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Data availability and requirements relevant for the Ariel space mission and other exoplanet atmosphere applications
HH Wills Physics Laboratory, School of Physics, University of Bristol, Tyndall Avenue, Bristol, United Kingdom; Centre for Exoplanet Science, University of St Andrews, North Haugh, St Andrews, United Kingdom.
Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Av. Circulaire 3, Uccle, Belgium.
Bard College, Institute of Astrophysics and Space Sciences, 30 Campus Rd, NY, Annandale-On-Hudson, United States; Institute of Astrophysics and Space Sciences, Rua das Estrelas, Porto, Portugal.
Department of Physics and Astronomy, University College London, London, United Kingdom.
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2024 (English)In: RAS Techniques and Instruments, E-ISSN 2752-8200, Vol. 3, no 1, p. 636-690Article in journal (Refereed) Published
Abstract [en]

The goal of this white paper is to provide a snapshot of the data availability and data needs primarily for the Ariel space mission, but also for related atmospheric studies of exoplanets and cool stars. It covers the following data-related topics: molecular and atomic line lists, line profiles, computed cross-sections and opacities, collision-induced absorption and other continuum data, optical properties of aerosols and surfaces, atmospheric chemistry, UV photodissociation and photoabsorption cross-sections, and standards in the description and format of such data. These data aspects are discussed by addressing the following questions for each topic, based on the experience of the 'data-provider' and 'data-user' communities: (1) what are the types and sources of currently available data, (2) what work is currently in progress, and (3) what are the current and anticipated data needs. We present a GitHub platform for Ariel-related data, with the goal to provide a go-to place for both data-users and data-providers, for the users to make requests for their data needs and for the data-providers to link to their available data. Our aim throughout the paper is to provide practical information on existing sources of data whether in data bases, theoretical, or literature sources.

Place, publisher, year, edition, pages
Oxford University Press, 2024. Vol. 3, no 1, p. 636-690
Keywords [en]
Algorithms, Ariel, Data Methods, Data needs, Numerical methods
National Category
Astronomy, Astrophysics and Cosmology
Identifiers
URN: urn:nbn:se:umu:diva-232169DOI: 10.1093/rasti/rzae039Scopus ID: 2-s2.0-85209083442OAI: oai:DiVA.org:umu-232169DiVA, id: diva2:1916518
Funder
EU, Horizon 2020, 883830EU, Horizon Europe, EP/Y006313/1Knut and Alice Wallenberg Foundation, (KAW 2020.0303Swedish Research Council, 2020-00238German Research Foundation (DFG)EU, Horizon 2020, 860470German Research Foundation (DFG), SA 4483/1-1German Research Foundation (DFG), DFG PR 36 24602/41EU, European Research Council, 101053033Available from: 2024-11-27 Created: 2024-11-27 Last updated: 2024-11-27Bibliographically approved

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Foltynowicz, Aleksandra

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