Analysis of IR-bright regions of Jupiter in JIRAM-Juno data: Methods and validation of algorithms. (November 2017)

• Record Type: Journal Article
• Authors: Grassi, D.; Ignatiev, N.I.; Sindoni, G.; d'Aversa, E.; Maestri, T.; Adriani, A.; Mura, A.; Filacchione, G.; Dinelli, B.M.; Noschese, R.; Cicchetti, A.; Piccioni, G.; Turrini, D.; Tosi, F.; Moriconi, M.L.; Olivieri, A.; Plainaki, C.; Amoroso, M.; Atreya, S.K.; Orton, G.S.; Bolton, S.
• Is Part Of: Journal of quantitative spectroscopy & radiative transfer. Volume 202(2017)
• Page Start: 200
• Page End: 209
• Publication Date: 2017-11
• Subjects: Spectrum analysis -- Periodicals; Radiation -- Periodicals; Analyse spectrale -- Périodiques; Rayonnement -- Périodiques; Radiation; Spectrum analysis; Periodicals; 543.0858
• DOI: 10.1016/j.jqsrt.2017.08.008
• Languages: English
• ISSNs: 0022-4073

Abstract

Highlights: A complete retrieval algorithm for the analysis of thermal radiation measured in JIRAM-Juno Jupiter spectra is presented. Code is capable to extract information about mean water vapour relative humidity, ammonia and phosphine mixing ratios and residual opacity in the 5 μm methane transparency window. Approximations in the forward radiative transfer scheme are the main limitations for the present version of the code. Abstract: In this paper, we detail the retrieval methods developed for the analysis of the spectral data from the JIRAM experiment on board of the Juno NASA mission [1], operating in orbit around Jupiter since July 2016. Our focus is on the analysis of the thermal radiation in the 5 µm transparency window in regions of lesser cloud opacity (namely, hot-spots). Moving from the preliminary analysis presented in [2], a retrieval scheme has been developed and implemented as a complete end-to-end processing software. Performances in terms of fit quality and retrieval errors are discussed from tests on simulated spectra, while some example and issue from usage on actual Jupiter data are also discussed. Following the suggestion originally presented in [3] for the analysis of the data from the Near Infrared Mapping Spectrometer (NIMS) on board of the NASA Galileo spacecraft, the state vector to be retrieved has been drastically simplified on physically sounding basis, aiming mostly to distinguish between the 'deep' content of minor gaseous components (H2 O, NH3, PH3 ) and their relative humidity or fractional scale height in the upper troposphere. The retrieval code is based on a Bayesian scheme [4], complemented by simulated annealing method for most problematic cases. The key parameters retrievable from JIRAM individual spectra are the NH3 and PH3 deep contents, the H2 O vapor relative humidity as well as the total aerosol opacity. Limitations related to the approximations of forward model methods are also assessed quantitatively.