Improved Modeling of Short and Long Term Characteristics of Ionospheric Disturbances During Active Years of the Solar Cycle
This activity has the objective of developing ionospheric models and adapt existing ones based on experimental data measured in activities during active periods of the solar cycle (e.g. MONITOR) able to:- reproduce the effects of the ionosphere in equatorial regions (temporal/spatial gradients and ionospheric scintillations)- reproduce small-scale effects such as TIDs or depletions and other disturbances- understand better the effects of geomagnetic storms in the ionosphere- adapt to changes in geomagnetic field and solar cycle- improve prediction and forecasting capabilities for ionospheric effects- understand the effects of such effects on GNSS systems
Extensive measurements over solar maximum will be carried out during the MONITOR activity under the GNSS Evolutions Programme and other experiments from external organisations. They will be able to provide a better insight on several processes affecting GNSS performance and they will have a proper basis for improved modelling. Such activities does not focus on a deep analysis of specific effects and the actual modelling of effects currently not considerd on average models. Also long-term characteristics shall be characterised on statistical basis.Furthermore, ionospheric climatological models uses monthly median maps of M(3000) and foF2 for ionospheric electron density and other predictions and internal analysis has indicated that such maps must be adapted to changes of geomagnetic field and solar cycle variations.The activity covers the following tasks:- Review and select relevant data from internal and external activities for the detailed characterisation of ionospheric effects (in the long and short-term).- Analyse tha data and process to remove external error contributions for the understanding of ionospheric characteristics. Compare with external data and geophysical indices.- Develop models suitable to analyse effects on GNSS systems and users.- Select datasets that reproduce effects on given scenarios, able to verify the models.- Analyse the effects on GNSS performance of the studied effects.