1. 5-9 November 20129ESSW, Brussels1 Solar activity impact on the Earth’s upper atmosphere review paper SG1.1.4 presented by Ivan Kutiev

2. 5-9 November 20129ESSW, Brussels2 Authors Kutiev*, Ivan(1), Ioanna Tsagouri(2), Loredana Perrone(2),Dora Pancheva(1), Plamen Mukhtarov(1), Andrei Mikhailov(4), Jan Lastovicka(5), Norbert Jakowski(6), Dalia Buresova(5), Estefania Blanch(7), Borislav Andonov(1),, David Altadill(7), Sergio Magdaleno(9), Mario Parisi(8) and J. Miquel Torta(7) 1 National Institute of Geophysics, Geodesy and Geography, Bulgarian Academy of Sciences, 2 Institute for Space Applications and Remote Sensing, National Observatory of Athens, Greece 3 Istituto Nazionale di Geofisica e Vulcanologia, Italy 4 Institute of Terrestrial Magnetism, Ionosphere, and Radio Propagation, Russian Academy of Sciences. 5 Institute of Atmospheric Physics ASCR, Czech Republic, 6 Institute of Communications and Navigation, German Aerospace Center, 7 Ebro Observatory, University Ramon Llull – CSIC, Spain 8 Dipartimento di Fisica, Università degli Studi di Roma, Italy 9 Atmospheric Sounding Station “El Arenosillo”, INTA, Huelva, Spain

3. 5-9 November 20129ESSW, Brussels3 Content 2. Medium- and long term ionospheric response to the changes in solar and geomagnetic activity 2.1 Response of low-latitude ionosphere to 27-day variations of solar and geomagnetic activity 2.2 Thermosphere- ionosphere coupling in response to recurrent geomagnetic activity 2.3 Long-term trends in the upper atmosphere and ionosphere and space weather/climate 2.4 Latitude dependent response of TEC to solar EUV changes 2.5. Ionospheric behaviour during prolonged minimum of the 23/24 solar cycle 3. Storm-time ionospheric response to the solar and geomagnetic forcing 3.1 Ionospheric response to geomagnetic activity during prolonged solar minimum 3.2 Polar cap absorption event of May 2005 in Antarctica 3.3 E-layer dominated ionosphere

4. 5-9 November 20129ESSW, Brussels4 Content – cont. 4. Modeling and forecasting techniques 4.1 Empirical model of the TEC response to the geomagnetic activity over the North American region 4.2 Advances in the development of ionospheric forecasting models 4.3 Real time forecasting tool for hmf2 at midlatitudes combining quiet and disturbance hmf2 models 4.4 DIAS effective sunspot number: an indicator of the ionospheric activity level over Europe 4.5 Retrieval of thermospheric parameters from routine ionospheric observations

5. 5-9 November 20129ESSW, Brussels5 Selected topics Medium-term ionospheric response to solar activity: 27-days oscillations of TEC The magnitude of 27-days oscillation in both rTEC27 (red line) and rTEC38 (green line) for the whole period of analysis 2000-2008. The magnitude of the 27-day oscillation in F10.7 is shown with the scale on the right (Kutiev et al. 2012).

6. 5-9 November 20129ESSW, Brussels6 Selected topics Medium-term ionospheric response to solar activity: 27-days oscillations of TEC Top: rTEC variations between days 180 and 270, in 2004, superimposed by a periodic variation (solid black curve), with period close to 27 days. Vertical arrows mark the start of some of these deviations, which coincide with the storms onsets (Kutiev et al. 2012).

7. 5-9 November 20129ESSW, Brussels7 Selected topics Medium-term ionospheric response to solar activity: 9-days planetary waves in foF2 and hmF2 (upper row of plots) Extracted from the COSMIC data 9-day zonally symmetric (s=0) waves seen in the ionospheric parameters: foF2 (left plot) and hmF2 (right plot); (bottom row of plots) Phase difference between the ionospheric parameters foF2 and the PI (left plot) and between hmF2 and PI (right plot); the thick white line shows the zero phase difference.

8. 5-9 November 20129ESSW, Brussels8 Selected topics Long-term trends in upper ionosphere The figure: Model simulation of trends in foF2 and hmF2 at noon, longitude 0 o, as a difference between the basic state and the state with doubled CO 2 concentration. Dashed curve – hmF2 for basic state; solid curve – hmF2 for doubled CO 2. After Qian et al. (2008). The role of space weather/climate in long- term changes and trends in the upper atmosphere-ionosphere was more important in the past, when it controlled the trends in ionospheric parameters, than it is at present, when the dominant controlling parameter seems to be increasing concentration of CO 2.

9. 5-9 November 20129ESSW, Brussels9 Selected topics E-layer dominated ionosphere (ELDI) Left panel: Typical electron density profile derived from GPS RO measurements onboard Formosat3/COSMIC, CHAMP and GRACE satellites. Right panel: Ellipse fit to the distribution of ELDI profiles, which show enhanced E-layer ionization (red dots). The yellow stars mark the focal points of the ellipse; the black star marks the center point of the circle fit which coincides with the position of the geomagnetic pole. (Mayer & Jakowski, 2009).

10. 5-9 November 20129ESSW, Brussels10 Selected topics Empirical ionosphere modeling: TEC/Kp dependence with time delays The figure: Two-dimensional (latitude-lag time) cross-correlation functions calculated between the rVTEC and Kp-index for 6 months of the year; the zero line is shown by dashed white line (Andonov et al. 2012). Ionospheric response to Kp changes is composed by two phases, positive and negative, with different duration and different time delay.

11. 5-9 November 20129ESSW, Brussels11 Selected topics SWIF combines the autoregression forecasting algorithm, called Time Series AutoRegressive – TSAR (Koutroumbas et al. 2008), with the empirical Storm Time Ionospheric Model – STIM (Tsagouri & Belehaki 2006, 2008) which formulates the ionospheric storm time response with solar wind parameters (magnitude of the IMF, its rate of change and Bz). STIM provides a correction factor to the quiet model TZAR). STIM estimates the time delay in the ionospheric storm onset and estimates the ionospheric storm time response by taking into account the latitude and the LT of the observation point at the storm onset. Empirical ionosphere modeling: foF2/SW parameters (SWIF)

12. 5-9 November 20129ESSW, Brussels12 Selected topics Empirical ionosphere modeling: hmF2 triggered by SW changes Global quiet-time behavior of hmF2, has been modeled by the Spherical Harmonic Analysis (SHA) technique (Altadill et al. 2009). Blanch (2009) has developed a model describing the storm time deviation of the peak height ΔhmF2, which uses a bell-shaped functions whose coefficients depend on IMF configuration, local time and season. Both models have been combined for modeling hmF2 under both quiet and disturbed conditions The figure: Red points represent experimental values and the red line shows the model prediction. The black points represent the average data and the black line corresponds the quiet time hmF2 prediction of SHA model. Vertical grey dashed line indicates the triggering time.

13. 5-9 November 20129ESSW, Brussels13 Selected topics Retrieval of thermospheric parameters from ionospheric data A new method has been developed (Mikhailov et al. 2012) to retrieve neutral temperature Tn and composition [O], [N2], [O2] from electron density profiles in the daytime mid-latitude F2-region under both quiet and disturbed conditions. The figure: Reduced to the Millstone Hill location and 400 km height CHAMP neutral gas density observations along with  10% error bars, MSISE-00 and JB2006 model predictions and the model extracted neutral gas density at 400 km height (stars) using ISR Ne(h) profiles for October 2002 (solar maximum).

14. 5-9 November 20129ESSW, Brussels14 Thank you