Abstract

Ancient sources contain numerous astronomical observations that can be used to establish absolute dates. Solar eclipses are particularly important in this context. In antiquity, eclipses were often perceived as a threat and bad omen, causing fear and potentially political disturbances. By far not every partial solar eclipse has been noticed by an unprepared observer. Changes in ambient illumination remain relatively inconspicuous until a large part of the solar disk is covered. Even when about three quarters of the Sun's area is obscured, the reduction in daylight may still pass largely unnoticed with the most dramatic changes in illumination occuring only during the very deep partial phases close to totality. Historical visibility must be understood primarily in terms of the conspicuous environmental effects of a deep eclipse—diminished and altered daylight, unusual shadows, and, near totality, a pronounced twilight-like appearance. These facts make eclipses of high magnitude particularly relevant when considering events that could have attracted widespread attention without advance knowledge of the phenomenon. A series of such high magnitude solar eclipses at a certain location within a limited number of years is a rare phenomenon. Such eclipse series have been interpreted to being the cause of political disturbances.

About This Material

This is a Hands-on Tutorial from the GTN which is usable either for individual self-study, or as a teaching material in a classroom.

Questions this will address

• How can we identify groups of solar eclipses above a user-defined observable magnitude within a specified time interval?
• How can runtime parameters make the analysis reusable and reproducible?

Learning Objectives

• Import a pre-calculated solar-eclipse dataset into Galaxy.
• Convert a text file to tab-separated tabular data.
• Split the eclipse magnitude and time of maximum eclipse fields into observable (mag1 / Tmax1) and theoretical (mag2 / Tmax2) magnitudes.
• Filter eclipses using a user-defined minimum observable magnitude.
• Sort eclipse records chronologically.
• Identify groups of N consecutive eclipses occurring within a user-defined maximum number of years.
• Remove duplicate eclipse records while retaining one occurrence of each eclipse.
• Run the analysis reproducibly with workflow parameters.