# Meteor Shower Modeling: Past and Future Draconid Outbursts

## TL;DR

This paper presents an updated numerical model of the Draconid meteoroid stream, accurately reproducing past outbursts and predicting future radio outbursts, including a previously unreported event in 1999.

## Contribution

The study improves existing meteoroid stream models by incorporating comet dust production evolution and validates predictions with historical observations.

## Key findings

- Accurately reproduces historical Draconid outbursts within half an hour.
- Predicts three future radio outbursts in 2019, 2025, and 2029.
- Identifies a previously unreported 1999 radio outburst confirmed by radar.

## Abstract

This work presents numerical simulations of meteoroid streams released by comet 21P/Giacobini-Zinner over the period 1850-2030. The initial methodology, based on Vaubaillon et al. (2005), has been updated and modified to account for the evolution of the comet's dust production along its orbit. The peak time, intensity, and duration of the shower were assessed using simulated activity profiles that are calibrated to match observations of historic Draconid outbursts. The characteristics of all the main apparitions of the shower are reproduced, with a peak time accuracy of half an hour and an intensity estimate correct to within a factor of 2 (visual showers) or 3 (radio outbursts). Our model also revealed the existence of a previously unreported strong radio outburst on October 9 1999, that has since been confirmed by archival radar measurements. The first results of the model, presented in Egal et al. (2018), provided one of the best predictions of the recent 2018 outburst. Three future radio outbursts are predicted in the next decade, in 2019, 2025 and 2029. The strongest activity is expected in 2025 when the Earth encounters the young 2012 trail. Because of the dynamical uncertainties associated with comet 21P's orbital evolution between the 1959 and 1965 apparitions, observations of the 2019 radio outburst would be particularly helpful to improve the confidence of subsequent forecasts.