Exoplanetology: Exoplanets & Exomoons

Interpolation and Synthesis of Sparse Samples in Exoplanet Atmospheric Modeling

By Keith Cowing
Status Report
astro-ph.EP
May 24, 2024
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Interpolation and Synthesis of Sparse Samples in Exoplanet Atmospheric Modeling
The left two panels show the distribution of surface average temperature for the ExoCAM (top) and ExoPlaSim (bottom) model calculations of SAMOSA case 4 (with 1200 W m−2 and 2.34 bar). The right panel shows the theoretical variogram curves for both models. The warmer substellar point is one contributing factor to the ExoCAM variogram showing greater dissimilarities at all spatial separations when compared to ExoPlaSim. — astro-ph.EP

This paper highlights methods from geostatistics that are relevant to the interpretation, intercomparison, and synthesis of atmospheric model data, with a specific application to exoplanet atmospheric modeling. Climate models are increasingly used to study theoretical and observational properties of exoplanets, which include a hierarchy of models ranging from fast and idealized models to those that are slower but more comprehensive.

Exploring large parameter spaces with computationally-expensive models can be accomplished with sparse sampling techniques, but analyzing such sparse samples can pose challenges for conventional interpolation functions. Ordinary kriging is a statistical method for describing the spatial distribution of a data set in terms of the variogram function, which can be used to interpolate sparse samples across any number of dimensions.

Variograms themselves may also be useful diagnostic tools for describing the spatial distribution of model data in exoplanet atmospheric model intercomparison projects. Universal kriging is another method that can synthesize data calculated by models of different complexity, which can be used to combine sparse samples of data from slow models with larger samples of data from fast models.

Ordinary and universal kriging can also provide a way to synthesize model predictions with sparse samples of exoplanet observations and may have other applications in exoplanet science.

Jacob Haqq-Misra, Eric T. Wolf, Thomas J. Fauchez, Ravi K. Kopparapu

Comments: Accepted for publication in the Planetary Science Journal
Subjects: Earth and Planetary Astrophysics (astro-ph.EP); Instrumentation and Methods for Astrophysics (astro-ph.IM); Atmospheric and Oceanic Physics (physics.ao-ph); Geophysics (physics.geo-ph)
Cite as: arXiv:2405.14693 [astro-ph.EP] (or arXiv:2405.14693v1 [astro-ph.EP] for this version)
https://doi.org/10.48550/arXiv.2405.14693
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Submission history
From: Jacob Haqq-Misra
[v1] Thu, 23 May 2024 15:29:18 UTC (158 KB)
https://arxiv.org/abs/2405.14693
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