@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 {471, title = {INVITED SCIENTIST TUTORIAL: Midlatitude Ionospheric Physics}, year = {2021}, month = {03/2021}, publisher = {HamSCI}, address = {Scranton, PA (Virtual)}, abstract = {
Abstract:\ The midlatitude portion of the ionosphere is located roughly between 30{\textdegree} and 60{\textdegree} magnetic latitude, where the vast majority of radio amateurs operate. The midlatitude ionosphere has historically been considered less {\textquoteleft}active{\textquoteright} than the high-latitude auroral regions or the low-latitude equatorial zone and has received less scientific attention. However, the bulk of humanity lives at these latitudes and major vulnerabilities to space weather disturbance are found there. Some will be well-known to radio amateurs operating HF communications links. Increased interest in the midlatitude ionosphere has spurred the deployment of new observational facilities such as the midlatitude component of SuperDARN and the Personal Space Weather Station. In this tutorial, Dr. Ruohoniemi will present a review of the physics of the midlatitude ionosphere, discuss recent advancements and open questions at the frontiers of research, and consider means by which the amateur radio community can contribute to advancing scientific understanding and technical capabilities.
Bio:\ Dr. J. Michael Ruohoniemi is a professor of electrical engineering at Virginia Tech and Principal Investigator of the\ Virginia Tech Super Dual Auroral Radar Network (SuperDARN) Laboratory. Dr. Ruohoniemi earned his B.S. from the University of King{\textquoteright}s College and Dalhousie University, Nova Scotia in 1981 and his Ph.D. from the University of Western Ontario in 1986. After graduation he joined the team at the Johns Hopkins University Applied Physics Laboratory that developed HF radar into the SuperDARN concept to study the auroral (high-latitude) ionosphere. As a faculty member at Virginia Tech, he led a consortium of universities in building a chain of SuperDARN radars at midlatitudes across the U.S. His scientific publications now have over 9,700 citations. Today, 12 of the more than 30 radars in the SuperDARN network make continuous observations of the midlatitude ionosphere in both hemispheres, and these observations have been instrumental in advancing midlatitude ionospheric science in numerous studies.
}, author = {J. Michael Ruohoniemi} }