Abstract. In this paper, we present observational evidence for the trans-polar propagation of large-scale Traveling Ionospheric Disturbances (TIDs) from their nightside source region to the dayside. On 13 February 2001, the 32 m dish of EISCAT Svalbard Radar (ESR) was directing toward the geomagnetic pole at low elevation (30 • ) during the interval 06:00-12:00 UT (MLT ≈ UT + 3 h), providing an excellent opportunity to monitor the ionosphere F-region over the polar cap. The TIDs were first detected by the ESR over the dayside north polar cap, propagating equatorward, and were subsequently seen by the mainland UHF radar at auroral latitudes around geomagnetic local noon. The propagation properties of the observed ionization waves suggest the presence of a moderately large-scale TIDs, propagating across the northern polar cap from the night-time auroral source during substorm conditions. Our results agree with the theoretical simulations by Balthazor and Moffett (1999) in which poleward-propagating large-scale traveling atmospheric disturbances were found to be self-consistently driven by enhancements in auroral heating.

Abstract. In this paper, climatological features of the polar F2-region electron density (N e ) are investigated by means of statistical analysis using long-term observations from the European Incoherent Scatter UHF radar (called EISCAT in the following) and the EISCAT Svalbard radar (ESR) during periods of quiet to moderate geomagnetic activity. Fieldaligned measurements by the EISCAT and ESR radars operating in CP-1 and CP-2 modes are used in this study, covering the years 1988-1999 for EISCAT and 1999-2003 for ESR. The data are sorted by season (equinox, summer and winter) and solar cycle phase (maximum, minimum, rising and falling). Some novel and interesting results are presented as follows: (1) The well-known winter anomaly is evident during the solar maximum at EISCAT, but it dies out at the latitude of the ESR; (2) The daytime peaks of N e at EISCAT for all seasons during solar maximum lag about 1-2 h behind those at ESR, with altitudes about 10-30 km lower. (3) In addition to the daytime peak, it is revealed that there is another peak just before magnetic midnight at ESR around solar maximum, especially in winter and at equinox. The daytime ionization peak around magnetic noon observed by ESR can be attributed to soft particle precipitation in the cusp region, whereas the pre-midnight N e maximum seems likely to be closely related to substorm events which frequently break out during that time sector, in particular for the winter case. (4) Semiannual variations are found at EISCAT during solar minimum and the falling phase of the solar cycle; at the rising phase, however, the EISCAT observations show no obvious seasonal variations.

SYM-H isone of the important indices for space weather. It indicates the intensity of magnetic storm, similarly to Dst index but with much higher time-resolution. In this paper an artificial neural network (ANN) of Nonlinear Auto Regressive with eXogenous inputs (NARX) has been developed to predict SYM-H index from solar wind and IMF data. In comparison with usual BP and Elman network, the new NRAX model shows much better prediction capability. For 15 testing great storms including 5 super-storms of Min. SYM-H < −200 nT, the cross-correlation of SYM-H indices between NARX network predicted and really observed is 0.91 as a whole. For the 5 individual super-storms, the lowest coefficients is 0.91 relating to the super-storm of March 2001 with Min.SYM-H of −434 nT; while for the two super-storms with Min. SYM-H ranging from −300 nT to −400 nT, the correlations reach as high as 0.93 and 0.96 respectively. The remarkable improvement of the model performance can be attributed to such a key feedback from the network output of SYM-H with a suitable length (about 120 min) to the input, which implies that some information on the quasi real-time ring currents with a proper length of history does its work in the prediction. It tells us that, in addition to the direct driving by solar wind and IMF, the own status of the ring current plays an important role in its evolution especially for recovery phase and must properly be considered in storm-time SYM-H prediction by ANN. The neural network model of NARX developed in this paper provides an effective way to achieve it. magnetic storm, SYM-H index, space weather, prediction, artificial neural network