Ionospheric Monitoring and Prediction Center

Radio signals transmitted by modern communication, navigation and Earth observation systems can be heavily disturbed by severe space weather events. Thus, strong temporal and spatial changes of the electron density in the ionosphere can significantly degrade the signal quality of various radio systems which even may lead to a complete loss of the signal. In order to provide space weather information that is in particular relevant for users of communication and navigation systems, the German Aerospace Center (DLR) is operating the online platform Space Weather Application Center Ionosphere (SWACI) since 2004 (http://swaciweb.dlr.de). SWACI has started as a feasibility study supported by the state government of Mecklenburg-Vorpommern for the real time provision of now- and forecast products characterizing the ionospheric state. Since then, SWACI has been continuously extended and improved and is now a grown up system with high accuracy products and dissemination solutions that forms the infrastructure for the present establishment of an Ionosphere Monitoring and Prediction Center (IMPC) at DLR. The IMPC is designed to be a reliable permanent ionospheric weather service using ground as well as space based GNSS data, vertical sounding data of ionosonde stations, radio beacons and solar wind data to provide relevant and precise information for GNSS users in the area of telecommunication, precise radio-measurements and navigation. IMPC products available in near real time form an essential part of risk assessment and mitigation of ionospheric threats during space weather events. Moreover, significant tasks like monitoring of critical ionospheric parameters, detection and assessment of ionospheric disturbances, modeling and prediction of relevant ionospheric parameters to forecast ionospheric conditions as well as provision of information and alerts relevant for GNSS users are covered by the IMPC. An overview on the recent status of the IMPC and the application oriented research towards even more sophisticated methods for spatial and temporal high-resolution reconstruction, modeling and forecasts of the ionosphere is presented in this paper.