Analysis of IR-bright regions of Jupiter in JIRAM-Juno data: Methods and validation of algorithms
Creators
- 1. Istituto di Astrofisica e Planetologia Spaziali – Istituto Nazionale di Astrofisica, Rome (Italy)
- 2. Institute of Cosmic Research, Russian Academy of Sciences, Moscow (Russian Federation)
- 3. Dipartimento di Fisica e Astronomia, University of Bologna (Italy)
- 4. Istituto di Scienze Atmosferiche e del Clima, Consiglio Nazionale delle Ricerche, Sede di Bologna (Italy)
- 5. Departamento de Fisica, Universidad de Atacama, Copiapò (Chile)
- 6. Istituto di Scienze Atmosferiche e del Clima, Consiglio Nazionale delle Ricerche, Sede di Roma (Italy)
- 7. Agenzia Spaziale Italiana, Sede di Matera (Italy)
- 8. Department of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, Michigan (United States)
- 9. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA (United States)
Description
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 (H2O, 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 H2O vapor relative humidity as well as the total aerosol opacity. Limitations related to the approximations of forward model methods are also assessed quantitatively.
Availability note (English)
Available from http://dx.doi.org/10.1016/j.jqsrt.2017.08.008Additional details
Identifiers
- DOI
- 10.1016/j.jqsrt.2017.08.008;
- PII
- S0022-4073(17)30293-5;
Publishing Information
- Journal Title
- Journal of Quantitative Spectroscopy and Radiative Transfer
- Journal Volume
- 202
- Journal Page Range
- p. 200-209
- ISSN
- 0022-4073
- CODEN
- JQSRAE
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 49049512
- Subject category
- S46: INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; S73: NUCLEAR PHYSICS AND RADIATION PHYSICS;
- Descriptors DEI
- ALGORITHMS; AMMONIA; COMPUTER CODES; HUMIDITY; JUPITER PLANET; MIXING RATIO; OPACITY; PHOSPHORUS HYDRIDES; SCALE HEIGHT; SIMULATION; SPECTRA; THERMAL RADIATION; WATER VAPOR
- Descriptors DEC
- DIMENSIONLESS NUMBERS; DIMENSIONS; ELECTROMAGNETIC RADIATION; FLUIDS; GASES; HEIGHT; HYDRIDES; HYDROGEN COMPOUNDS; MATHEMATICAL LOGIC; MOISTURE; NITROGEN COMPOUNDS; NITROGEN HYDRIDES; OPTICAL PROPERTIES; PHOSPHORUS COMPOUNDS; PHYSICAL PROPERTIES; PLANETS; RADIATIONS; VAPORS
Optional Information
- Copyright
- Copyright (c) 2017 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.