Published March 2025 | Published
Journal Article Open

Water in Protoplanetary Disks with JWST-MIRI: Spectral Excitation Atlas and Radial Distribution from Temperature Diagnostic Diagrams and Doppler Mapping

  • 1. ROR icon Texas State University
  • 2. ROR icon Vassar College
  • 3. ROR icon Jet Propulsion Lab
  • 4. ROR icon University of Maryland, College Park
  • 5. ROR icon University of Wisconsin–Madison
  • 6. ROR icon Space Telescope Science Institute
  • 7. ROR icon University of Exeter
  • 8. ROR icon Harvard-Smithsonian Center for Astrophysics
  • 9. ROR icon University of Virginia
  • 10. ROR icon NOIRLab
  • 11. ROR icon University of Arizona
  • 12. ROR icon California Institute of Technology
  • 13. ROR icon University of Michigan–Ann Arbor
  • 14. ROR icon Diego Portales University
  • 15. ROR icon University College London
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Abstract

This work aims at providing fundamental general tools for the analysis of water spectra as observed in protoplanetary disks with JWST-MIRI. We analyze 25 high-quality spectra from the JDISC Survey reduced with asteroid calibrators as presented in K. M. Pontoppidan et al. (2024). First, we present a spectral atlas to illustrate the clustering of H2O transitions from different upper-level energies (Eu) and identify single (unblended) transitions that provide the most reliable measurements. With that, we demonstrate two important excitation effects: the opacity saturation of ortho-para line pairs that overlap, and the subthermal excitation of excitation of v = 1–1 lines scattered across the v = 0–0 rotational band. Second, we define a shorter list of fundamental lines spanning Eu =  1500–6000 K to develop simple line-ratio diagnostic diagrams for the radial temperature distribution of water in inner disks, which are interpreted using discrete temperature components and power-law radial gradients. Third, we report the detection of disk-rotation Doppler broadening of molecular lines, which confirms the radial distribution of water emission including, for the first time, the radially extended ≈170–220 K reservoir close to the snowline. The combination of measured line ratios and broadening suggests that drift-dominated disks have shallower temperature gradients with an extended cooler disk surface enriched by ice sublimation. We also report the first detection of an H2O-rich inner disk wind from narrow blueshifted absorption in the ro-vibrational lines. We summarize these findings and tools into a general recipe to make the study of water in planet-forming regions reliable, effective, and sustainable for samples of >100 disks.

Copyright and License

© 2025. The Author(s). Published by the American Astronomical Society.

Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

Acknowledgement

We thank the referee for providing multiple suggestions that improved the clarity and usefulness of this work. This work includes observations made with the NASA/ESA/CSA James Webb Space Telescope. The JWST data used in this paper can be found in MAST: 10.17909/7w5s-f430. The data were obtained from the Mikulski Archive for Space Telescopes at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-03127 for JWST. The observations are associated with JWST GO Cycle 1 programs 1549, 1584, and 1640. Part of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004). The authors acknowledge support from NASA/Space Telescope Science Institute grants: JWST-GO-01640, JWST-GO-01584, and JWST-GO-01549. G.A.B. gratefully acknowledges support from NASA grant 80NSSC24K0149.

Facilities

JWST - James Webb Space Telescope.

Software References

Matplotlib (J. D. Hunter 2007), NumPy (S. van der Walt et al. 2011), SciPy (P. Virtanen et al. 2020), Seaborn (M. Waskom 2021), Astropy (Astropy Collaboration et al. 201320182022), LMFIT (M. Newville et al. 2014), iSLAT (M. Johnson et al. 2024), spectools_ir (C. Salyk 2022).

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Additional details

Created:
March 6, 2025
Modified:
March 6, 2025