International Meteor Organization (IMO)

Bulletin 16 of the International Leonid Watch:
Results of the 2000 Leonid Meteor Shower

Rainer Arlt and Marc Gyssens

published in WGN, the Journal of IMO 28:6 (December 2000), pp. 191-204

Abstract: A set of 614.22 observing hours covering the activity of the Leonid meteor shower as logged by 230 observers was used to determine the population index and activity profiles of the 2000 Leonids. Three clear maxima in terms of Zenithal Hourly Rates (ZHR) are found. The first peak at lambda=235.28±0.01 (November 17, 8h07m UT) falls about 15 minutes after the predicted passage time of the 1932 dust trail of Comet 55P/Tempel-Tuttle. The activity level was ZHR=130±20. The second maximum is broad and is best described by a 1-hour plateau of activity with a maximum possibly centered at lambda=236.09±0.01 (November 18, 3h24m UT) with ZHR=290±20. This enhancement covers the predicted time of the dust trail of the 1733 perihelion passage of the Comet. The third maximum is found near lambda=236.25±0.01 (November 18, 7h12m UT) with ZHR=480±20 occurring about 40 minutes before the predicted 1866 dust trail passage. The population index r, however, reaches a maximum value of 2.2 at exactly the predicted time - 40 minutes after the ZHR maximum. The r-value was almost constant for four hours between 3h and 7h UT on November 18.

Introduction

Another return of the Leonid meteor shower with prolific visual meteor rates was monitored in 2000, despite the unfavorable conditions with a Last Quarter Moon interfering with the peak nights. Its close position to the Leonid radiant caused difficulties in finding a suitable observing field. Problems with shower association may arise from a field located too far from the radiant. A major shower like the Leonids these years, however, is not so much affected by the problems of shower association because of the relatively large meteor numbers compared with the sporadic background activity.

Two major peaks were predicted by the dust trail orbital integrations of McNaught and Asher [1]. Such a dust trail is produced by the parent comet, 55P/Tempel-Tuttle, at each perihelion passage. A first maximum was expected at 3h44m UT on November 18, caused by the 1733 dust trail after 8 orbital revolutions. A second peak was expected at 7h51m UT on the same day, caused by the 1866 trail after 4 orbital revolutions. The prediction of peak ZHRs was more uncertain than for 1999, since comparable encounters with these dust trails covered by observations were missing. A possible enhancement of Leonid activity was also predicted for the 2-revolution trail of 1932 for 7h51m UT on November 17, which is exactly one day before the 4-revolution trail. The predicted peak times correspond to lambda=235.270, lambda=236.104, and lambda=236.278, respectively; all solar longitudes refer to equinox J2000.0.

Estimates of ZHR predictions in [1] were 100 for the two peaks on November 18, annotated with a comment on the uncertainty of these numbers for the 2000 Leonid return. The dust trail computations by Lyytinen and van Flandern [2] resulted in more optimistic values of 700 for the two November 18 peaks and 215 for the November 17 peak of the 4-revolution trail. More predictions were given by other authors, but we restrict ourselves to the forecasts based on the apparently most accurate dust-trail integrations.

We are most grateful to all the observers who have put their efforts in recording visual data for the 2000 Leonid meteor shower and who quickly submitted their reports for the utilization in the Visual Meteor Database. The following is an alphabetical list of all contributors for the activity period of the Leonids:

George Akrivas (AKRGE, 0.83), José Alvarellos (ALVJO, 1.57), Raquel Alvarez Franco (ALVRA, 3.65), Esther Amor Pérez (AMOES, 1.12), Birger Andresen (ANDBI, 2.14), Rainer Arlt (ARLRA, 1.04), Joseph D. Assmus (ASSJO, 6.29), Jure Atanackov (ATAJU, 2.72), Rachel Aubuchon (AUBRA, 1.30), Julia Babina (BABJL, 4.74), Pierre Bader (BADPI, 1.87), Istvan Balogh (BALIS, 3.69), Nicolás Barrile (BARNI, 1.50), Orlando Benítez Sanchez (BENOR, 4.31), Felix Bettonvil (BETFE, 2.23), Fuyan Bian (BIAFU, 2.25), Lukas Bolz (BOLLU, 1.09), Neil Bone (BONNE, 1.50), Ji\v{r}i Borovi\v{c}ka (BORJI, 0.10), Biswajit Bose (BOSBI, 3.00), Michael Boschat (BOSMI, 4.00), Dustin Brown (BRODU, 1.88), Joachim Broser (BROJO, 1.77), Andreas Buchmann (BUCAN, 4.33), William Burton (BURWL, 1.25), Alberto Carrillo Abadalejo (CARAL, 1.69), Christian Castillo (CASCH, 5.18), Milan Cekic (CEKMI, 0.33), Y.K. Chia (CHIYK, 2.50), José Lazo Contreras (CONJO, 2.17), José Luis Cruz García (CRUJO, 0.75), Chen-zhou Cui (CUICH, 3.25), Marc de Lignie (DE MA, 1.45), Benoit Dejust (DEJBE, 1.83), Susan Delaney (DELSU, 0.50), Parag B. Deotare (DEOPA, 0.68), Prasad Deshpande (DESPR, 2.00), Peter Detterline (DETPE, 4.81), Alberto J. Díaz Caballero (DIAAL, 0.73), Asdai Díaz Rodriguez (DIAAS, 2.28), Ted Dolter (DOLTE, 0.58), Michael Doyle (DOYMI, 3.86), John Drummond (DRUJO, 1.00), Shlomi Eini (EINSH, 1.80), Frank Enzlein (ENZFR, 1.36), Yuwei Fan (FANYU, 1.50), David Barba Fernández (FERDB, 1.77), Federico Fernandez Pardavila (FERFE, 1.40), Martin Galea (GALMR, 1.42), Petros Georgopoulos (GEOPE, 0.33), Jaroslav Gerbos (GERJA, 0.70), David Girling (GIRDA, 2.00), George W. Gliba (GLIGE, 1.65), Cándido Gómez Benítez (GOMCA, 2.57), Pedro Luis Gonzáles (GONPE, 2.91), Rui Goncalves (GONRU, 1.51), Nishant N. Gor (GORNI, 0.83), Lew Gramer (GRALE, 5.01), Robin Gray (GRARO, 7.15), Valentin Grigore (GRIVA, 3.73), Qin Guoming (GUOQI, 3.33), Rafael Haag (HAARA, 1.83), Pavol Habuda (HABPA, 1.21), Wayne T. Hally (HALWA, 8.25), Torsten Hansen (HANTO, 3.11), Takema Hashimoto (HASTA, 4.33), Roberto Haver (HAVRO, 0.53), Carlos Heredero (HERCA, 4.43), David Hernandez (HERDA, 7.58), Veerle Herrygers (HERVE, 0.75), Zoltán Hevesi (HEVZO, 1.00), Kamil Hornoch (HORKM, 5.77), Stein Hoydalsvik (HOYST, 1.32), Tamás Hubay (HUBTA, 4.00), Greg Hudson (HUDGR, 5.25), Maria Isaeva (ISAMA, 7.23), Emmanuel Jehin (JEHEM, 1.25), Manuel Jiménez del Barco (JIMMN, 3.01), Silvia Jiménez Baeza (JIMSI, 1.00), Carl Johannink (JOHCA, 6.93), Kevin Jones (JONKE, 0.58), Bhargav Joshi (JOSBH, 10.15), Tomislav Jurkic (JURTO, 3.75), Javor Kac (KACJA, 2.33), Primoz Kajdic (KAJPR, 0.55), Vaclav Kalas (KALVA, 0.75), Stephen Kaplan (KAPST, 1.00), Jani Katava (KATJA, 1.84), Lance Kelly (KELLA, 2.00), Ákos Kereszturi (KERAK, 3.50), Mark Kidger (KIDMA, 2.16), Gary Kiser (KISGA, 1.22), Dimitris Kobiliris (KOBDI, 0.67), Albert Kong (KONAL, 2.00), Ales Kratochvil (KRAAL, 0.75), John Krempasky (KREJO, 1.34), Rhishikesh Kulkarni (KULRH, 2.00), Ralf Kuschnik (KUSRA, 1.06), Marco Langbroek (LANMA, 6.07), Zsolt Lantos (LANZS, 4.00), Trevor Law (LAWTR, 3.82), Adrian Lelyen (LELAD, 4.93), Anna S. Levina (LEVAN, 1.54), Qing Liang (LIAQI, 3.50), Michael Linnolt (LINMI, 2.50), Robert Lunsford (LUNRO, 5.42), Hartwig Lüthen (LUTHA, 0.48), Veikko Mäkelä (MAKVE, 1.67), Adam Marsh (MARAD, 2.75), Christophe Marlot (MARCH, 5.74), David Martinez Delgado (MARDA, 2.53), Felix Martinez (MARFE, 1.98), José Alfonso dos Reis Martins (MARJO, 0.98), Pierre Martin (MARPI, 5.94), Antonio Martinez (MARTI, 1.74), Edgardo Ruben Masa Martín (MASED, 2.77), Michael Mattiazzo (MATME, 1.00), Stanislav Maticic (MATST, 1.25), Alastair McBeath (MCBAL, 3.00), Tom McEwan (MCETO, 1.00), Norman McLeod (MCLNO, 6.05), Frank Melillo (MELFR, 3.62), Huan Meng (MENHU, 1.75), Alex Mikishev (MIKAL, 1.75), Herman Mikuz (MIKHE, 1.00), Koen Miskotte (MISKO, 7.00), Amruta Modani (MODAM, 1.25), Sirko Molau (MOLSI, 1.09), Ivelina Momcheva (MOMIV, 5.06), Erick Mota Perez (MOTER, 1.05), Peter Mrazik (MRAPE, 0.70), Charles Munton (MUNCH, 0.50), Francisco Munoz (MUNFR, 4.20), Kiyohide Nakamura (NAKKI, 1.00), Michael Nezel (NEZMI, 2.67), Francisco Ocaña Gonzalez (OCAFR, 0.54), Eran Ofek (OFEER, 0.43), Masayuki Oka (OKAMA, 5.33), Dragana Okolic (OKODR, 1.23), Fiona O'Neill (ONEFI, 2.00), Kazuhiro Osada (OSAKA, 1.25), Alexei Pace (PACAL, 1.07), Martha Papadopoulou (PAPMA, 0.47), Mukesh Pathak (PATMU, 6.00), Persephoni Pauli (PAUPE, 0.48), Jorge Perez Doval (PERJO, 1.50), Natasa Petelin (PETNA, 0.74), Furio Pieri (PIEFU, 1.79), Carles Pineda Ferré (PINCA, 0.50), Dulce Plasencia (PLADU, 2.74), Mayuresh G. Prabhune (PRAMY, 3.80), Szaniszló Prohászka (PROSZ, 4.00), Nilesh Puntambekar (PUNNI, 1.75), Janne Pyykkö (PYYJA, 2.16), Rui Qi (QI RU, 1.90), Francisca Quetglas (QUEFR, 3.73), Joe Rao (RAOJO, 2.00), Pavol Rapavý (RAPPA, 1.21), Gaurav B. Rathode (RATGA, 4.00), Maikel Regueiro (REGMA, 1.68), Jürgen Rendtel (RENJU, 2.23), Klar Gilberto Renner (RENKL, 1.33), Mileny Roche Lamas (ROCMI, 2.50), Francisco Rodriguez Ramirez (RODFR, 3.25), Dzhelil Rufat (RUFJE, 2.83), Victor Ruiz Ruiz (RUIVI, 2.16), Julián Ruiz-Garrido Zabala (RUIZJ, 2.52), Elaina Runge (RUNEL, 1.17), Karl Runge (RUNKA, 2.00), Lukasz Sanocki (SANLU, 1.67), António C. Saraiva (SARAN, 1.65), Mikiya Sato (SATMK, 2.00), Tomoko Sato (SATTM, 2.00), Alex Scholten (SCHAE, 0.42), Claude Schneider (SCHCL, 0.50), René Scurbecq (SCURE, 1.40), Michal Sefara (SEFMI, 0.80), Hideki Seo (SEOHI, 1.00), Tone-Lill Seppola (SEPTO, 1.95), Miguel Serra Martin (SERMI, 3.95), Brian Shulist (SHUBR, 0.84), Vesna Slavkovic (SLAVE, 0.33), Manuel Solano Ruiz (SOLMA, 1.31), Wanfang Song (SONWA, 3.30), Yuying Song (SONYU, 1.08), Bjørn Sørheim (SORBJ, 0.84), George Spalding (SPAGE, 3.17), Pavel Spurný (SPUPA, 0.20), Umberto Mule Stagno (STAUM, 3.50), Jon Stewart-Taylor (STEJO, 2.97), Wesley Stone (STOWE, 2.00), Chensheng Sun (SUNCH, 2.75), Richard Taibi (TAIRI, 3.81), Tony Tanti (TANTO, 2.37), Kazumi Terakubo (TERKA, 1.50), Sanjay Thorat (THOSA, 3.75), Stanislav Tkachenko (TKAST, 7.23), Josep M. Trigo Rodriguez (TRIJO, 1.15), Mihaela Triglav (TRIMI, 0.62), Nikos Tsikripis (TSINI, 2.00), Arnold Tukkers (TUKAR, 4.00), Erwin van Ballegoy (VANER, 4.14), Frans Van Loo (VANFA, 5.95), Hendrik Vandenbruaene (VANHE, 3.26), Michel Vandeputte (VANMC, 7.76), George Varros (VARGE, 0.08), Vishnu Vardhan (VARVI, 5.53), Cis Verbeeck (VERCI, 4.83), Jan Verfl (VERJX, 1.00), Miroslav Vetrik (VETMI, 0.70), William Watson (WATWI, 0.78), Thomas Weiland (WEITH, 4.25), Anne Williams (WILAN, 3.25), Glenn Williams (WILGL, 3.25), Jean-Marc Wislez (WISJE, 4.14), Oliver Wusk (WUSOL, 1.41), Dan Xia (XIADA, 1.35), Karen Young (YOUKA, 2.00), Robert Young (YOURO, 2.50), Jure Zakrajsek (ZAKJU, 2.08), Zorana Zeravcic (ZERZO, 0.67), Cunli Zhang (ZHACU, 2.75), Dongyan Zha (ZHADO, 1.25), Ju Zhao (ZHAJU, 2.55), Zhou-sheng Zhang (ZHAZH, 9.66), Jing Zhong (ZHOJI, 0.60), Jin Zhu (ZHUJI, 2.33), Xiaojin Zhu (ZHUXI, 0.52), Ron Zincone (ZINRO, 3.62), Kamil Zloczewski (ZLOKA, 4.50),

from the following 38 countries:

Argentina, Austria, Australia, Belgium, Brazil, Bulgaria, Canada, Chile, China, Croatia, Cuba, Czech Republic, Finland, France, Germany, Greece, Hungary, India, Israel, Italy, Japan, Malta, the Netherlands, New Zealand, Norway, Poland, Portugal, Romania, Singapore, Slovakia, Slovenia, Spain, Switzerland, UK, Ukraine, USA, Venezuela, Yugoslavia.

The population index profile

The various dust trails might be detectable not only through the activity profile, but upon inspection of the population index variations as well. A total number of 535 magnitude distributions of Leonids were available, of which 525 could be used for the analysis. The remaining 10 distributions contained hundreds of meteors covering the entire observation of many hours. They were not applicable to this study.

The method used here to obtain population indices converts the average meteor magnitude distance from the limiting magnitude into a population index (r-value). This average magnitude distance <Delta m> is a unique function of r. Idealized magnitude distributions for various population indices hence deliver a set of corresponding <Delta m>. Rough steps of this conversion are given in Table 1. The method is based on the simulations by Richter [3]; a comparison with the regression-line method delivered no serious differences (despite the larger error margins of the latter) unlike the magnitude analysis of the 1999 Leonids.

Table 1: Conversion of the average meteor magnitude distance from the limiting magnitude, <Delta m>, into population indices. Note that a large value for <Delta m> denotes a low average magnitude.
r1.61.82.02.22.42.62.83.03.23.4
<Delta m>5.3014.5684.0693.7003.4133.1802.9872.8232.6822.559

The binning here is adaptive; the algorithm uses as many magnitude distributions successively in time as necessary to gather a given minimum meteor number. It derives r and starts with the next hitherto unused distribution. There is thus no additional smoothing involved. Natural smoothing occurs due to the length of the magnitude-distribution interval which may "hang out" of the binning interval.

For the period between lambda=236.00 and lambda=236.20, a minimum meteor number of 500 was adopted, whereas this limit was lowered to 200 for the adjacent periods before and after the two strongest peaks on November 18. The pre-set meteor number is the reason for the virtually invariable size of the error margins in each of these three periods. The final profile is shown in Figure 1; the numerical details are given in Table 2. In order to detect possible small-scale features, we chose the smaller bins (i.e., smaller minimum meteor number) for the encounter time with the 1866 dust trail, despite the limited number of magnitude distributions compared with the 1733 trail encounter. As the sample of individual observers is thus very small, we also give averages of the period after lambda=236.20 with a 500-meteor minimum in Table 3.

Young dust trails are typically attributed with a higher population index than the annual background activity of the shower. A slight hint on a maximum of the population index is visible very close to the time which will be favored by the activity profile as being the 8-revolution dust trail peak which was observed from Europe and Africa (precisely, at lambda=236.085 or 3h16m UT on November 18 with r=2.06).

Figure 1: Population index profile of the 2000 Leonids. The time period covered by this diagram runs from November 17, 1h UT to November 19, 1h UT.

Figure 2 Magnification of the population index profile of the 2000 Leonids for the period November 17, 20h30m to November 18, 10h50m UT.

Table 2: Averaged population index. Despite the smaller number of magnitude distributions, the period of the encounter with the 4-revolution dust trail is shown applying the lower limit of minimum meteor number. Table 3 shows that period with the same 500-meteor limit as was used for the 8-revolution encounter.
lambda (J2000.0)Obsnravg. lm
234.705182292.391±0.1475.19
235.081142042.551±0.1825.25
235.14762152.354±0.1476.03
235.26982312.128±0.1125.28
235.31592181.974±0.0965.64
235.378102131.780±0.0755.31
235.468122071.992±0.1004.94
235.722122122.340±0.1465.47
235.82592642.056±0.0964.72
235.88682072.103±0.1165.43
235.93582061.784±0.0765.73
235.98592131.901±0.0905.65
236.018205101.878±0.0545.65
236.037185371.829±0.0495.77
236.049205121.877±0.0545.67
236.062205161.923±0.0575.62
236.075195132.014±0.0645.55
236.085205412.063±0.0675.59
236.096277612.038±0.0555.74
236.105235402.008±0.0625.28
236.115265971.968±0.0565.74
236.124195632.063±0.0665.64
236.135196432.069±0.0635.62
236.145235162.083±0.0715.72
236.159205102.057±0.0695.79
236.173195031.966±0.0615.72
236.193165212.053±0.0685.79
236.20872252.019±0.0995.66
236.22462632.084±0.1005.41
236.24992262.049±0.1035.15
236.26693292.057±0.0865.18
236.27872402.229±0.1225.52
236.28882032.175±0.1255.10
236.30872652.164±0.1095.32
236.32872522.066±0.0995.44
236.364112022.060±0.1115.25
236.891132042.899±0.2445.50
237.2726332.030±0.3095.87

The enhancement has, however, only marginal significance. Moreover, as there is also a minimum in r for lambda=236.115 or 3h59m UT on November 18 with r=1.97, we consider these extrema to be statistical fluctuations and find the population index fairly constant over a long period of more than four hours in the UT-morning hours of November 18.

A maximum r-value occurs again for the 4-revolution trail as seen from the Americas, centered on lambda=236.278 or 7h52m UT on November 18 with r=2.23. The maximum is still visible in the coarser binning as given in Table 3, but the time is less well defined there, of course.

Table 3: Averaged population index of larger bins for the period lambda=236.2-237.0.
lambda (J2000.0)Obsnravg. lm
236.192165402.029±0.064+5.82
236.222155062.137±0.076+5.34
236.264175762.020±0.061+5.30
236.291185112.211±0.081+5.19
236.329145112.053±0.068+5.46
236.364112022.060±0.111+5.25
236.80581332.795±0.283+5.49

No population index extremum appears for the 2-revolution trail, which may be supposed to be richest in faint meteors, because it is younger than any other trail encountered. What is visible there is a gradual, almost linear decrease of r from lambda=235.1 to lambda=235.4 while the peak was expected near lambda=235.27.

Activity profile

We use the population index profile of Table 2 and Figure 1 to correct observations for their limiting magnitude to the standard value of lm=+6.5. Given the limiting magnitude lm, possible field obstruction factors F, and the elevation of the Leonid radiant, hR, the total correction for an individual (index i) observing period amounts to

Ci = r(6.5-lm) F / sin hR

Averages of the ZHR are weighed by that correction and the effective observing time Teff,i such that

<ZHR> = (1 + sumini) / sumi (Teff,i / Ci).

Again, no additional smoothing is applied apart from the overlap of periods due to Teff,i>0. Observing periods longer than the bin size are excluded from the average. That means that the maximum effective bin size due to interval overlap is twice the given bin size. A time correction to topocentric stream encounter [4] was not applied; the resolution of the profiles will not be as low as five minutes, which is the typical correction between geographical locations used here.

Table 4 lists the bin sizes used to cover the period of maximum Leonid activity with meaningful averages. Note that one hour corresponds to a solar-longitude difference of Delta lambda=0.0420 in those nights. A significant number of observations was divided in intervals of about one hour, and the bin size of 0.045 was explicitly chosen to include these observations. Similarly, for the high-resolution part, the bin size of 0.011 was chosen to include the numerous 15-minute observing periods.

Table 4: Bin sizes.
PeriodBin size
234.60-235.100.045°
235.10-235.350.022°
235.35-235.950.090°
235.95-236.370.011°
236.37-237.500.050°

Table 5: Detailed numerical data of the averaged ZHRs obtained from records with a minimum radiant elevation of hR=15°.
lambda (J2000.0)Obsn<ZHR> avg. lmlambda (J2000.0)Obsn <ZHR>avg. lm
234.681841334.0±9.15.71236.116091972252.0±8.15.65
234.828052649.7±9.65.34236.127768739235.9±8.75.62
234.857842735.8±6.85.49236.138256536191.1±8.25.68
234.955171825.8±5.95.46236.148642457211.4±9.95.82
234.993562039.1±8.55.12236.160538443230.3±10.95.80
235.0447135750.3±6.65.12236.170929435263.1±12.65.72
235.084793240.6±7.15.29236.181922380275.6±14.15.65
235.106682428.5±5.75.68236.192218238323.0±20.95.63
235.1217106661.6±7.55.70236.203514214332.6±22.75.41
235.147064346.1±6.95.84236.215118261396.1±24.55.42
235.167453432.1±5.45.88236.227120207326.1±22.65.56
235.189062776.4±14.45.28236.237219196323.6±23.15.52
235.212673383.6±14.35.31236.248430469483.1±22.35.54
235.236071751.8±12.25.73236.259334483437.9±19.95.47
235.254072054.1±11.85.87236.270343650419.5±16.45.47
235.27821059132.5±17.15.46236.281340504362.7±16.15.43
235.298494180.8±12.55.36236.292138397247.1±12.45.51
235.318682769.9±13.25.23236.303029277215.2±12.95.50
235.339392330.3±6.25.12236.313626218170.0±11.55.51
235.3717113330.1±5.25.10236.324719162163.3±12.85.50
235.438332354.2±11.15.38236.33401168105.5±12.75.46
235.71421917561.4±4.65.39236.3463762109.2±13.85.59
235.80521723649.2±3.25.47236.356543189.8±15.95.62
235.88371527985.6±5.15.68236.366343393.2±16.05.59
235.9630637118.7±19.35.55236.382095649.5±6.65.83
235.9740543124.9±18.85.64236.4114147538.0±4.45.79
235.98361049125.5±17.85.89236.472734337.0±5.66.01
235.99571272143.4±16.85.37236.617452735.6±6.75.78
236.005817113144.7±13.65.51236.668772828.2±5.25.72
236.017321145177.6±14.75.64236.767342834.9±6.55.17
236.027427330237.0±13.05.69236.924841031.4±9.55.65
236.038945512244.3±10.85.63236.9646112724.5±4.65.58
236.049549517232.6±10.25.59237.015362826.9±5.05.43
236.060566654243.9±9.55.56237.076083321.0±3.65.69
236.071654667269.5±10.45.57237.110052017.6±3.85.64
236.083268783256.9±9.25.70237.175331011.3±3.45.51
236.09361011019287.9±9.05.62237.31885219.4±11.25.55
236.10521151067250.0±7.65.59237.36133115.7±11.15.46

In this analysis, we did not compute individual perception coefficients. Such coefficients account for systematic properties of observers. They can be obtained from systematic deviations of an individual observer's ZHRs or corrected sporadic rates from the average. A few exceptional cases were specially treated here, however.

Veteran observer Norman McLeod (MCLNO) has a remarkable ability to spot faint stars; his corrected meteor rates settled very consistently at about 50% of the average rates seen by other observers. We applied a perception coefficient of cp=0.5 to observer MCLNO.

Japanese observer Kazuhiro Osada (OSAKA) has a very effective perception of meteors. His reports are not easy to correct for that effect, as the meteor perception appears to increase when more meteors are visible anyway. This is expressed by enhanced sporadic rates which climbed up to about 80 (!) for the Leonid maximum. If no major shower is active, sporadic rates lie between 40 and 50 for OSAKA. We chose a tentative perception factor of cp=4 to normalize his data, although his observations are atypical.

Finally, Mikiya Sato's (SATMK) data are reduced by cp=2 based on the generally higher-than-average sporadic and shower rates.

Figure 3: Entire ZHR profile of the 2000 Leonids. The minimum radiant elevation was 15°; observing periods longer than the bin size are excluded.

The general influence of corrections can be checked by varying the quality limits for the individual records. While the graphs in Figures 3 and 4 were produced with a minimum radiant elevation of hR=15°, the graph of Figure 5 involves more rigorous restrictions, namely hR>20° and C<8, with C the total correction factor. This means that, even if the radiant was high enough, limitations are imposed to the limiting-magnitude and cloud correction. The two graphs in Figures 4 and 5 are satisfactorily similar. Nevertheless, we will go into detail of observing effects in the following sections.

Limiting magnitude influence

The relatively poor conditions with the Moon high in the sky may have a systematic effect on the height of the ZHR maxima. We divided the observations into two samples, one with lm>+5.6 and the other with lm<+5.6. The second sample is a little more comprehensive with respect to the number of individual records, but was chosen deliberately in order to compensate for the lower meteor numbers due to poorer conditions. Indeed the graph of the second data set (Figure 8) shows somewhat higher ZHRs than the high-lm set (Figure 7), but the good news is that the shape of the profile is not drastically altered. The change in ZHR level can have two reasons: (i) the lm correction overestimates the loss of meteors, or (ii) the observers underestimated their limiting magnitude.

Table 7: Distribution of observing periods and effective observing time versus limiting magnitude.
Limiting magnitude4.0-4.54.5-5.05.0-5.5 5.5-6.06.0-6.56.5-7.0
Records9222558660944418
Teff37.2288.22171.18 203.42103.9110.27

Figure 4: Magnification of the ZHR profile of the 2000 Leonids near the peaks of the 8-revolution and 4-revolution trails. The period shown corresponds to November 17, 22h50m to November 18, 12h00m UT.

Figure 5: Restricted profile of the 2000 Leonids near the peaks of the 8-revolution and 4-revolution trails with a maximum total correction of 8.0 and a minimum radiant elevation of 20°.

Figure 6: Magnification of the ZHR profile of the 2000 Leonids near the peak of the 2-revolution trail. The graph is discussed in Section 6.

Figure 7: Maximum part of the ZHR profile of the 2000 Leonids from observations with lm>+5.6

Figure 8: Maximum part of the ZHR profile of the 2000 Leonids from observations with lm<+5.6.

The total graph of Figure 3 is closer to the high-lm Figure 7 with respect to ZHR amplitudes, since the averages are weighed with the inverse of the total correction, and periods under poor conditions - explicitly extracted for Figure 8 - have less weight than those recorded under good skies.

Cloud interference

In spite of a relatively broad but clear maximum for the 8-revolution trail between 3h and 4h UT on November 18, observers who were lucky to have good conditions for a long period in that night independently mentioned the obvious absence of a distinct peak according to both their impression and data. We have, therefore, split the data set into two other samples: one containing only long-duration observations from sites from where, at worst, occasional cloud cover of no more than 10% were reported; the second containing the remaining observations. The dataset of (European) long-term observers was formed by BADPI, BETFE, JIMMN, JOHCA, KIDMA, LANMA, MARDA, MASED, MISKO, MOMIV, OKODR, QUEFR, PLADU, RODFR, RUIVI, SERMI, VERCI, and WISJE.

The amazing result of splitting the data set in this way is shown in Figure 9, with the long-term observations at the left side and the "cloud-gap" observations at the right side. Indeed, the impression of the long-term watchers that the activity curve lacked a clear peak for the 8-revolution prediction features also in the analysis. The observers more or less being disturbed by clouds produce a graph with clear rise, peak, and fall of activity, with the maximum at lambda=236.09 (3h24m UT) being within a 20-minute error margin from the predicted passage of the 1733 trail. The long-term observers saw constant activity (with just a slight, downward trend) between lambda=236.06 and lambda=236.13 (between 2h41m and 4h21m UT). The level of activity is 230-250 for the long-term observers - the same as seen by the cloud-gap watchers who essentially topped this graph by "their" peak.

Figure 9: Maximum part of the 2000 Leonids from long-duration observations with no more than occasional 10% obstruction (left).

These two profiles of Figure 9 call for possible explanations. It is not unlikely that a psychological effect plays a role here. Expectations were high, and an observer waiting for a cloud gap may tend to "reward" his waiting by recording a good meteoric display. If the psychology during exciting events has such an impact, we would have to consider much larger error margins for other outbursts, which were covered by poor-condition data only.

We note that it may be more satisfactory to find other explanations maintaining the confidence in the observers that they try to record what they see rather than what is expected. Naturally, the expectations of the peak may lead to an increased number of observations with poor conditions. "If nothing worked out this night," the observer may have said, "these ten minutes round the peak will be recorded, however poor the sky is, however small the cloud-gap is." Together with the fact that low-lm data tend to produce higher ZHRs, a peak can be expected just as an indirect consequence of the expectations.

Our considerations would not be complete, however, if we would not also search for explanations the other way round: Were long-term observers possibly fatigued by the time the 1733 peak was expected? In this investigation, "fatigue" is meant in a very broad sense: when using this term, we do not so much think of fatigue caused by a need for sleep after several hours of concentrated observing, but rather of fatigue to the eyes and their ability to adapt to the darkness, because of their constant exposure to the moonlit sky background, although the two effects may reinforce each other, of course.

The observers did not start at the same time, and by the time one observer might have become fatigued, another just started fresh. The distribution of beginning times (UT) is: MOMIV, 23h24m; SERMI, 0h05m; QUEFR, 0h25m; JOHCA, 1h17m; MISKO, 1h18m; MASED, 1h21m; LANMA, 1h29m; JIMMN, 1h55m; WISJE, 2h00m; VERCI, 2h12m; MARDA, 2h15m; PLADU, 2h30m; KIDMA, 2h40m; RODFR, 2h42m; OKODR, 2h50m; RUIVI, 3h05m; BETFE, 3h16m; and BADPI, 3h25m.

We have two ways to tentatively check for possible fatigue. First we consider the temporal development of averaged sporadic rates of the two categories of observers. Indeed, we find a gradual decrease of HR_spor for the all-night observers with values of 23.7, 13.8, 9.6, 8.9, and 7.1 for 0.05 steps between 1h15m and 7h10m UT. The observer class with cloud interferences delivers 7.0, 5.5, 6.8, 9.5, and 15.6 - rather showing a rising tendency, as it would be expected approaching the culmination of the apex near 6h local time. This may indeed be an indication of fatigue for the former group.

Figure 10: Population index profiles for two groups of observers: black data refer to long-term observations with no cloud interference, grey values refer to the remaining observations with more or less cloud interference and breaks.

In a second attempt to check for possible fatigue, we computed the two independent population index profiles (for the Leonids, not the sporadics) for the two groups: fatigue would result in lower r-values because faint meteors are likely to be missed. This time, we applied a minimum meteor number of 600 in order to smear out small structures; we are only interested in the tendency over a period of several hours. The result is shown in Figure 10. Black values represent the all-night watchers' group, grey values refer to the "cloud group." Again, an opposite tendency with a decrease of r for the all-night observers and an increasing r for the "cloud-gappers" indicates fatigue as being important in long observations, at least under unfavorable circumstances. Note that these two tests are completely independent.

The distribution of locations is not significantly different for the two profiles, but the all-night observers' profile contains only locations in Bulgaria, Spain, Portugal, and Morocco. The remaining data set covers a much more extended area from the Crimea to the Canaries in longitude, and from Egypt to northern Norway in latitude. We consider it unlikely, though, that small-scale peculiarities within the dust trail caused southern Europe to see a flat profile instead of a peak, as suggested by the remaining European observations (partly from very similar locations, in fact).

The double peak of November 17

The dust trail integrations predicted a possible activity enhancement from the two-revolution trail ejected in 1932 for the UT-morning hours of November 17. Such an enhancement is indeed visible in Figure 3, with a ZHR level of about 130. As already noted in the IMO Shower Circulars [5], the profile exhibits a double peak near that time, with a somewhat lower, additional maximum preceding the peak close to the predicted time. The enlargement in Figure 6 shows the bimodal structure of this least prominent of the dust trail encounters. The times of the two maxima can be fixed at lambda=235.21 and lambda=235.28.

The average ZHR values given in Table 5 and shown in Figure 6 are not unproblematic, though. They are composed by individual reports of very high and very low activity. In fact, the numbers of individual reports involved in each of the averages in that part of the profile are not excitingly large, yet we decided not to smear out this feature of the graph by larger bins (cf., Table 4). Most of the observers contributing to the pre-1932 averages were experienced people, in alphabetical order ANDBI, BONNE, MCLNO, SEPTO, VANER, VERCI, and WISJE. Their ZHRs, however, range from 24 to 200 for the particular period between 6h00m and 6h30m UT. Possibly, more observing reports will help to clarify these contradictory activity values.

Particle integrations by Göckel and Jehn [6] indicate good activity from the 1932 trail in the morning of November 17. The particle numbers reaching Earth are small, but apart from the peak near lambda=235.27, we see another maximum with 75% of the strength of the former near lambda=235.20.

Conclusions

We present both population index profiles and ZHR profiles for the 2000 Leonids as derived from visual observations. Three major activity outbursts were found: lambda=235.28 (November 17, 8h07m UT) with ZHR=130± 20, lambda=236.09 (November 18, 3h24m UT) with ZHR=290± 20, and lambda=236.25 (November 18, 7h12m UT) with ZHR=480± 20. With respect to the predictions by McNaught and Asher [1], the corresponding offsets of the visual maxima are +15 minutes for the 1932 trail, -20 minutes for the 1733 trail, and -40 minutes for the 1866 trail, all rounded to the nearest 5 minutes. Note that the accuracy of the observational peak times is no higher than ±15 minutes anyway. It is noteworthy that the population index reached its maximum precisely at the predicted time of the 4-revolution dust trail, that is about 40 minutes after the ZHR maximum. The older 8-revolution trail is characterized by a broad shape with almost flat top in both the ZHR and population index graphs. The error margin of its ZHR maximum is set to ±20 here in order to account for the systematic differences between two observer groups as described in Section 5.

We may also conclude that the influence of the Moon - although disturbing the joy of a nice meteor display - did not ruin the actual results. A few tests for the influence of the conditions on the ZHR graph showed that peak times and peak activity levels are not dominated by the choice of correction factors. Also, an in depth-study of the considerations made above about the possible influence of fatigue in long observations under poor circumstances may result in even more refined instructions for optimal observation of major showers under poor Moon conditions. From this perspective, we are confident to be able to present meaningful results also for the 2002 Leonid meteor shower which will suffer from an almost Full Moon.

References

[1] R.H. McNaught, D.J. Asher, Leonid Dust Trails and Meteor Storms. WGN 27:2, 1999, pp. 85-102.

[2] E. Lyytinen, T. van Flandern, Meta Res. Bull. 8, 1999, pp. 33-40.

[3] J. Richter, personal communications, 1998.

[4] R.H. McNaught, D.J. Asher, Variation of Leonid Maximum Times with Location of Observer. Meteoritics and Planetary Science 34, 1999, pp. 975-978.

[5] M. Gyssens, Leonid Shower Circulars, November 2000.

[6] C. Göckel, R. Jehn, Testing Cometary Ejection Models To Fit the 1999 Leonids and To Predict Future Showers. Mon. Not. R. Astron. Soc. 317, 2000, pp. L1-L5.

Author's addresses

Rainer Arlt, Friedenstraße 5, 14109 Berlin, Germany, visual@imo.net.

Marc Gyssens, Heerbaan 74, 2530 Boechout, Belgium, wgn@imo.net.