Ares: A retrieval framework Mars model for ExoMars Trace Gas Orbiter NOMAD solar occultation measurements
- 1Imaging Group, Mullard Space Science Laboratory, Department of Space and Climate Physics, University College London, London, UK. Email: george.cann.15@ucl.ac.uk.
- 2Department of Physics and Astronomy, University College London, London, UK.
Abstract
Ares is a novel retrieval framework system, designed for the European Space Agency's (ESA) Trace Gas Orbiter (TGO) Nadir and Occultation for MArs Discovery (NOMAD) instrument, Solar Occultation (SO) channel. Ares provides unique insights into the chemical composition of the Martian atmosphere by applying methods utilised in exoplanetary atmospheric retrievals[1][2]. This insight may help unravel the nature of CH4 on Mars. The Ares model is here described including; the NOMAD SO channel instrument function model, Martian atmospheric molecular absorption cross-sections, geometry models and a NOMAD noise model. Ares atmospheric priors and forward models are presented, (i.e. simulated NOMAD observations), and are analysed, compared and validated against NASA’s Planetary Spectrum Generator (PSG)[3].
Introduction
In 2003, methane, CH4, was tentatively detected in the Martian atmosphere, at 10±5ppbv, varying by 0-30ppbv globally[4], and 10±3ppbv[5]. CH4 has, at most, a predicted photochemical lifetime of 300 years[6][7], the short lifetime of CH4 in the Martian atmosphere implies that CH4 should be uniformly distributed over Mars. However, non-uniform distributions have been observed[8]. This raises questions with regard to the source(s) and/or sink(s) of CH4. Abiotic and biotic sources have been suggested to explain the detection, ranging from Fischer-Tropsch-type (FTT) reactions[9] to methanogenesis by methanogenic archaea[10].
The NOMAD instrument[11][12], on-board the ESA’s Exomars TGO was designed to investigate the nature of methane, on Mars[13][8]. However, the arrival of the TGO and subsequent science mission has detected no CH4, with an upper limit of 0.05ppbv above 5km[14]. In contrast, NASA’s Curiosity Sample Analysis at Mars Tunable Laser Spectrometer instrument (SAM-TLS)[15] has made multiple measurements of CH4, including measuring an elevated CH4 background of 7.2±2.1ppbv CH4 over a 60-sol period in 2013[16]. Subsequently, using SAM-TLS, a mean CH4 abundance of 0.41±0.16ppbv was determined, as well as a repeatable seasonal variation from 0.24-0.65ppbv[17]. Moreover, on the 20th June 2019 a 19.5±0.18ppbv CH4 emission in Gale Crater was reported by SAM-TLS [18]. Furthermore, the Planetary Fourier Spectrometer (PFS)[19] on-board Mars Express detected 15.5±2.5ppbv of CH4, above Gale Crater on 16th June 2013, one day after SAM-TLS independently detected a CH4 spike of 5.78±2.27ppbv[20]. Since then PFS has detected no CH4[21].
The discrepancy between surface measurements by SAM-TLS and orbital measurements from NOMAD and PFS, combined with the independent confirmation of detection of CH4 by PFS, significantly constrains the mechanisms to corroborate the measurements. Here we present a novel retrieval framework model, Ares, designed for TGO NOMAD SO channel solar occultation measurements. Ares provides a unique insight into the Martian atmosphere by applying methods utilised in exoplanetary atmospheric retrievals. This insight could help unravel the nature of CH4 on Mars.
Methods
Ares is the Mars version of TauREx3[2], the 3rd generation of TauREx[1] (Tau Retrieval for Exoplanets). TauREx3 is a fully Bayesian atmospheric retrieval framework that uses Nested Sampling[22][23], and Markov chain Monte Carlo methods to sample the full likelihood space of possible solutions. This allows TauREx3 to produce marginalised and conditional posterior distributions of forward model parameters, which can be used to map correlations between these parameters. This is advantageous over other planetary atmospheric retrieval frameworks that only find the maximum-a-posteriori (MAP) solution through Optimal Estimation[24].
A NOMAD SO channel blaze function, acousto-optic tunable filter (AOTF) module has been incorporated into the Ares forward model. Furthermore, Martian ellipsoidal and spherical geometry modules have been included in order to calculate the atmospheric layer line-of-sight (LOS) intersection points and corresponding path lengths[25]. A Mars Climate Database (MCD) Python library, pymcd, has been written and linked to Ares, providing access to Martian vertical temperature, pressure and volume-mixing-ratio (VMR) profiles[26][27]. Moreover, Martian absorption cross-sections have been generated using HITRAN2016[28], accounting for expected Martian pressures, temperatures and CO2 broadening, due to the CO2-rich Martian atmosphere. Overall this enables Ares to produce simulated NOMAD SO channel transmission spectra.
Results
In order to validate Ares, the Ares forward model has been compared against output from NASA’s PSG[3]. The PSG is an online radiative transfer suite capable of synthesising Martian NOMAD SO channel spectra. Like Ares, the PSG extracts atmospheric priors from the MCD[26][27]. Ares Martian transmittance spectra, simulated using NOMAD observation metadata, compared against the PSG are shown to be in strong agreement, through running Ares and PSG forward models with mutual input variables, for wavenumber range 3011-3035cm-1, i.e. NOMAD SO channel diffraction order 134.
Figure 1: A schematic diagram of the TGO, Martian atmospheric layers and corresponding Ares posterior distributions, mapping correlations between atmospheric parameters, for diffraction order 134, at three tangent heights, in the lower, middle and upper atmosphere.
Conclusions
This research has described a novel retrieval framework, Ares, the Mars version of TauREx3[2], designed for TGO NOMAD SO channel solar occultation measurements. The Ares forward model can simulate NOMAD spectra, including instrumental effects due to the blaze function, AOTF, as well as AOTF temperature dependence. In this research Ares has been applied to simulate and perform self-retrieval of typical Martian mixing ratio concentration vertical profiles of CH4, H2O, and CO2. Simulated Ares and PSG NOMAD SO channel solar occultation observations have been compared and are in strong agreement, with marginalised and conditional posterior distributions subsequently generated. Showing that Ares offers a new method of research in Martian and solar system atmospheric science.
Acknowledgements
We would like to thank the UK Space Agency for their support of this Aurora Science studentship STFC:535385. We would also like to thank BIRA-IASB for providing test NOMAD spectra, in particular Ian Thomas for help in understanding the intricacies of NOMAD. Finally, we would like to thank the LMD and Ehouarn Millour for help in providing the MCDv5.3.
References
1.Waldmann et al.(2015),ApJ.[https://doi.org/10.1088/0004-637X/802/2/107].
2.Al-Refaie et al.(2019),Submitted to ApJ.[https://arxiv.org/pdf/1912.07759.pdf].
3.Villanueva et al.(2018),JQSRT.[https://doi.org/10.1016/j.jqsrt.2018.05.023].
4.Formisano et al.(2004),Science.[https://doi.org/10.1126/science.1101732].
5.Krasnopolsky et al.(2004),Icarus.[https://doi.org/10.1016/j.icarus.2004.07.004].
6.Summers et al.(2002),GRL.[https://doi.org/10.1029/2002GL015377].
7.Lefèvre and Forget(2009),Nature.[https://doi.org/10.1038/nature08228].
8.Mumma et al.(2009),Science.[https://doi.org/10.1126/science.1165243].
9.Morozova et al.(2007),Orig.Life.Evol.Biosph.[https://doi.org/10.1007/s11084-006-9024-7].
10.Allen et al.(2006),Eos.[https://doi.org/10.1029/2006EO410001].
11.Vandaele et al.(2015),Planet.SpaceSci.[https://doi.org/10.1016/j.pss.2015.10.003].
12.Robert et al.(2016),Planet.SpaceSci.[https://doi.org/10.1016/j.pss.2016.03.003].
13.Liuzzi et al.(2019),Icarus.[https://10.1016/j.icarus.2018.09.021].
14.Korablev et al.(2019),Nature.[https://doi.org/10.1038/s41586-019-1096-4].
15.Mahaffy et al.(2012),SpaceSci.Rev.[https://doi.org/10.1007/s11214-012-9879-z].
16.Webster et al.(2015),Science.[https://doi.org/10.1126/science.1261713].
17.Webster et al.(2018),Science.[https://doi.org/10.1126/science.aaq0131].
18.Moores et al.(2019),GRL.[https://doi.org/10.1029/2019GL083800].
19.Formisano et al.(1997),Adv.SpaceRes.[https://doi.org/10.1016/S0273-1177(97)00282-2].
20.Giuranna et al.(2019),Nature-Geoscience.[https://doi.org/10.1038/s41561-019-0331-9].
21.ESA(2019),[http://www.esa.int/Science_Exploration/Human_and_Robotic_Exploration/Exploration/ExoMars/ESA_s_Mars_orbiters_did_not_see_latest_Curiosity_methane_burst].
22.Skilling(2006),Bayesian-Anal.[https://projecteuclid.org/euclid.ba/1340370944].
23.Feroz et al.(2009),MNRAS,[http://dx.doi.org/10.1111/j.1365-2966.2009.14548.x].
24.Rodgers(2000),IMFAS,World-Scientific.
25.Thomas et al.(2018),[http://mars.aeronomie.be/en/exomars/observations/pages/EXM-NO-ICD-AER-00001-iss1rev11-EAICD_NOMAD_181026.pdf].
26.Forget et al.(1999),JGR.[https://doi.org/10.1029/1999JE001025].
27.Millour et al. (2018),[https://www.cosmos.esa.int/documents/1499429/1583871/Millour_E.pdf].
28.Gordon et al.(2016),JQSRT.[https://doi.org/10.1016/j.jqsrt.2017.06.038].
How to cite: Cann, G., Al-Rafaie, A., Waldmann, I., Walton, D., and Muller, J.-P.: Ares: A retrieval framework Mars model for ExoMars Trace Gas Orbiter NOMAD solar occultation measurements, Europlanet Science Congress 2020, online, 21 September–9 Oct 2020, EPSC2020-433, https://doi.org/10.5194/epsc2020-433, 2020