@proceedings {1018, title = {The Heliophysics Application Programming Interface on the PSWS}, year = {2026}, month = {03/2026}, publisher = {HamSCI}, address = {Newington, CT}, abstract = {One of the major enhancements being developed for the Personal Space Weather Network System is our implementation of the Heliophysics Application Programming Interface. This interface is being developed with help from Dr Robert Weigel of George Mason University to make HamSCI data more accessible to researchers. In the first version of the PSWS system, users have been able to download individual files to analysis, but this can be labor intensive and time-consuming if a lot of files are needed. The current NSF-funded effort will make the data more easily accessible to users by leveraging Python libraries that make data access transparent, such as hapiclient, hapiplot, hdpws, And SwarmPAL. This poster gives an overview of what will be included and how you will be able to use it.}, author = {William Engelke and Travis Atkison and Evan Hardt and Christian Hirschey and Gavin Ward and Annika Lee} } @proceedings {764, title = {Medium Scale Traveling Ionospheric Disturbances and their Connection to the Lower and Middle Atmosphere}, year = {2023}, month = {03/2023}, publisher = {HamSCI}, address = {Scranton, PA}, author = {Nathaniel A. Frissell and Francis Tholley and V. Lynn Harvey and Sophie R. Phillips and Katrina Bossert and Sevag Derghazarian and Larisa Goncharenko and Richard Collins and Mary Lou West and Diego F. Sanchez and Gareth W. Perry and Robert B. Gerzoff and Philip J. Erickson and William D. Engelke and Nicholas Callahan and Lucas Underbakke and Travis Atkison and J. Michael Ruohoniemi and Joseph B. H. Baker} } @proceedings {688, title = {Personal Space Weather Station Central Control and Database System}, year = {2023}, month = {03/2023}, publisher = {HamSCI}, address = {Scranton, PA}, abstract = {

As part of the Personal Space Weather Station (PSWS) project, our team has been developing the Central Control System and Central Database System that will be used to collect and store the data generated by the stations. The Central Control System functionality is being developed using Django, a Python based web framework. It is used to define how users will interact with the web server where their collected data will be uploaded, organized, and analyzed. It is also used to define models for the data being collected and how it will be stored in the Central Database System. In the server{\textquoteright}s current state, users can register accounts and stations as well as view lists of uploaded observations. Observation data can also be downloaded individually for analysis. The availability of the PSWS will allow a much larger sample of data to be collected daily. With this data, more accurate models of the ionosphere can be created, granting a better ability to predict how radio waves will be precisely affected by the ionosphere at any given moment and supporting ionospheric science.

}, author = {Anderson B. Liddle and Nicholas Muscalino and William D. Engleke and Travis Atkison} } @proceedings {624, title = {Detecting Large Scale Traveling Ionospheric Disturbances using Feature Recognition and Amateur Radio Data}, year = {2022}, month = {03/2022}, publisher = {HamSCI}, address = {Huntsville, AL}, abstract = {

A Large-Scale Transient Ionospheric Disturbance (LSTID) is a traveling perturbation in ionosphere electron density with a horizontal wavelength of approximately 1000 km and a period between 30 to 180 minutes. These can be detected by SuperDARN HF radar and GNSS Total Electron Content measurements. Recently it has been discovered that these can also be detected in amateur (ham) radio signal reports, which are now being generated in vast numbers by operators world-wide. A machine-learning technique was developed to find patterns in these data that indicate the presence of LSTIDs using an object detection technique.

}, author = {William D. Engelke and Nathaniel A. Frissell and Travis Atkison and Philip J. Erickson and Francis Tholley} } @conference {540, title = {HamSCI Personal Space Weather Station (PSWS): Architecture and Current Status}, booktitle = {NSF CEDAR (Coupling, Energetics, and Dynamics of Atmospheric Regions)}, year = {2021}, month = {06/2021}, publisher = {CEDAR}, organization = {CEDAR}, address = {Virtual}, abstract = {

Recent advances in geospace remote sensing have shown that large-scale distributed networks of ground-based sensors pay large dividends by providing a big picture view of phenomena that were previously observed only by point-measurements. While existing instrument networks provide excellent insight into ionospheric and space science, the system remains undersampled and more observations are needed to advance understanding. In an effort to generate these additional measurements, the Ham Radio Science Citizen Investigation (HamSCI, hamsci.org) is working with the Tucson Amateur Packet Radio Corporation (TAPR, tapr.org), an engineering organization comprised of volunteer amateur radio operators and engineers, to develop a network of Personal Space Weather Stations (PSWS). These instruments that will provide scientific-grade observations of signals-of-opportunity across the HF bands from volunteer citizen observers as part of the NSF Distributed Array of Small Instruments (DASI) program. A performance-driven PSWS design (~US$500) will be a modular, multi-instrument device that will consist of a dual-channel phase-locked 0.1-60 MHz software defined radio (SDR) receiver, a ground magnetometer with (~10 nT resolution and 1-sec cadence), and GPS/GNSS receiver to provide precision time stamping and serve as a GPS disciplined oscillator (GPSDO) to provide stability to the SDR receiver. A low-cost PSWS (\< US$100) that measures Doppler shift of HF signals received from standards stations such as WWV (US) and CHU (Canada) and includes a magnetometer is also being developed. HF sounding algorithms making use of signals of opportunity will be developed for the SDR-based PSWS. All measurements will be collected into a central database for coordinated analysis and made available for public access.

}, author = {Nathaniel A. Frissell and Dev Joshi and Veronica I. Romanek and Kristina V. Collins and Aidan Montare and David Kazdan and John Gibbons and William D. Engelke and Travis Atkison and Hyomin Kim and Scott H. Cowling and Thomas C. McDermott and John Ackermann and David Witten and Julius Madey and H. Ward Silver and William Liles and Steven Cerwin and Philip J. Erickson and Ethan S. Miller and Juha Vierinen} }