Extreme ionospheric conditions over Europe observed during the last solar cycle

Kurzfassung

Since GNSS signals are affected by the ionospheric plasma, the extreme variability of the ionosphere poses a threat to GNSS applications. We perform a review of ionospheric conditions over Europe during the last solar cycle focusing on parameters important for GNSS applications, such as ionospheric spatial and temporal gradients and the ionospheric de-correlation function. A large dataset of calibrated slant TEC measurements and TEC maps over Europe covering the entire last solar cycle has been generated and archived in DLR Neustrelitz. Using this data, we were able to determine both the “normal” ionospheric state and extreme ionospheric events over the European region. The probability density function (pdf) of TEC based ionospheric spatial gradients was computed for various geophysical conditions enabling us to present parameterized pdfs of spatial ionospheric gradients depending on selected geophysical parameters. Under disturbed ionospheric conditions, we find North-South dominance in ionospheric gradients over Europe. The largest horizontal TEC gradients observed during the last solar cycle over Europe were observed during severe ionospheric storms such as the “Halloween” storm at the end of October 2003. Using the TEC maps, reconstructed from calibrated slant TEC measurements, we were able to distinguish spatial gradients and temporal variations of TEC at selected grid points of the maps. The TEC rate of change was analysed in a similar way as the spatial ionospheric gradients, i.e. the TEC rate of change dependence on geophysical parameters was investigated and the largest observed temporal changes were estimated. The ionospheric spatial de-correlation function is a measure of how independent TEC measurements are depending on their distance. It is an important input for the design of GBAS systems, for Kriging algorithms, and for the construction of the so-called generalized covariance matrix. The ionospheric de-correlation function is estimated for different geo-physical conditions, such as low and high solar activity and quiet and disturbed geomagnetic conditions. By comparing the measured de-correlation with de-correlation values obtained from ionosphere models representing climatological or "normal" ionospheric conditions, we check whether pdf-dependencies on geophysical parameters such as the F10.7 solar radio flux, latitude and azimuth are consistent with the model values. This comparison will also indicate whether the results obtained over the European region can be extrapolated to other regions, e.g. low latitudes. Most ionospheric perturbations are closely related to changes of geomagnetic activity usually described by geomagnetic indices, such as the DST or KP index. However, as our studies show, there remain a number of ionospheric disturbances which are obviously not related to variations of geomagnetic indices. Thus, to describe the perturbation degree of the ionosphere in a reliable manner, we suggest describing the ionospheric perturbation degree by a specific ionospheric perturbation index. Since most of current global ionospheric information is obtained thanks to the innovative GNSS technology, it is suggested to use GNSS derived parameters such as TEC for defining such an index. In addition to the high effectiveness of ionospheric monitoring by GNSS measurements, this technique is also sufficiently robust in the presence of ionospheric perturbations. Furthermore, the derived quantities such as TEC are directly usable for mitigating ionospheric range errors in space based positioning and navigation. Ionosphere signal delay is one of the major contributors to pseudo range residual error for both absolute positioning and for relative positioning (GBAS); therefore a detailed impact analysis at pseudo-range level will be made. Absolute error impact represented by the instantaneous variance for all satellites in view for a given period of measurements at three different locations and the relative error impact represented by the instantaneous covariance for all pairs of visible satellites derived from the ionosphere de-correlations results presented above is investigated. A generalized model of instantaneous covariance matrix is generated in line with the ionosphere measurement model described above. The results are compared with a standard covariance matrix and conclusions on its applicability to positioning algorithms will be drawn.