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Characterization of the space environment at Mercury’ orbit P. Diego, M. Laurenza, M.Storini, and S. Massetti IAPS/INAF - Italy.

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Presentation on theme: "Characterization of the space environment at Mercury’ orbit P. Diego, M. Laurenza, M.Storini, and S. Massetti IAPS/INAF - Italy."— Presentation transcript:

1 Characterization of the space environment at Mercury’ orbit P. Diego, M. Laurenza, M.Storini, and S. Massetti IAPS/INAF - Italy

2 Space Climate study to point out environmental conditions between 0.3 and 0.47 A.U. for BepiColombo mission.  Short–term and long–term solar variability are considered  Results are compared to OMNI data at 1 A.U. Mercury’s magnetosphere response to different SW inputs are considered Suprathermal particles flux occurrences and fluxes are analyzed Index

3 Solar Activity - Short Term Variability Corotating Structures; 27-days recurrent streams, (HSSs from Coronal Holes), Solar Magnetic Sectors Transient Solar Phenomena; Solar Flares, ICMEs (e.g. Magnetic Clouds (MC), Non Compressive Density Enhancements (NCDE)) In order to identify occurrences of persistent conditions at Mercury’s orbit only the largest (duration > 12h) perturbations have been selected. The durations of this short term variability span from hours to days. Shorter time-scale fluctuations are not considered for our purpose.

4 Solar Activity Long Term Variability Solar Activity cycle; duration, amplitude and phases, Gnevyshev Gap Even and odd solar cycles; The time scale of this variability spans from few months (cycle increase / decrease, G-Gap,…) up to 22 years (Hale cycle)

5 Data Used and Events Selection Helios 1 and 2 hourly data for period from 1975 to 1980 between 0.3 and 0.47 A.U. (about 2x30 days/year) Perturbation category individuated are: HSSs from CH (e.g. Mavromichalaki et al. 1988) ICME from active regions. Among them we selected: Magnetic Clouds (MC – Burlaga 1981) Non Compressive Density Enhancements (NCDE – Gosling et al. 1977) 22 HSSs, 11MCs, and 27 NCDEs have been identified Helios 1 data for April 1977. Orange selections indicate HSSs, grey a NCDE, and blue a Magnetic Cloud

6 Number of selected perturbations for each Helios, 1and 2, passage at Mercury’s orbit along with Solar Cycle n. 21 profile. Interplanetary Shock numbers (Volkmer and Neubauer, 1985) are superimposed (red markers).

7 Solar Perturbations occurrences are displayed in % of total observation time. High percentage could depend on reduced time of observations.

8 Why do we separate classes of perturbations? Because the relative percentage of each class depends on long term solar activity variations such as phase, amplitude. The phase of cycle; by definition is the temporal evolution of Sunspots Number Odd numbered cycle features; enhanced transient activity during rise and maxima, higher amplitude of maxima (Cliver et al. 1996) Even numbered features; enhanced co-rotating solar structure during descending phases The amplitude of solar cycle determines the ratio of active regions and CH at mid solar latitudes While the first two are easily identified, the third one should be forecasted. To forecast the solar cycle amplitude we could study the persistence of polar magnetic structures. In fact for some dynamo models [e.g. Dikpati et al., 2004; Choudhuri et al., 2008] the polar field is essential for the generation of sunspots of the subsequent cycle, although their persistence could lead to opposite results when predicting the sunspots maximum amplitude.

9 Polar CH lifetime and extension are inversely related to the strength of Sun's polar fields of the following activity cycle[e.g. Rowse and Roxburgh, 1983; Bravo and Stewart, 1994]. Diego et al. (JGR, 2009) performed an alghoritm to evaluate the CH persistence by analysing a century of corotating perturbations effect on geomagnetic activity. The Persistence index computed during descending phases shows a high anti-correlation with the following solar activity cycle amplitude.

10 Global Sunspot’s Areas for solar cycle n. 24 has been predicted to be the lowest of the last 100 years!

11 Range of V is nearly constant from 0.3 to1 A.U. Ratio between average values of Helios and OMNI data (H/O) is: H/O(V tot ) = 1.0 H/O(V HSS ) = 1.0 H/O(V MC ) = 0.9 H/O(V NCDE ) = 0.9 Transient Perturbations show lower values (200-280 km/s) not fount at 1 A.U.

12 Range of D is near 10 times higher at Mercury’s orbit Ratio between average values of Helios and OMNI data (H/O) is: H/O(D tot ) = 9.2 H/O(D HSS ) = 10.2 H/O(D MC ) = 11.6 H/O(D NCDE ) = 8.8 Relative position of different classes of perturbation remains the same

13 Range of T is near 2 times higher at Mercury’s orbit Ratios between averaged values of Helios and OMNI data (H/O) is: H/O(T tot ) = 2.0 H/O(T HSS ) = 1.9 H/O(T MC ) = 1.5 H/O(T NCDE ) = 1.9 Relative position of different classes of perturbation remains the same

14 Range of B is nearly 4 times higher at Mercury’s orbit Ratios between averaged values: H/O(B tot ) = 5.0 H/O(B HSS ) = 6.3 H/O(B MC ) = 3.6 H/O(B NCDE ) = 4.8 In the inner heliosphere HSSs have IMF B values. comparable to transient’s ones. The radial gradient is greater of about a factor 2 for HSS with respect to transients (according to Burlaga’s (2001) global range of variability 3-6)

15 Range of Bx is nearly 6 times higher at Mercury’s orbit Ratios between averaged values : For positive values: H/O(Bx tot ) = 7.0 H/O(Bx HSS ) = 8.1 H/O(Bx MC ) = 5.4 H/O(Bx NCDE ) = 6.1 For negative values: H/O(Bx tot ) = 7.6 H/O(Bx HSS ) = 9.9 H/O(Bx MC ) = 5.4 H/O(Bx NCDE ) = 7.0 Results in agreement with Parker. The Bx of HSSs has the same behavior as B

16 Range of By is nearly 3 times higher at Mercury’s orbit Ratios between Ranges: H/O(By tot ) = 2.9 H/O(By HSS ) = 4.1 H/O(By MC ) = 2.4 H/O(By NCDE ) = 3.2 Results in agreement with Parker. Contributions on Alfvenic fluctuations during HSSs enlarge the range at Mercury’s orbit (Korth et al., 2011, Diego et al.2005)

17 Range of Bz is near 4 times higher at Mercury’s orbit Ratios between Ranges: H/O(Bz tot ) = 3.7 H/O(Bz HSS ) = 4.2 H/O(Bz MC ) = 3.1 H/O(Bz NCDE ) = 4.3 Results show radial decrease ≈ 1/r and a ratio Bz/By ≈ 0.6 In agreement with Mariani et al. (1979)

18 B (nT)BxPos (nT)BxNeg (nT)By (nT)Bz (nT)D (cm -3 )T (K)V (km/s) Parker Spiral (deg) Total 33.723.8-24.40.70.368.9242800417.6-16.9 Total_std 9.910.89.813.610.747.5162700120.627.3 HSSs 35.326.6-26.71.20.837.9383258541.8-15.2 HSSs_std 7.68.28.911.6815.916320011421.02 MCs 32.821.2-19.9-1.80.6111.7145023337.6-17.4 MCs_std 12.311.69.416.314.644.19103049.135 NCDEs 30.519.4-21.70.4 99.4149800338.3-19.6 NCDEs_std 11.210.811.414.411.348.710530061.732.8 Helios Data between 0.3 and 0.47 A.U. Average values Average values of Total dataset are in agreement with previous works (e.g. Burlaga 2001 and reference therein).

19 B (nT)BxPos (nT)BxNeg (nT) By (nT) (*) Bz (nT) (*) D (cm -3 )T (K)V (km/s) Parker Spiral (deg) Total 5.07.07.63.5-10.09.22.01.00.8 Total_std 3.25.44.72.93.78.51.61.20.6 HSSs 6.38.19.9-1.2-13.310.21.91.00.7 HSSs_std 5.14.85.94.14.29.41.61.30.5 MCs 3.65.4 -2.0-12.011.61.50.90.5 MCs_std 3.24.54.12.43.17.01.00.7 NCDEs 4.86.17.02.08.81.90.91.1 NCDEs_std 3.65.7 3.24.36.01.00.90.7 Ratios between Helios and OMNI. (*) Average values of OMNI data close to zero

20 Magnetospheric Model – Toffoletto Hill modified by Massetti Empirical–analytical magnetospheric model starting from the Toffoletto–Hill TH93 Code (Toffoletto and Hill, 1989, 1993). The new model has been fine tuned to approximately match the Mariner10 data (flyby III), and to reproduce some of the key features of the self-consistent hybrid model of Kallio and Janhunen (2003). IMF BX component in the model contributes to depict a realistic IMF–magnetosphere Reconnection geometry. Dipole values used is computed by Anderson et al, (2011) as 195 ± 10 nT/RM 3 HSSs Positive x y x z

21 HSSs Negative Sketch of the Mercury’s magnetosphere, computed for different values of IMF components, showing the spatial distribution of the field lines, which are: open on the dayside (X GSM ≥-1), (red) open on the tail (X GSM <-1), (grey). closed (blue).

22 MC Positive x y x z x y x z MC negative

23 NCDE Positive x y x z x y x z NCDE Negative

24 Intensity emission (kiloRayleigh) of the D2 line of Na (brightest sodium line). White profile evidences the planet position (dotted meridian are for the region not illuminated by the Sun). On the left a double spot probably due to IMF component sudden variations. On the right a single spots as in the case of defined IMF polarity. The input is a HSS the magnetic configuration could last for several days. Courtesy of V. Mangano (IAPS-INAF)

25 Suprathermal Particles SEP dependence on solar activity has been extensively investigated (e.g. Nymmik, 1999, Storini et al. 2008) and many computational model has been performed (see Vainio et al. for a review). Part of their database is summarized in figure above (Laurenza et al. 2007). Peak flux upper limit at 1 A.U. is close to 10 5 pfu on hourly averaged data.

26 28 April 1978 SEP event is one of identified magnetically connected events (Gardini et al. (2011) for a list) Helios 1 and 2, and IMP 8 magnetically connected within 20°; separated of 0.7 A.U. in radial distance.

27 Proton fluxes recorded in the energy range 4−40 MeV by Helios 1, Helios 2, IMP 8 spacecraft during 1974−1982 are used to analyze all SEP events for which at least two spacecraft have their nominal magnetic footpoint within 20◦ in heliocentric longitude from each other. Radial dependence ~ R  α = 2.13 r = 0.99 The upper limit of Peak Fluxes at 0.3 A.U. is ≈ 10 6 pfu (for >10 MeV proton energy)

28 Summary Helios 1 and 2 data for 1975-1980 have been used to evaluate the space environment between 0.3 and 0.47 A.U. in the most similar condition s for BepiColombo mission. Statistical features for different classes of perturbations have been compared between Mercury’s and Earth’s orbits Relative occurrence s of corotating and transient perturbations have been studied in relation to long term solar variability and its predictability. Response of Mercury’s Magnetosphere for different SW inputs are displayed to identify field lines connected to external environment Suprathermal particles fluxes data for two solar activity cycles have been used to evaluate occurrence, peaks and fluences at Earth’s orbit. The same parameters (upper limit) can be inferred at Mercury’s orbit by using the radial gradient computed with Helios and IMP8 data.


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