Monitoring the meteoroid flux using worldwide volunteers

Talk given at the dot Astronomy 3 meeting,
4 April 2011, Oxford.

Transcript

1. Monitoring the meteoroid flux using worldwide volunteers Geert Barentsen (@GeertMcTwit) International Meteor Organization
2. Who am I?
3. PhD slave student: IPHAS Photometric Halpha Survey (Barentsen et al. 2011)
4. NGC Catalogue (Dreyer 1888) Armagh Observatory - Northern Ireland Cup Anemometer (Robinson 1846) Human Orrery
5. OASES - Art & Astronomy for peace http://star.arm.ac.uk/~mdp/oases/ Contact: Miruna Popescu (mdp@arm.ac.uk)
6. Crowdsourcing HR diagram Effort or training required to participate #Crowd Meteor counting Giants Dwarfs This talk 500 000 5 000 000 5 000 500
7. 1) Human eyeball observations still important! 2) Motivate citizen observers with quicklook analysis. 3) Smartphones/Twitter: promising but tricky. (Perseids - Fred Bruenjes) Key points
8. Who cares about meteoroids?!
9. US Navy Transit Satellite (before being shot with a 5 cm metal ball moving at 6 km/s) (Cooke 2010)
10. Aftermath
11. Hubble solar panels: hundreds of mm-sized impacts http://space-env.esa.int/madweb/
12. Tunguska timing+direction = consistent with Taurid meteor shower from comet Encke (e.g. Kresak 1978, Jopek 2008) Several km-sized objects now found in Taurid stream: 2003 WP21, 2002 XM35, 2004 GT10 (Jenniskens 2008) 'Breaking' News: comets like to fragment 73P/Schwassman-Wachmann 3 (Spitzer)
13. So what do we observe?
14. Churyumov-Gerasimenko dust trails (model: Jeremie Vaubaillon) Meteoroid streams: complex! (Inferred from David Hogg's model of everything)
15. Dust trail (~ 1 hour) Meteor Rate Meteoroid streams: complex! Flux profiles are the primary tool to constrain models.
16. Citizen-run video camera network International Meteor Organization - http://www.imo.net
17. 12 new meteor showers discovered (Molau 2009) Only in western countries
18. Fast-readout CCD Human eye Resolution 1 ~ 2 megapixel 120 megarod Sensitivity @ 50 fps 10-6 ~ 10-7 lux (1 - 4th magnitude) 10-8 lux (6th magnitude) Dynamic range 1 : 1 000 1 : 1 000 000 000 (delay) Challenge: meteors move at 10 - 100 pixels / second
19. Interval Limiting magnitude Count Tape recorder (+ brightness distribution) Visual observations
20. Perseid 2009 meteor shower - visual counts A B C 2009 August 13 5:23 UT Landsat 5 loses attitude control (Cooke 2010) Human observations: best-available temporal+spatial coverage
21. Realtime results - demonstrate the contribution of individuals Time Meteor activity #observers
22. http://www.imo.net
23. Can we use smartphones?
24. (Hartwig Lüthen 2001) (Sirko Molau 1989)
25. Faint (54) Pause Bright (26) Fireball (3) Recording 00:17:23 Meteors Prototype being developed under NASA contract (not shown)
26. LCD screens always produce white light Problematic for flux observations Solution: red plastic cover?!
27. Where did you first see the object? Where did you last see the object? Automated triangulation of crowd vectors to classify: meteors, thai balloons, satellites, kittens ... Q: „What did I see?!“ A: „Give us your vectors!“ Smartphones useful for single UFO-like events
28. Can we use Twitter data?
29. World's largest sensor network Optical detector Processor sensors dump output on Twitter ? Sound sensor Battery Tripod
30. USGS Twitter Earthquake Detections (Earle 2010) Cost of project: less than 1 seismometer Epicenter 'Earthquake' Tweets
31. Tweet: #meteorwatch [postcode] [country] [meteor count] (But: participants did not report interval or 'zero' meteors )
32. Date curl --user l:p --data "track=meteor,meteors,meteorite,..." http://stream.twitter.com/1/statuses/filter.json #Tweets Feb 2010 Mar 2011 Harvesting meteor tweets 1.1 million meteor tweets since Feb 2011
33. @VeloVeggies: just saw a gigantic fireball over the southeast. brighter then the moon and blue green color. @sarahrattenborg: holy balls. meteor. @RobinLeaf: we just saw a freaking meteorite!!!! omg! @maggiedammit: holy cr*p a meteor just burned up so bright it woke us P(Fireball | Tweets) #expletives ∝
34. 2010 April 14/15 Fireball News reports 10 am 10 pm
35. Tweets largely driven by TV & newspaper media Soap (Classifier: yes, but needs more training data.)
36. 1) Human eyeball observations still important! 2) Motivate citizen observers with quicklook analysis. 3) Smartphones/Twitter: promising but tricky. (Perseids - Fred Bruenjes) Key points
37. Thank you