First automated GMN trajectories
More than 100 meteor stations all over the world send their data to our GMN server every day. Until now, this data was sitting idle on the server disk drives. The last couple of months I focused on writing code for automated multi-station meteor trajectory estimation, and now I’m happy to report the first results!
The GMN serverside scripts are using the open-source meteor trajectory code from the Western Meteor Python Library, an implementation of the novel Monte Carlo trajectory solver which produces trajectories of superior accuracy when compared to older methods of trajectory estimation. The paper about it has been submitted to MNRAS and will be published soon.
In this first preliminary data release, we show high quality meteor orbits recorded with GMN cameras from December 2018 up until now (late August 2019). We only select meteor trajectories with the minimum of 6 astrometry measurements per station, minimum convergence angle of 5 degrees, maximum eccentricity of 1.5, maximum radiant error of 2 degrees, and the maximum velocity error of 10%. Low quality trajectories usually have a low number of data point or unfavourable observation geometry, even though the astrometry calibration is good. RMS, the software that GMN stations run, recalibrates the astrometric plate on every image that has a meteor detection, ensuring the high quality of solutions.
Figure 1 shows a Sun-centered ecliptic plot of 14 006 orbits in this first data release. The meteor orbit density is colour coded and several major showers can be seen (Perseids, Southern Delta Aquarids, Geminids, Capricornids, etc.), as well as the sporadic sources. The dataset also contains trajectories of several minor showers, e.g. 3 Camelopardalid orbits. I still need to write a module for orbital shower association, until then the association needs to be done manually.
Figure 2 shows a plot of individual orbits colour coded by the geocentric velocity in the same coordinate system. As expected, the velocities increase up to the maximum of ~71 km/s close to the Earth’s apex in the middle of the plot.
Figure 3 shows a map of 45 stations which were used for trajectory estimation. There are more stations that report meteor observations, but they are either single-station or their calibrations and geospatial coordinates need to be confirmed before they are used for trajectory estimation.
Finally, we give a link to raw data so interested readers may take a look for themselves: trajectory_summary
This data set is preliminary, thus one should keep in mind that there might be erroneous entries in it. If the data is used, we ask that you reference GMN and this blog post.
Clear skies,
Denis Vida