Connecting JWST Silicate Cloud Observations to Exoplanet Cloud Microphysics with Nimbus

Sven Kiefer; Caroline V. Morley; Melanie Rowland

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arXiv · 2603.13167

Connecting JWST Silicate Cloud Observations to Exoplanet Cloud Microphysics with Nimbus

Sven Kiefer·Caroline V. Morley·Melanie Rowland

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Abstract

The unprecedented accuracy of JWST has led to the detection of silicate clouds in exoplanet atmospheres, allowing for the first time to probe cloud formation in extreme environments. While parametrized cloud descriptions can fit these observations, the results do not fully agree with microphysical models. To bridge this gap, we developed Nimbus, a fast microphysical cloud model that can constrain cloud formation processes from observations and utilize Virga, an equilibrium condensation model balancing gravitational settling and diffusion. Using both models, we investigate WASP-107 b, WASP-17 b, VHS-1256 b, and YSES-1 c to determine their cloud structure and constrain cloud formation processes. Our results show that all four planets have cluster-sized silicate particles (r ~ 1 nm) at high altitudes. Within Nimbus and Virga, these particles can only be explained by highly inefficient cloud particle settling (fsed < 0.1) or by inefficient growth rates due to low sticking coefficients (s < 0.0001). Our results also show that the sticking coefficient is directly linked to the vertical extent of clouds and can therefore be constrained using the broad shape of the spectral energy distribution. The sticking coefficients found for VHS-1256 b and YSES-1 c are in agreement with expectations from laboratory experiments under Earth-like conditions (0.01 < s < 0.3). Panchromatic observations were crucial to achieve these constraints. Future cloud studies should therefore aim to combine observational data from 1 micron to 10 micron whenever possible.

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Sven Kiefer, Caroline V. Morley, Melanie Rowland. 2026-03-13. Connecting JWST Silicate Cloud Observations to Exoplanet Cloud Microphysics with Nimbus. https://arxiv.org/abs/2603.13167

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