Features

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VirES for Swarm — Web Client

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Here is a demonstration of the main features of the VirES for Swarm web user interface.

Slides with detailed information on service usage can be found here.

Various Swarm product data can be visualized on the platform plotted over the globe and shown in a scatter plot. The scatter plot allows for dual y-axes with independent zoom and panning features. Different variables can be plotted in multiple vertically-stacked plots sharing the common x-axis. The time slider and various controls offer the possibility to make selections and set criteria for data filtering and visualization which immediately take effect on the display.

The subset of Swarm data selected by the user in this way can be downloaded in different file formats. The downloaded data can be combined to fit various use cases.

VirES allows visual and numerical comparison with geomagnetic models, analysis with respect to various ancillary data and generation of publication-ready plots and diagrams in an intuitive and powerful yet customizable interface.

VirES for Swarm — API

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In addition to the web graphical user interface, the data can be accessed directly trough the VirES server API using an alternative client such as the VirES Python client.

VirES for Swarm — Heliophysics API

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Selected datasets can be also accesses through the Heliophysics API (HAPI). For more details about see the description of the VirES for Swarm HAPI server.

VirES for Swarm — Jupyter Lab

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The direct data access using the VirES Python client can be performed in Jupyter notebook running in the VirES for Swarm Jupyter based Virtual Research Environment (VRE).

To access the VirES for Swarm Jupyter Lab you need to have a VirES account (sign up) and login in VRE.

Data

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Data from the following Swarm products are available in VirES:

• Low resolution (1Hz) magnetic VFM vector and ASM scalar data (MAGx_LR_1B)
• High resolution (50Hz) magnetic VFM vector data (MAGx_HR_1B, accessible via the Python client, readily available in VRE)
• Plasma data (2Hz) from the Langmuir probe including electron temperature and plasma density (EFIx_LP_1B)
• Ionospheric bubble index data (IBIxTMS_2F)
• Ionospheric total electron content data (TECxTMS_2F)
• Field aligned current (single and dual S/C) (FACxTMS_2F and FAC_TMS_2F)
• Dayside equatorial electric field data (EEFxTMS_2F)
• Characteristics of the plasma density and plasma irregularities along the orbit (IPDxIRR_2F)
• High-latitude ionospheric horizontal sheet current densities profiles calculated using the Line Current (AEJxLPL_2F) and Spherical Elementary Current Systems (AEJxLPS_2F) methods
• High-latitude ionospheric horizontal sheet current boundaries and peaks locations calculated using the Line Current (AEJxPBL_2F) and Spherical Elementary Current Systems (AEJxPBS_2F) methods
• Aurora oval boundaries determined from the field aligned current data (AOBxFAC_2F)
• Mid-latitude ionospheric trough (MIT) boundaries and minima based on the Langmuir probe electron density and temperature measurements (MITx_LP_2F), accessible via the Python client.
• Mid-latitude ionospheric trough (MIT) boundaries and minima derived from the GPS TEC estimate (MITxTEC_2F), accessible via the Python client.
• Midnight plasma-pause index (PPI) and the associated SSFAC boundaries (PPIxFAC_2F), accessible via the Python client.
• Thermal ion imager cross track flow data at 2 Hz (EFIx_TCT02) and 16 Hz (EFIx_TCT16). The 16 Hz dataset is accessible via the Python client.
• Thermal ion imager ion temperature estimates (EFIxTIE_2).
• Ion drift, density and effective mass data (EFIxIDM_2).
• Swarm spacecrafts' positions (MODx_SC_1B) accessible via the Python client.
• Thermospheric density (SW_DNSxACC_2_ and SW_DNSxPOD_2_) accessible via the Python client.

VirES also provides access to the Swarm FAST L1B and L2 The latests 6 months of the FAST MAGx_LR_1B, MAGx_HR_1B, EFIx_LP_1B, MODx_SC_1B, and FACxTMS_2F data are available through the VirES API and HAPI interfaces.

The VirES API also provides access to:

• Hourly, 1 minute and 1 second ground magnetic observatory data (AUX_OBS) from INTERMAGNET and WDC
• 1 and 4 months Virtual Observatory data (VOBS) from the GVO project.
• Calibrated platform magnetometer measurements from the CHAMP (CH_ME_MAG_LR_3), CryoSat-2 (CS_MAG), GOCE (GO_MAG_ACAL_CORR and GO_MAG_ACAL_CORR_ML), GRACE (GRACE_x_MAG) and GRACE-FO (GFx_FGM_ACAL_CORR and GFx_MAG_ACAL_CORR_ML) missions.
• Thermospheric density and crosswind products from the CHAMP (CH_DNS_ACC_2_ and CH_WND_ACC_2_), GRACE (GR_DNSxACC_2_ and GR_WNDxACC_2_), and GRACE-FO (GF_DNSxACC_2_ and GF_WNDxACC_2_) missions.
• Multi-mission crossover and plane alignment conjunctions of the Swarm, CHAMP, GOCE, GRACE, and GRACE-FO spacecrafts (MM_CON_EPH_2_).

These datasets can be accessed with the VirES Python client, readily available in VRE.

The following models of the Earth's magnetic field and its components (core, crust, lithospheric, magnetospheric, and ionospheric magnetic field) are available

• 13th generation of the International Geomagnetic Reference Field (IGRF 13) released in December 2019 by the International Association of Geomagnetism and Aeronomy
• The latest version of the CHAOS high resolution geomagnetic field model derived from Swarm, MSS-1, CSES, CryoSat-2, CHAMP, SAC-C, and Ørsted satellite magnetic data along with ground observatory data (CHAOS-8)
• Spherical harmonic model of the main (core) field and its temporal variation (MCO_SHA_2C)
• Spherical harmonic model of the main (core) field and its temporal variation (MCO_SHA_2D)
• Spherical harmonic model of the lithospheric field (MLI_SHA_2C)
• Spherical harmonic model of the lithospheric field (MLI_SHA_2D)
• LCS-1 high-resolution lithospheric field model, derived from CHAMP and Swarm satellite observations (LCS-1)
• MF7 crustal field model, derived from CHAMP satellite observations (MF7)
• Spherical harmonic model of the lithospheric field (MLI_SHA_2E)
• Spherical harmonic model of the large-scale magnetospheric field and its Earth-induced counterpart (MMA_SHA_2C primary and secondary field)
• Spherical harmonic model of the large-scale magnetospheric field and its Earth-induced counterpart (MMA_SHA_2F primary and secondary field)
• CHAOS spherical harmonic model of the large-scale magnetospheric field and its Earth-induced counterpart (CHAOS-MMA primary and secondary field)
• Spherical harmonic model of the daily geomagnetic variation at middle latitudes (Sq) and low latitudes (EEJ) (MIO_SHA_2C primary and secondary field)
• Spherical harmonic model of the daily geomagnetic variation at middle latitudes (Sq) and low latitudes (EEJ) (MIO_SHA_2D primary and secondary field)
• Model of the associated magnetic field of the ionospheric current system (AMPS)

Users can also work with Custom Models and upload own Spherical Harmonic Expansion coefficients (SHC file format)

The global context of space weather is provided in form of:

• Disturbance storm time index (Dst Index) and its rate of change.
• Disturbances in the horizontal component of the Earth's magnetic field (planetary Kp Index)
• Observed daily measure of the solar radio flux per unit frequency at a wavelength of 10.7 cm (F10.7 index) read from the auxiliary AUX_F10_2_ product.

The data accessible on VirES consists of the newest versions available and any new consolidated products (OPER) will appear in VirES within 4 hours after being published. New FAST products will appear in VirES within 15 minutes after publishing. The data updates may get delayed when a large bulk of re-processed products is published.

Sign up

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To access Swarm data you simply sign up (register) as a user by providing user profile information such as username, email and optionally title, country, institution and an executive description of the project in which your Swarm data is being used.

Log in

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