WAM-IPE provides neutral atmospheric parameters from the ground to the upper thermosphere at around 500 km.
WAM was developed based on the spectral version of the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) used for medium-range numerical weather prediction. The WAM system is used to quantify the impact of lower atmosphere weather on the upper atmosphere and ionosphere, as well as the response to solar and geomagnetic activity. The thermospheric parameters calculated by WAM are fed into IPE for calculating the responses in the ionosphere. The ESMF 3D re-gridding capability is used for exchanging the information. IPE is a time-dependent and global three-dimensional model that provides densities, temperatures, and velocity of ions and electron from 90 km to several Earth radii. The International Geomagnetic Reference Field (IGRF) coordinate system is used to accurately represent Earth’s magnetic field. The fieldline calculations are based on the Field Line Interhemispheric Plasma (FLIP) model. The ExB transport is applied zonally and meridionally across Earth’s magnetic field. The magnetic field line or flux-tube coordinate system is designed for seamless perpendicular plasma transport pole-to-pole. In the operational setting, both models use the Weimer empirical ion convection model and TIROS auroral empirical model, both driven by the solar wind data, to specify the external energy input from the magnetosphere.
Inputs for Weimer model: Interplanetary magnetic field, By and Bz, in nT Solar wind density and speed, ρ and v, in cm-3 and km s-1
Primary timed-dependent output fields, specified in latitude, longitude, and pressure level: Geopotential height: Height of pressure surfaces (cm) Temperatures: Neutral, ion, electron (K) Neutral winds: zonal, meridional, (cm s-1), vertical (s-1) Composition: O, O2, NO, N(4S), N(2D) (mass mixing ratios - dimensionless) Ion and electron densities: O+, O2+, Ne (cm-3), (NO+ is calculated from Ne - (O+ + O2+)) Electric potential: (V) Ion drift
Model is time-dependant.
- Global Ionosphere
Space Weather Impacts
- Ionosphere variability (navigation, communications)
- Atmosphere variability (satellite/debris drag)
- Fang, T.-W., R. Akmaev, R. A. Stoneback, T. Fuller-Rowell, H. Wang, and F. Wu (2016), Impact of midnight thermosphere dynamics on the equatorial ionospheric vertical drifts, J. Geophys. Res. Space Physics, 121, 4858–4868
- Fang, T.-W., T. Fuller-Rowell, V. Yudin, T. Matsuo, R. Viereck (2018), Quantifying the sources of ionosphere day-to-day variability, J. Geophys. Res. Space Physics, 123
- Fuller-Rowell, T. J., R. Akmaev, F. Wu, A. Anghel, N. Maruyama, D. N. Anderson, M. V. Codrescu, M. Iredell, S. Moorthi, H.-M. Juang, Y.-T. Hou, and G. Millward (2008), Impact of terrestrial weather on the upper atmosphere, Geophys. Res. Lett., 35, L09808
- Fuller-Rowell, T., Z. Li, T.-W. Fang, M. Fedrizzi, M. MacCandless, E. Sutton, S. Iyer, M. Jah, A. Medema (2021), Neutral Density for Satellite Drag and Space Traffic Management from an Operational Physics-Based Model, Abstract SA24B-09 presented at 2021 AGU Fall Meeting, 13-17 Dec
- Maruyama, N., Y.-Y. Sun, P. G. Richards, J. Middlecoff, T.-W. Fang, T. J. Fuller-Rowell, R. A. Akmaev, J.-Y. Liu, and C. Valladares (2016), A new source of the midlatitude ionospheric peak density structure revealed by a new Ionosphere-Plasmasphere model, Geophys. Res. Lett., 43
- Fang, T.-W., Kubaryk, A., Goldstein, D., Li, Z., Fuller-Rowell, T., Millward, G., et al. (2022). Space Weather Environment During the SpaceX Starlink Satellite Loss in February 2022. Space Weather, 20, e2022SW003193.
Code Languages: Fortran
- Jia Yue, NASA/GSFC (CCMC Model Host)
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