Crowdsourced Doppler measurements of time standard stations demonstrating ionospheric variability

Kristina Collins,John Gibbons,Nathaniel Frissell,Aidan Montare,David Kazdan, Darren Kalmbach, David Swartz, Robert Benedict,Veronica Romanek,Rachel Boedicker,William Liles,William Engelke,David G. McGaw, James Farmer, Gary Mikitin, Joseph Hobart, George Kavanagh,Shibaji Chakraborty

EARTH SYSTEM SCIENCE DATA(2023)

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摘要
Ionospheric variability produces measurable effects in Doppler shift of HF (high-frequency, 3-30 MHz) skywave signals. These effects are straightforward to measure with low-cost equipment and are conducive to citizen science campaigns. The low-cost Personal SpaceWeather Station (PSWS) network is a modular network of community-maintained, open-source receivers, which measure Doppler shift in the precise carrier signals of time standard stations. The primary goal of this paper is to explain the types of measurements this instrument can make and some of its use cases, demonstrating its role as the building block for a large-scale ionospheric and HF propagation measurement network which complements existing professional networks. Here, data from the PSWS network are presented for a period of time spanning late 2019 to early 2022. Software tools for the visualization and analysis of this living dataset are also discussed and provided. These tools are robust to data interruptions and to the addition, removal or modification of stations, allowing both short- and long-term visualization at higher density and faster cadence than other methods. These data may be used to supplement observations made with other geospace instruments in event-based analyses, e.g., traveling ionospheric disturbances and solar flares, and to assess the accuracy of the bottomside estimates of ionospheric models by comparing the oblique paths obtained by ionospheric ray tracers with those obtained by these receivers. The data are archived at https://doi.org/10.5281/zenodo.6622111 (Collins, 2022).
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关键词
doppler,standard stations,variability
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