1. Consequences of Impacts based on Atmospheric Trajectory Analysis maria.gritsevich@nls.fi Maria Gritsevich, Esko Lyytinen, Jouni Peltoniemi, Josep Trigo-Rodríguez, Manuel Moreno-Ibáñez, Detlef Koschny et al.

2. The problem Just about 20 historical cases belonging to both categories… The first piece of the Annama meteorite found in the frame of the FFN in spring 2014 About 100.000 meteorites in the today’s worldwide collections 2 recent fireballs observed by the Finnish Fireball Network (FFN) on March 27 and 28 images from the FGI’s Metsähovi Research Station, http://www.fgi.fi About 100.000 meteors registered yearly by various Fireball Networks

3. Outline  Introduction  Method implemented for parameters’ identification  Model validation  General statistics and consequences

4. Basic definitions  A meteoroid is a solid object moving in interplanetary space, of a size considerably smaller than an asteroid and larger than an atom  A meteor is a visible path of a meteoroid that enters Earth's atmosphere. Most meteors are visible in altitude range 70 to 100 km  A fireball (or bolide) is essentially bright meteor with larger intensity  A meteorite is a part of a meteoroid or asteroid that survives its passage through the atmosphere and impact with the ground

5. Past terrestrial impacts The largest verified impact crater on Earth (Vredefort) ~300 km

6. Past terrestrial impacts Different types of impact events, examples: formation of a massive single crater (Vredefort, Barringer) ~300 km ~1,2 km

7. Past terrestrial impacts Different types of impact events, examples: formation of a massive single crater (Vredefort, Barringer, Lonar Lake) ~300 km ~1,2 km ~1,8 km

8. Past terrestrial impacts Dispersion of craters and meteorites over a large area (Sikhote-Alin) ~1,2 km

9. Past terrestrial impacts Tunguska ~1,2 km ~1,8 km

10. Tunguska after 100 years… Area over 2000 km 2

11. Another reason why we are interested The three forms of extraterrestrial bodies. Meteorites (right) are remnants of the extraterrestrial bodies (asteroids, comets, and their dusty trails, left) entering Earth’s atmosphere and forming an event called a meteor or fireball (middle). Meteorite (fall) recovery is exciting since it is a cheap analogue to the sample return mission. …or:

12. What can we do in the lab? Nondestructive physical properties, including measurements of extraterrestrial materials:  Bulk and grain density  Porosity  Reflectance measurements  Magnetic susceptibility  Internal structure (x-ray microtomography)  Development of methods for nondestructive thermal and mechanical properties measurements  Some of the parameters can be determined at wide temperature range (5-1080 K) Our combined database contains thousands of individual meteorites. Results are published and/or shared within the scientific community.

13. Example of the obtained results 300 μm Porosity Metal rich rim Magnetic susceptibility was used as a tool to identify of non-ureilitic meteorites within Almahata Sitta (2008 TC 3 ) meteorite collection Porosity mapping using XMT

14. Study of Chelyabinsk meteorite LL5 impact-melt breccia Two types of rocks: –Light-colored lithology o Monomict breccia o Shocked to S3-4 level o Microscopic fracturing of grains –Dark-colored lithology (shock darkened) o More extensively shocked o Contains significant amount of impact-melt o Inter- and intra-granular fractures are being impregnated with a dense network of thin, fine grained impact melt veins, composed predominantly of troilite and metal. o Sulphide-metal melt is the darkening agent. Light Dark Kohout et al. 2014

15. Physical properties (Chelyabinsk) Light-coloredDark-colored Bulk density (g/cm 3 )3.32 (s.d. 0.09)3.27 (s.d.0.08) Grain density (g/cm 3 )3.51 (s.d. 0.07)3.42 (s.d. 0.10) Porosity (%)6.0 (s.d. 3.2)5.7 (s.d. 1.7) Magnetic susceptibility (log in 10 -9 Am 2 /kg) 4.49 (s.d. 0.07)4.52 (s.d. 0.15)  no significant difference observed between light- and dark-colored lithology  all values but magnetic susceptibility match other LL chondrites  magnetic susceptibility is in intermediate L/LL range  compared to a typical LL chondrite Chelyabinsk meteorites are richer in metallic iron

16. Spectral properties (Chelyabinsk) Shock darkening causes:  Reduction of the reflectance  Shallowing of the 1 µm olivine absorption band  No slope change (unlike space weathering)

17. Classical double-station program allow us to calculate:  meteor height  length along trajectory  meteor intensity  spectrum first attempts:  Harvard Meteor Project  Ondrejov Observatory in Czechoslovakia first success:  bright fireball photographed on April 7, 1959: four meteorites were found near Příbram in Czechoslovakia in the area predicted from the double- station photographic data (Ceplecha, 1961)

18. gggg

19. The largest piece (Luhy, 4.5 kg)

20. Meteorite falls with known orbit Trigo-Rodriguez et al. 2015

21.  Introduction  Method implemented for parameters’ identification  Model validation  General statistics and consequences

22. Groundbased observations The information on meteor body entry into the atmosphere contains detailed dynamic and photometric observational data. The important input parameters are: the fireball brightness I (t), its height h (t) and its velocity V (t)

23. Interpretation of meteor observations Dynamical Photometric Usually simplified case used is: “Full” scenario utilized e.g. in Gritsevich & Koschny, 2011 and Bouquet et al. 2014

24. ‘Scaling up’ the dynamical case  m = M/M e ; M e – pre-atmospheric mass  v = V/V e ; V e – velocity at the entry into the atmosphere  y = h/h 0 ; h 0 – height of homogeneous atmosphere  s = S/S e ; S e – middle section area at the entry into the atmosphere  ρ=ρ а /ρ 0 ;  0 – gas density at sea level

25. Two additional equations  variations in the meteoroid shape can be described as (Levin, 1956)  assumption of the isothermal atmosphere* ρ=exp(-y) *See (Lyytinen & Gritsevich, 2016) for other atmospheric models

26. Analytical solution of dynamical eqs. y = ∞, v = 1, m = 1  Initial conditions where exponential integral is defined as:

27. Suitable parameterization is the key  characterizes the aerobraking efficiency, since it is proportional to the ratio of the mass of the atmospheric column along the trajectory, which has the cross section S е, to the body’s mass  is proportional to the ratio of the fraction of the kinetic energy of the unit body’s mass to the effective destruction enthalpy μ characterizes the possible role of the meteoroid rotation in the course of the flight

28. The key dimensionless parameters used  characterizes the aerobraking efficiency, since it is proportional to the ratio of the mass of the atmospheric column along the trajectory, which has the cross section S е, to the body’s pre-atmospheric mass  is proportional to the ratio of the fraction of the kinetic energy of the unit body’s mass to the effective destruction enthalpy μ characterizes the possible role of the meteoroid rotation in the course of the flight (Gritsevich, Koschny, 2011; Bouquet et al. 2014)

29. The key dimensionless parameters used  is proportional to the ratio of the fraction of the kinetic energy of the unit body’s mass to the effective destruction enthalpy μ characterizes the possible role of the meteoroid rotation in the course of the flight (Gritsevich, Koschny, 2011; Bouquet et al. 2014)

30. Determination of α and β t, sech, kmV, km/sec 0,058,814,54 0,256,114,49 0,453,514,47 0,650,814,44 0,848,214,40 1,045,514,34 1,242,814,23 1,440,214,05 1,637,513,79 1,835,013,42 2,032,512,96 2,230,212,35 2,427,911,54 2,625,910,43 2,824,2 8,89 3,022,67,24 3,221,55,54 3,321,04,70 On the right: Data of observations of Innisfree fireball (Halliday et al., 1981) On the right: Data of observations of Innisfree fireball (Halliday et al., 1981)  The problem is solved by the least squares method (Gritsevich, 2009)

31.  Introduction  Method for parameters’ identification  Model validation  General statistics and consequences

32. Terminal height calculation Calculated terminal heights (using described parameterization) vs. observed terminal heights for the MORP fireballs. See (Moreno-Ibáñez et al., 2015) for further details Calculated terminal heights (using described parameterization) vs. observed terminal heights for the MORP fireballs. See (Moreno-Ibáñez et al., 2015) for further details

33. The Finnish Fireball Network The Finnish Fireball Network (FFN) was established in 2002 as a result of growing interest to continuous meteor and fireball monitoring using dedicated equipment initiated by Ilkka Yrjölä in 1998. In the current state the network consists of the 24 active stations with permanent instrumental setup and monitors a surface over Finland and neighbouring areas of about 400.000 km 2. Most of the active stations are run by amateur astronomers. A majority of interesting events are reduced the following days after the registration and the atmospheric trajectories corresponding to the visual path of fireballs are reproduced using the fb_entry program (Lyytinen and Gritsevich, 2013 & 2016). Selected cases are studied more thoroughly including mass computation, dark flight simulations, and pre-impact orbit estimate.

34. Murmansk / Kola fireball, FN20140419 © Ursa, Taivaanvahti observation database. © Asko Aikkila, Ursa Fireball Network The fireball was very bright and was witnessed in Russia, Finland, and Norway Finnish Fireball Network imaged the fireball from Kuusamo, Mikkeli and Muhos sites Dash-board video made in Snezhnogorsk

35. Kola fireball, April 19, 2014 © Ursa, Taivaanvahti observation database. © Asko Aikkila, Ursa Fireball Network

36. Kola fireball, April 19, 2014 © Ursa, Taivaanvahti observation database. © Asko Aikkila, Ursa Fireball Network

37. Kola fireball, April 19, 2014 © Ursa, Taivaanvahti observation database. © Asko Aikkila, Ursa Fireball Network

38. Trigo-Rodríguez et al. 2015

39. Impact site Projection of the fireball track

40. Visualization of the fireball Illustration by Mikko Suominen / “Tähdet ja Avaruus”

41. Height (km) vs Velocity (km/s) Fb_entry program, Lyytinen & Gritsevich, 2013 & 2016 Velocity (km/s)

42. Results of calculations Ve, km/s  αβMeMe MtMt 24,2333,7˚8,331,61476 kg13,8 kg

43. Fits well to the other meteorite falls fireballVe, km/s sin  αβ Annama 24,230,558,331,61 Lost City 14,150,6111,111,16 Innisfree 14,540,938,251,70 Neuschwanstein 20,950,763,922,57

44. Impact site Numerical simulations Color code of simulated fragments: blue are 10 kg North 

45. May 29, first meteorite! 5 days meteorite expedition May, 29 first meteorite recovered 120.35 g

46. Annama meteorite Analysis done at the Czech Geological Survey & University of Helsinki H5 ordinary chondrite S2 shock level W0 weathering degree Bulk density 3,5 g/cm 3 Grain density 3,8 g/cm 3 Porosity 5 % X

47. Orbital parameters Collision point Name Annama 20140418RMS Epoch 2014-04- 18T22:14:30 B, deg67.932 L, deg30.762 H, km83.87 Az, deg176.1±0.20 El, deg34.3±0.40 V, km/s24.23±0.50 Epoch 2014-04- 14T22:14:30 a, AU1.99±0.12 e0.69±0.02 i, deg14.65±0.46 Ω, deg28.611±0.001 ω, deg264.77±0.55 M, deg342.10±1.81 Apollo-type orbit of the meteoroid

48.  Introduction  Method implemented for parameters’ identification  Model validation  General statistics and consequences

49. Distribution of parameters α and β for MORP fireballs ∆ Innisfree

50. Looking for ‘Meteorite region’ sin  = 0.7 and 1; M min = 8 kg ∆ Innisfree

51. Some historical events

52. Same events on the plane (lnα, ln β ) ~1,2 km

53. Same events on the plane (lnα, ln β ) ~1,2 km 0 < α < 1, 0 < β < 1 α >1, β > 1 0 1 α > 1, 0 < β < 1

54. Meteorite / crater production criteria ~1,2 km *

55. Conclusions Consideration of dimensionless parameters α, β and μ allows to predict consequences of the impact. These parameters effectively characterize the ability of entering body to survive an atmospheric entry and reach the ground. The set of these parameters can be used to solve direct as well as inverse problems, when one has to evaluate properties of entering body based on observations. The results are applicable to study properties of the near-Earth space and can be used to predict and quantify fallen meteorites, and thus to speed up recovery of their fragments. In particular, the model enabled quick recovery of the Annama – the (only) 22nd meteorite with reconstructed atmospheric trajectory & known orbit. Several versions of the described algorithm were implemented and are available upon request (including C++, Python, Excel)

56. Thank you very much!

57. Why do we pass from y to exp(-y) ?

58. Newton's Second Law of Motion

59. Mass computation Initial Mass depends on ballistic coefficient