Typically the solar radio emission at 10.7 cm is used to scale the critical euv radiation that is absorbed by the Earth's neutral atmosphere. In the latter half of 2008 this radio emission from the Sun was at the lowest levels seen in the last 50 years and the persistence of these low levels has never been recorded before. Here we show that these uniquely low levels of solar radiation produce similarly unique behavior in the Earth's ionosphere and the upper atmosphere. Most remarkably, the altitude extent of the ionosphere is significantly smaller than our present reference models would predict for these levels of solar activity. The transition height resides near 450 km at night and rises to only 850 km during the daytime. At night, this unusually contracted ionospheric shell around the equator has a temperature of only 600 K and prior to sunrise the ion number densities at the transition height fall below 10⁴ cm⁻³.

Computational analysis has become ubiquitous within the heliophysics community. However, community standards for peer review of codes and analysis have lagged behind these developments. This absence has contributed to the reproducibility crisis, where inadequate analysis descriptions and loss of scientific data have made scientific studies difficult or impossible to replicate. The heliophysics community has responded to this challenge by expressing a desire for a more open, collaborative set of analysis tools. This article summarizes the current state of these efforts and presents an overview of many of the existing Python heliophysics tools. It also outlines the challenges facing community members who are working toward the goal of an open, collaborative, Python heliophysics toolkit and presents guidelines that can ease the transition from individualistic data analysis practices to an accountable, communalistic environment.

The International Reference Ionosphere (IRI) model is widely used in the ionospheric community and considered the gold standard for empirical ionospheric models. The development of this model was initiated in the late 1960s using the FORTRAN language; for its programming approach, the model outputs were calculated separately for each given geographic location and time stamp. The Consultative Committee on International Radio (CCIR) and International Union of Radio Science (URSI) coefficients provide the skeleton of the IRI model, as they define the global distribution of the maximum useable ionospheric frequency foF2 and the propagation factor M(3,000)F2. At the U.S. Naval Research Laboratory, a novel Python tool was developed that enables global runs of the IRI model with significantly lower computational overhead. This was made possible through the Python rebuild of the core IRI component (which calculates ionospheric critical frequency using the CCIR or URSI coefficients), taking advantage of NumPy matrix multiplication instead of using cyclic addition. This paper explains in detail this new approach and introduces all components of the PyIRI package.