A Simple Diagram to Classify Meteoroid Impacts

A simple diagram to classify meteoroid impacts

Maria Gritsevich and Eleanor Sansom

Acknowledgments to Manuel Moreno, Esko Lyytinen, Elizabeth Silber, Desert Fireball Network & Finnish Fireball Network [email protected] Outline q Introduction

q Method implemented for parameters’ identification

q Model validation

q General statistics and consequences Past terrestrial impacts

~300 km

The largest verified impact crater on Earth (Vredefort) Past terrestrial impacts

~300 km

~1,2 km

Different types of impact events, examples: formation of a massive single crater (Vredefort, Barringer) Past terrestrial impacts

~300 km

~1,2 km

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

~1,2 km

Dispersion of craters and meteorites over a large area (e.g. Sikhote-Alin) Past terrestrial impacts

~1,2 km

~1,8 km

Tunguska Tunguska after 100 years…

Area over 2000 km2 q Introduction

q Method implemented for parameters’ identification

q Model validation

q General statistics and consequences 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 velocity V (t) Interpretation of meteor observations

Photometric Dynamical

Usually simplified case used is: Low-variable dV approach = 0 dt

“Full” scenario utilized e.g. in Ø No assumptions needed Gritsevich & Koschny, 2011 and Bouquet et al. 2014 Ø Based on mathematical fit Suitable parameterization is the key

2 1 ρ 0 h0 Se chVe α = cd , β = (1- μ) * , μ = log m s 2 M e sin γ 2cd H a 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 Sе, to the body’s mass b 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 The key dimensionless parameters used

(air-in- front-of -the-body) 1 ρ0h0 Se 1 M α = cd = cd 2 M e sin γ 2 M e a 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 Sе, to the body’s pre-atmospheric mass b 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) The key dimensionless parameters used

2 2 chVe chVe M e β = (1- μ) * = (1- μ) * = 2cd H 2cd H M e E = (1- μ)c / c kin h d E (required-to- fully-destroy-the-object-in-the-atmosphere) b 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) Determination of α and β t, sec h, km V, km/sec On the right: 0,0 58,8 14,54 Data of observations of Innisfree 0,2 56,1 14,49 0,4 53,5 14,47 fireball (Halliday et al., 1981) 0,6 50,8 14,44 0,8 48,2 14,40 1,0 45,5 14,34 1,2 42,8 14,23 y(v) = ln 2a + b + 1,4 40,2 14,05 1,6 37,5 13,79 2 1,8 35,0 13,42 -ln(Ei(b)-Ei(bv )) 2,0 32,5 12,96 2,2 30,2 12,35 2,4 27,9 11,54 xez dz 2,6 25,9 10,43 Ei()x= 2,8 24,2 8,89 ò z -¥ 3,0 22,6 7,24 3,2 21,5 5,54 q The problem is solved by the least 3,3 21,0 4,70 squares method (Gritsevich, 2009) q Introduction

q Method for parameters’ identification

q Model validation

q General statistics and consequences 1. Pre-atmospheric size estimate

• When meteorites are recovered one can use the models by Leya and Masarik (2009) to translate cosmogenic radionuclide activities measured in the laboratory into meteoroid “sizes” (deﬁned as physical radius x density, with a unit of g∙cm-2)

• An impressive match is observed between the sizes obtained based on using described here and cosmogenic radionuclide analysis, see e.g. estimates given for Park Forest (Meier et al. 2017), Kosice (Povinec et al. 2015, Gritsevich et al. 2017), and a summary table with earlier results in (Gritsevich 2008). 2. Terminal height calculation

Calculated terminal heights (using described parameterization) vs. observed terminal heights for the MORP fireballs. See (Moreno-Ibáñez et al. 2015, 2017) for further details 3. Annama fireball //recently also the Ozerki J

• The fireball was very bright and was witnessed in Russia, Finland, and Norway © Asko Aikkila, Ursa Fireball Network • Finnish Fireball Network imaged the fireball from Kuusamo, Mikkeli and Muhos sites (FN20140419) © Ursa, Taivaanvahti observation database. • Dash-board video made in Snezhnogorsk Annama fireball, April 19, 2014

Illustration by Mikko Suominen / “Tähdet ja Avaruus” Height (km) vs Velocity (km/s)

Velocity (km/s)

Fb_entry program, Lyytinen & Gritsevich, 2013 & 2016 Fits well to the other meteorite falls

fireball Ve, km/s sing α β

Annama 24,23 0,55 8,33 1,61

Lost City 14,15 0,61 11,11 1,16

Innisfree 14,54 0,93 8,25 1,70

Neuschwanstein 20,95 0,76 3,92 2,57 NumericalImpact simulations site North à

Color code of simulated fragments: blue are <0.3 kg, green 0.3 - 1 kg, yellow 1 - 3 kg, orange 3 - 10 kg, red >10 kg 5May days 29, meteorite first meteorite! expedition

120.35 g

May, 29 first meteorite recovered J Annama meteorite

• Analysis done at the Czech Geological Survey & University of Helsinki X • H5 ordinary chondrite • S2 shock level • W0 weathering degree • Bulk density 3,5 g/cm3 • Grain density 3,8 g/cm3 • Porosity 5 %

Kohout et al. 2017 q Introduction

q Method implemented for parameters’ identification

q Model validation

q General statistics and consequences Distribution of parameters α and β for MORP fireballs

ln β

0 -1 0 1 2 3 4 5 6 7 ln α

-1

-2

-3

∆ Innisfree Looking for ‘Meteorite region’

M t ³ M min , vt << 1 ln β

0 -1 0 1 2 3 4 5 6 7 ln α

-1

ba+3ln =- ln mmin -2

-3 sing = 0.7 and 1; M = 8 kg min ∆ Innisfree Some historical events

Original mass, Collected meteorites, № Event a b t kg

Canyon Diablo meteorite 1 > 106 > 30×103 0.1 ~ 0.1 (Barringer Crater) 2 Tunguska 0.2×106 - 0.3 30

3 Sikhote Alin 200 > 28×103 1.2 0.15

4 Neuschwanstein 0.5 6.2 3.9 2.5

5 Benešov 0.2 ? 7.3 1.8

6 Innisfree 0.18 4.58 8.3 1.7

7 Lost City 0.17 17.2 11.1 1.2 Same events on the plane (lnα, lnβ)

lnβ (1) Crater Barringer ( 2)

(2) Tunguska 3

(3) Sikhote Alin (4) Neuschwanstein 2 (5) Benešov

(6) Innisfree 1 ( 4) (5 ) (7) Lost City (6) (7) 0 -3 -2 -1 0 1 2 lnα

-1

( 3 ) -2 (1)

-3

~1,2 km Same events on the plane (lnα, lnβ)

lnβ ( 2) (1) Crater Barringer 3 (2) Tunguska

(3) Sikhote Alin 2 α >1, β > 1 (4) Neuschwanstein 0 < α < 1, β > 1 (5) Benešov 1 ( 4) (5 ) (6) Innisfree (6) (7) Lost City (7) 0 -3 -2 -1 0 1 2 lnα

-1 0 < α < 1, 0 < β < 1 α > 1, 0 < β < 1 ( 3 ) -2 (1)

-3

~1,2 km Meteorite / crater production criteria

(1) Crater Barringer lnβ (2) Tunguska ( 2) (3) Sikhote Alin 3 (4) Neuschwanstein (5) Benešov 2 (6) Innisfree

(7) Lost City 1 ( 4) † (5 ) (6) (*) Annama * (7) (†) Chelyabinsk 0 -3 -2 -1 0 1 2 lnα

-1

( 3 ) -2 (1)

-3

~1,2 km Meteorite / crater production criteria

(1) Crater Barringer lnβ (2) Tunguska ( 2) (3) Sikhote Alin 3 (4) Neuschwanstein (5) Benešov 2 (6) Innisfree

(7) Lost City 1 ( 4) † (5 ) (6) (*) Annama * (7) (†) Chelyabinsk 0 -3 -2 -1 0 1 2 lnα

-1

( 3 ) -2 (1)

-3

~1,2 km Using the criteria for the large datasets Conclusions α,β => consequences of an impact: » Meteorites » Craters » Airburst => success cases include meteorite recoveries: » Annama » Ozerki => applicable to big data (Sansom, Gritsevich et al. ApJ 2019)

Several versions of the described algorithm were implemented and are available upon request (including C++, Python, Excel) Thank you very much!

Further reading and references in:

http://www.springer.com/us/book/9783319461786#aboutBook https://www.researchgate.net/profile/Maria_Gritsevich/publications Interpretation of meteor observations

Photometric Dynamical dE dV 1 I = -t × M=- cr VS2 , dt dt 2 da Usually simplified case used is: dh dV =-V sin,g = 0 dt dt dM 1 “Full” scenario utilized e.g. in H* =- cr VS3 Gritsevich & Koschny, 2011 dt 2 ha and Bouquet et al. 2014 ‘Scaling up’ the dynamical case

2 2 dv1 r00hSe r vs dm 1 r0h0Se Ve rv s mc=d ; = ch dyM2e singdy 2 M e H * sing

qm = M/Me; Me – pre-atmospheric mass q v = V/Ve; Ve – velocity at the entry into the atmosphere q y = h/h0; h0 – height of homogeneous atmosphere q s = S/Se; Se – middle section area at the entry into the atmosphere q ρ=ρа/ρ0; r0 – gas density at sea level Two additional equations q variations in the meteoroid shape can be described as (Levin, 1956) S M = ( ) m Se M e q assumption of the isothermal atmosphere* ρ=exp(-y)

*See (Lyytinen & Gritsevich, 2016) for other atmospheric models Analytical solution of dynamical eqs.

q Initial conditions y = ∞, v = 1, m = 1

æ 1- v2 ö m(v) = expç- b ÷ è 1- m ø y(v) = ln 2a + b - ln(Ei(b ) - Ei(b v2 ))

x e zdz where exponential integral is defined as: Ei(x) = ò -¥ z The problem

2 fireballs observed by the Finnish Fireball Network (FFN) on March 27 and 28

images from the FGI’s Metsähovi Research Station, The first piece of the Annama http://www.fgi.fi meteorite found in the frame of the FFN in spring 2014 About 100.000 meteors registered About 100.000 meteorites in yearly by various the today’s worldwide Fireball Networks collections

Just about 30 historical cases belonging to both categories… Orbital parameters

Name Annama 20140418 RMS Apollo-type orbit of the meteoroid 2014-04- Epoch 18T22:14:30 B, deg 67.932 L, deg 30.762 H, km 83.87 Az, deg 176.1 ±0.20 El, deg 34.3 ±0.40 V, km/s 24.23 ±0.50 2014-04- Epoch 14T22:14:30 a, AU 1.99 ±0.12 e 0.69 ±0.02 i, deg 14.65 ±0.46 Collision point Ω, deg 28.611 ±0.001 ω, deg 264.77 ±0.55 M, deg 342.10 ±1.81 ‘Meteor Toolkit’ (Dmitriev et al., 2015) Another reason why we are interested

…or:

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. Multi-station observation program

allow us to calculate: q meteor height q length along trajectory q meteor intensity q spectrum

first attempts: q Harvard Meteor Project q Ondrejov Observatory in Czechoslovakia

first success: q 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) ggg Meteorite falls with known orbit

More details at http://www.meteoriteorbits.info/ 3. 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 km2. 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.