Heliophysics and amateur radio: citizen science collaborations for atmospheric, ionospheric, and space physics research and operations
Bibliographic record
Abstract
The amateur radio community is a global, highly engaged, and technical community with an intense interest in space weather, its underlying physics, and how it impacts radio communications. The large-scale observational capabilities of distributed instrumentation fielded by amateur radio operators and radio science enthusiasts offers a tremendous opportunity to advance the fields of heliophysics, radio science, and space weather. Well-established amateur radio networks like the RBN, WSPRNet, and PSKReporter already provide rich, ever-growing, long-term data of bottomside ionospheric observations. Up-and-coming purpose-built citizen science networks, and their associated novel instruments, offer opportunities for citizen scientists, professional researchers, and industry to field networks for specific science questions and operational needs. Here, we discuss the scientific and technical capabilities of the global amateur radio community, review methods of collaboration between the amateur radio and professional scientific community, and review recent peer-reviewed studies that have made use of amateur radio data and methods. Finally, we present recommendations submitted to the U.S. National Academy of Science Decadal Survey for Solar and Space Physics (Heliophysics) 2024–2033 for using amateur radio to further advance heliophysics and for fostering deeper collaborations between the professional science and amateur radio communities. Technical recommendations include increasing support for distributed instrumentation fielded by amateur radio operators and citizen scientists, developing novel transmissions of RF signals that can be used in citizen science experiments, developing new amateur radio modes that simultaneously allow for communications and ionospheric sounding, and formally incorporating the amateur radio community and its observational assets into the Space Weather R2O2R framework. Collaborative recommendations include allocating resources for amateur radio citizen science research projects and activities, developing amateur radio research and educational activities in collaboration with leading organizations within the amateur radio community, facilitating communication and collegiality between professional researchers and amateurs, ensuring that proposed projects are of a mutual benefit to both the professional research and amateur radio communities, and working towards diverse, equitable, and inclusive communities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.055 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.004 | 0.018 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.034 | 0.018 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".