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AGILE Observation of Terrestrial gamma-Ray Flashes

AGILE Observation of Terrestrial gamma-Ray Flashes. Martino Marisaldi (INAF-IASF Bologna) ‏ on behalf of the AGILE Team TGF Workshop 2011 University of Alabama in Huntsville (USA), July 13-14 2011. 1. Outline. Characteristics of the AGILE TGF sample

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AGILE Observation of Terrestrial gamma-Ray Flashes

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  1. AGILE Observation of Terrestrial gamma-Ray Flashes Martino Marisaldi (INAF-IASF Bologna)‏ on behalf of the AGILE Team TGF Workshop 2011 University of Alabama in Huntsville (USA), July 13-14 2011 1

  2. Outline • Characteristics of the AGILE TGF sample • TGFs and global lightning activity (new!) • Localization of TGFs in gamma-rays from space • High energy spectrum Credit: Alan Stonebraker M. Marisaldi 2

  3. Operating TGF detectors Effective Area vs. Energy LAT ? Fermi-GBM 12xNaI AGILE GRID AGILE-MCAL GBM 2xBGO RHESSI GBM BGO Fermi-GBM NaI Data from: Smith et al. (2002), Meegan et al. (2009), Labanti et al. (2009), Tavani et al. (2009)

  4. The AGILE payload 40 cm • 30 CsI(Tl) bars with Photodiode readout • 1400 cm2 geometrical area • ~300 cm2 effective area @ 1 MeV • 330 keV – 100 MeV energy range • 14% energy resolution FWHM @ 1.3 MeV • 2 s timing accuracy in photon-by-photon mode • Clever, fully-programmable trigger logic on time scales from 8s to 16ms, 1ms and 300s Labanti et al., NIM A (2009): instrument paper Fuschino et al., NIM A (2008): trigger logic Marisaldi et al., A&A (2008): GRB detections Marisaldi et al., JGR (2010): TGF detections

  5. MCAL TGF detection rate > 250 class A TGFs + ~130 class B TGFs since June2008 ~10 TGF/month since Mar.'09 ~10 class A TGF/month ~ 5 class B TGF/month 24 months 1st AGILE TGF catalog in preparation 1ms trigger onset 34 TGFs Published in M. Marisaldi et al., J. Geoph. Res., 115, A00E13, 2010. After entering Spinning mode M. Marisaldi 5

  6. The AGILE TGF sample Average properties A AND B class: Number of counts = 14 +/- 9 Duration = (0.8 +/- 0.4) ms Energy = (4.0 +/- 1.7) MeV M. Marisaldi 6

  7. Basic properties Class A (old) Class B

  8. Longitude and local time AGILE class A AGILE class B RHESSI

  9. TGF-lightning correlation LIS/OTD global lightning distribution (10 Years of data) 0.5 x 0.5 deg per bin Flash rate [fl/km-2/year] MCAL exposure [Seconds per bin] (Mar 2009-Feb 2010) Trigger logic really active 2.5 x 1.0 deg [lon x lat] Lightning distribution multiplied by the MCAL exposure to direct comparison with 12 Months of AGILE TGFs 0.68 correlation coefficient for global case BUT… 2D Kolmogorov Smirnov probability = 0.002 for TGFs to be drawn from the same distribution of lightning! LIS-OTD high resolution full climatology available at http://thunder.msfc.nasa.gov/

  10. TGF / lightning statistical comparison

  11. AGILE / lightning statistical comparison • Assuming the spread of TGF / flash ratio holds at all latitude, and considering 44 ± 5 flash/s (Christian et al. 2003), we obtain 220 ÷ 570 TGFs / day, in agreement with Carlson et al. 2009. • Fuschino F., et al., GRL in press (2011) • The excess of TGFs over Central America and South East Asia with respect to Africa is confirmed (Smith et al., 2010) • The high degree of correlation obtained for South East Asia suggests that global lightning activity over this region is by far a better proxy for TGFs than on other continental regions. Climatic effect? (Splitt et al., 2010) • Thanks to the low inclination orbit AGILE provides the highest TGF detection rate surface density, good for seasonal/annual variability studies

  12. GRID pointing FOV 120° MCAL non-imaging FOV 4 Imaging TGFs from space? • MCAL detected TGF photons up to 40 MeV and possibly above • So, why not looking for detections in the AGILE gamma-ray imager (GRID) sensitive above 20 MeV? • It would be the first direct localization of TGFs in gamma-rays M. Marisaldi 12

  13. GRID pointing EARTH FOV 120° TGF ON-BOARD ALBEDO FILTERING  MCAL non-imaging FOV 4 Imaging TGFs from spacewith AGILE GRID Two ways to bypass it... M. Marisaldi 13

  14. GRID pointing EARTH FOV 120° TGF  MCAL non-imaging FOV 4 Imaging TGFs from spacewith AGILE GRID 1. Albedo filtering disabled ~ 100 days between 2008 – 2009 for test purposes Forward events. Cannot be default because of telemetry limitations M. Marisaldi 14

  15. EARTH FOV 120° TGF GRID pointing ON-BOARD ALBEDO FILTERING  MCAL non-imaging FOV 4 Imaging TGFs from spacewith AGILE GRID 2. Sometimes the albedo filter can “mistake” a track with the complementary one So, events coming from the Earth can be accepted by the on-board filter and sent to telemetry: Reverse events M. Marisaldi 15

  16. 12 significance 4 6 3 13 GRID events within 2 ms from TGFs T0! Imaging TGFs in gamma rays Search for GRID events in temporal coincidence with 119 MCAL TGFs detected between Jun. 2008 – Dec. 2009 M. Marisaldi 16

  17. GRID pointing Reverse event direction (TGF source)‏ Geographical distribution AGILE footprint GRID  projection M. Marisaldi 17

  18. TGF 12809-19 in details (2010 Oct. 16 20:44:55 UT) GOES IR image ~5 minutes before TGF Credits: B. Carlson, Univ. Bergen g-ray source TRMM-LIS pass ~1 hour before TGF

  19. Cohen et al., GRL 2010 Geographical distribution Event clustering at < 400 km from AGILE footprint Consistency with pervious detections based on RHESSI TGFs and sferics (Cummer et al., GRL 2005, Cohen et al., GRL 2010)‏ Results published in Marisaldi et al., Phys. Rev. Letters 105, 128501 (2010) M. Marisaldi 19

  20. New GRID detections

  21. bad good AGILE AGILE Compton interaction TGF production region TGF production region Do GRID photons come directly from the production region? 540 km 15-20 km the incoming photon direction tracks the production region. the incoming photon direction DOES NOT tracks the production region. No way to be aware of it. Is it probable??? M. Marisaldi 21

  22. bad good AGILE AGILE Compton interaction Compton interaction 40 km TGF production region TGF production region Do GRID photons come directly from the production region? 540 km Compton and pair production cross section in air become equivalent at ~25MeV: Compton interaction for low-energy GRID events cannot be ignored 15-20 km <3% probability to scatter above 40 km: the GRID photon tracks the source within the angular resolution M. Marisaldi 22

  23. 50 MeV Implications for production models Roussel-Doupre et al. Sp. Sci. Rev. 2009 High energy photons track well the electric field orientation at the source A new tool to probe remotely the production site electric field M. Marisaldi 23

  24. significant detection of  >40 MeV uneplained by standard RREA model: challenge for emission models Cumulative spectrum 110 TGFs 1806 photons 142  E> 10 MeV 26  E> 20 MeV Broken powerlaw model b = -2.7 RREA cutoff powerlaw model Results published in Tavani et al., Phys. Rev. Letters 106, 018501 (2011) M. Marisaldi 24

  25. High energy events

  26. 26

  27. 27

  28. MCAL high energy calibration On ground ___ simulations ___ MCAL exp. data AGILE on-ground calibration performed at INFN Beam Test Facility, Frascati, with Bremmstrahlung g-rays by 460 MeV e- on Si target

  29. MCAL high energy calibration In flight GRB 090510 prompt Extended emission MCAL data MCAL data GRID UL GRIDdata Giuliani et al., ApJL 708 (2010) L84

  30. Dead Time estimate <NGBM> AMCAL / AGBM energy Ntot / NT50 bright <NMCAL> (exp) range events ratio bias ??? <~1 130 x 300/700 x 0.40 x 2 x Fbias = 45 <NMCAL> = 14 a factor ~3 less than predicted: probable contribution due to dead time A factor ~2.3 was already evidenced comparing MCAL and RHESSI spectra (Marisaldi et al., JGR, 2010) Contributions due to: detectors readout, anticoincidence shield, digital frontend registers. To be addressed by dedicated MC simulations

  31. Conclusions • AGILE is an important instrument for TGF science: • energy range extended up to 100 MeV • the only one with <1ms trigger logic • photon-by-photon with s timing • ~equatorial orbit • AGILE detects ~10 TGFs / month with current selection criteria. Rate can be 50% increased with improved offline selections • Dead time significantly affects measurements • 7% TGFs can be localized in space by means of the AGILE gamma-ray imager. • Energy spectrum seems harder than previously expected, challenging current theoretical models. • Correlation with global lightning activity shows significant regional variability M. Marisaldi 31

  32. THANK YOU! First AGILE TGF detections: Marisaldi et al., JGR 115, A00E13 (2010) TGF g-ray localization: Marisaldi et al., Phys Rev Lett 105, 128501 (2010) TGF high-energy spectrum: Tavani et al., Phys Rev Lett 106, 018501 (2011) AGILE TGFs & lightning activity: Fuschino et al., GRL in press (2011) Credit: Alan Stonebraker

  33. Extra slides M. Marisaldi 33

  34. Terrestrial Gamma-ray Flashes (TGF)‏ Gamma-ray flashes with incoming direction compatible with the Earth surface. Few millisecond typical duration; hard spectrum (up to tens MeV)‏ Discovered by BATSE (Fishman et al., Science, 1994) and observed by RHESSI up to 20 MeV (Smith et al., Science, 2005) Clearly associated to lightning discharges during thunderstorms by means of correlation with VLF sferic waves detection on ground (Inan et al., GRL, 1996; Cummer et al., GRL, 2005)‏ >2008: Observed by AGILE and Fermi-GBM 2009: AGILE reports energy up to 40MeV (Marisaldi et al., JGR 2010)‏ Geophysical phenomena observed from space by instruments designed for gamma-ray astrophysics Challenging detection: timing and energy range are key issues

  35. 1994: BATSE discovery of TGF ~ 70 TGF detected on 9 life-Years typically 100 counts/TGF Main limitations: - On-Board Trigger Logic performances (shorter timescale 64ms)‏ - Large statistics BUT only 4 energy bins for time-tagged events Fishman et al., Science, 1994

  36. 2005: RHESSI detection up to 20 MeV TGF Distribution with lighting frequency per km2 per Year Smith et al., Science, 2005 • Contiuous time-tagged event list • NO ON-BOARD TRIGGER LOGIC • 10– 20 TGF per month • Typically 20-30 counts/TGF • ~800 TGFs reported in the 1st RHESSI TGF catalog (Grefenstette et al., JGR, 2009)‏

  37. RREA Production model Relativistic Runaway Electron Avalanche (RREA) with relativistic feedback (Dwyer 2008)‏ Bremsstrahlung + Compton scattering RHESSI cumulative spectrum is compatible with a production altitude of 15-21 km (just above tropical thunderstorms)‏ Still hint for individual spectral variability: differences in production altitudes or viewing angle? BATSE events seem produced at higher altitude (two different populations?) but discrepancy is reduced if dead-time effects are properly accounted for (Grefenstette et al., 2008; Ostgaard et al., 2008)‏ Dwyer and Smith, GRL (2005)‏ Carlson, Lehtinen and Inan (2007)‏ M. Marisaldi 37

  38. Why AGILE is good for TGF science? • MCAL energy range is extended up to 100 MeV: probing the high energy tail of the TGF spectrum • Efficient trigger at ms and sub-ms time scale (the TGF time scale): not biased toward brightest events • segmented independent detectors: low dead time and pile-up • photon-by-photon data download for triggered events with 2s time resolution • <100s absolute timing accuracy: mandatory for sferics correlation • AGILE orbit at 2.5° inclination is optimal for mapping the equatorial region, where most of the events take place, with unprecedented exposure M. Marisaldi 38

  39. Recent developments • Observations • space observations by Fermi and AGILE • airplane observations (the ADELE experiment)‏ • Climatology • RHESSI TGFs vs. lightning occurrence and tropopause height (Smith et al., JGR, 2010)‏ • Modeling • relativistic feedback, flux and dose estimates (Dwyer 2008, 2010)‏ • VLF signature of relativistic runaway electrons (Fullekrug et al., 2010)‏ • New missions • ASIM, Taranis, Firefly M. Marisaldi 39

  40. MCAL Burst Trigger Logic • Long (SW evaluated)time windows: 64ms, 256ms, 1.024s, 8.192s 4 spatial zones and 3 energy ranges • Short (HW evaluated)time windows: sub-millisecond, 1ms, 16ms First trigger logic at ~1ms time scale • Very flexible:more than 2000 parameters for full configuration; dedicated look-up tables to accept/reject triggers • Current threshold settings: • 16ms: >22 counts • 1ms: >10 counts • 293s: > 8 counts M. Marisaldi 40

  41. Trigger selection Key parameter: Hardness Ratio HR = (n. evt E>1.4 MeV) / (n. evt. E<1.4 MeV)‏ Selection criteria to reject known instrumental triggers: HR > 0.5 All other triggers Known instrumental triggers Known instrumental triggers M. Marisaldi 41

  42. RHESSI AGILE double peaked feature on South East Asia sharp cut on western Africa late afternoon occurrence peak AGILE vs RHESSI:longitude and local time 1st RHESSI TGF catalog Grefenstette et al., JGR, (2009)‏ selected RHESSI TGFs in a +/- 2.5° latitude belt (like AGILE orbit) T0 < 1st Jan. 2006: 84 TGFs Longitude and local time distributions are compatible M. Marisaldi 42

  43. Trigger 11026-1 in details Light curve Position distribution Energy vs time All range <0.7 MeV 0.7-1.4 MeV 1.4-2.8 MeV >2.8 MeV 40 MeV Bar address vs time M. Marisaldi 43

  44. Single TGF energy spectrum 011026-1 cutoff powerlaw fit the 0.5-30 MeV range  = -0.6 +/- 1.0 E0 = (5.4 +/- 3.0) MeV red. 2 = 1.1 (5 d.o.f.)‏ Spectral parameters are poorly constrained due to limited statistics 011026-1 spectrum is compatible with cumulative spectrum Need more bright events M. Marisaldi 44

  45. AGILE-MCAL vs RHESSI Aeff,R =~50 cm2 @1MeV Photopeak Aeff,M ~110 cm2 @1MeV Total Aeff,M ~300 cm2 @1MeV MCAL RHESSI Smith et al., (2002) M. Marisaldi Labanti et al., (2009)‏ 45

  46. AGILE vs RHESSI:cumulative spectrum RHESSI AGILE cutoff powerlaw fit the 0.5-20 MeV range  = -0.1 +/- 0.3 E0 = 4.4 +/- 1.2 MeV red. 2 = 0.8 (18 d.o.f.)‏ cutoff powerlaw fit the 0.5-30 MeV range  = 0.4 +/- 0.2 E0 = 6.6 +/- 1.2 MeV red. 2 = 1.5 (34 d.o.f.)‏ Spectral shapes are compatible AGILE model fits well RHESSI data too BUT AGILE seems to select a harder population M. Marisaldi 46

  47. AGILE vs RHESSI:cumulative spectrum E cutoff vs. alpha confidence intervals AGILE RHESSI    Spectral shapes are compatible BUT AGILE seems to select a harder population M. Marisaldi 47

  48. 12 × NaI + 2 × BGO AGILE vs Fermi-GBM AGILE TGF 11026-1 Fermi TGF #7 Fermi: + larger effective area and lower threshold: more statistics on single events - trigger on time >=16ms: less events, brightness bias (AGILE triggers on >=290s)‏ from A. Von Kienlin, presentation at the 7th AGILE WS M. Marisaldi 48

  49. Lightning annual variabilityabove the equator LIS-OTD high resolution full climatology available at http://thunder.msfc.nasa.gov/

  50. TGF and lightning variability Next step: study annual variability

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