Results of the IMO Video Meteor Network - July 2008
===================================================
From the viewpoint of the weather, July was comparable with the month before:
It was not perfect, but there is no reason to complain if nine cameras
managed to collect twenty or more observing nights. Especially in the last
few days of July the skies were clear at almost every site, so that at times
more than twenty cameras were operated in parallel. Needless to say that we
could collect more observing times and meteors than in any other July before.
The increasing meteor activity - mainly thanks to the alpha-Capricornids
and southern delta-Aquariids - was highly welcome. At mid-July first Perseids
became visible. They are a minor shower at the beginning, but towards the
end of July they became dominating. Only the southern delta-Aquariids could
catch up with the Perseid counts in the days of their maximum around July 28.
A nice example for an SDA radiant plot was provided by TOMIL, the camera of
Tomas and Milos Weber (figure 1, left). It was able to record 63 meteors
(including 11 SDA) within just two hours on July 27/28 thanks to the powerful
image intensifier. Rosta Stork of Ondrejov enjoyed even better observing
conditions in the next night, when he recorded 273 meteors (among them 33 SDA)
in less than six hours (figure 1, right).
Figure 1: The radiant plots of TOMIL (left ) from July 27/28 and OND1 (right)
from July 28/29 show nicely the radiant of the southern delta-Aquariids.
The "most beautiful" meteor of the month, however, was captured by Stefano
Crivello, who recorded a double Capricornid on July 27 at 01:55 UT (figure 2).
Figure 2: Double Capricornid, recorded by Stefano Crivello with STG38 on July
27, 01:55 UT.
Beside archiving the July data also the next full analysis of the video
meteor database was prepared in the last few days. In particular the scatter
respectively observing errors of video meteors with respect to position
and angular velocity was of interest. As explained before, the meteor shower
analysis relies on the accumulation of probabilities, that meteors origin
from a particular radiant with given position and velocity. That probability
is derived from two quantities - the distance at which the backward
prolongation of the meteor misses the (point-like) radiant, and the
difference between the observed and the expected angular velocity. The
latter one is calculated from the distance of the meteor from the radiant,
and the meteor shower velocity.
Those who have used the Radiant software of Rainer Arlt know the phenomenon:
With the parameter "Standard Deviation" you can adjust whether the
probability distribution of a meteor in probability mode becomes a small
droplet (small scatter, the radiation area can be well defined) or a large
area (large scatter, the radiant can be determined only approximately).
You need to adjust the settings by trial and error: When the standard
deviation is set too small, random sub-radiants will show up, whereas a
meteor shower radiant becomes blurred, when the standard deviation is set
too large.
In the 2006 analysis I had chosen both for the scatter in angular velocity
and radiant distance a normal (Gaussian) distribution. The standard
deviation was set empirically to a "sensible" value. This time, the
standard deviation was to be computed from data. For this reason, short
intervals in solar longitude at the maximum times of the Perseids,
Orionids, and Geminids were chosen, in which the radiant was compact and
showed only little drift. Then all shower members in these solar longitude
intervals were determined (more than 33,000 meteors overall) and the
distributions were computed, how the angular meteor velocity differed from
the expected value and how far the backward prolongation missed the radiant.
In addition, the dependency of these distributions from the angular
velocity of the meteor and its distance from the radiant was analysed.
Here is a summary of the results:
* On average, the scatter is lower than expected. The observed angular
velocity of half of all meteors deviates less than half a degree per second
from the expected value (whereby the underlying PosDat database contains
only integer values for the velocity, anyway), and the backward prolongation
missed the radiant by less than three quarter of a degree. At one sigma
(68.3%) the deviation is 0.8 deg/s and 1.3 deg.
* Ihe distributions are not Gaussian as expected, but can be well described
by a Laplace distribution (i.e. a function of the type e^-x instead of e^-x*x).
The main difference is, that for large values the Laplace function converges
much slower to zero than the Gauss function.
* There is a clear dependency between the scatter in angular velocity and the
meteor velocity (the faster the meteors, the large the scatter - the scatter
for meteors that move faster than 30 deg/s is about twice as large as for
meteors slower than 10 deg/s). On the other hand, the scatter of the radiant
miss distance of the backward prolongations is essentially independent from
the distance of the meteor from the radiant.
The IMO handbook for meteor observers, by the way, suggests that in the
analysis of visual observation larger errors should be accepted both for
the angular velocity and the radiant miss distance for meteors that are
fast or far away from the radiant.
Figure 3 and 4 show the cumulative distributions for those 33,000 Perseids,
Orionids and Geminids.
Figure 3: Cumulative distribution of velocity errors for different angular
velocities of meteors. Small crosses mark the corresponding Laplace fits.
Figure 4: Cumulative distribution of radiant miss distances for different
distances of the meteor from the radiant. Small crosses mark an lower and
upper Laplace fit.
Ironially, when I carried out the meteor database analysis for the first
time before the AKM spring meeting 2006, I accidentally used a Laplace
distribution. Later I noticed this "error" and used a normal distribution
for the analysis later presented at the 2006 IMC - as one usually does if
the true probability distribution is unknown. Now it turns out that the
Laplace distribution would have been better. The influence of the
distribution is not as dramatic, however, that we may expect completely
different results now. At least the next analysis will not be done with
empirically set parameters, but with a probability distribution derived
from data, so from the point of view of probability theory everything is fine.
Strictly speaking, the distributions models only the scatter for compact
radiants. If the radiation area is of bigger size, the distribution should
be wider as well - but that's a different topic.
1. Observers
============
Code Name Place Camera FOV LM Nights Time Meteors
--------------------------------------------------------------------------------
BENOR Benitez-S. Las Palmas TIMES4 (1.4/50) 20 dg 3 mag 5 33.5 h 93
TIMES5 (0.95/50) 10 dg 3 mag 5 18.4 h 34
BRIBE Brinkmann Herne HERMINE (0.8/6) 55 dg 3 mag 23 75.6 h 252
CASFL Castellani Monte Baldo BMH1 (0.8/6) 55 dg 3 mag 21 88.9 h 278
BMH2 (0.8/6) 55 dg 3 mag 27 95.4 h 261
CRIST Crivello Valbrevenna STG38 (0.8/3.8) 80 dg 3 mag 4 14.9 h 64
ELTMA Eltri Venezia MET38 (0.8/3.8) 80 dg 3 mag 3 19.7 h 123
GONRU Goncalves Tomar TEMPLAR1(0.8/3.8) 80 dg 3 mag 27 161.1 h 451
HERCA Hergenroth. Tucson SALSA (1.2/4) 80 dg 3 mag 15 73.0 h 229
HINWO Hinz Brannenburg AKM2 (0.85/25) 32 dg 6 mag 11 41.1 h 206
KACJA Kac Kostanjevec METKA (0.8/8) 42 dg 4 mag 11 64.2 h 187
Kamnik REZIKA (0.8/6) 55 dg 3 mag 8 38.5 h 165
Ljubljana ORION1 (0.8/8) 42 dg 4 mag 23 103.9 h 297
LUNRO Lunsford Chula Vista BOCAM (1.4/50) 60 dg 6 mag 22 89.5 h 1031
MOLSI Molau Seysdorf AVIS2 (1.4/50) 60 dg 6 mag 13 55.9 h 955
MINCAM1 (0.8/6) 55 dg 3 mag 19 84.9 h 273
Ketzuer REMO1 (0.8/3.8) 80 dg 3 mag 24 91.5 h 412
REMO2 (0.8/3.8) 80 dg 3 mag 24 88.5 h 439
PRZDA Przewozny Berlin ARMEFA (0.8/6) 55 dg 3 mag 14 69.5 h 428
SLAST Slavec Ljubljana KAYAK1 (1.8/28) 50 dg 4 mag 20 78.4 h 154
STOEN Stomeo Scorze MIN38 (0.8/3.8) 80 dg 3 mag 13 73.9 h 291
STORO Stork Kunzak KUN1 (1.4/50) 55 dg 6 mag 2 11.5 h 253
Ondrejov OND1 (1.4/50) 55 dg 6 mag 4 21.3 h 693
STRJO Strunk Herford MINCAM2 (0.8/6) 55 dg 3 mag 14 32.8 h 86
MINCAM3 (0.8/8) 42 dg 4 mag 5 19.2 h 66
MINCAM5 (0.8/6) 55 dg 3 mag 11 34.9 h 113
WEBMI Weber Chouzava TOMIL (1.4/50) 50 dg 6 mag 6 10.9 h 237
YRJIL Yrjola Kuusankoski FINEXCAM (0.8/6) 55 dg 3 mag 1 1.8 h 7
--------------------------------------------------------------------------------
Sum 31 1592.7 h 8078
2. Observing Times (h)
======================
July 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15
--------------------------------------------------------------------------------
BENOR - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - -
BRIBE 5.9 - 0.3 6.0 - 2.8 0.3 0.8 - - - 1.0 5.0 6.3 0.8
CASFL 6.0 2.5 4.0 6.0 - - 4.1 - 5.2 4.7 0.7 3.2 2.8 3.8 6.4
6.0 1.1 3.5 1.2 - 0.8 1.6 1.6 5.2 0.5 0.5 2.0 2.8 4.5 6.4
CRIST - - - - 2.7 - - - - - - - - - 6.3
ELTMA - - - - - - - - - - - - - - -
GONRU 0.8 7.3 7.2 - 7.3 7.4 7.4 7.4 3.4 1.0 1.9 6.3 7.4 7.2 7.5
HERCA - - - - - - - 2.0 - - - - - - 3.2
HINWO 4.4 4.8 - 4.9 2.3 - - 2.0 - 2.1 - - - - 5.4
KACJA 6.1 - 1.7 - 4.0 - - - - 6.6 4.2 6.2 - - -
5.6 6.2 0.5 - 5.9 - - 6.3 - 4.7 - 3.8 - - -
6.3 3.3 3.2 - 6.3 - - 2.9 5.5 6.5 6.6 3.6 - 3.7 5.7
LUNRO 2.6 3.0 - 7.5 - - - - - 3.0 1.0 6.0 7.7 2.7 5.8
MOLSI 4.5 - - 3.7 3.1 - 4.9 - - 4.9 - - - - 4.5
5.7 1.8 - 5.7 3.7 - 5.8 5.9 - 4.9 - - - 1.2 6.1
4.4 4.5 - - 4.5 - 4.7 0.7 3.2 - 0.3 3.9 5.0 1.0 -
4.4 4.5 - - 4.6 0.6 3.1 0.7 4.7 - 0.7 2.3 4.9 2.5 -
PRZDA - - - - - - - - 4.8 - - 3.4 5.0 - -
SLAST 4.8 2.0 0.3 - 4.6 - 2.0 3.7 4.0 5.8 5.2 - - - 5.0
STOEN 5.5 - - 5.7 - - 5.1 6.1 5.8 5.6 - - - - 6.2
STORO - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - -
STRJO 3.4 3.0 - 0.5 - 2.5 0.5 - - - 0.6 1.4 4.3 3.4 -
3.7 - - - - - - - - - - - - - -
2.1 - - 1.0 - - - - - - - 0.5 - - -
WEBMI - 1.9 - - 2.0 - 1.9 - - - - - - - -
YRJIL - - - - - - - - - - - - - - -
--------------------------------------------------------------------------------
Sum 82.2 45.9 20.7 42.2 51.0 14.1 41.4 40.1 41.8 50.3 21.7 43.6 44.9 36.3 69.3
July 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
-------------------------------------------------------------------------------------
BENOR - - - - - - - - - - 6.5 7.0 3.8 8.1 8.1 -
- - - - - - - - - - 1.5 3.8 6.6 2.5 4.0 -
BRIBE 2.0 - - 4.4 2.8 1.6 3.9 6.6 5.7 - 0.8 4.7 6.8 0.8 2.0 4.3
CASFL 2.2 - - 4.4 - - 5.7 6.7 6.7 3.3 - - - 3.8 2.5 4.2
4.6 - 1.0 6.5 - - 6.7 6.7 3.2 6.8 1.0 6.9 5.9 3.2 2.0 3.2
CRIST - - - 1.1 - - - - - - 4.8 - - - - -
ELTMA - - - - - - - - - - - 6.9 5.6 - - 7.2
GONRU 7.4 7.5 1.2 - 6.0 5.2 5.2 7.1 4.1 - 7.7 - 7.6 7.9 6.7 8.0
HERCA 6.3 4.0 3.1 - - 5.1 5.1 0.5 4.5 4.3 - 2.5 7.6 7.9 8.4 8.5
HINWO - - - - - - - - - 1.5 - 6.0 - 1.4 - 6.3
KACJA - - - 6.8 - - - - - - - 6.9 7.3 - 7.0 7.4
5.5 - - - - - - - - - - - - - - -
6.7 - 0.9 6.8 - - 3.5 2.1 3.1 4.1 - 7.2 7.2 4.3 1.6 2.8
LUNRO 1.7 5.9 - - 1.0 8.0 2.0 2.6 2.3 7.9 4.0 - 3.6 3.3 4.0 3.9
MOLSI - - - - - - - 5.0 - 4.8 - 5.8 5.7 3.5 0.3 5.2
- - 0.7 - 0.8 - - 6.5 0.5 6.6 - 6.7 6.8 6.7 3.1 5.7
3.6 - 0.7 2.7 1.8 - 3.9 5.5 1.1 5.6 5.7 5.8 5.9 4.9 6.0 6.1
3.6 - 1.6 0.3 1.8 - 4.5 5.5 - 4.7 5.7 5.8 5.9 4.0 6.0 6.1
PRZDA - - - 3.1 - - 5.5 5.6 0.7 5.7 5.8 5.8 5.9 6.0 6.1 6.1
SLAST 5.3 - 1.0 3.4 - - - 2.8 3.1 4.9 - 4.8 5.6 5.1 5.0 -
STOEN - - - - - - - 5.4 6.6 - - 6.7 6.8 - 1.5 6.9
STORO - - - - - - - - - - - - 6.8 4.7 - -
- - - - - - - - - - - - 5.9 3.6 6.2 5.6
STRJO 4.5 - - 1.4 0.5 - 1.7 - - - - - - - 5.1 -
- - - - - - - - 0.5 - - - 4.1 - 5.3 5.6
- - - - - - - 5.0 3.0 3.5 - 3.4 5.0 0.5 5.3 5.6
WEBMI - - - - - - - - - - - 2.0 1.1 - 2.0 -
YRJIL - - - - - - - - - - - - - - - 1.8
-------------------------------------------------------------------------------------
Sum 53.4 17.4 10.2 40.9 14.7 19.9 47.7 73.6 45.1 63.7 43.5 98.7127.5 82.2 98.2110.5
3. Results (Meteors)
====================
July 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15
--------------------------------------------------------------------------------
BENOR - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - -
BRIBE 13 - 1 13 - 6 1 3 - - - 3 18 15 2
CASFL 15 4 9 15 - - 13 - 10 8 3 7 4 12 28
11 4 6 5 - 3 7 5 11 1 1 6 4 8 20
CRIST - - - - 13 - - - - - - - - - 21
ELTMA - - - - - - - - - - - - - - -
GONRU 1 15 20 - 14 18 12 21 11 3 8 16 18 18 16
HERCA - - - - - - - 5 - - - - - - 9
HINWO 15 11 - 30 8 - - 8 - 10 - - - - 25
KACJA 19 - 1 - 7 - - - - 17 14 17 - - -
24 17 1 - 19 - - 24 - 33 - 7 - - -
17 7 4 - 19 - - 6 25 16 17 7 - 8 17
LUNRO 7 6 - 30 - - - - - 5 2 20 15 5 10
MOLSI 72 - - 53 40 - 78 - - 79 - - - - 70
19 4 - 16 7 - 14 12 - 15 - - - 4 24
12 15 - - 10 - 12 3 15 - 1 8 24 2 -
17 15 - - 14 1 14 2 18 - 2 15 17 5 -
PRZDA - - - - - - - - 22 - - 9 17 - -
SLAST 11 2 1 - 9 - 2 7 8 11 11 - - - 14
STOEN 15 - - 11 - - 22 17 16 15 - - - - 21
STORO - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - -
STRJO 5 5 - 1 - 7 1 - - - 1 3 8 10 -
11 - - - - - - - - - - - - - -
4 - - 3 - - - - - - - 1 - - -
WEBMI - 34 - - 27 - 53 - - - - - - - -
YRJIL - - - - - - - - - - - - - - -
--------------------------------------------------------------------------------
Sum 288 139 43 177 187 35 229 113 136 213 60 119 125 87 277
July 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
-------------------------------------------------------------------------------------
BENOR - - - - - - - - - - 20 20 16 24 13 -
- - - - - - - - - - 3 7 16 3 5 -
BRIBE 6 - - 15 8 5 18 27 24 - 2 23 24 3 8 14
CASFL 5 - - 8 - - 17 30 17 17 - - - 20 9 27
12 - 2 13 - - 20 17 12 19 2 25 23 8 5 11
CRIST - - - 3 - - - - - - 27 - - - - -
ELTMA - - - - - - - - - - - 36 43 - - 44
GONRU 12 18 1 - 11 10 9 23 13 - 34 - 42 35 25 27
HERCA 9 9 8 - - 13 18 1 13 17 - 13 22 36 33 23
HINWO - - - - - - - - - 11 - 38 - 10 - 40
KACJA - - - 17 - - - - - - - 26 22 - 23 24
40 - - - - - - - - - - - - - - -
20 - 2 19 - - 8 3 7 22 - 20 20 18 10 5
LUNRO 5 12 - - 3 36 5 5 5 27 120 - 169 176 177 191
MOLSI - - - - - - - 81 - 64 - 126 107 68 3 114
- - 2 - 2 - - 15 3 19 - 37 21 16 6 37
8 - 1 8 5 - 12 15 2 18 38 40 40 17 60 46
6 - 4 4 14 - 14 28 - 20 34 39 47 11 55 43
PRZDA - - - 11 - - 38 35 6 28 47 46 58 30 38 43
SLAST 12 - 1 7 - - - 3 4 6 - 12 10 14 9 -
STOEN - - - - - - - 14 29 - - 39 43 - 4 45
STORO - - - - - - - - - - - - 171 82 - -
- - - - - - - - - - - - 273 56 215 149
STRJO 8 - - 7 1 - 3 - - - - - - - 26 -
- - - - - - - - 1 - - - 17 - 14 23
- - - - - - - 19 6 8 - 16 18 1 20 17
WEBMI - - - - - - - - - - - 63 12 - 48 -
YRJIL - - - - - - - - - - - - - - - 7
-------------------------------------------------------------------------------------
Sum 143 39 21 112 44 64 162 316 142 276 327 626 1214 628 806 930
Sirko Molau, 2008/08/29