Jupiter radio emission probability tool

Jupiter is a source of intense radio emissions in the decametric wavelength range observable from ground (above ∼10 MHz) and from space (down to a few kHz). The strong anisotropy of the Jovian radio sources results in characteristic shapes in the temporal-spectral domain, which can be used to identified the various types of Jovian radio components. The Jupiter Probability Tool provides users with Jovian radio emission observability predictions, depending on the observers location, and the radio emission class. The application can be used for observation planning or data analysis for ground or space observations.


Introduction
Jupiter low frequency radio emissions have been studied since their discovery (Burke and Franklin, 1955), with ground (from 10 to 40 MHz) and space observatories (down to a few kHz), the ground based observations being limited by the ionospheric cutoff at ∼10 MHz. The Jovian radio spectrum displays several components, which can be identified in dynamic spectra (time series of spectra), thanks to their temporal-spectral arc-shaped characteristic features (see, e.g.: Zarka, 2000;. Moreover, a subset of Jovian radio components are driven by the interaction between the Jovian magnetic field and the Galilean moons, specifically with the moon Io (Bigg, 1963), but also with Europa and Ganymede (Louis et al., 2017a;Zarka et al., 2018a). The arc-shaped temporal-spectral geometry is a consequence of the radio emission mechanism, which produces a strongly anisotropic beaming pattern. Hence the observer's location is a key parameter for prediction the observability of Jovian radio emissions. Jupiter observation probability maps have been produced with the first published catalogues (see e.g.: Bigg, 1963;Leblanc et al., 1981), relating the observer's longitude in the Jovian System III frame (Higgins et al., 1997) and the phase of Io.
Planning or analysing Jupiter radio observations thus requires to know the observation geometry: observation date, observer's location and phase of the Jovian moons. In this article, we present an online application providing the probability of observing Jovian radio components depending on the observation and Jovian system geometries.

Use cases and requirements
The first use case is the analysis of a Jupiter low frequency radio observation. As presented in the introduction section, the interpretation of Jupiter radio emission observations requires an detailed knowledge of the geometry of the Jovian system, together with the observer's location. The observation configuration shall be displayed in a two-dimensional diagram with axes being (a) the longitude of the observer (usually in Jupiter system III longitude) also known as "Central Meridian Longitude" (or CML), and (b) the selected Moon phase with respect to the observer. Such a diagram is referred to as a "Phase-CML" map. Many Phase-CML maps have been published (see, e.g., Leblanc et al., 1981;Marques et al., 2017;Zarka et al., 2018a). Comparing the selected observation configuration with Phase-CML maps greatly facilitates the Jupiter decametric radio emission observation interpretation. A second critical aspect of the Jovian radio emissions is their shape in the temporal-spectral domain. Comparing the observed shape with predicted ones would also strengthen the scientific interpretation (see, e.g., Louis et al., 2017b).
The second use case is the preparation of a Jupiter low frequency radio observation. The same geometry configuration display against Phase-CML maps allows to select observation times with higher probability of detecting the studied radio component. Furthermore, in order to prepare a ground based observation, the knowledge of Jupiter's elevation as seen from the observer's location is also required.
A series of design requirements has been derived from the two use cases.
• Time range: The observation time (or time range) shall be configurable. • Predefined observer: Space missions with a low frequency instrument (e.g., Cassini, Juno, Wind, STEREO-A, STEREO-B, Galileo...), as well as major ground based low frequency radio observatories (e.g., Long Wavelengths Array, Nançay Decameter Array...) shall be easily configurable. • Custom ground-based observer: For ground based observation, it shall be possible to set the location of an observatory (e.g., for radio amateur observatories). • Jovian Moon Control: In the recent studies of Jovian radio emissions, Europa and Ganymede controlled radio emissions have been reported (Louis et al., 2017a;Zarka et al., 2018a) in addition to the long-studied Io-controlled emissions. Control by Callisto and Amalthea are also mentioned in some publications (Marques et al., 2017;Zarka et al., 2018a). The interface shall allow users to select the moon of interest (i.e., Io, Europa, Ganymede, Callisto and Amalthea). • Phase-CML maps: The various published probability or occurrence Phase-CML maps shall be available for comparison , which includes Phase-CML maps from Leblanc et al. (1993)

Existing tools
We have identified a set of existing tools serving the identified needs (observation planning and observation interpretation).

Nançay decameter array probability maps
The Nançay Decameter Array (NDA, Lamy et al., 2017) is a phased array located in Nançay Radioastronomy Observatory (ORN), routinely observing Jupiter and the Sun. In addition to the data products 1 , the NDA team is providing its users with a series of monthly Io Phase-CML probability maps, as well as the time of the Jupiter transit at the observer's location, as shown in Figure 1.

Radio jupiter pro
The Radio Sky Publishing 2 team developed tools to help the preparation of Jupiter radio observation, in the frame of the RadioJOVE citizen science project (Thieman et al., 2006;Fung et al., 2020). The Radio Jupiter Pro application 3 specifically provides Io Phase-CML probability map, plots indicating the elevation of Jupiter

Jupiter radio map
Jupiter Radio Map 4 is a java based application providing the Jovian radio observation probability, in an Io Phase-CML map. This application has been developed by a Japanese team (Kochi National College of Technology, Kochi). The tool displays an Io Phase-CML map, overlaid with the trace of the observational geometry, as selected on the user interface. It also used to be published as an iOS application.

ExPRES
The ExPRES (Exoplanetary and Planetary Radio Emission Simulator, Louis et al., 2019) is a radio observation modeling code dedicated to planetary radio emissions. It allows to construct dynamic spectra predictions, for an observation geometry and a set of radio emission conditions.

Online application
The "Jupiter Probability Tool" application has been designed following the requirements presented in Section 2. The tools cited in Section 3 are already implementing part of project requirements. Hence, our application's graphical user interface implements some interface features found in existing tools (e.g., the location of Jupiter on the Phase-CML map, similarly to the Radio Jupiter Pro tool, as shown in Figure 2). However, since the previous tools are not open source, none of their code have been reused. 4 Jupiter Radio Map: http://jupiter.kochi-ct.jp/jrm/ The application is using the SPICE kernel system (Acton et al., 2018) for computing observational and planetary ephemerides. It also displays contextual data, when available, such as observational data (e.g., from the NDA database) and pre-computed modeled data from the ExPRES modeling tool.
The application has been developed as a joint project between the MASER (Measuring, Analysing and Modeling of Emissions in the Radio range) service , and the NDA team (Lamy et al., 2017), with support of PADC (Paris Astronomical Data Centre). Figure 3 shows a screenshot of the tool user interface. The tagged elements of this interface are described in Table 1. The online Jupiter Probability Tool application  is currently available at: https://jupiter-probability-tool.obspm.fr.

Development details
The application is developed in python, using the flask 5 web development library (Grinberg, 2018). The Solar System bodies and spacecraft ephemerides are retrieved using the python-webgeocalc 6 library, accessing a dedicated WebGeoCalc server (Acton et al., 2018) installed at the Observatoire de Paris. That server is configured to serve locally SPICE kernels for NASA, ESA and JAXA space mission. The NDA Jupiter data are retrieved using the das2 (Piker, 2017) protocol, connecting to a das2 server implemented and maintained by the Nançay Data Centre (CDN), at the Nançay Radio Observatory (ORN). The ExPRES simulation runs are retrieved from a local  Table 1. server as CDF 7 files, and are accessed using the spacepy. PyCDF (Niehof et al., 2022) module. The application also uses the Pillow 8 , numpy (Harris et al., 2020), astropy (The Astropy Collaboration et al., 2018), matplotlib (Hunter, 2007) and sqlalchemy (Bayer, 2012).

Ephemerides computation
The observational geometry is computed in a two-step process. First the location of the observer is retrieved with a STATE_VECTOR query to the WebGeoCalc server, using the LATITUDINAL representation (providing latitude, longitude and distance in the selected frame), the IAU_JUPITER reference frame, and the aberration correction set to CN + S (see WebGeoCalc documentation for details). In the following listings, we assume the timestamp variable is a iterable containing the list of times to be used for computation (list of datetime.datetime objects). The kernels variable contains the list of meta-kernels to be usedfor the current computation. For Earth-based observatories, the Solar System Kernels are selected. For space mission, the specific meta-kernel has to added. Finally, the observer variable contains the observer's name.

Tag
Type Description 1 List Observatory selection: A list of predefined observatories. At the time of writing of the paper, the list of observatories is: NDA (Nançay Decameter Array, Nancay, France), UTR-2 (Kharkiv, Ukraine), Iitate (Japan), LWA (Long Wavelength Array, New Mexico, United States), I-LOFAR (Irish LOFAR station), and the Juno spacecraft. In order to manually enter the location of an observatory, use the "Custom (Earth-based)" entry 2,3,4 Number Observer's coordinates: For ground based observatories, the latitude 1) in degrees, longitude 2) in degrees, and altitude in m above see level of the observatory (automatically filled in upon selection of the predefined observatory) )%360 Listing 2: Second State Vector query to Webgeocalc: computing the moon's Phase.
The Phase of the moon is then: The elevation of Jupiter for ground observatories is retrieved with a STATE_VECTOR call on the WebGeoCalc server, using the RA_DEC representation. The obtained sky coordinates are transformed into altazimuthal coordinates using astropy and the observatory location.

Summary and perspectives
The Jupiter Probability Tool application is a science ready tool for preparing and analysing Jupiter radio observations. It has already been used in several studies. Louis et al. (2021) prepared a series of joint Jupiter decametric observations on three international LOFAR stations (Ireland, France and Germany) using the Jupiter Probability Tool. Lamy et al. (2022a) is a comment on a published paper. The authors made use of the application to support their argumentation. Lamy et al. (2022b) also made use of the application to confirm that the observed emissions were Io-controlled emissions.
A series of improvement and new features are planned for the next versions of the application. Firstly, new observatories shall be implemented, especially space missions with low frequency radio instrumentation, such as, e.g., Cassini; STEREO-A; STEREO-B; WIND; Galileo; JUICE; Voyager 1; Voyager 2; and Mars Express. Improvement of the application to adhere to the FAIR (Findable, Accessible, Interoperable, and Reusable) principles (Wilkinson et al., 2016) are also in preparation. One of the planned feature in this context is the addition of provenance (Servillat et al., 2022) information to the output figures (with the provision of the list of citations to be used if the figures are included in a scientific publication), thus improving the reusability of the application products.

Data availability statement
The code of the application is currently not open (except the lines presented in the paper). The data used in this application are all openly available: ExPRES collection (Louis et al., 2020), NDA Jupiter Routine collection (Lamy et al., 2021), Phase-CML maps , and the Juno SPICE kernel dataset (Semenov et al., 2017).

Author contributions
BC and LL prepared the application requirements. SA developed the application. BC and LL reviewed and commented the application during the development process. BC wrote the first version of the papier. SA and LL commented and proofread the manuscript.

Funding
The work is supported by the Europlanet 2024 Research Infrastructure project, which has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 871149.