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GITM (25.11)

Global Ionosphere Thermosphere Model (GITM)

Model Description

The Global Ionosphere Thermosphere Model (GITM) is a three-dimensional, non-hydrostatic model of the Earth's thermosphere and ionosphere system. Unlike many thermosphere-ionosphere models that use pressure coordinates and assume hydrostatic equilibrium, GITM uses an altitude-based spherical grid and explicitly solves the full vertical momentum equation, allowing realistic simulation of vertical dynamics, gravity-wave propagation, and auroral-region upwelling.

GITM solves the coupled continuity, momentum, and energy equations for both neutral and ion species. The standard Earth configuration includes major neutral species O, O2, N2, NO, N(4S), and He, along with additional excited neutral states and ion species including O+, O2+, NO+, N2+, N+, and He+. The model includes separate vertical velocities for individual neutral species and incorporates neutral-neutral frictional coupling, semi-implicit chemistry, ion-neutral coupling, ionospheric electrodynamics, EUV heating, auroral precipitation effects, and thermal conduction.

GITM supports both global and regional simulations with flexible horizontal resolution and a stretched vertical grid extending from approximately 90 km to 600 km altitude. The model can operate in one-dimensional, regional, or fully global configurations. It uses MPI-based domain decomposition for high-performance parallel computing and dynamically adjusts its time step according to local velocities, sound speed, and grid spacing.

The model includes multiple options for high-latitude electrodynamic forcing, including Weimer, AMIE, SWMF, and OVATION Prime drivers. Auroral precipitation can include diffuse, monoenergetic, broadband, and ion aurora using Fang et al. parameterizations. Solar EUV forcing may be specified using FISM/FISM2 irradiance spectra, including eclipse and nightside irradiance capability.

GITM has been extensively validated against multiple observational data sets, including GOCE thermospheric densities and winds, GUVI O/N2 composition ratios, and GNSS total electron content (TEC) observations during geomagnetic storm periods.

GITM uses a flexible stretched grid system in latitude, longitude, and altitude, allowing users to configure the spatial resolution according to the scientific application and computational resources available. Current CCMC production runs use a horizontal resolution of 1° in latitude and 4° in longitude.

Model Figure(s) :

Model Inputs Description

  • Solar EUV irradiance (F10.7 and FISM2 spectral irradiance)
  • Interplanetary Magnetic Field (IMF)
  • Solar wind velocity and density
  • Auroral electrojet (AE) indices
  • High-latitude electric potential models (e.g., Weimer05 (default), AMIE, SWMF)
  • Auroral precipitation models (e.g., Feature Tracking of Aurora (FTA; default), Fuller-Rowell and Evans, OVATION Prime)
  • Initial atmospheric specification: Empirical atmosphere (MSIS/IRI)
  • Lower boundary tidal forcing and wave specification: MSIS

Model Outputs Description

  • Neutral temperature
  • Ion temperature
  • Electron temperature
  • Neutral winds: zonal, meridional, vertical
  • Plasma velocities: zonal, meridional, field-aligned/vertical
  • Neutral mass density (kg/m³)
  • Number densities of neutral species: O, O2, N2, NO, N(4S), He
  • Number densities of ion species: O+, O2+, NO+, N2+, N+, He+
  • Electron density (m⁻³)
  • Total Electron Content (TEC)
  • O/N2 composition ratio
  • Joule heating
  • EUV heating
  • Chemical heating rates
  • Electric potential and ionospheric conductances
  • Auroral energy deposition and ionization rates

Model Caveats

  • GITM is typically limited to altitudes below approximately 600 km and does not fully represent the plasmasphere; therefore, global TEC can be underestimated.
  • Numerical diffusion and boundary-condition assumptions can affect the development of small-scale structures and wave propagation.
  • Model results are sensitive to high-latitude electrodynamic drivers, auroral precipitation specification, and lower-boundary tidal forcing.
  • Different empirical forcing models (e.g., Weimer, AMIE, OVATION Prime) can produce substantially different thermosphere-ionosphere responses.
  • The model uses parameterized photoelectron heating and auroral energy deposition schemes rather than fully kinetic treatments.
  • Some ion species are solved chemically but are not fully advected.
  • Validation studies indicate that GITM may overestimate O/N2 ratios and daytime TEC while underestimating nighttime TEC during some geomagnetic storm conditions (Ridley et al., 2026).

Change Log


 

 

Model Acknowledgement/Publication Policy (if any)

Ridley, A. J., Wu, C., Bukowski, A., & Bell, J. (2026). Updates, examples and validation of the global ionosphere thermosphere model. Space Weather, 24, e2025SW004925. https://doi.org/10.1029/ 2025SW004925

Model Domains:

Global_Ionosphere
Thermosphere

Space Weather Impacts:

Ionosphere variability (navigation, communications)
Atmosphere variability (satellite/debris drag)

Phenomena :

Variablility_of_Plasma_Density
Atmosphere_Expansion
Neutral_Composition_Change
Neutral_Wind_Change
Ion_Drift_Velocity
Equatorial_Anomaly
Traveling_Ionospheric_Disturbances
Traveling_Atmospheric_Disturbances

Simulation Type(s):

Physics-based

Temporal Dependence Possible? (whether the code results depend on physical time?)

true

Model is available at?

CCMC

Source code of the model is publicly available?

true

CCMC Model Status (e.g. onboarding, use in production, retired, only hosting output, only source is available):

production

Code Language:


Regions (this is automatically mapped based on model domain):

Contacts :

Aaron.Ridley, ModelDeveloper
Jack.Wang, ModelHostContact

Acknowledgement/Institution :

Department of Atmosphere, Oceanic and Space Sciences, University of Michigan

Relevant Links :

Publications :

  • Ridley, A. J., Y. Deng, and G. Toth., 2006, The Global Ionosphere-Thermosphere Model (GITM). J. Atmos. Solar-Terrestr. Phys. 68, 839-864.
  • Bilitza, D., 2001, International reference ionosphere 2000, Radio Science 36, 261.
  • Ridley, A., Crowley, G., Freitas, C., 2000, An empirical model of the ionospheric electric potential, Geophysics Research Letters 27, 3675.
  • Weimer, D., 1996, A flexible, IMF dependent model of high- latitude electric potential having space weather applications, Geophysics Research Letters 23, 254.
  • Weimer, D. R.: Improved ionospheric electrodynamic models and application to calculating Joule heating rates, J. Geophys. Res., 110, 05 306, doi:10.1029/2004JA010884, 2005.
  • Richmond, A., 1995, Ionospheric electrodynamics using magnetic apex coordinates, J. Geomagn. Geo-electr. 47, 191.
  • Hedin, A., 1991, Extension of the MSIS thermosphere model into the middle and lower atmosphere, Journal of Geophysical Research 96, 1159.
  • Heppner, J., Maynard, N., 1987, Empirical high-latitude electric field models, Journal of Geophysical Research 92, 4467.
  • Foster, J., 1983, An empirical electric field model derived from Chatanika radar data, Journal of Geophysical Research 90, 981.
  • Fuller-Rowell, T. and Evans, D.: Height-integrated Pedersen and Hall conductivity patterns inferred from TIROS-NOAA satellite data, J. Geophys. Res., 92, 7606, 1987.
  • Ridley, A. J., Wu, C., Bukowski, A., & Bell, J. (2026). Updates, examples and validation of the global ionosphere thermosphere model. Space Weather, 24, e2025SW004925
  • Model Access Information :

    Access URL: https://github.com/GITMCode/GITM
    Access URL Name: Public Repository
    Repository ID: spase://CCMC/Repository/NASA/GSFC/CCMC
    Availability: online
    AccessRights: OPEN
    Format: HTML
    Encoding: None

    Access URL: https://ccmc.gsfc.nasa.gov/ror/requests/IT/GITM/gitm_user_registration.php
    Access URL Name: Runs-on-Request
    Access Resource ID (for ROR use):
    Access Resource Version (for ROR use):
    Repository ID: spase://CCMC/Repository/NASA/GSFC/CCMC
    Availability: online
    AccessRights: OPEN
    Format: HTML
    Encoding: None

    Linked to Other Spase Resource(s) (example: another SimulationModel) :

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