphere during a space weather event: first results from the PLASMON project, J. Space Weather Space Clim., 3, A23 (www.swsc-journal.org/articles/swsc/pdf/2013/01/swsc120062.pdf).

Collaborator IMAGE Chain

Tanskanen, E.I. (2009), A comprehensive high-throughput analysis of substorms observed by IMAGE magnetometer network: Years 1993-2003 examined, 114, A05204, doi:10.1029/2008JA013682.

Collaborator MACCS

Engebretson, M. J., W. J. Hughes, J. L. Alford, E. Zesta, L. J. Cahill, Jr., R. L. Arnoldy, and G. D. Reeves (1995), Magnetometer array for cusp and cleft studies observations of the spatial extent of broadband ULF magnetic pulsations at cusp/cleft latitudes , J. Geophys. Res., 100, 19371-19386, doi:10.1029/95JA00768.

Collaborator McMAC Chain

Chi, P. J., M. J. Engebretson, M. B. Moldwin, C. T. Russell, I. R. Mann, M. R. Hairston, M. Reno, J. Goldstein, L. I. Winkler, J. L. Cruz-Abeyro, D.-H. Lee, K.Yumoto, R. Dalrymple, B. Chen, and J. P. Gibson (2013), Sounding of the plasmasphere by Mid-continent MAgnetoseismic Chain magnetometers, J. Geophys. Res. Space Physics, 118, doi:10.1002/jgra.50274.

Collaborator MAGDAS / 210 Chain

Yumoto, K,. and the CPMN Group (2001), Characteristics of Pi 2 magnetic pulsations observed at the CPMN stations: A review of the STEP results, Earth Planets Space, 53, 981-992.

Collaborator CARISMA

Mann, I. R., et al. (2008), The upgraded CARISMA magnetometer array in the THEMIS era, Space Sci. Rev., 141, 413–451, doi:10.1007/s11214-008-9457-6.

Collaborator AALPIP

Clauer, C. R., et al. (2014), An autonomous adaptive low-power instrument platform (AAL-PIP) for remote high-latitude geospace data collection, Geosci. Instrum. Methods Data Syst., 3, 211–227, doi:10.5194/gi-3-211-2014

Collaborator INTERMAGNET

Love, J. J., Chulliat, A., (2013), An international network of magnetic observatories, Eos, 94(42), 373-374, doi:10.1002/2013EO420001

SuperMAG

Gjerloev, J. W. (2012), The SuperMAG data processing technique, J. Geophys. Res., 117 , A09213, doi:10.1029/2012JA017683.

Indices SML, SMU, SME

Newell, P. T., and J. W. Gjerloev (2011), Evaluation of SuperMAG auroral electrojet indices as indicators of substorms and auroral power, J. Geophys. Res., 116, A12211, doi:10.1029/2011JA016779.

Indices SMLs, SMLd, SMUs, SMUd

Gjerloev, J. W., R. A. Hoffman, S. Ohtani, J. Weygand, and R. Barnes, Response of the Auroral Electrojet Indices to Abrupt Southward IMF Turnings (2010), Annales Geophysicae, 28, 1167-1182.

Indices SME-LT, SMU-LT, SML-LT

Newell, P. T., and J. W. Gjerloev (2014), Local geomagnetic indices and the prediction of auroral power, J. Geophys. Res. Space Physics, 119, doi:10.1002/2014JA020524.

Indices SMR, SMR-LT

Newell, P. T. and J. W. Gjerloev (2012), SuperMAG-Based Partial Ring Current Indices, J. Geophys. Res., 117, doi:10.1029/2012JA017586.

Substorm List

Forsyth, C., Rae, I. J., Coxon, J. C., Freeman, M. P., Jackman, C. M., Gjerloev, J., and Fazakerley, A. N. ( 2015), A new technique for determining Substorm Onsets and Phases from Indices of the Electrojet (SOPHIE), J. Geophys. Res. Space Physics, 120, 10,592– 10,606, doi:10.1002/2015JA021343.

Frey, H. U., Mende, S. B., Angelopoulos, V., and Donovan, E. F. (2004), Substorm onset observations by IMAGE‐FUV, J. Geophys. Res., 109, A10304, doi:10.1029/2004JA010607.

Gjerloev, J. W. (2012), The SuperMAG data processing technique, J. Geophys. Res., 117, A09213,  doi:10.1029/2012JA017683.

Liou, K. (2010),  Polar Ultraviolet Imager observation of auroral breakup, J. Geophys. Res.,  115, A12219, doi:10.1029/2010JA015578.

Newell, P. T., and J. W. Gjerloev (2011), Evaluation of SuperMAG auroral electrojet indices as indicators of substorms and auroral power, J. Geophys. Res., 116, A12211, doi:10.1029/2011JA016779.

Newell, P. T., and J. W. Gjerloev (2011), Substorm and magnetosphere characteristic scales inferred from the SuperMAG auroral electrojet indices, J. Geophys. Res., 116, A12232, doi:10.1029/2011JA016936.

Ohtani, S., and J. Gjerloev, Is the Substorm Current Wedge an Ensemble of Wedgelets?: Revisit to Midlatitude Positive Bays, accepted, J. Geophys. Res, 2020.

Download Gridded Solutions

SuperMAG uniformly gridded solutions are distributed in NetCDF format. Please see the NetCDF website for more details on this format. The files are for the complete day of interest.

If you need a large amount of data then please use the Large Downloads tab.

By downloading data from SuperMAG you agree to follow the Rules of the Road.

Log on to download data.
Enter Security Code:

Having trouble downloading files? Make sure your browser is configured to allow automatic downloads of multiple files from SuperMAG (see FAQ)

Rules of the Road

SuperMAG is made possible by the generous contribution of data by numerous collaborators. To ensure their continued operation the user must follow the below rules-of-the-road. Data, plots or derived data products are provided under the limitations of "fair use" and cannot be redistributed. Contact the individual instrument PI and the SuperMAG PI for requests that are in conflict with these restrictions.

The user is requested to acknowledge individual collaborators and SuperMAG when original data, derived data, movies, or data products are used in publications and/or presentations.

When Using Data

In all cases:

  • Include acknowledgement as listed on the SuperMAG website.
  • Include references to a technical papers for stations used (see list below).
  • Include SuperMAG reference: Gjerloev, J. W. (2012), The SuperMAG data processing technique, J. Geophys. Res., 117, A09213, doi:10.1029/2012JA017683.

In cases that only a few stations play a key role and their data are central to the scientific conclusion of the paper:

  • Offer of co-authorship to the PI (or PIs) of those stations and reference the appropriate paper (see list below).
When Using Indices
  • Include the text: “We gratefully acknowledge the SuperMAG collaborators (https://supermag.jhuapl.edu/info/?page=acknowledgement)”
  • Include appropriate reference for indices used (see list below).
  • Include SuperMAG reference: Gjerloev, J. W. (2012), The SuperMAG data processing technique, J. Geophys. Res., 117, A09213, doi:10.1029/2012JA017683.
When Using Substorm Lists
  • If the substorm onset list is central to your study please offer co-authorship to the authors of the technique you use.
  • When using substorm lists please include acknowledgements found here.
  • Include appropriate reference (see list below)
  • For details please see https://supermag.jhuapl.edu/substorms.
When Using OMNI When Using Imaging When using INTERMAGNET Data

References

Collaborator EMMA

Lichtenberger J., M. Clilverd, B. Heilig, M. Vellante, J. Manninen, C. Rodger, A. Collier, A. Jørgensen, J. Reda, R. Holzworth, and R. Friedel (2013), The plasmasphere during a space weather event: first results from the PLASMON project, J. Space Weather Space Clim., 3, A23 (www.swsc-journal.org/articles/swsc/pdf/2013/01/swsc120062.pdf).

Collaborator IMAGE Chain

Tanskanen, E.I. (2009), A comprehensive high-throughput analysis of substorms observed by IMAGE magnetometer network: Years 1993-2003 examined, 114, A05204, doi:10.1029/2008JA013682.

Collaborator MACCS

Engebretson, M. J., W. J. Hughes, J. L. Alford, E. Zesta, L. J. Cahill, Jr., R. L. Arnoldy, and G. D. Reeves (1995), Magnetometer array for cusp and cleft studies observations of the spatial extent of broadband ULF magnetic pulsations at cusp/cleft latitudes , J. Geophys. Res., 100, 19371-19386, doi:10.1029/95JA00768.

Collaborator McMAC Chain

Chi, P. J., M. J. Engebretson, M. B. Moldwin, C. T. Russell, I. R. Mann, M. R. Hairston, M. Reno, J. Goldstein, L. I. Winkler, J. L. Cruz-Abeyro, D.-H. Lee, K.Yumoto, R. Dalrymple, B. Chen, and J. P. Gibson (2013), Sounding of the plasmasphere by Mid-continent MAgnetoseismic Chain magnetometers, J. Geophys. Res. Space Physics, 118, doi:10.1002/jgra.50274.

Collaborator MAGDAS / 210 Chain

Yumoto, K,. and the CPMN Group (2001), Characteristics of Pi 2 magnetic pulsations observed at the CPMN stations: A review of the STEP results, Earth Planets Space, 53, 981-992.

Collaborator CARISMA

Mann, I. R., et al. (2008), The upgraded CARISMA magnetometer array in the THEMIS era, Space Sci. Rev., 141, 413–451, doi:10.1007/s11214-008-9457-6.

Collaborator AALPIP

Clauer, C. R., et al. (2014), An autonomous adaptive low-power instrument platform (AAL-PIP) for remote high-latitude geospace data collection, Geosci. Instrum. Methods Data Syst., 3, 211–227, doi:10.5194/gi-3-211-2014

Collaborator INTERMAGNET

Love, J. J., Chulliat, A., (2013), An international network of magnetic observatories, Eos, 94(42), 373-374, doi:10.1002/2013EO420001

SuperMAG

Gjerloev, J. W. (2012), The SuperMAG data processing technique, J. Geophys. Res., 117 , A09213, doi:10.1029/2012JA017683.

Indices SML, SMU, SME

Newell, P. T., and J. W. Gjerloev (2011), Evaluation of SuperMAG auroral electrojet indices as indicators of substorms and auroral power, J. Geophys. Res., 116, A12211, doi:10.1029/2011JA016779.

Indices SMLs, SMLd, SMUs, SMUd

Gjerloev, J. W., R. A. Hoffman, S. Ohtani, J. Weygand, and R. Barnes, Response of the Auroral Electrojet Indices to Abrupt Southward IMF Turnings (2010), Annales Geophysicae, 28, 1167-1182.

Indices SME-LT, SMU-LT, SML-LT

Newell, P. T., and J. W. Gjerloev (2014), Local geomagnetic indices and the prediction of auroral power, J. Geophys. Res. Space Physics, 119, doi:10.1002/2014JA020524.

Indices SMR, SMR-LT

Newell, P. T. and J. W. Gjerloev (2012), SuperMAG-Based Partial Ring Current Indices, J. Geophys. Res., 117, doi:10.1029/2012JA017586.

Substorm List

Forsyth, C., Rae, I. J., Coxon, J. C., Freeman, M. P., Jackman, C. M., Gjerloev, J., and Fazakerley, A. N. ( 2015), A new technique for determining Substorm Onsets and Phases from Indices of the Electrojet (SOPHIE), J. Geophys. Res. Space Physics, 120, 10,592– 10,606, doi:10.1002/2015JA021343.

Frey, H. U., Mende, S. B., Angelopoulos, V., and Donovan, E. F. (2004), Substorm onset observations by IMAGE‐FUV, J. Geophys. Res., 109, A10304, doi:10.1029/2004JA010607.

Gjerloev, J. W. (2012), The SuperMAG data processing technique, J. Geophys. Res., 117, A09213,  doi:10.1029/2012JA017683.

Liou, K. (2010),  Polar Ultraviolet Imager observation of auroral breakup, J. Geophys. Res.,  115, A12219, doi:10.1029/2010JA015578.

Newell, P. T., and J. W. Gjerloev (2011), Evaluation of SuperMAG auroral electrojet indices as indicators of substorms and auroral power, J. Geophys. Res., 116, A12211, doi:10.1029/2011JA016779.

Newell, P. T., and J. W. Gjerloev (2011), Substorm and magnetosphere characteristic scales inferred from the SuperMAG auroral electrojet indices, J. Geophys. Res., 116, A12232, doi:10.1029/2011JA016936.

Ohtani, S., and J. Gjerloev, Is the Substorm Current Wedge an Ensemble of Wedgelets?: Revisit to Midlatitude Positive Bays, accepted, J. Geophys. Res, 2020.

Download ULF Parameters

SuperMAG derived ULF parameters are distributed in NetCDF format. Please see the NetCDF website for more details on this format. The files are for the complete day of interest.

By downloading data from SuperMAG you agree to follow the Rules of the Road.

Files include:
  • N,E,Z 1-sec data (error corrected, rotated & baseline removed)
  • ULF Pc2—Pc5 parameters (see ULF Waves for more details)
Log on to download data.
Enter Security Code:

Having trouble downloading files? Make sure your browser is configured to allow automatic downloads of multiple files from SuperMAG (see FAQ)

Rules of the Road

SuperMAG is made possible by the generous contribution of data by numerous collaborators. To ensure their continued operation the user must follow the below rules-of-the-road. Data, plots or derived data products are provided under the limitations of "fair use" and cannot be redistributed. Contact the individual instrument PI and the SuperMAG PI for requests that are in conflict with these restrictions.

The user is requested to acknowledge individual collaborators and SuperMAG when original data, derived data, movies, or data products are used in publications and/or presentations.

When Using Data

In all cases:

  • Include acknowledgement as listed on the SuperMAG website.
  • Include references to a technical papers for stations used (see list below).
  • Include SuperMAG reference: Gjerloev, J. W. (2012), The SuperMAG data processing technique, J. Geophys. Res., 117, A09213, doi:10.1029/2012JA017683.

In cases that only a few stations play a key role and their data are central to the scientific conclusion of the paper:

  • Offer of co-authorship to the PI (or PIs) of those stations and reference the appropriate paper (see list below).
When Using Indices
  • Include the text: “We gratefully acknowledge the SuperMAG collaborators (https://supermag.jhuapl.edu/info/?page=acknowledgement)”
  • Include appropriate reference for indices used (see list below).
  • Include SuperMAG reference: Gjerloev, J. W. (2012), The SuperMAG data processing technique, J. Geophys. Res., 117, A09213, doi:10.1029/2012JA017683.
When Using Substorm Lists
  • If the substorm onset list is central to your study please offer co-authorship to the authors of the technique you use.
  • When using substorm lists please include acknowledgements found here.
  • Include appropriate reference (see list below)
  • For details please see https://supermag.jhuapl.edu/substorms.
When Using OMNI When Using Imaging When using INTERMAGNET Data

References

Collaborator EMMA

Lichtenberger J., M. Clilverd, B. Heilig, M. Vellante, J. Manninen, C. Rodger, A. Collier, A. Jørgensen, J. Reda, R. Holzworth, and R. Friedel (2013), The plasmasphere during a space weather event: first results from the PLASMON project, J. Space Weather Space Clim., 3, A23 (www.swsc-journal.org/articles/swsc/pdf/2013/01/swsc120062.pdf).

Collaborator IMAGE Chain

Tanskanen, E.I. (2009), A comprehensive high-throughput analysis of substorms observed by IMAGE magnetometer network: Years 1993-2003 examined, 114, A05204, doi:10.1029/2008JA013682.

Collaborator MACCS

Engebretson, M. J., W. J. Hughes, J. L. Alford, E. Zesta, L. J. Cahill, Jr., R. L. Arnoldy, and G. D. Reeves (1995), Magnetometer array for cusp and cleft studies observations of the spatial extent of broadband ULF magnetic pulsations at cusp/cleft latitudes , J. Geophys. Res., 100, 19371-19386, doi:10.1029/95JA00768.

Collaborator McMAC Chain

Chi, P. J., M. J. Engebretson, M. B. Moldwin, C. T. Russell, I. R. Mann, M. R. Hairston, M. Reno, J. Goldstein, L. I. Winkler, J. L. Cruz-Abeyro, D.-H. Lee, K.Yumoto, R. Dalrymple, B. Chen, and J. P. Gibson (2013), Sounding of the plasmasphere by Mid-continent MAgnetoseismic Chain magnetometers, J. Geophys. Res. Space Physics, 118, doi:10.1002/jgra.50274.

Collaborator MAGDAS / 210 Chain

Yumoto, K,. and the CPMN Group (2001), Characteristics of Pi 2 magnetic pulsations observed at the CPMN stations: A review of the STEP results, Earth Planets Space, 53, 981-992.

Collaborator CARISMA

Mann, I. R., et al. (2008), The upgraded CARISMA magnetometer array in the THEMIS era, Space Sci. Rev., 141, 413–451, doi:10.1007/s11214-008-9457-6.

Collaborator AALPIP

Clauer, C. R., et al. (2014), An autonomous adaptive low-power instrument platform (AAL-PIP) for remote high-latitude geospace data collection, Geosci. Instrum. Methods Data Syst., 3, 211–227, doi:10.5194/gi-3-211-2014

Collaborator INTERMAGNET

Love, J. J., Chulliat, A., (2013), An international network of magnetic observatories, Eos, 94(42), 373-374, doi:10.1002/2013EO420001

SuperMAG

Gjerloev, J. W. (2012), The SuperMAG data processing technique, J. Geophys. Res., 117 , A09213, doi:10.1029/2012JA017683.

Indices SML, SMU, SME

Newell, P. T., and J. W. Gjerloev (2011), Evaluation of SuperMAG auroral electrojet indices as indicators of substorms and auroral power, J. Geophys. Res., 116, A12211, doi:10.1029/2011JA016779.

Indices SMLs, SMLd, SMUs, SMUd

Gjerloev, J. W., R. A. Hoffman, S. Ohtani, J. Weygand, and R. Barnes, Response of the Auroral Electrojet Indices to Abrupt Southward IMF Turnings (2010), Annales Geophysicae, 28, 1167-1182.

Indices SME-LT, SMU-LT, SML-LT

Newell, P. T., and J. W. Gjerloev (2014), Local geomagnetic indices and the prediction of auroral power, J. Geophys. Res. Space Physics, 119, doi:10.1002/2014JA020524.

Indices SMR, SMR-LT

Newell, P. T. and J. W. Gjerloev (2012), SuperMAG-Based Partial Ring Current Indices, J. Geophys. Res., 117, doi:10.1029/2012JA017586.

Substorm List

Forsyth, C., Rae, I. J., Coxon, J. C., Freeman, M. P., Jackman, C. M., Gjerloev, J., and Fazakerley, A. N. ( 2015), A new technique for determining Substorm Onsets and Phases from Indices of the Electrojet (SOPHIE), J. Geophys. Res. Space Physics, 120, 10,592– 10,606, doi:10.1002/2015JA021343.

Frey, H. U., Mende, S. B., Angelopoulos, V., and Donovan, E. F. (2004), Substorm onset observations by IMAGE‐FUV, J. Geophys. Res., 109, A10304, doi:10.1029/2004JA010607.

Gjerloev, J. W. (2012), The SuperMAG data processing technique, J. Geophys. Res., 117, A09213,  doi:10.1029/2012JA017683.

Liou, K. (2010),  Polar Ultraviolet Imager observation of auroral breakup, J. Geophys. Res.,  115, A12219, doi:10.1029/2010JA015578.

Newell, P. T., and J. W. Gjerloev (2011), Evaluation of SuperMAG auroral electrojet indices as indicators of substorms and auroral power, J. Geophys. Res., 116, A12211, doi:10.1029/2011JA016779.

Newell, P. T., and J. W. Gjerloev (2011), Substorm and magnetosphere characteristic scales inferred from the SuperMAG auroral electrojet indices, J. Geophys. Res., 116, A12232, doi:10.1029/2011JA016936.

Ohtani, S., and J. Gjerloev, Is the Substorm Current Wedge an Ensemble of Wedgelets?: Revisit to Midlatitude Positive Bays, accepted, J. Geophys. Res, 2020.

Station Information

Station name, geographic location and IAGA code can be downloaded as an ASCII file. The file includes a description of variables and other information.

When using this file please acknowledge the SuperMAG collaboration by including the reference below.

Some of the three letter codes are not official IAGA codes but are designated by SuperMAG.

Bxx indicate BAS operated stations
Txx indicate THEMIS project stations
Mxx indicate McMac operated stations
Cxx indicate CARISMA operated stations
Exx indicate ENIGMA operated stations
Pxx indicate EMMA operated stations
Sxx indicate SAMNET operated stations
Axx indicate AMBER operated stations
Gxx indicate MAGDAS operated stations
PGx indicate MIST operated stations
Rxx indicate Magstar operated stations

References:

Gjerloev, J. W. (2012), The SuperMAG data processing technique, J. Geophys. Res., 117, A09213, doi:10.1029/2012JA017683.

Gjerloev, J. W. (2009), A Global Ground-Based Magnetometer Initiative, EOS, 90, 230-231, doi:10.1029/2009EO270002.

Stations

SuperMAG Web Service API

Please be considerate when using the API. If you need a large amount of data then please use the Large Downloads tab.

By downloading data from SuperMAG you agree to follow the Rules of the Road.

Low fidelity magnetometer data and indices can be downloaded via the SuperMAG Web Service API. The SuperMAG Web Service API is a REST interface composed of three primary web service endpoints (The following URLs are web service endpoints and are not meant to be navigated to directly from a web browser!):

The SuperMAG Web Service API may be interacted with directly or via IDL/Python client.

NOTE: If you would like to use the SuperMAG Web Service API directly (i.e. without using one of the clients provided below), the IDL/Python client code, documentation, and the example code in the documentation should provide you with all the details you need to build your own custom SuperMAG Web Service API client in any programming or scripting language that supports making HTTPS GET requests.

IDL Client (IDL version 8.3 or above required)

Download data and indices from SuperMAG directly into your IDL program using the SuperMAG Webservice IDL Client.

  • Download IDL Client
  • Download IDL Client Documentation
  • View IDL Client Documentation Hide IDL Client Documentation
    SuperMAG IDL Client 1.0
    SuperMAG Web Service API IDL Client Documentation
    IDL version 8.3 or above required

    ◆  SuperMAGGetInventory()

    IDL function that retrieves an array of available stations for a given event.
    Parameters
    useridyour supermag user id
    yrstart year of event
    mostart month of event
    dystart day of event
    hrstart hour of event
    mtstart minute of event
    scstart second of event (for now this is ignored as we are only dealing with the 1 minute data)
    extentextent or length of the event in seconds (3600= 1 hour, 86400 = 1 day)
    iaarThe array of available stations is returned in iarr
    error(optional) returns an error message back as a string
    Returns
    Boolean set to zero on success or 1 on error. If the keyword parameter “error” is provided an error message is returned back as a string.

    Example Usage

    PRO SuperMAGTestInventory, userid
       s=SuperMAGGetInventory(userid, 2013, 2, 3, 12, 30, 0, 86400, iarr, error=errstr)
       if (s eq 0) then begin
         print, errstr
          stop
       endif
       print, 'Available stations'
       for i=0, n_elements(iarr)-1 do print, iarr[i]
       stop
    END
    

    ◆  SuperMAGTimeToYMDHMS()

    IDL helper function used convert double precision numbers representing time epochs into the associated set of constituent time elements.
    Parameters
    tvalAn array of double precision numbers giving the time in seconds since 1970-01-01 0:00UTC (i.e. the times to convert)
    yrtval year
    motval month
    dytval day
    hrtval hour
    mttval minute
    sctval second

    Example Usage

    tval=[1521202124,1521203460,1521203520]
    SuperMAGTimeToYMDHMS,tval,yr,mo,dy,hr,mt,sc
    

    ◆  SuperMAGGetDataArray()

    IDL function that retrievies station magnetometer data for a given event and IAGA station code.
    Parameters
    useridyour supermag user id
    yrstart year of event
    mostart month of event
    dystart day of event
    hrstart hour of event
    mtstart minute of event
    scstart second of event (for now this is ignored as we are only dealing with the 1 minute data)
    extentextent or length of the event in seconds (3600= 1 hour, 86400 = 1 day)
    stationIAGA code of the requested station
    tvalThe time of the samples is returned in the array tval. The time array is an array of double precision numbers giving the time since 1970-01-01 0:00UTC (This is a standard representation of time on computer systems).
    nThe N vector component is returned in the two dimensional array of length extent/60 specified by n. The second dimension refers to the coordinate system, so ‘N[*,0]’ contains the component of the vector in the standard NEZ coordinates, N[*,1] contains the geographic mapping of the N vector component.
    eThe E vector component is returned in the two dimensional array of length extent/60 specified by e. The second dimension refers to the coordinate system, so ‘E[*,0]’ contains the component of the vector in the standard NEZ coordinates, E[*,1] contains the geographic mapping of the E vector component.
    zThe A vector component is returned in the two dimensional array of length extent/60 specified by z. The second dimension refers to the coordinate system, so ‘Z[*,0]’ contains the component of the vector in the standard NEZ coordinates, Z[*,1] contains the geographic mapping of the Z vector component.
    error(optional) If supplied, An error message will be returned in the string error
    MLT(optional) If supplied, The MLT/MCOLAT of the station will be returned in the two dimensional array of length extent/60 specified by MLT.
    MAG(optional) If supplied, The Magnetic coordinates of the station will be returned in the two dimensional array of length extent/60 specified by MAG.
    GEO(optional) If supplied, The Geographic coordinates of the station will be returned in the two dimensional array of length extent/60 specified by GEO.
    DECL(optional) If supplied, The Declination from IGRF Model will be returned in the array of length extent/60 specified by DECL.
    SZA(optional) If supplied, The solar zenith angle will be returned in the array of length extent/60 specified by SZA.
    DELTA(optional) If the keywoard DELTA is supplied, The baseline NEZ vector start values will be subtracted from the NEZ vector components in the resulting n, e, and z arrays.
    BASELINE(optional) If BASELINE is specified, It must be set to one of three values:
    "all" (default)Subtract both the daily and yearly NEZ baselines
    "yearly"Subtract the yearly NEZ baseline, but do not subtract the daily NEZ baseline
    "none"Do not subtract either the yearly or the daily NEZ baseline
    Returns
    Boolean set to zero on success or 1 on error. If the keyword parameter “error” is provided an error message is returned back as a string.

    Example Usage

    PRO SuperMAGTestDataArray, userid
       s=SuperMAGGetDataArray(userid, 2015, 8, 12, 10, 30, 0, 86400*4, 'THL', tval, n, e, z, error=errstr, MLT=mlt, $
                              SZA=sza, MAG=mag, BASELINE='none')
       if (s eq 0) then begin
          print, errstr
          stop
       endif
       if n_elements(tval) eq 0 then begin
          print,'No Data'
          stop
       endif
       SuperMAGTimeToYMDHMS,tval,yr,mo,dy,hr,mt,sc
       print, 'N (NEZ)=',n[*,0],'E (NEZ)=',e[*,0],'Z (NEZ)=',z[*,0]
       print, 'mag=',mag[0,0],mag[0,1]
       print, 'sza=',sza
       stop
    END
    

    ◆  SuperMAGGetDataStruct()

    IDL function that retrievies station magnetometer for a given event and IAGA station code. The data is returned as a single array of structs. This function returns the same data as SuperMAGGetDataArray(), but is intended for "power" users who are comfortable dealing with IDL structures.
    Parameters
    useridyour supermag user id
    yrstart year of event
    mostart month of event
    dystart day of event
    hrstart hour of event
    mtstart minute of event
    scstart second of event (for now this is ignored as we are only dealing with the 1 minute data)
    extentextent or length of the event in seconds (3600= 1 hour, 86400 = 1 day)
    stationIAGA code of the requested station
    magdataAn array of IDL structs, where each struct contains the requested data at a particular event time epoch (e.g. tval,n,e,z,MLT,MAG,GEO,DECL,SZA, see SuperMAGGetDataArray definition above)
    error(optional) If supplied, An error message will be returned in the string error
    ALL(optional) If the keywoard "ALL" is supplied, everything is returned (e.g. MLT, MAG, GEO, DECL, and SZA are all returned in magdata)
    MLT(optional) If the keywoard "MLT" is supplied, the MLT/MCOLAT of the station will be returned in magdata.
    MAG(optional) If the keywoard "MAG" is supplied, the Magnetic coordinates of the station will be returned in magdata.
    GEO(optional) If the keywoard "GEO" is supplied, the Geographic coordinates of the station will be returned in magdata.
    DECL(optional) If the keywoard "DECL" is supplied, the Declination from IGRF Model will be returned in magdata.
    SZA(optional) If the keywoard "SZA" is supplied, the solar zenith angle will be returned in magdata.
    DELTA(optional) If the keywoard "DELTA" is supplied, the baseline NEZ vector start values will be subtracted from the NEZ vector components in the resulting n, e, and z arrays.
    BASELINE(optional) If BASELINE is specified, it must be set to one of three values:
    "all" (default)Subtract both the daily and yearly NEZ baselines
    "yearly"Subtract the yearly NEZ baseline, but do not subtract the daily NEZ baseline
    "none"Do not subtract either the yearly or the daily NEZ baseline
    Returns
    Boolean set to zero on success or 1 on error. If the keyword parameter “error” is provided an error message is returned back as a string.

    Example Usage

    PRO SuperMAGTestDataStruct, userid
       s=SuperMAGGetDataStruct(userid, 2015, 8, 12, 10, 30, 0, 3600, 'THL', magdata, error=errstr,$ 
                               /MLT,/SZA,/MAG,/GEO)
       if (s eq 0) then begin
          print, errstr
          stop
       endif
       if n_elements(magdata) eq 0 then begin
          print,'No data'
          stop
       endif
       tval=magdata[*].tval
       N_NEZ=magdata[*].N.nez
       E_NEZ=magdata[*].E.nez
       Z_NEZ=magdata[*].Z.nez
       MLT=magdata[*].MLT
       MCOLAT=magdata[*].MCOLAT
       MLON=magdata[*].MLON
       MLAT=magdata[*].MLAT
       GLON=magdata[*].GLON
       GLAT=magdata[*].GLAT 
       SZA=magdata[*].SZA
       SuperMAGTimeToYMDHMS,tval,yr,mo,dy,hr,mt,sc
       print, 'N (NEZ)=',N_NEZ,'E (NEZ)=',E_NEZ,'Z (NEZ)=',Z_NEZ
       stop
    END
    

    ◆  SuperMAGGetIndicesArray()

    IDL function that retrievies a set of magnetic indices for a given event.
    Parameters
    useridyour supermag user id
    yrstart year of event
    mostart month of event
    dystart day of event
    hrstart hour of event
    mtstart minute of event
    scstart second of event (for now this is ignored as we are only dealing with the 1 minute data)
    extentextent or length of the event in seconds (3600= 1 hour, 86400 = 1 day)
    tvalThe time of the samples is returned in the array tval. The time array is an array of double precision numbers giving the time since 1970-01-01 0:00UTC (This is a standard representation of time on computer systems).
    error(optional) If supplied, An error message will be returned in the string error
    SME(optional) If supplied, the SME indice will be returned in the array specified by SME (See definition of SME indice)
    SML(optional) If supplied, the SML indice will be returned in the array specified by SML (See definition of SML indice)
    SMU(optional) If supplied, the SMU indice will be returned in the array specified by SMU (See definition of SMU indice)
    MLAT(optional) If supplied, the magnetic latitude of the SME indice will be returned in the array specified by MLAT
    MLT(optional) If supplied, the magnetic local time of the SME indice will be returned in the array specified by MLT
    GLAT(optional) If supplied, the geographic latitude of the SME indice will be returned in the array specified by GLAT
    GLON(optional) If supplied, the geographic longitude of the SME indice will be returned in the array specified by GLON
    STID(optional) If supplied, the IAGA station codes of the stations used to compute the SME indices will be returned in the array specified by STID
    NUM(optional) If supplied, the number of stations used to compute SME indices will be returned in the array specified by NUM
    SUNSME(optional) If supplied, the Sunlit SME indice will be returned in the array specified by SUNSME (See definition of Sunlit SME indice)
    SUNSML(optional) If supplied, the Sunlit SML indice will be returned in the array specified by SUNSML (See definition of Sunlit SML indice)
    SUNSMU(optional) If supplied, the Sunlit SMU indice will be returned in the array specified by SUNSMU (See definition of Sunlit SMU indice)
    SUNMLAT(optional) If supplied, the magnetic latitude of the Sunlit SME indice will be returned in the array specified by SUNMLAT
    SUNMLT(optional) If supplied, the magnetic local time of the Sunlit SME indice will be returned in the array specified by SUNMLT
    SUNGLAT(optional) If supplied, the geographic latitude of the Sunlit SME indice will be returned in the array specified by SUNGLAT
    SUNGLON(optional) If supplied, the geographic longitude of the Sunlit SME indice will be returned in the array specified by SUNGLON
    SUNSTID(optional) If supplied, the IAGA station codes of the stations used to compute the Sunlit SME indices will be returned in the array specified by SUNSTID
    SUNNUM(optional) If supplied, the number of stations used to compute the Sunlit SME indices will be returned in the array specified by SUNNUM
    DARKSME(optional) If supplied, the Dark SME indice will be returned in the array specified by DARKSME (See definition of Dark SME indice)
    DARKSML(optional) If supplied, the Dark SML indice will be returned in the array specified by DARKSML (See definition of Dark SML indice)
    DARKSMU(optional) If supplied, the Dark SMU indice will be returned in the array specified by DARKSMU (See definition of Dark SMU indice)
    DARKMLAT(optional) If supplied, the magnetic latitude of the Dark SME indice will be returned in the array specified by DARKMLAT
    DARKMLT(optional) If supplied, the magnetic local time of the Dark SME indice will be returned in the array specified by DARKMLT
    DARKGLAT(optional) If supplied, the geographic latitude of the Dark SME indice will be returned in the array specified by DARKGLAT
    DARKGLON(optional) If supplied, the geographic longitude of the Dark SME indice will be returned in the array specified by DARKGLON
    DARKSTID(optional) If supplied, the IAGA station codes of the stations used to compute the Dark SME indices will be returned in the array specified by DARKSTID
    DARKNUM(optional) If supplied, the number of stations used to compute the Dark SME indices will be returned in the array specified by DARKNUM
    REGIONALSME(optional) If supplied, the Regional SME indice will be returned in the array specified by REGIONALSME (See definition of Regional SME indice)
    REGIONALSML(optional) If supplied, the Regional SML indice will be returned in the array specified by REGIONALSML (See definition of Regional SML indice)
    REGIONALSMU(optional) If supplied, the Regional SMU indice will be returned in the array specified by REGIONALSMU (See definition of Regional SMU indice)
    REGIONALMLAT(optional) If supplied, the magnetic latitude of the Regional SME indice will be returned in the array specified by REGIONALMLAT
    REGIONALMLT(optional) If supplied, the magnetic local time of the Regional SME indice will be returned in the array specified by REGIONALMLT
    REGIONALGLAT(optional) If supplied, the geographic latitude of the Regional SME indice will be returned in the array specified by REGIONALGLAT
    REGIONALGLON(optional) If supplied, the geographic longitude of the Regional SME indice will be returned in the array specified by REGIONALGLON
    REGIONALSTID(optional) If supplied, the IAGA station codes of the stations used to compute the Regional SME indices will be returned in the array specified by REGIONALSTID
    REGIONALNUM(optional) If supplied, the number of stations used to compute the Regional SME indices will be returned in the array specified by REGIONALNUM
    SMR(optional) If supplied, the SMR indice will be returned in the array specified by SMR (See definition of SMR indice)
    LTSMR(optional) If supplied, the SMR LT indice will be returned in the array specified by LTSMR (See definition of SMR LT indice)
    LTNUM(optional) If supplied, the number of stations used to compute the SMR LTN indice will be returned in the array specified by LTNUM
    NSMR(optional) If supplied, the number of stations used to compute the SMR indices will be returned in the array specified by NSMR
    BGSE(optional) If supplied, the Solar Wind B field (GSE) parameter will be returned in the array specified by BGSE
    BGSM(optional) If supplied, the Solar Wind B field (GSM) parameter will be returned in the array specified by BGSM
    VGSE(optional) If supplied, the Solar Wind V (GSE) parameter will be returned in the array specified by VGSE
    VGSM(optional) If supplied, the Solar Wind V (GSM) parameter will be returned in the array specified by
    PDYN(optional) If supplied, the Solar Wind Dynamic Pressure parameter will be returned in the array specified by PDYN
    EPSILON(optional) If supplied, the Solar Wind ε Parameter parameter will be returned in the array specified by EPSILON
    NEWELL(optional) If supplied, the Solar Wind Newell parameter will be returned in the array specified by NEWELL
    CLOCKGSE(optional) If supplied, the IMF Clock Angle (GSE) parameter will be returned in the array specified by CLOCKGSE
    CLOCKGSM(optional) If supplied, the IMF Clock Angle (GSM) parameter will be returned in the array specified by CLOCKGSM
    DENSITY(optional) If supplied, the Solar Wind Plasma Density parameter will be returned in the array specified by DENSITY
    Returns
    Boolean set to zero on success or 1 on error. If the keyword parameter “error” is provided an error message is returned back as a string.

    Example Usage

    PRO SuperMAGTestIndicesArray, userid
       s=SuperMAGGetIndicesArray(userid, 2012, 2, 3, 12, 30, 0, 3600, tval, error=errstr, $
                                 SME=sme, SML=sml,SMU=smu, $
                                 MLAT=mlat,MLT=mlt,GLAT=glat, $
                                 GLON=glon,STID=stid,NUM=num)
       s=SuperMAGGetIndicesArray(userid, 2012, 2, 3, 12, 30, 0, 3600, tval, error=errstr, $
                                 SUNSME=sunsme, SUNSML=sunsml, SUNSMU=sunsmu, $
                                 SUNMLAT=sunmlat, SUNMLT=sunmlt, SUNGLAT=sunglat, $
                                 SUNGLON=sunglon, SUNSTID=sunstid, SUNNUM=sunnum)
       s=SuperMAGGetIndicesArray(userid, 2012, 2, 3, 12, 30, 0, 3600, tval, error=errstr, $
                                 DARKSME=darksme, DARKSML=darksml, DARKSMU=darksmu, $
                                 DARKMLAT=darkmlat, DARKMLT=darkmlt, DARKGLAT=darkglat, $
                                 DARKGLON=darkglon, DARKSTID=darkstid, DARKNUM=darknum)
       s=SuperMAGGetIndicesArray(userid, 2012, 2, 3, 12, 30, 0, 3600, tval, error=errstr, $
                                 REGIONALSME=regionalsme, REGIONALSML=regionalsml, REGIONALSMU=regionalsmu, $
                                 REGIONALMLAT=regionalmlat, REGIONALMLT=regionalmlt, REGIONALGLAT=regionalglat, $
                                 REGIONALGLON=regionalglon, REGIONALSTID=regionalstid, REGIONALNUM=regionalnum)
       s=SuperMAGGetIndicesArray(userid, 2012, 2, 3, 12, 30, 0, 3600, tval, error=errstr, $
                                 SMR=smr,LTSMR=ltsmr,LTNUM=ltnum,NSMR=nsmr)
       s=SuperMAGGetIndicesArray(userid, 2012, 2, 3, 12, 30, 0, 3600, tval, error=errstr, $
                                 BGSE=bgse, BGSM=bgsm, VGSE=vgse, VGSM=vgsm)
       s=SuperMAGGetIndicesArray(userid, 2012, 2, 3, 12, 30, 0, 3600, tval, error=errstr, $
                                 PDYN=pdyn, EPSILON=epislon, NEWELL=newell, $
                                 CLOCKGSE=clockgse, CLOCKGSM=clockgsm, DENSITY=density)
       if n_elements(tval) eq 0 then begin
          print, 'No Indices'
          stop
       endif
       SuperMAGTimeToYMDHMS, tval, yr, mo, dy, hr, mt, sc
       stop
    END
    

    ◆  SuperMAGGetIndicesStruct()

    IDL function that retrievies a set of magnetic indices for a given event. The data is returned as a single array of structs. This function returns the same data as SuperMAGGetIndicesArray(), but is intended for "power" users who are comfortable dealing with IDL structures.
    Parameters
    useridyour supermag user id
    yrstart year of event
    mostart month of event
    dystart day of event
    hrstart hour of event
    mtstart minute of event
    scstart second of event (for now this is ignored as we are only dealing with the 1 minute data)
    extentextent or length of the event in seconds (3600= 1 hour, 86400 = 1 day)
    inxdataAn array of IDL structs, where each struct contains the requested data at a particular event time epoch
    error(optional) If supplied, An error message will be returned in the string error
    INDICESALL(optional) If the keywoard "INDICESALL" is supplied, all indices are returned in inxdata
    IMFALL(optional) If the keywoard "IMFALL" is supplied, all IMF parameters are returned in inxdata
    SWIALL(optional) If the keywoard "SWIALL" is supplied, all Solar Wind parameters are returned in inxdata
    SME(optional) If the keywoard "SME" is supplied, the SME indice will be returned in inxdata (See definition of SME indice)
    SML(optional) If the keywoard "SML" is supplied, the SML indice will be returned in inxdata (See definition of SML indice)
    SMU(optional) If the keywoard "SMU" is supplied, the SMU indice will be returned in inxdata (See definition of SMU indice)
    MLAT(optional) If the keywoard "MLAT" is supplied, the magnetic latitude of the SME indice will be returned in inxdata
    MLT(optional) If the keywoard "MLT" is supplied, the magnetic local time of the SME indice will be returned in inxdata
    GLAT(optional) If the keywoard "GLAT" is supplied, the geographic latitude of the SME indice will be returned in inxdata
    GLON(optional) If the keywoard "GLON" is supplied, the geographic longitude of the SME indice will be returned in inxdata
    STID(optional) If the keywoard "STID" is supplied, the IAGA station codes of the stations used to compute the SME indices will be returned in inxdata
    NUM(optional) If the keywoard "NUM" is supplied, the number of stations used to compute SME indices will be returned in inxdata
    SUNSME(optional) If the keywoard "SUNSME" is supplied, the Sunlit SME indice will be returned in inxdata (See definition of Sunlit SME indice)
    SUNSML(optional) If the keywoard "SUNSML" is supplied, the Sunlit SML indice will be returned in inxdata (See definition of Sunlit SML indice)
    SUNSMU(optional) If the keywoard "SUNSMU" is supplied, the Sunlit SMU indice will be returned in inxdata (See definition of Sunlit SMU indice)
    SUNMLAT(optional) If the keywoard "SUNMLAT" is supplied, the magnetic latitude of the Sunlit SME indice will be returned in inxdata
    SUNMLT(optional) If the keywoard "SUNMLT" is supplied, the magnetic local time of the Sunlit SME indice will be returned in inxdata
    SUNGLAT(optional) If the keywoard "SUNGLAT" is supplied, the geographic latitude of the Sunlit SME indice will be returned in inxdata
    SUNGLON(optional) If the keywoard "SUNGLON" is supplied, the geographic longitude of the Sunlit SME indice will be returned in inxdata
    SUNSTID(optional) If the keywoard "SUNSTID" is supplied, the IAGA station codes of the stations used to compute the Sunlit SME indices will be returned in inxdata
    SUNNUM(optional) If the keywoard "SUNNUM" is supplied, the number of stations used to compute the Sunlit SME indices will be returned in inxdata
    DARKSME(optional) If the keywoard "DARKSME" is supplied, the Dark SME indice will be returned in inxdata (See definition of Dark SME indice)
    DARKSML(optional) If the keywoard "DARKSML" is supplied, the Dark SML indice will be returned in inxdata (See definition of Dark SML indice)
    DARKSMU(optional) If the keywoard "DARKSMU" is supplied, the Dark SMU indice will be returned in inxdata (See definition of Dark SMU indice)
    DARKMLAT(optional) If the keywoard "DARKMLAT" is supplied, the magnetic latitude of the Dark SME indice will be returned in inxdata
    DARKMLT(optional) If the keywoard "DARKMLT" is supplied, the magnetic local time of the Dark SME indice will be returned in inxdata
    DARKGLAT(optional) If the keywoard "DARKGLAT" is supplied, the geographic latitude of the Dark SME indice will be returned in inxdata
    DARKGLON(optional) If the keywoard "DARKGLON" is supplied, the geographic longitude of the Dark SME indice will be returned in inxdata
    DARKSTID(optional) If the keywoard "DARKSTID" is supplied, the IAGA station codes of the stations used to compute the Dark SME indices will be returned in inxdata
    DARKNUM(optional) If the keywoard "DARKNUM" is supplied, the number of stations used to compute the Dark SME indices will be returned in inxdata
    REGIONALSME(optional) If the keywoard "REGIONALSME" is supplied, the Regional SME indice will be returned in inxdata (See definition of Regional SME indice)
    REGIONALSML(optional) If the keywoard "REGIONALSML" is supplied, the Regional SML indice will be returned in inxdata (See definition of Regional SML indice)
    REGIONALSMU(optional) If the keywoard "REGIONALSMU" is supplied, the Regional SMU indice will be returned in inxdata (See definition of Regional SMU indice)
    REGIONALMLAT(optional) If the keywoard "REGIONALMLAT" is supplied, the magnetic latitude of the Regional SME indice will be returned in inxdata
    REGIONALMLT(optional) If the keywoard "REGIONALMLT" is supplied, the magnetic local time of the Regional SME indice will be returned in inxdata
    REGIONALGLAT(optional) If the keywoard "REGIONALGLAT" is supplied, the geographic latitude of the Regional SME indice will be returned in inxdata
    REGIONALGLON(optional) If the keywoard "REGIONALGLON" is supplied, the geographic longitude of the Regional SME indice will be returned in inxdata
    REGIONALSTID(optional) If the keywoard "REGIONALSTID" is supplied, the IAGA station codes of the stations used to compute the Regional SME indices will be returned in inxdata
    REGIONALNUM(optional) If the keywoard "REGIONALNUM" is supplied, the number of stations used to compute the Regional SME indices will be returned in inxdata
    SMR(optional) If the keywoard "SMR" is supplied, the SMR indice will be returned in inxdata (See definition of SMR indice)
    LTSMR(optional) If the keywoard "LTSMR" is supplied, the SMR LT indice will be returned in inxdata (See definition of SMR LT indice)
    LTNUM(optional) If the keywoard "LTNUM" is supplied, the number of stations used to compute the SMR LTN indice will be returned in inxdata
    NSMR(optional) If the keywoard "NSMR" is supplied, the number of stations used to compute the SMR indices will be returned in inxdata
    BGSE(optional) If the keywoard "BGSE" is supplied, the Solar Wind B field (GSE) parameter will be returned in inxdata
    BGSM(optional) If the keywoard "BGSM" is supplied, the Solar Wind B field (GSM) parameter will be returned in inxdata
    VGSE(optional) If the keywoard "VGSE" is supplied, the Solar Wind V (GSE) parameter will be returned in inxdata
    VGSM(optional) If the keywoard "VGSM" is supplied, the Solar Wind V (GSM) parameter will be returned in the array specified by
    PDYN(optional) If the keywoard "PDYN" is supplied, the Solar Wind Dynamic Pressure parameter will be returned in inxdata
    EPSILON(optional) If the keywoard "EPSILON" is supplied, the Solar Wind ε Parameter parameter will be returned in inxdata
    NEWELL(optional) If the keywoard "NEWELL" is supplied, the Solar Wind Newell parameter will be returned in inxdata
    CLOCKGSE(optional) If the keywoard "CLOCKGSE" is supplied, the IMF Clock Angle (GSE) parameter will be returned in inxdata
    CLOCKGSM(optional) If the keywoard "CLOCKGSM" is supplied, the IMF Clock Angle (GSM) parameter will be returned in inxdata
    DENSITY(optional) If the keywoard "DENSITY" is supplied, the Solar Wind Plasma Density parameter will be returned in inxdata
    Returns
    Boolean set to zero on success or 1 on error. If the keyword parameter “error” is provided an error message is returned back as a string.

    Example Usage

    PRO SuperMAGTestIndicesStruct, userid
       s=SuperMAGGetIndicesStruct(userid, 2012, 2, 3, 12, 30, 0, 3600, inxdata, error=errstr,$ 
                                  /INDICESALL,/IMFALL,/SWIALL)
       if (s eq 0) then begin
          print, errstr
          stop
       endif
       if n_elements(inxdata) eq 0 then begin
         print,'No indices'
         stop
       endif
       tval=inxdata[*].tval
       SME=inxdata[*].SME
       SUNSME=inxdata[*].SMES
       DARKSME=inxdata[*].SMED
       SMR=inxdata[*].SMR
       print,'SME=',SME,'Sunlit SME=',SUNSME,'Dark SME =',DARKSME,'SMR=',SMR
       stop
    END
    

Python Client (Python version 3 required)

Download data and indices from SuperMAG directly into your Python program using the SuperMAG Webservice Python Client.

  • Download Python Client
  • Download Python Client Documentation
  • View Python Client Documentation Hide Python Client Documentation
    SuperMAG Python Client 1.0
    SuperMAG Web Service API Python Client Documentation
    Python 3 required. Package 'pandas' required (pip install pandas). If your worksite, like APL, requires SSL certs to access URLs, package 'certifi' must also be installed (pip install certifi)

    ◆  (status,stations)=SuperMAGGetInventory(userid,start,extent)

    Python function that retrieves a list of available stations for a given event.
    Parameters
    useridyour supermag user id
    startstart date of event, either in the format 'YYYY-MM-DDThhmm' or as a list [YYYY, MM, DD, hh, mm] (seconds are optional)
    extentextent or length of the event in seconds (3600= 1 hour, 86400 = 1 day)
    Returns
    List of available stations. If there was an error, return is the error message.

    Example Usage

    
    
    start=[2019,11,15,10,40,00] # alt: start='2019-11-15T10:40'
    (status,stations) = SuperMAGGetInventory(userid,start,3600)
    print(stations)   
    for i in range(len(stations)-1):
       print(i,stations[i])
    

    ◆  (status,sm_data)=SuperMAGGetData(userid,start,extent,flags,station,FORMAT='list')

    Python function that retrievies station magnetometer data for a given event and IAGA station code. By default it returns the data as a pandas dataframe. You can add the optional 'FORMAT' keyword to tell it to return the data as a python list instead of a pandas dataframe (the default).
    Parameters
    useridyour supermag user id
    yrstart date of event, either in the format 'YYYY-MM-DDThhmm' or as a list [YYYY, MM, DD, hh, mm] (seconds are optional)
    extentextent or length of the event in seconds (3600= 1 hour, 86400 = 1 day)
    stationIAGA code of the requested station
    flagslist in string or list form of which data items to return and processing flags to use (see below). The full list of data items is either 'all' or 'mlt,mag,geo,decl,sza'. Flags can alternately be in list format, e.g. ["mlt" "mag" "geo" "decl" "sza"]. Processing flags available are 'delta=start', 'baseline=none', 'baseline=yearly'. Flags are not case-sensitive
    MLT(optional) If supplied, The MLT/MCOLAT of the station will be returned in the two dimensional array of length extent/60 specified by MLT.
    MAG(optional) If supplied, The Magnetic coordinates of the station will be returned in the two dimensional array of length extent/60 specified by MAG.
    GEO(optional) If supplied, The Geographic coordinates of the station will be returned in the two dimensional array of length extent/60 specified by GEO.
    DECL(optional) If supplied, The Declination from IGRF Model will be returned in the array of length extent/60 specified by DECL.
    SZA(optional) If supplied, The solar zenith angle will be returned in the array of length extent/60 specified by SZA.
    DELTA(optional) If the keywoard DELTA is supplied, The baseline NEZ vector start values will be subtracted from the NEZ vector components in the resulting n, e, and z lists.
    BASELINE(optional) If BASELINE is specified, It must be set to one of three values:
    "baseline='all'" (default)Subtract both the daily and yearly NEZ baselines
    "baseline='yearly'"Subtract the yearly NEZ baseline, but do not subtract the daily NEZ baseline
    "baseline='none'"Do not subtract either the yearly or the daily NEZ baseline
    FORMAT='list'Optional, if given as "FORMAT='list'", routine will return a python list instead of a pandas dataframe
    Returns
    Structure with all return data. If there was an error, return is the error message. The format of the returns is as follows.
    tvalThe time of the samples is returned as the structure element tval. The time array is an array of double precision numbers giving the time since 1970-01-01 0:00UTC (This is a standard representation of time on computer systems).
    extThe binned duration for each sample is returned, typically '60' representing the 1-minute bins of standard SuperMAG data
    iagaThe 3-letter station code provided is returned in the structure, useful for identification when you have multiple sets of data.
    NThe N vector component is returned in the two structure element arrays of length extent/60 specified by N. The second dimension refers to the coordinate system, so ‘N.nez’ contains the component of the vector in the standard NEZ coordinates, 'N.geo' contains the geographic mapping of the N vector component.
    EThe E vector component is returned in the two structure element arrays of length extent/60 specified by E. The second dimension refers to the coordinate system, so ‘E.nez’ contains the component of the vector in the standard NEZ coordinates, 'E.geo' contains the geographic mapping of the E vector component.
    ZThe A vector component is returned in the two structure element arrays of length extent/60 specified by Z. The second dimension refers to the coordinate system, so ‘Z.nez]’ contains the component of the vector in the standard NEZ coordinates, 'Z.geo' contains the geographic mapping of the Z vector component.
    mlt(optional) If supplied, The MLT/MCOLAT of the station will be returned in the two structure element arrays 'mlt' and 'mcolat' of length extent/60 specified by MLT.
    mag(optional) If supplied, The Magnetic coordinates of the station will be returned in the two structure element arrays 'mlat' and 'mlon' of length extent/60 specified by MAG.
    geo(optional) If supplied, The Geographic coordinates of the station will be returned in the two structure element arrays 'glon' and 'glat' of length extent/60 specified by GEO.
    decl(optional) If supplied, The Declination from IGRF Model will be returned as a structure element array 'decl' of length extent/60 specified by DECL.
    sza(optional) If supplied, The solar zenith angle will be returned as a structure element array 'sza' of length extent/60 specified by SZA.

    Example Usage

    
    
        tval=data.tval
        mlt=data.mlt
        ### Python way                                                              
        N_nez = [temp['nez'] for temp in data.N]
        N_geo = [temp['geo'] for temp in data.N]
        ### or, supermag helper shorthand way                                       
        N_nez = sm_grabme(data,'N','nez')
        N_geo = sm_grabme(data,'N','geo')
        #                                                                           
        plt.plot(tval,N_nez)
        plt.plot(tval,N_geo)
        plt.ylabel('N_geo vs N_nez')
        plt.xlabel('date')
        plt.show()
    	
        
    sample plot of data

    ◆  (status,sm_indices)=fetchSuperMAG(userid,start,extent,flags,FORMAT='list')

    Python function that retrievies a set of magnetic indices for a given event. By default it returns the data as a pandas dataframe. You can add the optional 'FORMAT' keyword to tell it to return the data as a python list instead of a pandas dataframe (the default).
    Parameters
    useridyour supermag user id
    yrstart date of event, either in the format 'YYYY-MM-DDThhmm' or as a list [YYYY, MM, DD, hh, mm] (seconds are optional)
    extentextent or length of the event in seconds (3600= 1 hour, 86400 = 1 day)
    flagslist in string or list form of which data items to return and processing flags to use (see below). The full list of data items is either 'all' or any subset, e.g. 'sme, sunsme, darksme'. Flags can alternately be in list format, e.g. ["sme" "sunsme" "darksme"]. Several flags have alternative names which you are free to use (these are derived from the set of tags the SuperMAG web server uses natively.) Flags are not case-sensitive.
     
    SME(optional) If supplied, the SME indice will be returned in the structure array '.SME' (See definition of SME indice)
    SML(optional) If supplied, the SML indice will be returned in the structure array '.SML' (See definition of SML indice)
    SMU(optional) If supplied, the SMU indice will be returned in the structure array '.SMU' (See definition of SMU indice)
    NUM(optional) If supplied, the number of stations used to compute SME indices will be returned in the structure array '.SMEnum'
    (optional) the following options return additional data items, but only if SME, SML and/or SMU is set (for SME, returns both .SMU and .SML entries; for SMU, only .SMU entries; for SML, only .SML entries)
    MLAT(optional) If supplied, the magnetic latitude of the SME indice will be returned in the structure array '.SMLmlat' and '.SMUmlat'
    MLT(optional) If supplied, the magnetic local time of the SME indice will be returned in the structure array '.SMLmlt' and '.SMUmlt'
    GLAT(optional) If supplied, the geographic latitude of the SME indice will be returned in the structure array '.SMLglat' and '.SMUglat'
    GLON(optional) If supplied, the geographic longitude of the SME indice will be returned in the structure array '.SMLglon' and '.SMUglon'
    STID(optional) If supplied, the IAGA station codes of the stations used to compute the SME indices will be returned in the structure array '.SMLstid' and '.SMUstid'
    baseall(optional) If supplied, is the equivalent of the set of 'sme,sml,smu,mlat,mlt,glat,glon,stid,num'
    SUNSME (alt: smes)(optional) If supplied, the Sunlit SME indice will be returned in the structure array '.SMEs' (See definition of Sunlit SME indice)
    SUNSML (alt: smls)(optional) If supplied, the Sunlit SML indice will be returned in the structure array '.SMLs' (See definition of Sunlit SML indice)
    SUNSMU (alt: smus)(optional) If supplied, the Sunlit SMU indice will be returned in the structure array '.SMUs' (See definition of Sunlit SMU indice)
    SUNNUM (alt: nums)(optional) If supplied, the number of stations used to compute the Sunlit SME indices will be returned in the structure array '.sunnum'
    (optional) the following options return additional data items, but only if SMEs, SMLs and/or SMUs is set (for SMEs, returns both .SMUs and .SMLs entries; for SMUs, only .SMUs entries; for SMLs, only .SMLs entries)
    SUNMLAT (alt: mlats)(optional) If supplied, the magnetic latitude of the Sunlit SME indice will be returned in the structure array '.SMLsmlat' and '.SMUsmlat'
    SUNMLT (alt: mlts)(optional) If supplied, the magnetic local time of the Sunlit SME indice will be returned in the structure array '.SMLsmlt' and '.SMUsmlt'
    SUNGLAT (alt: glats)(optional) If supplied, the geographic latitude of the Sunlit SME indice will be returned in the structure array '.SMLsglat' and '.SMUsglat'
    SUNGLON (alt: glons)(optional) If supplied, the geographic longitude of the Sunlit SME indice will be returned in the structure array '.SMLsglon' and '.SMUsglon'
    SUNSTID (alt: stids)(optional) If supplied, the IAGA station codes of the stations used to compute the Sunlit SME indices will be returned in the structure array '.SMLstid' and '.SMUstid'
    sunall(optional) If supplied, is the equivalent of the set of 'smes,smls,smus,mlats,mlts,glats,glons,stids,nums'
    DARKSME (alt: smed)(optional) If supplied, the Dark SME indice will be returned in the structure array '.darksme' (See definition of Dark SME indice)
    DARKSML (alt: smld)(optional) If supplied, the Dark SML indice will be returned in the structure array '.darksml' (See definition of Dark SML indice)
    DARKSMU (alt: smud)(optional) If supplied, the Dark SMU indice will be returned in the structure array '.darksmu' (See definition of Dark SMU indice)
    DARKNUM (alt: numd)(optional) If supplied, the number of stations used to compute the Dark SME indices will be returned in the structure array '.darknum'
    (optional) the following options return additional data items, but only if SMEd, SMLd and/or SMUd is set (for SMEd, returns both .SMUd and .SMLd entries; for SMUd, only .SMUd entries; for SMLd, only .SMLd entries)
    DARKMLAT (alt: mlatd)(optional) If supplied, the magnetic latitude of the Dark SME indice will be returned in the structure array '.SMLdmlat' and '.SMUdmlat'
    DARKMLT (alt: mltd)(optional) If supplied, the magnetic local time of the Dark SME indice will be returned in the structure array '.SMLdmlt' and '.SMUdmlt'
    DARKGLAT (alt: glatd)(optional) If supplied, the geographic latitude of the Dark SME indice will be returned in the structure array '.SMLdglat' and '.SMUdglat'
    DARKGLON (alt: glond)(optional) If supplied, the geographic longitude of the Dark SME indice will be returned in the structure array '.SMLdglon' and '.SMUdglon'
    DARKSTID (alt: stidd)(optional) If supplied, the IAGA station codes of the stations used to compute the Dark SME indices will be returned in the structure array '.SMLdtid' and '.SMUdtid'
    darkall(optional) If supplied, is the equivalent of the set of 'smed,smld,smud,mlatd,mltd,glatd,glond,stidd,numd'
    REGIONALSME (alt: smer)(optional) If supplied, the Regional SME indice will be returned in the structure array '.SMEr' (See definition of Regional SME indice)
    REGIONALSML (alt: smlr)(optional) If supplied, the Regional SML indice will be returned in the structure array '.SMLr' (See definition of Regional SML indice)
    REGIONALSMU (alt: smur)(optional) If supplied, the Regional SMU indice will be returned in the structure array '.SMUr' (See definition of Regional SMU indice)
    REGIONALNUM (alt: numr)(optional) If supplied, the number of stations used to compute the Regional SME indices will be returned in the structure array '.SMErnum'
    (optional) the following options return additional data items, but only if SMEr, SMLr and/or SMUr is set (for SMEr, returns both .SMUr and .SMLr entries; for SMUr, only .SMUr entries; for SMLr, only .SMLr entries)
    REGIONALMLAT (alt: mlatr)(optional) If supplied, the magnetic latitude of the Regional SME indice will be returned in the structure array '.SMLsmlat' and '.SMUsmlat'
    REGIONALMLT (alt: mltr)(optional) If supplied, the magnetic local time of the Regional SME indice will be returned in the structure array '.SMLsmlt' and '.SMUsmlt'
    REGIONALGLAT (alt: glatr)(optional) If supplied, the geographic latitude of the Regional SME indice will be returned in the structure array '.SMLsglat' and '.SMUsglat'
    REGIONALGLON (alt: glonr)(optional) If supplied, the geographic longitude of the Regional SME indice will be returned in the structure array '.SMLsglon' and '.SMUsglon'
    REGIONALSTID (alt: stidr)(optional) If supplied, the IAGA station codes of the stations used to compute the Regional SME indices will be returned in the structure array '.SMLstid' and '.SMUstid'
    regall(optional) If supplied, is the equivalent of the set of 'sme,sml,smu,mlat,mlt,glat,glon,stid,num'
    SMR(optional) If supplied, the SMR indice will be returned in the structure array '.smr' (See definition of SMR indice)
    LTSMR(optional) If supplied, the SMR LT indices will be returned in the structure arrays '.smr00','.smr06','.smr12','.smr18' (See definition of SMR LT indice)
    LTNUM(optional) If supplied, the number of stations used to compute the SMR LTN indice will be returned in the structure arrays '.smrnum00','.srmnum06','.smrnum12','.smrnum18'
    NSMR(optional) If supplied, the number of stations used to compute the SMR indices will be returned in the structure array '.nsmr'
    plusall(optional) If supplied, is the equivalent of the set of 'sme,sml,smu,mlat,mlt,glat,glon,stid,num'
    all(optional) If supplied, is the equivalent to all the above, 'baseall,sunall,darkall,regall,plusall' (but not the swi and imf keys below)
    BGSE(optional) If supplied, the Solar Wind B field (GSE) parameter will be returned in the structure array '.bgse'
    BGSM(optional) If supplied, the Solar Wind B field (GSM) parameter will be returned in the structure array '.bgsm'
    VGSE(optional) If supplied, the Solar Wind V (GSE) parameter will be returned in the structure array '.vgse'
    VGSM(optional) If supplied, the Solar Wind V (GSM) parameter will be returned in the structure array '.vgsm'
    imfall(optional) If supplied, is the equivalent of the set of 'sme,sml,smu,mlat,mlt,glat,glon,stid,num'
    PDYN(optional) If supplied, the Solar Wind Dynamic Pressure parameter will be returned in the structure array '.pdyn'
    EPSILON(optional) If supplied, the Solar Wind ε Parameter parameter will be returned in the structure array '.epsilon'
    NEWELL(optional) If supplied, the Solar Wind Newell parameter will be returned in the structure array '.newell'
    CLOCKGSE(optional) If supplied, the IMF Clock Angle (GSE) parameter will be returned in the structure array '.clockgse'
    CLOCKGSM(optional) If supplied, the IMF Clock Angle (GSM) parameter will be returned in the structure array '.clockgsm'
    DENSITY(optional) If supplied, the Solar Wind Plasma Density parameter will be returned in the structure array '.density'
    swiall(optional) If supplied, is the equivalent of the set of 'sme,sml,smu,mlat,mlt,glat,glon,stid,num'
    FORMAT='list'Optional, if given as "FORMAT='list'", routine will return a python list instead of a pandas dataframe
    Returns
    Structure with all return data. If there was an error, return is the error message. The format of the returns is as follows.
    tvalThe time of the samples is returned as the structure element tval. The time array is a list of double precision numbers giving the time since 1970-01-01 0:00UTC (This is a standard representation of time on computer systems).
    The following data structure arrays are returned, dependent on which optional flags you requested. Note that no data is returned unless flags are specified, there is no 'default dataset'.
    decl(optional) If supplied, The Declination from IGRF Model will be returned as a structure element array 'decl' of length extent/60 specified by DECL.
    Base data:Structure elements as defined above and named: .SME, .SML, .SMLmlat, .SMLmlt, .SMLglat, .SMLglon, .SMLstid, .SMU, .SMUmlat, .SMUmlt, .SMUglat, .SMUglon, .SMUstid, .SMEnum
    Sunlit data: Structure elements as defined above and named: .SMEs, .SMLs, .SMLsmlat, .SMLsmlt, .SMLsglat, .SMLsglon, .SMLsstid, .SMUs, .SMUsmlat, .SMUsmlt, .SMUsglat, .SMUsglon, .SMUsstid, .SMEsnum
    Dark data: Structure elements as defined above and named: .SMEd, .SMLd, .SMLdmlat, .SMLdmlt, .SMLdglat, .SMLdglon, .SMLdstid, .SMUd, .SMUdmlat, .SMUdmlt, .SMUdglat, .SMUdglon, .SMUdstid, .SMEdnum
    Regional data: Structure elements as defined above and named: .SMEr, .SMLr, .SMLrmlat, .SMLrmlt, .SMLrglat, .SMLrglon, .SMLrstid, .SMUr, .SMUrmlat, .SMUrmlt, .SMUrglat, .SMUrglon, .SMUrstid, .SMErnum
    Plus data:Structure elements as defined above and named: .smr, .smrnum00, .smrnum06, .smrnum12, .smrnum18
    IMF data:Structure elements as defined above and named: .bgse, .bgsm, .vgse, .vgsm
    SWI data:Structure elements as defined above and named: .clockgse, .clockgsm, .density, .dynpres, .epsilon, .newell

    Example Usage

    
    
       (status,idxdata) = SuperMAGGetIndices(userid,start,3600,'swiall,density,dar\
    kall,regall,smes')
       #print(status)
       #print(idxdata)                                                             
       allkeys = idxdata.keys() # an example of showing the data keys fetched
    
       # let us plot slices
       tval=idxdata.tval
       hours=list(range(24))
       y=idxdata.SMLr
       for i in range(len(tval)-1):
          plt.plot( hours, y[i] )
          plt.ylabel('SMLr')
          plt.xlabel('hour')
          plt.title('SMLr variation by hour, for successive days')
    
       plt.show()
    
        
    sample plot of indices

    ◆  data = sm_grabme(mydataframe,key,subkey))

    Optional, Python SuperMAG helper function used to extract nested structure items from the pandas dataframe.
    Parameters
    mydataframeA SuperMAG (or any) pandas dataframe with nested items.
    keykey to dataframe row item
    subkeysubkey of item in selected key data
    Returns
    Data subset item you requested from the dataframe.

    Example Usage

    
        (status,data) = SuperMAGGetData(userid,start,3600,'all')
        tval =data.tval # get list of times
        
        # data contains, in each row, item 'N' that has subkeys 'nez' and 'geo'
        ### Python way to access data
        N_nez = [temp['nez'] for temp in data.N]
        N_geo = [temp['geo'] for temp in data.N]
        ### Our helper function
        N_nez = sm_grabme(data,'N','nez')
        N_geo = sm_grabme(data,'N','geo')
    
        # Either way, you can now use it and plot it
        plt.plot(tval,N_nez)
        plt.plot(tval,N_geo)
        plt.ylabel('N_geo vs N_nez')
        plt.xlabel('date')
        plt.show()
    
        

    ◆  sm_microtest(testchoice,userid)

    This is a simple unit test that runs each of the 3 fetches (stations, data, indices) for a small sample case. If this works, everything is set up accurately on your system.
    Parameters
    testchoiceIndicate which test to run: 1 = get sample stations, 2 = get sample data, 3 = get sample indices, 4 = run all 3 tests.
    useridyour supermag user id
    Returns
    Displays and/or plots the sample data to verify functionality.

    Example Usage

    
        from supermag_api import *
        userid='YOUR_SUPERMAG_USER_ID'
        sm_microtest(4,userid)
        

    ◆  Optional, pandas dataframes versus Comma Separated Values (csv) files

    Examples: Here is a simple example of saving to a '.csv' file, then reading the pandas data back from it.

    Example Usage

    
    
    	# first fetch the data
    	(status,idxdata) = SuperMAGGetIndices(userid,start,3600,'all,swiall,imfall')
    	
    	# to save the data, there are many formats.  Here is how to save as csv
    	idxdata.to_csv('mydata.csv')
    
    	# to read it back in later
    	import pandas as pd
    	import re
    	# you can read it into any variable name, we just used 'mydata2b' as an example
    	mydata2b=pd.read_csv('mydata.csv',index_col=0) 
    	# now you can do all the above items again, with one exception: each line of the CVS file got split into a dict (key-value pairs) but items like 'vsge' are part of the pandas structure
    	# the 'd.get()' approach will _not_ work once read from csv
    	
    	# goal is a list of stations
    	stationlist2=sm_csvitem_to_list(mydata2b.SMLrstid) 
    	# grabs a list of stations for row 0
    	slist = stationlist2[0] 
    	# grabs the first station for row 0
    	s1 = stationlist2[0][0] 
    
    	# goal is a dict of coords or other values
    	vgse=sm_csvitem_to_dict(mydata2b.vgse) 
    	# grab just the 'X' value for the 1st row of data
    	x = vgse[0]['X'] 
    	#grab all the 'X' values as a new list
    	vgse_x = [mydat['X'] for mydat in vgse] 
    	# grab all 3 as their own list
    	vgse_xyz = [(mydat['X'],mydat['Y'],mydat['Z']) for mydat in vgse] 
    
        

    ◆  Optional, Extended Examples

    Examples: Here are some sample manipulations of the SuperMAG data and indices items. Code is provided, with python comments after the # indicating sample data that is retrieved by the code.

    Example Usage

    
        ####################
        # DATA fetches
        # BARE CALL, dataframe returned
        (status,mydata1a) = SuperMAGGetData(userid,start,3600,'','HBK')
        mydata1a        # is 1440 rows x 6 columns dataframe
        mydata1a.keys() # Index(['tval', 'ext', 'iaga', 'N', 'E', 'Z'], dtype='object')
    
        # CALL with ALLINDICES, dataframe returned
        (status,mydata1a) = SuperMAGGetData(userid,start,3600,'all','HBK')
        mydata1a        # is 1440 rows x 12 columns dataframe
        mydata1a.keys() # Index(['tval', 'ext', 'iaga', 'glon', 'glat', 'mlt', 'mcolat', 'decl', 'sza', 'N', 'E', 'Z'], dtype='object')
    
        # BARE CALL, list returned
        (status,mydata1b) = SuperMAGGetData(userid,start,3600,'','HBK',FORMAT='list')
        len(mydata1b)  # is 1440 rows of dicts (key-value pairs)
        mydata1b[0:1]  # {'tval': 1572726240.0, 'ext': 60.0, 'iaga': 'DOB', 'N': {'nez': -3.942651, 'geo': -5.964826}, 'E': {'nez': 4.492887, 'geo': 0.389075}, 'Z': {'nez': 7.608168, 'geo': 7.608168}}
    
        # CALL with ALLINDICES, list returned
        (status,mydata1b) = SuperMAGGetData(userid,start,3600,'all','HBK',FORMAT='list')
        mydata1b        # is 1440 rows of dicts (key-value pairs)
        mydata1b[0:1]  # {'tval': 1572726240.0, 'ext': 60.0, 'iaga': 'DOB', 'glon': 9.11, 'glat': 62.07, 'mlt': 21.694675, 'mcolat': 30.361519, 'decl': 3.067929, 'sza': 124.698227, 'N': {'nez': -3.942651, 'geo': -5.964826}, 'E': {'nez': 4.492887, 'geo': 0.389075}, 'Z': {'nez': 7.608168, 'geo': 7.608168}}
      
        ####################
        # INDICES fetches
        (status,idxdata) = SuperMAGGetIndices(userid,start,3600)
        idxdata  # empty!
    
        (status,idxdata) = SuperMAGGetIndices(userid,start,3600,'all,swiall,imfall')
        idxdata  # 1440 rows x 77 columns dataframe
        idxdata.keys() # Index(['tval', 'SME', 'SML', 'SMLmlat', 'SMLmlt', 'SMLglat', 'SMLglon', 'SMLstid', 'SMU', 'SMUmlat', 'SMUmlt', 'SMUglat', 'SMUglon', 'SMUstid', 'SMEnum', 'SMEs', 'SMLs', 'SMLsmlat', 'SMLsmlt', 'SMLsglat', 'SMLsglon', 'SMLsstid', 'SMUs', 'SMUsmlat', 'SMUsmlt', 'SMUsglat', 'SMUsglon', 'SMUsstid', 'SMEsnum', 'SMEd', 'SMLd', 'SMLdmlat', 'SMLdmlt', 'SMLdglat', 'SMLdglon', 'SMLdstid', 'SMUd', 'SMUdmlat', 'SMUdmlt', 'SMUdglat', 'SMUdglon', 'SMUdstid', 'SMEdnum', 'SMEr', 'SMLr', 'SMLrmlat', 'SMLrmlt', 'SMLrglat', 'SMLrglon', 'SMLrstid', 'SMUr', 'SMUrmlat', 'SMUrmlt', 'SMUrglat', 'SMUrglon', 'SMUrstid', 'SMErnum', 'smr', 'smr00', 'smr06', 'smr12', 'smr18', 'smrnum', 'smrnum00', 'smrnum06', 'smrnum12', 'smrnum18', 'bgse', 'bgsm', 'vgse', 'vgsm', 'clockgse', 'clockgsm', 'density', 'dynpres', 'epsilon', 'newell'], dtype='object')
        #
        # just INDICESALL = 67 columns, above 'tval' through 'smrnum18'
        # just IMFALL = 5 columns, Index(['tval', 'bgse', 'bgsm', 'vgse', 'vgsm'], dtype='object')
        # just SWIALL = 7 columns, Index(['tval', 'clockgse', 'clockgsm', 'density', 'dynpres', 'epsilon', 'newell'], dtype='object')
        #
        # Dataframes are awesome!  To manipulate, just pull out what you need
        import pandas as pd  # call once at the top of your code if you are using dataframes
        tval = idxdata.tval
        density = idxdata.density
        vgse = idxdata.vgse
        # or all as 1 line of code
        tval, density, vgse = idxdata.tval, idxdata.density, idxdata.vgse
        # note that vgse is itself a dictionary of values for X/Y/Z, so you can get subitems from it like this
        vgse_x = [d.get('X') for d in idxdata.vgse]
    
    
        ####################
        # Using Lists instead of DataFrames
        #
        # We also offer a list format, for users who prefer to work in python lists
        (status,mydata2c) = SuperMAGGetIndices(userid,start,3600,'all,swiall,imfall',FORMAT='list')
        len(mydata2c)  # is 1440 rows of dicts (key-value pairs)
        mydata2c[0:1] # {'tval': 1572726240.0, 'SME': 58.887299, 'SML': -27.709055, 'SMLmlat': 73.529922, 'SMLmlt': 23.321493, 'SMLglat': 76.510002, 'SMLglon': 25.01, 'SMLstid': 'HOP', 'SMU': 31.178246, 'SMUmlat': 74.702339, 'SMUmlt': 2.090216, 'SMUglat': 79.480003, 'SMUglon': 76.980003, 'SMUstid': 'VIZ', 'SMEnum': 118, 'SMEs': 34.451469, 'SMLs': -16.599854, 'SMLsmlat': 62.368008, 'SMLsmlt': 9.399416, 'SMLsglat': 62.299999, 'SMLsglon': 209.800003, 'SMLsstid': 'T39', 'SMUs': 17.851616, 'SMUsmlat': 73.989975, 'SMUsmlt': 18.228394, 'SMUsglat': 67.93, 'SMUsglon': 306.429993, 'SMUsstid': 'ATU', 'SMEsnum': 54, 'SMEd': 58.887299, 'SMLd': -27.709055, 'SMLdmlat': 73.529922, 'SMLdmlt': 23.321493, 'SMLdglat': 76.510002, 'SMLdglon': 25.01, 'SMLdstid': 'HOP', 'SMUd': 31.178246, 'SMUdmlat': 74.702339, 'SMUdmlt': 2.090216, 'SMUdglat': 79.480003, 'SMUdglon': 76.980003, 'SMUdstid': 'VIZ', 'SMEdnum': 64, 'SMEr': [29.685059, 29.857538, 31.387127, 41.707573, 10.320444, 10.885443, 9.604616, 13.479583, 15.471248, 15.471248, 15.714731, 5.434914, 12.13654, 11.156847, 9.62884, 14.752592, 14.752592, 24.204388, 21.41181, 21.41181, 27.121195, 46.345322, 51.403328, 51.403328], 'SMLr': [-27.709055, 1.320708, -0.208882, -10.529325, -10.529325, -10.529325, -9.248499, -13.123466, -16.599854, -16.599854, -16.599854, -5.449972, -5.449972, -4.470279, -2.942272, -6.352773, -6.352773, -6.352773, -3.560194, -3.560194, -7.514064, -22.651047, -27.709055, -27.709055], 'SMLrmlat': [73.529922, 51.264774, 47.791527, 66.696564, 66.696564, 66.696564, 41.771515, 70.602707, 62.368008, 62.368008, 62.368008, 67.471809, 67.471809, 60.639145, 68.500282, 72.20977, 72.20977, 72.20977, 75.762718, 75.762718, 77.33667, 71.889503, 73.529922, 73.529922], 'SMLrmlt': [23.321493, 2.119074, 3.578985, 4.929673, 4.929673, 4.929673, 5.414416, 8.57761, 9.399416, 9.399416, 9.399416, 11.35623, 11.35623, 12.266475, 13.977451, 16.720993, 16.720993, 16.720993, 19.65963, 19.65963, 21.307804, 22.863134, 23.321493, 23.321493], 'SMLrglat': [76.510002, 55.029999, 52.169998, 71.580002, 71.580002, 71.580002, 47.799999, 71.300003, 62.299999, 62.299999, 62.299999, 61.756001, 61.756001, 53.351002, 58.763, 63.75, 63.75, 63.75, 72.300003, 72.300003, 76.769997, 74.5, 76.510002, 76.510002], 'SMLrglon': [25.01, 82.900002, 104.449997, 129.0, 129.0, 129.0, 132.414001, 203.25, 209.800003, 209.800003, 209.800003, 238.770004, 238.770004, 247.026001, 265.920013, 291.480011, 291.480011, 291.480011, 321.700012, 321.700012, 341.369995, 19.200001, 25.01, 25.01], 'SMLrstid': ['HOP', 'NVS', 'IRT', 'TIK', 'TIK', 'TIK', 'BRN', 'BRW', 'T39', 'T39', 'T39', 'FSP', 'FSP', 'C06', 'FCC', 'IQA', 'IQA', 'IQA', 'SUM', 'SUM', 'DMH', 'BJN', 'HOP', 'HOP'], 'SMUr': [1.976003, 31.178246, 31.178246, 31.178246, -0.208882, 0.356117, 0.356117, 0.356117, -1.128606, -1.128606, -0.885122, -0.015059, 6.686568, 6.686568, 6.686568, 8.399819, 8.399819, 17.851616, 17.851616, 17.851616, 19.60713, 23.694275, 23.694275, 23.694275], 'SMUrmlat': [52.904049, 74.702339, 74.702339, 74.702339, 47.791527, 54.29908, 54.29908, 54.29908, 66.244217, 66.244217, 57.76614, 54.597057, 55.715378, 55.715378, 55.715378, 57.829525, 57.829525, 73.989975, 73.989975, 73.989975, 70.473801, 68.194489, 68.194489, 68.194489], 'SMUrmlt': [0.510692, 2.090216, 2.090216, 2.090216, 3.578985, 6.394085, 6.394085, 6.394085, 9.99274, 9.99274, 11.729218, 12.269058, 13.969843, 13.969843, 13.969843, 16.160952, 16.160952, 18.228394, 18.228394, 18.228394, 21.200783, 22.967857, 22.967857, 22.967857], 'SMUrglat': [56.432999, 79.480003, 79.480003, 79.480003, 52.169998, 59.970001, 59.970001, 59.970001, 64.047997, 64.047997, 51.882999, 47.664001, 45.870998, 45.870998, 45.870998, 48.650002, 48.650002, 67.93, 67.93, 67.93, 70.900002, 71.089996, 71.089996, 71.089996], 'SMUrglon': [58.567001, 76.980003, 76.980003, 76.980003, 104.449997, 150.860001, 150.860001, 150.860001, 220.889999, 220.889999, 239.973999, 245.791, 264.916992, 264.916992, 264.916992, 287.549988, 287.549988, 306.429993, 306.429993, 306.429993, 351.299988, 25.790001, 25.790001, 25.790001], 'SMUrstid': ['ARS', 'VIZ', 'VIZ', 'VIZ', 'IRT', 'MGD', 'MGD', 'MGD', 'DAW', 'DAW', 'C13', 'C10', 'C08', 'C08', 'C08', 'T50', 'T50', 'ATU', 'ATU', 'ATU', 'JAN', 'NOR', 'NOR', 'NOR'], 'SMErnum': [5, 3, 3, 4, 5, 6, 6, 4, 8, 9, 12, 13, 20, 17, 17, 11, 12, 14, 12, 14, 22, 51, 51, 35], 'smr': 0.252399, 'smr00': -0.531382, 'smr06': 0.885406, 'smr12': 1.051192, 'smr18': -0.395618, 'smrnum': 72, 'smrnum00': 26, 'smrnum06': 23, 'smrnum12': 6, 'smrnum18': 17, 'bgse': {'X': 1.07, 'Y': -3.75, 'Z': -0.74}, 'bgsm': {'X': 1.07, 'Y': -3.82, 'Z': -0.06}, 'vgse': {'X': -351.100006, 'Y': -5.5, 'Z': -4.0}, 'vgsm': {'X': 351.100006, 'Y': 6.128625, 'Z': -2.947879}, 'clockgse': 258.340698, 'clockgsm': 268.664337, 'density': 5.03, 'dynpres': 1.25, 'epsilon': 29.468521, 'newell': 2504.155029}
        # sample accessing
        print(mydata2c[0]['tval'],mydata2c[0]['density'])  # single element
        result=[ (myeach['tval'],myeach['density']) for myeach in mydata2c] # pull out pairs e.g. 'tval, density')
        # two-line method for extracting any variable set from this
        pairsets= [ (myeach['tval'],myeach['density'],myeach['vgse']) for myeach in mydata2c] # same, pull out pairs, only assign e.g. x=tval, y=density
        tval, density, vgse = [ [z[i] for z in pairsets] for i in (0,1,2)]
        # since 'vgse' is itself an dict of 3 values X/Y/Z, you can pull out nested items like this
        pairsets= [ (myeach['tval'],myeach['density'],myeach['vgse']['X']) for myeach in mydata2c] # same, pull out pairs, only assign e.g. x=tval, y=density
        tval, density, vgse_x = [ [z[i] for z in pairsets] for i in (0,1,2)]
        # the above methods are extensible to any number of variables, just update the (0,1,2) to reflect now many you have
      
        

Matlab Client (Matlab 2017 or later required)

Download data and indices from SuperMAG directly into your Matlab program using the SuperMAG Webservice Matlab Client.

  • Download Matlab Client
  • Download Matlab Client Documentation
  • View Matlab Client Documentation Hide Matlab Client Documentation
    SuperMAG MATLAB Client 1.0
    SuperMAG Web Service API MATLAB Client Documentation
    MATLAB 2017 or later required.

    ◆  stations=fetchSuperMAG('inventory',userid,start,extent)

    MATLAB function that retrieves an array of available stations for a given event.
    Parameters
    categoryfirst parameter must be set to 'inventory' to return stations
    useridyour supermag user id
    startstart date of event, either in the format 'YYYY-MM-DDThhmm' or as an array [YYYY, MM, DD, hh, mm] (seconds are optional)
    extentextent or length of the event in seconds (3600= 1 hour, 86400 = 1 day)
    noisy(optional) If the keywoard NOISY is supplied, the fetching routine will display the URL used and the first three rows of data, to help verify success to the user.
    Returns
    Array of available stations. If there was an error, return is the error message.

    Example Usage

    
    mydata=fetchSuperMAG('inventory',userid,'2019-11-15T10:40',3600)
    disp('Available Stations')
    for i = 1:length(mydata)
       disp( mydata{i} )
    end
    

    ◆  sm_data=fetchSuperMAG('data',userid,start,extent,flags,station)

    MATLAB function that retrievies station magnetometer data for a given event and IAGA station code.
    Parameters
    categoryfirst parameter must be set to 'data' to return stations
    useridyour supermag user id
    yrstart date of event, either in the format 'YYYY-MM-DDThhmm' or as an array [YYYY, MM, DD, hh, mm] (seconds are optional)
    extentextent or length of the event in seconds (3600= 1 hour, 86400 = 1 day)
    stationIAGA code of the requested station
    flagslist in string or array form of which data items to return and processing flags to use (see below). The full list of data items is either 'all' or 'mlt,mag,geo,decl,sza'. Flags can alternately be in array format, e.g. ["mlt" "mag" "geo" "decl" "sza"]. Processing flags available are 'delta=start', 'baseline=none', 'baseline=yearly'. Flags are not case-sensitive
     
    MLT(optional) If supplied, The MLT/MCOLAT of the station will be returned in the two dimensional array of length extent/60 specified by MLT.
    MAG(optional) If supplied, The Magnetic coordinates of the station will be returned in the two dimensional array of length extent/60 specified by MAG.
    GEO(optional) If supplied, The Geographic coordinates of the station will be returned in the two dimensional array of length extent/60 specified by GEO.
    DECL(optional) If supplied, The Declination from IGRF Model will be returned in the array of length extent/60 specified by DECL.
    SZA(optional) If supplied, The solar zenith angle will be returned in the array of length extent/60 specified by SZA.
    DELTA(optional) If the keywoard DELTA is supplied, The baseline NEZ vector start values will be subtracted from the NEZ vector components in the resulting n, e, and z arrays.
    BASELINE(optional) If BASELINE is specified, It must be set to one of three values:
    "baseline='all'" (default)Subtract both the daily and yearly NEZ baselines
    "baseline='yearly'"Subtract the yearly NEZ baseline, but do not subtract the daily NEZ baseline
    "baseline='none'"Do not subtract either the yearly or the daily NEZ baseline
    noisy(optional) If the keywoard NOISY is supplied, the fetching routine will display the URL used and the first three rows of data, to help verify success to the user.
    Returns
    Structure with all return data. If there was an error, return is the error message. The format of the returns is as follows.
    tvalThe time of the samples is returned as the structure element tval. The time array is an array of double precision numbers giving the time since 1970-01-01 0:00UTC (This is a standard representation of time on computer systems).
    extThe binned duration for each sample is returned, typically '60' representing the 1-minute bins of standard SuperMAG data
    iagaThe 3-letter station code provided is returned in the structure, useful for identification when you have multiple sets of data.
    NThe N vector component is returned in the two structure element arrays of length extent/60 specified by N. The second dimension refers to the coordinate system, so ‘N.nez’ contains the component of the vector in the standard NEZ coordinates, 'N.geo' contains the geographic mapping of the N vector component.
    EThe E vector component is returned in the two structure element arrays of length extent/60 specified by E. The second dimension refers to the coordinate system, so ‘E.nez’ contains the component of the vector in the standard NEZ coordinates, 'E.geo' contains the geographic mapping of the E vector component.
    ZThe A vector component is returned in the two structure element arrays of length extent/60 specified by Z. The second dimension refers to the coordinate system, so ‘Z.nez]’ contains the component of the vector in the standard NEZ coordinates, 'Z.geo' contains the geographic mapping of the Z vector component.
    mlt(optional) If supplied, The MLT/MCOLAT of the station will be returned in the two structure element arrays 'mlt' and 'mcolat' of length extent/60 specified by MLT.
    mag(optional) If supplied, The Magnetic coordinates of the station will be returned in the two structure element arrays 'mlat' and 'mlon' of length extent/60 specified by MAG.
    geo(optional) If supplied, The Geographic coordinates of the station will be returned in the two structure element arrays 'glon' and 'glat' of length extent/60 specified by GEO.
    decl(optional) If supplied, The Declination from IGRF Model will be returned as a structure element array 'decl' of length extent/60 specified by DECL.
    sza(optional) If supplied, The solar zenith angle will be returned as a structure element array 'sza' of length extent/60 specified by SZA.

    Example Usage

    
    
    sm_data=fetchSuperMAG('data',userid,'2019-11-15T10:40',3600,'all,delta=start,baseline=yearly','HBK');
    
    % simple plot of two nested structure elements
    tval=[sm_data.tval]
    % extract the N.geo and N.nez elements
    N=[sm_data.N]   
    % plot the N.geo and N.nez elements
    plot( [tval], [N.geo])
    hold on
    plot( [tval], [N.nez])
    hold off
    title("N geo vs N nez")
    xlabel("date")
    ylabel("N vector")
    %
    % Alternate way to extract a nested structure element such as sm_data.N.geo
    N_geo = arrayfun(@(k) sm_data(k).N.geo, 1:numel(sm_data));
    plot([sm_data.tval], N_geo)
    %
    % if you prefer everything as arrays instead of structures:
    TVAL=sm_data[*].tval
    N_NEZ = arrayfun(@(k) sm_data(k).N.nez, 1:numel(sm_data));
    E_NEZ = arrayfun(@(k) sm_data(k).E.nez, 1:numel(sm_data));
    Z_NEZ = arrayfun(@(k) sm_data(k).Z.nez, 1:numel(sm_data));
    MLT=[sm_data.mlt];
    MCOLAT=[sm_data.mcolat];
    MLON=[sm_data.mlon];
    MLAT=[sm_data.mlat];
    GLON=[sm_data.glon];
    GLAT=[sm_data.glat];
    SZA=[sm_data.sza];
    
        
    sample plot of data

    ◆  sm_indices=fetchSuperMAG('indices',userid,start,extent,flags)

    MATLAB function that retrievies a set of magnetic indices for a given event.
    Parameters
    categoryfirst parameter must be set to 'data' to return stations
    useridyour supermag user id
    yrstart date of event, either in the format 'YYYY-MM-DDThhmm' or as an array [YYYY, MM, DD, hh, mm] (seconds are optional)
    extentextent or length of the event in seconds (3600= 1 hour, 86400 = 1 day)
    flagslist in string or array form of which data items to return and processing flags to use (see below). The full list of data items is either 'all' or any subset, e.g. 'sme, sunsme, darksme'. Flags can alternately be in array format, e.g. ["sme" "sunsme" "darksme"]. Several flags have alternative names which you are free to use (these are derived from the set of tags the SuperMAG web server uses natively.) Flags are not case-sensitive.
     
    SME(optional) If supplied, the SME indice will be returned in the structure array '.SME' (See definition of SME indice)
    SML(optional) If supplied, the SML indice will be returned in the structure array '.SML' (See definition of SML indice)
    SMU(optional) If supplied, the SMU indice will be returned in the structure array '.SMU' (See definition of SMU indice)
    NUM(optional) If supplied, the number of stations used to compute SME indices will be returned in the structure array '.SMEnum'
    (optional) the following options return additional data items, but only if SME, SML and/or SMU is set (for SME, returns both .SMU and .SML entries; for SMU, only .SMU entries; for SML, only .SML entries)
    MLAT(optional) If supplied, the magnetic latitude of the SME indice will be returned in the structure array '.SMLmlat' and '.SMUmlat'
    MLT(optional) If supplied, the magnetic local time of the SME indice will be returned in the structure array '.SMLmlt' and '.SMUmlt'
    GLAT(optional) If supplied, the geographic latitude of the SME indice will be returned in the structure array '.SMLglat' and '.SMUglat'
    GLON(optional) If supplied, the geographic longitude of the SME indice will be returned in the structure array '.SMLglon' and '.SMUglon'
    STID(optional) If supplied, the IAGA station codes of the stations used to compute the SME indices will be returned in the structure array '.SMLstid' and '.SMUstid'
    baseall(optional) If supplied, is the equivalent of the set of 'sme,sml,smu,mlat,mlt,glat,glon,stid,num'
    SUNSME (alt: smes)(optional) If supplied, the Sunlit SME indice will be returned in the structure array '.SMEs' (See definition of Sunlit SME indice)
    SUNSML (alt: smls)(optional) If supplied, the Sunlit SML indice will be returned in the structure array '.SMLs' (See definition of Sunlit SML indice)
    SUNSMU (alt: smus)(optional) If supplied, the Sunlit SMU indice will be returned in the structure array '.SMUs' (See definition of Sunlit SMU indice)
    SUNNUM (alt: nums)(optional) If supplied, the number of stations used to compute the Sunlit SME indices will be returned in the structure array '.sunnum'
    (optional) the following options return additional data items, but only if SMEs, SMLs and/or SMUs is set (for SMEs, returns both .SMUs and .SMLs entries; for SMUs, only .SMUs entries; for SMLs, only .SMLs entries)
    SUNMLAT (alt: mlats)(optional) If supplied, the magnetic latitude of the Sunlit SME indice will be returned in the structure array '.SMLsmlat' and '.SMUsmlat'
    SUNMLT (alt: mlts)(optional) If supplied, the magnetic local time of the Sunlit SME indice will be returned in the structure array '.SMLsmlt' and '.SMUsmlt'
    SUNGLAT (alt: glats)(optional) If supplied, the geographic latitude of the Sunlit SME indice will be returned in the structure array '.SMLsglat' and '.SMUsglat'
    SUNGLON (alt: glons)(optional) If supplied, the geographic longitude of the Sunlit SME indice will be returned in the structure array '.SMLsglon' and '.SMUsglon'
    SUNSTID (alt: stids)(optional) If supplied, the IAGA station codes of the stations used to compute the Sunlit SME indices will be returned in the structure array '.SMLstid' and '.SMUstid'
    sunall(optional) If supplied, is the equivalent of the set of 'smes,smls,smus,mlats,mlts,glats,glons,stids,nums'
    DARKSME (alt: smed)(optional) If supplied, the Dark SME indice will be returned in the structure array '.darksme' (See definition of Dark SME indice)
    DARKSML (alt: smld)(optional) If supplied, the Dark SML indice will be returned in the structure array '.darksml' (See definition of Dark SML indice)
    DARKSMU (alt: smud)(optional) If supplied, the Dark SMU indice will be returned in the structure array '.darksmu' (See definition of Dark SMU indice)
    DARKNUM (alt: numd)(optional) If supplied, the number of stations used to compute the Dark SME indices will be returned in the structure array '.darknum'
    (optional) the following options return additional data items, but only if SMEd, SMLd and/or SMUd is set (for SMEd, returns both .SMUd and .SMLd entries; for SMUd, only .SMUd entries; for SMLd, only .SMLd entries)
    DARKMLAT (alt: mlatd)(optional) If supplied, the magnetic latitude of the Dark SME indice will be returned in the structure array '.SMLdmlat' and '.SMUdmlat'
    DARKMLT (alt: mltd)(optional) If supplied, the magnetic local time of the Dark SME indice will be returned in the structure array '.SMLdmlt' and '.SMUdmlt'
    DARKGLAT (alt: glatd)(optional) If supplied, the geographic latitude of the Dark SME indice will be returned in the structure array '.SMLdglat' and '.SMUdglat'
    DARKGLON (alt: glond)(optional) If supplied, the geographic longitude of the Dark SME indice will be returned in the structure array '.SMLdglon' and '.SMUdglon'
    DARKSTID (alt: stidd)(optional) If supplied, the IAGA station codes of the stations used to compute the Dark SME indices will be returned in the structure array '.SMLdtid' and '.SMUdtid'
    darkall(optional) If supplied, is the equivalent of the set of 'smed,smld,smud,mlatd,mltd,glatd,glond,stidd,numd'
    REGIONALSME (alt: smer)(optional) If supplied, the Regional SME indice will be returned in the structure array '.SMEr' (See definition of Regional SME indice)
    REGIONALSML (alt: smlr)(optional) If supplied, the Regional SML indice will be returned in the structure array '.SMLr' (See definition of Regional SML indice)
    REGIONALSMU (alt: smur)(optional) If supplied, the Regional SMU indice will be returned in the structure array '.SMUr' (See definition of Regional SMU indice)
    REGIONALNUM (alt: numr)(optional) If supplied, the number of stations used to compute the Regional SME indices will be returned in the structure array '.SMErnum'
    (optional) the following options return additional data items, but only if SMEr, SMLr and/or SMUr is set (for SMEr, returns both .SMUr and .SMLr entries; for SMUr, only .SMUr entries; for SMLr, only .SMLr entries)
    REGIONALMLAT (alt: mlatr)(optional) If supplied, the magnetic latitude of the Regional SME indice will be returned in the structure array '.SMLsmlat' and '.SMUsmlat'
    REGIONALMLT (alt: mltr)(optional) If supplied, the magnetic local time of the Regional SME indice will be returned in the structure array '.SMLsmlt' and '.SMUsmlt'
    REGIONALGLAT (alt: glatr)(optional) If supplied, the geographic latitude of the Regional SME indice will be returned in the structure array '.SMLsglat' and '.SMUsglat'
    REGIONALGLON (alt: glonr)(optional) If supplied, the geographic longitude of the Regional SME indice will be returned in the structure array '.SMLsglon' and '.SMUsglon'
    REGIONALSTID (alt: stidr)(optional) If supplied, the IAGA station codes of the stations used to compute the Regional SME indices will be returned in the structure array '.SMLstid' and '.SMUstid'
    regall(optional) If supplied, is the equivalent of the set of 'sme,sml,smu,mlat,mlt,glat,glon,stid,num'
    SMR(optional) If supplied, the SMR indice will be returned in the structure array '.smr' (See definition of SMR indice)
    LTSMR(optional) If supplied, the SMR LT indices will be returned in the structure arrays '.smr00','.smr06','.smr12','.smr18' (See definition of SMR LT indice)
    LTNUM(optional) If supplied, the number of stations used to compute the SMR LTN indice will be returned in the structure arrays '.smrnum00','.srmnum06','.smrnum12','.smrnum18'
    NSMR(optional) If supplied, the number of stations used to compute the SMR indices will be returned in the structure array '.nsmr'
    plusall(optional) If supplied, is the equivalent of the set of 'sme,sml,smu,mlat,mlt,glat,glon,stid,num'
    all(optional) If supplied, is the equivalent to all the above, 'baseall,sunall,darkall,regall,plusall' (but not the swi and imf keys below)
    BGSE(optional) If supplied, the Solar Wind B field (GSE) parameter will be returned in the structure array '.bgse'
    BGSM(optional) If supplied, the Solar Wind B field (GSM) parameter will be returned in the structure array '.bgsm'
    VGSE(optional) If supplied, the Solar Wind V (GSE) parameter will be returned in the structure array '.vgse'
    VGSM(optional) If supplied, the Solar Wind V (GSM) parameter will be returned in the structure array '.vgsm'
    imfall(optional) If supplied, is the equivalent of the set of 'sme,sml,smu,mlat,mlt,glat,glon,stid,num'
    PDYN(optional) If supplied, the Solar Wind Dynamic Pressure parameter will be returned in the structure array '.pdyn'
    EPSILON(optional) If supplied, the Solar Wind ε Parameter parameter will be returned in the structure array '.epsilon'
    NEWELL(optional) If supplied, the Solar Wind Newell parameter will be returned in the structure array '.newell'
    CLOCKGSE(optional) If supplied, the IMF Clock Angle (GSE) parameter will be returned in the structure array '.clockgse'
    CLOCKGSM(optional) If supplied, the IMF Clock Angle (GSM) parameter will be returned in the structure array '.clockgsm'
    DENSITY(optional) If supplied, the Solar Wind Plasma Density parameter will be returned in the structure array '.density'
    swiall(optional) If supplied, is the equivalent of the set of 'sme,sml,smu,mlat,mlt,glat,glon,stid,num'
    noisy(optional) If the keywoard NOISY is supplied, the fetching routine will display the URL used and the first three rows of data, to help verify success to the user.
    Returns
    Structure with all return data. If there was an error, return is the error message. The format of the returns is as follows.
    tvalThe time of the samples is returned as the structure element tval. The time array is an array of double precision numbers giving the time since 1970-01-01 0:00UTC (This is a standard representation of time on computer systems).
    The following data structure arrays are returned, dependent on which optional flags you requested. Note that no data is returned unless flags are specified, there is no 'default dataset'.
    decl(optional) If supplied, The Declination from IGRF Model will be returned as a structure element array 'decl' of length extent/60 specified by DECL.
    Base data:Structure elements as defined above and named: .SME, .SML, .SMLmlat, .SMLmlt, .SMLglat, .SMLglon, .SMLstid, .SMU, .SMUmlat, .SMUmlt, .SMUglat, .SMUglon, .SMUstid, .SMEnum
    Sunlit data: Structure elements as defined above and named: .SMEs, .SMLs, .SMLsmlat, .SMLsmlt, .SMLsglat, .SMLsglon, .SMLsstid, .SMUs, .SMUsmlat, .SMUsmlt, .SMUsglat, .SMUsglon, .SMUsstid, .SMEsnum
    Dark data: Structure elements as defined above and named: .SMEd, .SMLd, .SMLdmlat, .SMLdmlt, .SMLdglat, .SMLdglon, .SMLdstid, .SMUd, .SMUdmlat, .SMUdmlt, .SMUdglat, .SMUdglon, .SMUdstid, .SMEdnum
    Regional data: Structure elements as defined above and named: .SMEr, .SMLr, .SMLrmlat, .SMLrmlt, .SMLrglat, .SMLrglon, .SMLrstid, .SMUr, .SMUrmlat, .SMUrmlt, .SMUrglat, .SMUrglon, .SMUrstid, .SMErnum
    Plus data:Structure elements as defined above and named: .smr, .smrnum00, .smrnum06, .smrnum12, .smrnum18
    IMF data:Structure elements as defined above and named: .bgse, .bgsm, .vgse, .vgsm
    SWI data:Structure elements as defined above and named: .clockgse, .clockgsm, .density, .dynpres, .epsilon, .newell

    Example Usage

    
    sm_data=fetchSuperMAG('indices',userid,'2019-11-15T10:40',3600,'all');
    
    ; plot time vs a data item
    plot([sm_data.tval],[sm_data.SMEs])  
    hold on
    plot([sm_data.tval],[sm_data.SMLs])
    hold off
    
    % plot time vs a multi-dimensional data item
    tval=[sm_data.tval];
    y=[sm_data.SMLr];
    nrows = length(tval);	
    hours = 0:23;
    for i=1 : nrows
      plot( hours, y(:,i) )
      hold on
    end
    hold off
    title('Sample Plot, SMLr vs Hour across multiple days') ;
    
        
    sample plot of indices

R Client (Package "httr" is required)

Download data and indices from SuperMAG directly into your R program using the SuperMAG Webservice R Client.

(High Fidelity Web Service API Support Coming Soon...)



SuperMAG 1-sec data have been rotated into a local magnetic coordinate system (see below) and the main field has been removed using the baseline technique described in the first reference below (e.g. Gjerloev, J. W., 2012).

Data Cadence

The SuperMAG 1-sec data have been derived from measurements with a 0.5 Hz or higher sampling rate (see ULF Parameters for details)

Coordinate System

Coordinate System

Global studies require all data to be rotated into a common known coordinate system. Data provided to SuperMAG from the collaborators are typically in either:

  • Geographic coordinates (north (X), east (Y), vertical down (Z))
  • Geographic coordinates (horizontal intensity (H), declination (D) and vertical down (Z))
  • Geomagnetic coordinates> (magnetic north (H), magnetic east (D) and vertical down (Z))
with or without baselines subtracted. During intitial setup the sensor axes are oriented in either the geographic or local magnetic coordinate system. The Earth main field, however, is constantly changing so the geomagnetic coordinate system is time dependent. The various uncertainties in mind SuperMAG decided to make no assumptions as to the initial setup of the magnetometer other than the Z-axis being vertical. Using the two horizontal components SuperMAG determines a slowly varying time dependent declination angle and subsequently rotates the horizontal components into a local magnetic coordinate system for which the magnetic east component (E) is minimized and the magnetic north component (N) is maximized. Note that geomagnetic coordinates are routinely labeled HDZ although the units of the D-component can be nT or an angle. Likewise, the D-component is often found to have a significant offset. As a consequence SuperMAG decided to denote the components:

B=(BN,BE,BZ)

where
  • N-direction is local magnetic north
  • E-direction is local magnetic east
  • Z-direction is vertically down

By definition the typical value (offset) of the E-component is zero. This reference system is independent of the actual orientation of the two horizontal magnetometer axes and the data can be rotated to any desired coordinate system using the appropriate IGRF model.

Magnetic Local Time (MLT) is calculated using the solar local time (Jean Meeus, Astronomical Algorithms, 2nd edition, ISBN-13: 978-0943396613) and the AACGM system. For more info and a cautionary note see: https://omniweb.gsfc.nasa.gov/vitmo/cgmm_des.html

Baseline Determination

SuperMAG provides four options for the user:

  1. Subtract the daily variations and yearly trend (using Gjerloev, 2012)
  2. Subtract only the yearly trend (using Gjerloev, 2012)
  3. Do not subtract any baseline
  4. Subtract the start value from thee remaining of the interval.

SuperMAG thus provides 3 different solutions. The user should use the appropriate dataset for the study. As an example a study of the Sq current or the equatorial electrojet should not subtract the daily variations since this will remove part of this signal.

The purpose of determining the baseline is to perform a separation of sources. The measured field on the surface of the Earth is due to a list of sources:

Bmeasured = Bmain + BSq + BFAC + BRC + BEJ + BMP + ...

where the right side terms indicate the contribution due to: The Earth main field; the Sq current system; the field-aligned currents; the ring current; the auroral electrojets; and the magnetopause currents.

The focus of SuperMAG is ionosphere-magnetosphere research so perturbations produced by currents flowing in and between the ionosphere and the magnetosphere should be maintained while all other sources to the measured field should be removed. According to Ampere’s law it is impossible to determine a single unique current solution from the measured field. It is, however, possible to make a separation of sources if reasonable assumptions are made. For example, that the Earth main field is slowly varying compared to all other sources.

The question as to how the baseline should be determined is still under debate as evident from the stream of new papers being published (e.g. Mayaud, 1980; Menvielle et al., 1995; Takahashi et al., 2001; Janzhura and Troshichev, 2008). The fundamental problem is that there is no objective way to evaluate the quality of each technique. In validating any result or technique it is required that a set of ground-truth observations exists. Agreeing with another set of results does not provide an argument of validity, as both could be erroneous. This is particularly true for baseline determination as just about any data provider and as many scientists have developed their own technique.

As mentioned above the purpose of the baseline determination is fundamentally to perform a separation of sources. As there is no objective way to separate the sources neither is there a way to perform an objective evaluation. We therefore conclude that the user of the data must keep in mind the assumptions used in the baseline determination and draw conclusions accordingly.

The above discussion (see Gjerloev, 2012 for an extensive discussion) is why SuperMAG provides four options for the user.

Fitted Magnetometer Vectors

The uniformly gridded data are derived from statistical-based method which combines with basis function expansion techniques (Waters et al., 2015) to provide extensive maps of the ground level perturbation magnetic field from 40° magnetic latitude to the magnetic pole for all longitudes. The method combines all available data from the SuperMAG data base, Principal Component Analysis, and a spherical cap harmonic basis function expansion in order to fill in magnetic perturbation data where there are no magnetometers and produce the poloidal current potential. The final uniform solutions are derived from measured perturbations and the fill-in (model) vectors. On the website are shown the measured perturbations and the final fitted solutions. The fill-in (model) vectors are not shown. Download gridded solutions here including:

  • Uniformly gridded Fill-in or Model Vectors
  • Uniformly gridded Fitted Vectors in an MLT-MLat grid
  • Uniformly gridded Fitted Vectors in an equal area grid (AACGM)

References

Waters, C. L., J. W. Gjerloev, M. Dupont, and R. J. Barnes (2015), Global maps of ground magnetometer data, J. Geophys. Res. Space Physics, 120,doi:10.1002/2015JA021596

Main Field or Baseline

For SuperMAG 1-sec data the main field, or baseline, has been removed using the technique described in Gjerloev, J. W., 2012 to subtract the daily variations and yearly trend (see description of 1 minute resolution Mmagnetometer data for details).

ULF Parameters

All ULF data products are derived from the 1-sec SuperMAG data (see ULF Parameters for a description of the details).

Reference

Gjerloev, J. W., 2012. The SuperMAG data processing technique, J. Geophys. Res., 117, A09213, doi:10.1029/2012JA017683.

Janzhura, A. S. and O. A. Troshichev, 2008. Determination of the running daily geomagnetic variation, J.Atmos.Solar-Terr.Phys. 70, 962-972, doi:10.1016/j.jastp.2007.11.004.

Mayaud, P. N., Derivation, 1980. Meaning and use of geomagnetic indices, Geophys.Monographs,Ser., 22, 154, AGU, Washington D.C.

Menvielle, M., N. Papitashvili, L. Hakkinen, and C. Suckdorff, 1995. Computer production of K indices: Review and comparison of methods, Geophys.J.Int., 123, 866-886, doi:10.1111/j.1365-246X.1995.tb06895.x

Takahashi, K., B. toth, and J. V. Olson, 2001. An automated procedure for near-real-time Kp estimates, J. Geophys. Res., 106, 21,017-21,032, doi:10.1029/2000JA000218.

SuperMAG Data Variable Definitions

SuperMAG Data Variable Definitions

SuperMAG data download files contain the following variables

IAGA Station ID Ground mag stations have a 3 letter code. Some of these codes are not official but are assigned by SuperMAG (For more info see Station Information).
Geo. Lon. Geographic Longitude
Geo. Lat. Geographic Latitude
Mag. Lon. Geomagnetic Longitude (We use the AACGM approach for calculating Geomagnetic Longitude and as this field is constantly changing this calculation is a function of year and date)
Mag. Lat. Geomagnetic Latitude (We use the AACGM approach for calculating Geomagnetic Latitude and as this field is constantly changing this calculation is a function of year and date)
MLT Magnetic local time
Mag Colat. Geomagnetic co-latitude. Mag colat = 90-Mag.lon.
Mag. Declination Declination of the magnetic field at the station. We use the global magnetic field model IGRF.
Solar Zenith Angle Angle between Sun-Earth line and the station nadir line.
Mag. Field NEZ Magnetic field in a local magnetic field coordinate system. (For more info see Coordinate System).
Mag. Field Geo. Magnetic field in a geographic coordinate system.
dbn_nez, dbe_nez, dbz_nez Magnetic field perturbations in a local magnetic field coordinate system. (For more info on how the main field has been removed see Baseline Determination).
dbn_geo, dbe_geo, dbz_geo Magnetic field perturbations in a geographic coordinate system. (For more info on how the main field has been removed see Baseline Determination).

To Download Data, Indices and Gridded Solutions

To Download Data, ULF Parameters and Gridded Solutions

SuperMAG provides three options:

  1. Plot an event (data, indices or polar plots) and download the one minute resolution data from that event. SuperMAG uses the philosophy of 'What you see is what you get.' Select 'Indices', 'Line Plots' or 'Polar Plots', plot an event and then download.
  2. Download one minute resolution data directly into your application using the SuperMAG Web Service API (IDL/Python clients available).
  3. Download one minute resolution data from the 'Download Data' page. This option is for users who already know the time range and/or stations of interest to them:
    • The 'Large Downloads' tab provides access to prepacked One-Year-All-Stations or All-Years-One-Station one minute resolution NetCDF files (These files are very large, but they are hosted in the cloud and will download faster than other the download options).
    • The 'Custom Downloads' tab allows the user to generate a custom download file containing one minute resolution data for the time range and stations of interest (28 day max duration). The 'Custom Downloads' tab also provides the ability to generate a custom download file containing one minute resolution data for a single station for an entire year.
    • The 'Gridded Solutions' tab allows the user to download prepacked NetCDF files containing the one minute resolution gridded solutions for a given day.
  1. Plot an event (data or polar plots) and download the one second resolution data from that event. SuperMAG uses the philosophy of 'What you see is what you get.' Select 'Line Plots' or 'Polar Plots', plot an event and then download.
  2. Download one second resolution data directly into your application using the SuperMAG Web Service API (IDL/Python clients available).
  3. Download one second resolution data from the 'Download Data' page. This option is for users who already know the time range and/or stations of interest to them:
    • The 'Large Downloads' tab allows the user to generate One-Day-All-Stations one second resolution data files
    • The 'Custom Downloads' tab allows the user to generate a custom download file containing one second resolution data for the time range and stations of interest (one day max duration).
    • The 'ULF Parameters' tab allows the user to download prepacked NetCDF files containing the one second resolution gridded solutions and ULF Pc2-Pc5 parameters for a given hour on a given day.

Helpful Information