Juno/Waves estimated flux density Collection (Version 01)

A new version of this dataset is available at: https://doi.org/10.25935/fwtq-v202

• DOI: https://doi.org/10.25935/6jg4-mk86
• Publisher: PADC/MASER
• License: CC-BY 4.0
• Citation: Louis, C. K., P. Zarka and B. Cecconi (2021). Juno/Waves estimated flux density Collection (Version 01) [Data set]. PADC. https://doi.org/10.25935/6jg4-mk86

Link to data repository

• Access to data

How to display the data

To display this dataset easily, we recommend using the Autoplot software (Faden et al., 2010). Once the software is installed, just load the juno-waves-flux_density_v01.vap file by doing `File>Open .vap file...’

Description

This datasets contain the Juno/Waves estimated flux density based on Cassini/RPWS measurements at Jupiter.

How are the flux density estimated?
The steps to derive the flux density are the following :

• Use times series from PDS data in linear scale
• Apply FFT filtering to remove interferences
• Subtract a background (calculated from dB values) in linear scale
• For LFR and HFR-High sub-receivers:
  • Correct for 1/R² dependence
  • Select data intervals of 4 consecutive Jovian rotation with 15° < Latitude_magnetic < 15° and Distance > 30 R_J (same configuration than Cassini)
  • Build median 1% and 50% occurrence spectra and match with Cassini-RPWS and Voyager-PRA ones (Zarka 1992, Zarka et al. 2004) to derive a gain table between 3.5 kHz and 40.5 MHZ.
  • Extrapolate the gains down to 1 kHz
• For the HFR-Low sub-receiver:
  • No 1/R² dependence correction
  • Select data acquired during the ±2 hours around perijoves (when signal is observed by this sub-receiver)
  • Use the continuity of the signal between the LFR-High, HFR-Low and HFR-High sub-receiver to determine the HFR-Low gains.

Once the gains have been obtain, the steps to estimate the density flux are the following :

• Use PDS data in linear scale, resample to 1 second
• Apply an FFT-filtering by selecting the first eight harmonic of the spacecraft spin—period, with a width of δf=7% of the frequency around the peaks
• Apply the gains of Table 1 (3^rd row) which gives local-estimated flux densities
• Optionally, correct for 1/R² dependence to normalize the flux to a constant distance. This should not be done e.g. when studying local wave Electric-field, but should be done when studying the statistical latitudinal distribution of the radio beaming, as in the Louis et al. (2021) study.
• Optionally subtract the time-independent background in linear scale of Table 1 (4^th row)

A complete description of the methodology used to estimate the flux density can be found in Louis et al. (2021 doi).

List of Datasets

• IDL save files
  • dataset at a temporal resolution of 1 second or 15 seconds containing the estimated flux density data with the intensity values in linear (ZLINCAL variable)
• CDF files
  • dataset at a temporal resolution of 1 second, containing the estimated flux density data with the intensity values in linear (data variable), the gain, the background and the background standard deviation values.
• Quicklook
  • Daily Dynamic spectrums in pdf and png format.

Rules of use

• We kindly request the authors of any communications and publications using these data to let us know about them, include minimal citation to the reference below and appropriate acknowledgements whenever needed.
• References: Louis et al. (2021, doi)
• Acknowledgements: see the acknowledgement field

Link to the data at PDS

• PDS data access

Acknowledgements
The MASER Juno/Waves CDR collection has been calculated by C. Louis, P. Zarka, K. Dabidin, P.-A. Lampson, F. Magalhaes, A. Boudouma, M. Marques and B. Cecconi. The authors acknowledge the Observatoire de Paris, CNES, CNRS for funding and supporting this work and B. Kurth and the University of Iowa and the Juno/Waves team for providing access to the Juno/Waves data accessible online from PDS at https://doi.org/10.17189/1519708. The authors thank J. Faden and C. Piker for their work on the Autoplot software.

BC was also supported by PADC and EPN2024-RI. The Europlanet 2024 Research Infrastructure (EPN2024-RI) project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871149.

Contact
Any question or request should be addressed to contact.maser@obspm.fr

Appendix

References

• Faden, J.B., Weigel, R.S., Merka, J. et al. Autoplot: a browser for scientific data on the web. Earth Sci Inform 3, 41–49 (2010), doi: 10.1007/s12145-010-0049-0.
• Kurth, W.S., and Piker C.W., JUNO E/J/S/SS WAVES CALIBRATED SURVEY FULL RESOLUTION V2.0, JNO-E/J/SS-WAV-3-CDR-SRVFULL-V2.0, NASA Planetary Data System, 2022, doi: 10.17189/1520498.
• Louis, C. K., Zarka, P., Dabidin, K., Lampson, P.-A., Magalhães, F. P., Boudouma, A., et al. (2021). Latitudinal beaming of Jupiter’s radio emissions from Juno/Waves flux density measurements. Journal of Geophysical Research: Space Physics, 126, e2021JA029435, doi: 10.1029/2021JA029435.
• Zarka, P. (1992). The auroral radio emissions from planetary magnetospheres: What do we know, what don’t we know, what do we learn from them? Advances in Space Research, 12(8), 99–115, doi: 10.1016/0273-1177(92)90383-9.
• Zarka, P., Cecconi, B., & Kurth, W. S. (2004). Jupiter’s low-frequency radio spectrum from Cassini/Radio and Plasma Wave Science (RPWS)
  absolute flux density measurements. Journal of Geophysical Research, 109, A09S15, doi: 10.1029/2003JA010260.