Data Analysis Pipeline for Distributed Doppler Measurements Using Citizen Science Datasets From 2020 and 2021 Eclipse Festival Campaigns

Doppler observations of time standard stations are an ideal basis for multi-instrument citizen science campaigns, particularly during solar eclipses. Through the Eclipse Festivals of Frequency Measurement, successful citizen science campaigns have been conducted for the eclipses of 2020 and 2021, garnering support from volunteers worldwide. However, audio data collected during these campaigns cannot be processed in real time, as a data collection campaign with a duration of a few days can result in a year or more worth of audio data. Furthermore, ensuring the longevity of this program demands a robust software framework which can be adapted to evolving data collection needs. We report our system for processing this data using parallel computation on a High Performance Computing Cluster (HPCC) and resulting visualizations of the data from recent Eclipse Festivals. This undergraduate project encompasses three parts: processing, parallelization, and visualization of data. The codebase developed in this project, which uses Bash, Python, R, MATLAB and Slurm, will be reused for future Eclipse Festivals and long-term data collection, ultimately supporting the Low-Cost Personal Space Weather Station initiative under the National Science Foundations Distributed Array of Small Instruments (DASI) program. It can also be adapted for other use cases of distributed geophysical instrumentation, and prospects for broader reuse will be discussed.