Climate, Weather and Health
History meets Science
Meteorology Beyond Borders
Applied and Computational Historical Astronomy
organized by Susanne M. Hoffmann
SOC: dr. dr. Susanne M Hoffmann (FSU Jena), Prof. dr. Gerd Graßhoff (HU Berlin) and Prof. dr. Gudrun Wolfschmidt (U Hamburg)
LOC: Karsten Markus-Schnabel, Markus Hundertmark
This was a splinter meeting at the Annual Meeting of the German Astronomical Society.
25 September 2020
Always since the discovery of precession by Hipparchus ~2200 years ago, astronomers have made use of data from all available historical epochs in addition to very recent own observations. Many processes in astrophysics evolve on long time-scales, especially in cases where accretion is involved. The longterm variability of stars, evolution of transients and their remains (e.g. supernova remnants) as well as questions on longterm evolution of close binaries (such as symbiotic or cataclysmic systems) could be investigated by taking historical data into account. However, historical observers normally did not understand what they saw and did not apply modern standards of follow-up observation and notion. Many observational records are preserved only due to astrological beliefs in political or religious context. Using these old data to enlarge our temporal base line of observation, thus, challenges scholars to inter- and transdisciplinary work of historical studies and astrophysics.
Applied historical astronomy needs to evaluate, sort, and classify the historical data, needs to find them in text and maps, and often distinguish them from errors in the copying tradition. In order to identify modern counterparts of historical data, the tools of computational astronomy need to be applied and events which changed the physics of a system (like supernovae) have to be distinguished from events of only geometrical origin (e.g. microlensing).
This meeting shall assemble talks on naked-eye astronomy, historical celestial maps, globes and uranographies from all epochs and geographical regions, computational history of science, and big data astronomy.