Linked space physics models for operational ionospheric forecasting

Details Linked space physics models for operational ionospheric forecasting Linked space physics models for operational ionospheric forecasting

Dec 2003

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2003agufmsm11a..01t&link_type=abstract

American Geophysical Union, Fall Meeting 2003, abstract #SM11A-01

Mathematics

Logic

0358 Thermosphere: Energy Deposition, 2427 Ionosphere/Atmosphere Interactions (0335), 2431 Ionosphere/Magnetosphere Interactions (2736), 2447 Modeling And Forecasting, 9820 Techniques Applicable In Three Or More Fields

Scientific paper

The shorter-term variable impact of the Sun's photons, solar wind particles, and interplanetary magnetic field upon the Earth's environment that can adversely affect technological systems is colloquially known as space weather. It includes, for example, the effects of solar coronal mass ejections, solar flares and irradiances, solar and galactic energetic particles, as well as the solar wind, all of which affect Earth's magnetospheric particles and fields, geomagnetic and electrodynamical conditions, radiation belts, aurorae, ionosphere, and the neutral thermosphere and mesosphere. These combined effects create risks to space and ground systems from electric field disturbances, irregularities, and scintillation, for example, where these ionospheric perturbations are a direct result of space weather. A major challenge exists to improve our understanding of ionospheric space weather processes and then translate that knowledge into operational systems. Ionospheric perturbed conditions can be recognized and specified in real-time or predicted through linkages of models and data streams. Linked systems must be based upon multi-spectral observations of the Sun, solar wind measurements by satellites between the Earth and Sun, as well as by measurements from radar and GPS/TEC networks. Models of the solar wind, solar irradiances, the neutral thermosphere, thermospheric winds, joule heating, particle precipitation, substorms, the electric field, and the ionosphere provide climatological best estimates of non-measured current and forecast parameters. We report on a team effort that is developing a prototype operational ionospheric forecast system to detect and predict the conditions leading to dynamic ionospheric changes. The system will provide global-to-local specifications of recent history, current epoch, and 72-hour forecast ionospheric and neutral density profiles, TEC, plasma drifts, neutral winds, and temperatures. Geophysical changes will be captured and/or predicted (modeled) at their relevant time scales ranging from 10-minute to hourly cadences. 4-D ionospheric densities are being specified using data assimilation techniques, coupled with physics-based and empirical models for thermospheric, solar, electric field, particle, and magnetic field parameters that maximize accuracy in locales and regions at the current epoch, maintain global self-consistency, and improve reliable forecasts. We report on a system architecture underlying the linkage of models and data streams that is operationally reliable and robust to serve commercial space weather needs.

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