Dataset Open Access

Reflection Spectra Repository for Cool Giant Planets

Ryan J. MacDonald; Mark S. Marley; Jonathan J. Fortney; Nikole K. Lewis

Supplementary material for Exploring H2O Prominence in Reflection Spectra of Cool Giant Planets - ApJ 858, 69 (2018).

This repository contains 65520 model reflection spectra of cool giant planets. The grid explores the influence of metallicity, gravity, effective temperature, and sedimentation efficiency on H2O absorption signatures in giant planet atmospheres. We also include two animations to visualise how the prominence of H2O absorption evolves over this parameter space. The included models range over:

*m => 1-100 x solar (log(m) @ 0.0, 0.5, 1.0, 1.5, 1.7, 2.0 dex) <-- log(m) = 1.7 new for V2 of the database.
*g => 1-100 m/s2 (evenly over log(g) in steps of 0.1 dex)
*Teff => 150-400 K (linearly in steps of 10 K)
*fsed => 1-10 (linearly in steps of 1)

(V 1.0, March 30th 2018):

Initial release of the reflection spectra repository. 

(V 2.0, Oct 1st 2019): 

The cool giant reflection spectra grid has been re-computed using the latest version of the PICASO albedo code (doi: 10.3847/1538-4357/ab1b51). This fixes a few bugs and adds new model features (e.g. Raman scattering, see Batalha+2019).

The new grid is packaged as a HDF5 file with an accompanying python script 'Open_Albedo_Database.py'. The python script is provided to show how to open the albedo database, plot the spectra, and save spectra as a .txt file. The user need only change 4 lines (specifying log(m), log(g), Teff, fsed) and run the python script to produce a plot of the albedo spectra (both with and without H2O absorption).

NEW: (V 2.1, Oct 3rd 2019): 

Fixed a bug causing models with log(g) = 3.4 or 3.9 to not display cloud opacity.

Files (1.1 GB)
Name Size
Animation_f_vs_T.mp4
md5:8fd248aba579db2379f051b7e44bd523
2.7 MB Download
Animation_g_vs_T.mp4
md5:a48d6529b189847f9c156fc628ae73d6
2.5 MB Download
Cool_giant_albedo_database.hdf5
md5:1afef286cedebcd86990fc83480df08b
1.1 GB Download
Open_Albedo_Database.py
md5:ab9600f2ce58eb0e24fe6a26f259530d
4.4 kB Download
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