Data availability and requirements relevant for the Ariel space mission and other exoplanet atmosphere applications

Katy L Chubb*, Séverine Robert, Clara Sousa-Silva*, Sergei N Yurchenko*, Nicole F Allard, Matt G Lodge, et al.

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

1 Citation (Scopus)

Abstract

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.
Original languageEnglish
Pages (from-to)636-690
Number of pages55
JournalRAS Techniques and Instruments
Volume3
Issue number1
Early online date19 Sept 2024
DOIs
Publication statusE-pub ahead of print - 19 Sept 2024

Bibliographical note

Publisher Copyright:
© 2024 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society.

Keywords

  • Data Methods
  • Data needs
  • Numerical methods
  • Algorithms
  • Ariel

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