In winter and equinoctial season nights, the main trough of the F region is an important stable structure of the ionosphere at the border between mid and high latitudes. Therefore it has to be taken into account in modelling and mapping approaches. Werner and Prölss (1995) derived a model for the position of the trough minimum which has found wide acceptance. The model is based on in-situ electron density data measured aboard the low orbiting Dynamic Explorer satellite DE 2 (1981-1986). We present results for other properties of the main trough derived from the same data set. These results are sufficiently good for modelling purposes which need reliable information on the depth, the equatorward and poleward width and the steepness of the walls of the trough. Because of the eccentric orbit of DE 2 (orbit height between about 300-1000 km) it was necessary to «project» observed electron densities to the peak of the F 2 layer. This was done by means of the electron density model COSTprof. The database was restricted to those cases for which the height of DE 2 was below 700 km. Examples are shown for «typical» troughs observed under various conditions.

Usually regional and global electron density models provide large scale spatial structures only and smooth out the smaller scale features of the electron density distribution. We present a method to modulate existing electron density models by multiplication: M(h, φ, λ, t) = L(h, φ, λ, t) × S1(h, φ, λ, t) × S2(h, φ, λ, t) × ... Sn(h, φ, λ, t) M: resulting electron density distribution, L: large scale model, S1...Sn: modulating models for n the smaller scale structures; h: height; φ, λ: geographic coordinates, t: Universal Time. There are no restrictions to the nature of the large scale model provided it takes height and horizontal coordinates as input. Examples are models of the "profiler" type which use large scale "maps" for profile anchor points (e.g., E, F1, F2 peak properties) like the International Reference Ionosphere (IRI). Typical examples for smaller scale structures are ridges, troughs and wavelike disturbances. The advantage of modulation by multiplication is that there is no danger to get zero or negative values of electron density as long as the background and modulations are >0 everywhere. For each modulation model, unity means "undisturbed".

A complete three dimensional formulation for the main trough has been constructed on the basis of Dynamic Explorer (DE) data. The model uses the trough minimum model published by Werner and Prölss (which is also based on DE data) and a time dependent shape of the trough. The shape parameters — depth of the trough — equatorward half-width — poleward half-width — steepness of the equatorward wall — steepness of the poleward wall have been derived from Dynamic Explorer electron densities gained in the height region below 700 km and scaled to the F2 layer peak by means of the COSTprof model. Our trough model uses the medians of the shape parameters for three seasons (winter, equinox, summer) and two magnetic local time intervals (“day” and “night”).

COSTTEC is a monthly median regional map for ionospheric electron content. The data used for the mapping effort are monthly and bi-hourly medians from Differential Doppler observations on the signals of the Navy Navigation Satellites (NNSS) made at Graz/Austria and Lindau/Harz, Germany. COSTTEC uses linear dependences of electron content on the solar activity index R12, on geographic latitude and on geographic longitude. For the local time dependence and for the seasonal dependence it uses Fourier decomposition. The decomposition converts the 12x12 time domain medians into 12x12 Fourier coefficients. For the maps only 5x5 coefficients are kept (time independent term, diurnal and semi-diurnal variation, annual and semi-annual variations and all combinations). Finally the maps consist of 2x3 sets of 5x5 Fourier coefficients: 3 sets for high and 3 sets for low solar activity. At each solar activity level one set is for a central point, one for the latitudinal and one for the longitudinal gradients. Since no TEC data could be used to derive the longitude dependence it was necessary to incorporate experience from F2 peak density behaviour.We report on the reasons for the chosen mapping approach, demonstrate the most important map properties and show comparisons between observations and TEC map data. (C) 2000 Elsevier Science Ltd. All rights reserved.

Space Weather effects influence the atmosphere of the Earth, among others stratospheric ozone. One other region of the upper atmosphere which shows very strong Space Weather dependence is the ionosphere. It is a very important region because it affects satellite communication and navigation. On the other hand the ionization is a good tracer and indicator for various Space Weather influences. In this respect the ionosphere has no predictive capabilities and cannot support early warning but it provides one link between the sun, the solar wind, the magnetosphere and the neutral atmosphere. Solar EUV induced inospheric effects are coupled to solar radiation related events in the neutral atmosphere and therefore ionospheric effects give some qualitative hints at possible effects on stratospheric ozone. Ionospheric Space Weather effects can be observed continously from the ground by means of propagation effects on radio waves. Electron content (TEC) is a very important descriptive quantity for the ionosphere of the Earth. TEC is gained by means of “propagation effects” which are observed on received radio signals which are transmitted from artificial satellites. TEC data have been collected in Europe systematically and on a longterm basis since 1965. The data are used to investigate “geophysical events”, e.g., the Space Weather related (magnetic) storm effects. They are also used to formulate empirical models which describe the large scale and longterm behaviour of average TEC data, usually of monthly medians. We show examples for “instantaneous” TEC data, for a monthly median TEC model and for TEC maps produced on a regular basis for application purposes.

The double-sunspot-cycle variation in terrestrial magnetic activity has been well known for about 30 years. In 1990 we examined and compared the low-solar-activity (LSA) part of two consecutive cycles and predicted from this database and from published results the existence of a double-sunspot-cycle variation in total electron content (TEC) of the ionosphere too. This is restricted to noontime when the semi-annual component is well developed. Since 1995 we have had enough data for the statistical processing for high-solar-activity (HSA) conditions of two successive solar cycles. The results confirm the LSA findings. The annual variation of TEC shows a change from an autumn maximum in cycle 21 to a spring maximum during the next solar cycle. Similar to the aa indices for geomagnetic activity the TEC data show a phase change in the 1-year component of the Fourier transform of the annual variation. Additionally we found the same behaviour in the F-layer peak electron density (Nmax) over four solar cycles. This indicates that there exists a double-sunspot-cycle variation in the F-layer ionization over Europe too. It is very likely coupled with the 22-year cycle in geomagnetic activity.

In the frame of PRIME (Prediction and Retrospective Ionospheric Modeling over Europe) a regional TEC model has been developed from data gained by the Differential Doppler effect on the 150/400 MHz signals of the polar orbiting NNSS satellites. The model uses 4 sets of 5 × 5 Fourier coefficients, 2 sets for high solar activity (HSA), 2 for low solar activity (LSA). In each case one set is valid for 52.5°N, the other gives the latitudinal gradients. The Fourier terms represent the seasonal and local time mean (time independent term), the annual, the semi-annual, the diurnal, the semi-diurnal components and the combinations of annual and diurnal variation. The model was adopted by the PRIME project. Various combinations of Differential Doppler with Faraday data were tested too, the Faraday data were used to improve the diurnal variation in the models. Since differences in the TEC behaviour were found between odd and even solar cycles, two different regional models, one for odd, the other for even cycles, have been constructed. The differences concern the vernal-autumnal asymmetry around noon time: in the even cycles TEC was higher in spring than in autumn, the odd cycles showed the opposite (autumnal maxima).