Authors: Christina Kay (JHU APL)

Remote imaging of the Sun, corona, and interplanetary space allow us to observe  structures as they develop and how they propagate out through the heliosphere. Remote imaging instruments observe sunlight scattered off the electrons within these dynamic structures. This approach inherently loses information about the 3D structure because the line of sight (LoS) is compressed into 2D images of total brightness per pixel. Some of this information can be recovered using reconstruction techniques.  Often, a graphical user interface (GUI) is used to manually align a wireframe shape with simultaneous images from different satellite viewpoints.

We present a new fully Python-based GUI, the Wireframe Object Mapped onto Background Alignment Tool (WOMBAT), which functions similarly to existing community tools, but offers more wireframes, additional wireframe shapes, and support for a wider range of observations, including SoloHI and PSP WISPR. Additionally, WOMBAT can calculate the masses enclosed by wireframe objects using basic electron-scattering theory. The Density Inferred from Nice Grid Object (DINGO) routine when used with WOMBAT, derives densities within the wireframe region using 3D wireframe shapes and LoS-integrated masses. These densities can also be extrapolated to expected in situ observations using a basic propagation model. We present WOMBAT and DINGO, including their new user-friendly features, their application to modern missions, and their ability to track mesoscale features to greater distances. WOMBAT and DINGO can facilitate routine mass measurements, thereby improving both space weather forecasting and scientific research.