@proceedings {975, title = {Incorporating HamSCI Project into a College Physics Course: A Progress Report}, year = {2025}, month = {03/2025}, publisher = {HamSCI}, address = {Newark, NJ}, abstract = {

We report on citizen science activities in a physics course and Space Force ROTC training designed to engage undergraduate students and cadets in the HamSCI Personal Space Weather Station (PSWS) project. The New Jersey Institute of Technology (NJIT) Physics Department offers a senior-level lab course, "Advanced Physics Lab," where students are expected to gain hands-on experience with experimental techniques, instrumentation, theoretical and applied electronics, solid-state electronic devices, and experiments in modern physics by performing quantitative measurements of fundamental physical parameters. In this lab, students work in a largely unstructured environment, where they are provided with equipment and related manuals to conduct experiments with minimal instructor supervision. Traditionally, students have followed preset lab setups, guided by the manuals that accompany the equipment. While this approach helps students relate lab results to established physics theories and principles, its impact has been limited due to a lack of "hands-on" experience and real-world application demonstrations. The HamSCI PSWS project provides an excellent opportunity to address this gap. Through the project, students build and test scientific instruments, using them for investigations that engage them directly in scientific inquiry. This paper presents an evaluation of the impact of this undergraduate class activity on future workforce development, utilizing HamSCI resources.

}, author = {Hyomin Kim and Jeremy McLynch and Joseph Visone and Dominick Santelli and Sergio Santelli and Gareth Perry and Nathaniel Frissell and Gary Mikitin and John Gibbons and David Witten} } @proceedings {953, title = {Integration \& Validation of a Standardized Library \& File Format for PyDARNMUSIC \& DARNtids: Migrating From Legacy Pickle Files to HDF5 \& Implementing a Comprehensive Testing Suite}, year = {2025}, month = {03/2025}, publisher = {HamSCI}, address = {Newark, NJ}, abstract = {

The PyDARN Multiple Signal Classification (PyDARN-MUSIC) algorithm is a general, widely used sign processing algorithm for determining the parameters of multiple wavefronts arriving at an antenna array from measurements made on the signals received at the array elements. It has been used in previous Super Dual Auroral Radar Network (SuperDARN) studies to determine the size, strength, speed, and direction of Medium Scale Traveling Ionospheric Disturbances (MSTIDs). DARNtids (Dual Auroral Radar Network Traveling Ionospheric Disturbances) is a python-based open-source software toolkit that first detects level of MSTID activity in SuperDARN data and then runs the MSTID MUSIC analysis software on event periods with significant MSTIDs. DARNtids can run the SuperDARN MUSIC algorithm automatically on thousands\  individual analysis periods. Both PyDARN-MUSIC and DARNtids use pickle files for storing Python objects\  byte streams. Pickle files are fragile and cannot be easily manipulated and used on modern systems. They are specific to Python, produce massive serialized values, and are slower than alternative options. As result, both repositories have experienced software engineering challenges related to portability, interoperability, testability, and maintainability, thereby forcing runs to take significantly longer than necessary, data to be stored inefficiently, and the debugging process to be difficult. We present the methodology taken to seamlessly replace dependencies on pickle files in PyDARN-MUSIC and DARNtids integrating the Hierarchical Data Format Version 5 (HDF5) file format and library. We further discuss validation techniques via the newly implemented PyDARN-MUSIC test suite to ensure numerical data accuracy between existing pickle file results and new HDF5 result.

}, author = {Nicholas Guerra and James Fox and Thomas Pisano and Michael Molzen and Nathaniel Frissell and Paul Jackowitz and Joseph B. H. Baker and J. Michael Ruohoniemi} } @proceedings {972, title = {Investigating January 2016 Traveling Ionospheric Disturbance Causes with SuperDARN}, year = {2025}, month = {03/2025}, publisher = {HamSCI}, address = {Newark, NJ}, abstract = {

Medium-Scale Traveling Ionospheric Disturbances (MSTIDs) are quasi-periodic variations of F-region ionospheric densities that are most often associated with atmospheric gravity waves (GWs) generated in the lower neutral atmosphere. The ionospheric variations caused by MSTIDs can focus and defocus HF radio signals, propagating through the ionosphere, thereby causing changes in the range at which these radio signals are refracted back to Earth. Using this principle, high frequency radars such as those in the Super Dual Auroral Radar Network (SuperDARN) can be used to observe MSTIDs. The SuperDARN MSTID Multiple Signal Classification (MUSIC) Algorithm can be used to determine the period, wavelength, speed, and direction of propagation of the observed MSTIDs. We present SuperDARN observations over the North American continent for the period of 11-16 January 2016 as shown in Vadas et. Al. 2024. \ This period is known to be important in terms of the polar vortex generating GWs that seed MSTID activity through multi-step vertical coupling processes. A period of low MSTID activity is observed from 11-13 January followed by a period of elevated MSTID activity from 14-16 January, which is observed across multiple radar fields of view. For this period of interest, an Investigation of MUSIC{\textquoteright}s radar-by-radar reports of observed MSTID parameters including direction of propagation, speed, and period and their comparison to polar vortex activity level observation is also presented.\ 

}, author = {Michael Molzen and Nathaniel Frissell and Sharon Vadas and Lynn Harvey} } @proceedings {936, title = {Ionospheric Variability{\textquoteright}s Impact on HF Propagation: Insights from Grape V1 Doppler Residuals and PHaRLAP Ray Tracing}, year = {2025}, month = {03/2025}, publisher = {HamSCI}, address = {Newark, NJ}, abstract = {

This study investigates the impact of ionospheric variability on HF (3-30 MHz) skywave propagation, a critical aspect of long-range radio communication. Using a dedicated HamSCI Grape V1 low-IF receiver (K2MFF) at NJIT, we analyze long-term Doppler residual measurements of the 10 MHz WWV signal from Fort Collins, CO. Our observations reveal a strong correlation between stable daytime propagation and a Cauchy distribution of Doppler residuals, while sporadic nighttime conditions align more with a combination of exponential power and log-normal statistics. This pattern is consistent across our dataset, barring dates of atypical solar irradiance on the ionosphere, such as during high-class solar flares and solar eclipses. We compare these findings with PHaRLAP ray-tracing simulations using an IRI ionosphere model, allowing us to visualize the signal{\textquoteright}s ray path and pinpoint the ionospheric altitudes (100-400 km) responsible for observed features. Raytracing results attribute daytime signal stability to a superposition of multi-hop modes, while nighttime oscillations linked to TIDs are measurable due to 1-hop dominance. By examining diurnal variations in Doppler residuals, this work provides amateur radio operators with a better understanding of ionospheric dynamics and their impact on HF communication, ultimately contributing to improved prediction of propagation conditions and more effective use of the HF spectrum. Additionally, this work provides a foundation for interpreting real-time propagation data and understanding the effects of solar activity and ionospheric variations on signal quality and reliability for amateur radio communication.

}, author = {Sabastian Fernandes and Gareth Perry and Tiago Trigo and Nathaniel Frissell and John Gibbons} } @proceedings {648, title = {Introducing Undergraduates to Research Through Solar Flares, Python, and Amateur Radio}, year = {2022}, month = {03/2022}, publisher = {HamSCI}, address = {Huntsville, AL}, abstract = {
In an effort to introduce research and scientific writing earlier to physics and engineering undergraduate students, we designed a Space Physics Project in Fall of 2021 to add to Foundations of Physics and Engineering at the University of Scranton. To complete the project, students worked with data from the Geostationary Operational Environmental Satellite (GOES) spacecraft, as well as amateur (ham) radio data collected by Reverse Beacon Network (RBN, reversebeacon.net) and the Weak Signal Propagation Reporting Network (WSPRNet, wsprnet.org).
}, author = {Rachel (Umbel) Frissell and Nathaniel Frissell and Nicholas Truncale} } @conference {53, title = {The Ionosphere{\textquoteright}s Pocket Litter: Exploiting Crowd-Sourced Observations}, booktitle = {Fall AGU - Oral Presentation}, year = {2015}, month = {12/2015}, publisher = {American Geophysical Union}, organization = {American Geophysical Union}, address = {San Francisco, CA}, abstract = {

One of the biggest challenges faced in developing and testing our understanding of the ionosphere is acquiring data that characterizes the latitudinal and longitudinal variability of the ionosphere. While there are extensive networks of ground sites that sample the vertical distribution, we have rather poor coverage over the oceans and in parts of the southern hemisphere. Our ability to validate the ionospheric models is limited by the lack of point measurements and those measurements that essentially constitute characterization of horizontal gradients. In this talk, we discuss and demonstrate the use of various types of crowd-sourced information that enables us to extend our coverage over these regions. We will discuss new sources of these data, concepts for new experiments and the use of these data in assimilative models. We note that there are new, low cost options for obtaining data that broaden the participation beyond the aeronomy/ionospheric community.

}, author = {Ethan S. Miller and Nathaniel Frissell and Stephen Kaeppler and Robert Demajistre and Andrew Knuth} }