Analysis of IR-bright regions of Jupiter in JIRAM-Juno data: Methods and validation of algorithms

被引:8
|
作者
Grassi, D. [1 ]
Ignatiev, N. I. [2 ]
Sindoni, G. [1 ]
d'Aversa, E. [1 ]
Maestri, T. [3 ]
Adriani, A. [1 ]
Mura, A. [1 ]
Filacchione, G. [1 ]
Dinelli, B. M. [4 ]
Noschese, R. [1 ]
Cicchetti, A. [1 ]
Piccioni, G. [1 ]
Turrini, D. [1 ,5 ]
Tosi, F. [1 ]
Moriconi, M. L. [4 ]
Olivieri, A. [6 ]
Plainaki, C. [6 ]
Amoroso, M. [6 ]
Atreya, S. K. [7 ]
Orton, G. S. [8 ]
Bolton, S. [9 ]
机构
[1] Ist Nazl Astrofis, Ist Astrofis & Planetol Spaziali, Rome, Italy
[2] Russian Acad Sci, Inst Cosm Res, Moscow, Russia
[3] Univ Bologna, Dipartimento Fis & Astron, Bologna, Italy
[4] CNR, Ist Sci Atmosfer & Clima, Sede Di Bologna, Italy
[5] Univ Atacama, Dept Fis, Copiapo, Chile
[6] Agenzia Spaziale Italiana, Sede Di Matera, Italy
[7] Univ Michigan, Dept Climate & Space Sci & Engn, Ann Arbor, MI 48109 USA
[8] CALTECH, Jet Prop Lab, Pasadena, CA USA
[9] Southwest Res Inst, San Antonio, TX USA
关键词
RADIATIVE-TRANSFER; CLOUD STRUCTURE; ATMOSPHERIC COMPOSITION; MODEL;
D O I
10.1016/j.jqsrt.2017.08.008
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
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 pm 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. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:200 / 209
页数:10
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