The reproducibility crisis was sparked five years ago by a Nature survey that revealed most researchers have tried and failed to reproduce another scientist’s experiments (Baker, 2016). Although the severity of the crisis is still being debated, it has spurred researchers to include reproducibility and open science practices in their work. To that end, the Python in Heliophysics Community (PyHC) encourages members of the heliophysics community to create “executable papers,” which are interactive pieces of software that combine text, data, and code to enable readers to reproduce every step taken to arrive at a publication’s conclusions. We describe the development of an executable paper—in this case, one centered around magnetopause boundary crossings in satellite data—our coordination efforts between scientists and software developers, and the current technology that makes this possible. We aim to promote this novel paper format and be an example to the heliophysics community of how scientists and software developers can work together to produce research that is transparent and reproducible.

We present a methodology to define strong, moderate, and intense space weather events based on probability distributions. We have illustrated this methodology using a long-duration, uniform data set of 1.8-3.5 MeV electron fluxes from multiple LANL geosynchronous satellite instruments but a strength of this methodology is that it can be applied uniformly to heterogeneous data sets. It allows quantitative comparison of data sets with different energies, units, orbits, etc. The methodology identifies a range of times, “events”, using variable flux thresholds to determine average event occurrence in arbitrary 11-year intervals (“cycles”). We define strong, moderate, and intense events as those that occur 100, 10, and 1 time per cycle and identify the flux thresholds that produce those occurrence frequencies. The methodology does not depend on any ancillary data set (e.g. solar wind or geomagnetic conditions). We show event probabilities using GOES > 2 MeV fluxes and compare them against event probabilities using LANL 1.8-3.5 MeV fluxes. We present some examples of how the methodology picks out strong, moderate, and intense events and how those events are distributed in time: 1989 through 2018, which includes the declining phases of solar cycles 22, 23, and 24. We also provide an illustrative comparison of moderate and strong events identified in the geosynchronous data with Van Allen Probes observations across all L-shells. We also provide a catalog of start and stop times of strong, moderate, and intense events that can be used for future studies.