Energetic neutral atom (ENA) observations contain useful information about ion and neutral abundances in planetary magnetospheres. They are created when energetic ions interact with a planet's neutral exosphere and transfer their charge onto neutral particles, leaving a neutral particle with the original ion's energy and direction of motion. These particles can be observed remotely, as their motion is no longer determined by the planetary magnetic field. Cassini's Ion and Neutral Camera (INCA) obtained such remote observations of Saturn's magnetosphere for more than a decade. To simplify large-scale analyses of this vast dataset, it is useful to re-bin and re-project all observations into a common reference frame, as the perspective of the imagery varies significantly depending on Cassini's position and attitude. Most ions and neutrals are confined to Saturn's equatorial plane due to the planet's rapid rotation, making this the source region of most ENAs and an ideal common reference frame. We developed an algorithm projecting all of INCA's ENA observations into a regular grid in Saturn's equatorial plane, creating a clean and easy-to-use dataset which can be utilized to investigate the morphology and dynamics of Saturn's ring current. The ring current is directly related to, for example, Saturn's ultraviolet auroral emissions and magnetic reconnection in the nightside magnetosphere. We further performed data cleaning, identifying observations possibly contaminated by sunlight or ions or affected by calibration procedures and bit errors. Both the projected data and a Python routine for loading the data while flagging possible contamination events and returning geometric information will be stored in an open access repository.
This is especially useful for planetary science, where hot plasma from within a magnetosphere interacts with the planet's neutral exosphere to create ENAs, making their remote observation a valuable tool for characterizing the energetic plasma environment within the magnetosphere. An example for this is Saturn, a rapidly rotating gas giant which is surrounded by a ring of hot ions whose dynamics reflect changes in the Magnetospheric environment. Observations of ENAs from Saturn's magnetosphere can hence help understand the occurrence and effects of magnetic reconnection events and their relation to the powerful aurorae above the planet's poles, for example.
Here we compile a dataset of such ENA observations from the entire Cassini mission in order to improve accessibility to the data and stimulate further scientific studies on these topics and others. The original observations are highly heterogeneous, including measurements from various viewing angles and distances depending on Cassini's orbit and plagued by different types of data contamination. We reduce the complexity of the data by projecting all observations onto a regular grid in Saturn's equatorial plane where the majority of the neutral and hot ion populations are confined, as shown on slide 2. Additionally, we identify different sources of data contamination attributable to different causes such as for example instrument malfunction, errors in data transmission and contamination by energetic ion beams passing the detector shielding - an example event of the latter type is shown on slide 4.
The result is a clean set of equatorial projections of ENA observations from the entire Cassini mission, including more than 600,000 single exposures with a total exposure time of more than five years. Only observations from a distance larger than 4 Saturn radii from the equatorial plane were taken into account in order to remove observations obtained from with the ENA source region. The temporal coverage of the available data is best during Cassini's high elevation orbit sections, highlighted in blue on slide 3. The projections cover a square area with a side length of 60 Saturn radii centered on the planet, with a resolution of 2 pixels per Saturn radius. The final data will be made accessible online together with a publication on the processing procedure and with Python code and instructions detailing usage of the files.