GNGTS 2014 - Atti del 33° Convegno Nazionale

GNGTS 2014 S essione 2.1 29 Ionospheric Disturbances were considered possible sources of particle flux perturbations as in past discussions (Sgrigna et al. , 2005). Sudden Ionospheric Disturbances are produced in the ionosphere by enhanced solar radiation during solar flares, which include VLF-LF effects (Deshpande et al. , 1972), and cosmic rays (Inan et al. , 2007). In order to include the geomagnetic and extraterrestrial influences on the particle fluctuations, the counting rate data were associated to daily averages of the geomagnetic Ap index and Sudden Ionospheric Disturbances (http:// www.aavso.org/solar-sids ), as well as three hour averages of the Ap index (ftp://ftp.ngdc.noaa . gov/STP/GEOMAGNETICDATA/APSTAR/apindex). The counting rate exclusions from the correlation analysis occurred when geomagnetic indexes overcame thresholds, which were calculated by annual and 11-year Sun particle modulations (Fidani et al. , 2012). As counting rate fluctuations originating in the magnetosphere also occur in sub-storm activity, the quality of the selected quiet geomagnetic days was verified including days with Dst variations (http:// wdc.kugi.kyoto-u.ac.jp/dst_final/index.html ) less than 30 nT. The first step of the analysis was to define the significant electron counting rate fluctuations. Data processing started by building a map of daily counting rates in the geomagnetic invariant space (Walt, 1994), since counting rates are strongly variable along the satellite orbit. Counting rates compared at each geographical position was same as considering the counting rate contribution fromseveral phenomena at different energies, which showa very irregular behaviour with a sudden counting rate increase of several powers to the tenth. A multi-peak distribution descending from such an approach gives no standard statistical results. Adiabatic invariants, however, allow for the determination of different geographical positions where particles are expected to possess the same dynamics and where counting rate deviations can be studied (McIlwain, 1966); thereby permitting to search for fluctuations. Here, particle dynamics were described by their adiabatic invariants: geomagnetic field at mirror points B m and the magnetic shell parameter L . The parametrization of B m = B/cos2α with respect to the geomagnetic field B and the pitch angles α at each other position were introduced, so to represent counting rate in a 4-dimensional matrix ( t ; L ; α ; B ) including time. Unlike previous works (Aleksandrin et al. , 2003; Sgrigna et al. , 2005), the introduction of B parameter was useful because it allowed to control the strong counting rate spatial variability when it entered the South Atlantic Anomaly (Asikainen and Mursula, 2008). As made in past works, to obtain less than 1% probability that the counting rate fluctuations x s were of a statistical origin, the condition P(x s ) < 0.01 had to be satisfied by following the method described in (Fidani et al. , 2008). The counting rate x was considered to be a significant counting rate fluctuation with probability greater than 99% if x > x s , corresponding to the same adiabatic coordinates. Poisson distributions at all regions were expressed by their averages in the adiabatic space. Being so, it was possible to verify if NOAA particle telescopes revealed any significant counting rate fluctuations along the entire satellite orbit. For example, single electron burst events were defined by simply joining contiguous 8 s electron counting rates which exceeded x s , up to a maximum total duration of 600 seconds (Fidani et al., 2010). The pattern obtained by summing the daily 8 s electron counting rates which exceeded x s at low L - shell intervals between 1998 and 2011, for the 0° detector with electron energy from 30 keV to 100 keV is shown in Fig. 1. Correlation between earthquakes and electron bursts. The correlation was defined by filling a histogram with the differences T EQ - T EB , between the earthquake time T EQ and the electron burst time T EB , only for those seismic events and particle precipitations which satisfied | L EQ − L EB | ≤ 0.1. This calculation was performed at different altitudes of earthquake epicentre projections, by estimating L EQ at each altitude from -600 km up to 3200 km in increments of 100 km. To reduce the effects of solar activity, data corresponding to low values of Ap indexes were chosen for three and 24 hour intervals (Fidani et al. , 2012). Furthermore, electron burst data were considered “Sun influenced” when Sudden Ionospheric Disturbances occurred within the