Files
Abstract
Clouds are the largest source of uncertainty in climate simulations. For exoplanets, cloud simulation is particularly challenging due to the lack of observational data to tune parameterized cloud models. This presents a barrier to answering the grand challenge of assessing the prevalence of life beyond Earth, as it undermines our ability to predict exoplanet habitability and interpret observations.
In this thesis, I apply CARMA, a resolved bin cloud microphysics model, to conduct first-principle simulations of water clouds on terrestrial exoplanets. Because CARMA explicitly models physical processes and is less heavily tuned than parameterized schemes, it is expected to be more robust when extrapolated to exoplanet contexts.
In Chapter 2, I apply CARMA in a one-dimensional (1D) setup to simulate globally averaged exoplanet clouds and explore how cloud microphysics responds to changes in planetary parameters. I examine the impact on cloud radiative effect (CRE) and analyze how specific processes modeled by CARMA—nucleation, condensation, evaporation, coagulation, and vertical transport—contribute to it. I find that parameters determining the atmospheric thermal structure, including surface pressure and stellar flux, have the largest impact on CRE. Other factors such as gravity and aerosol number density affect microphysical processes like activation and transport, with a weaker but still significant effect. These simulations provide resolved cloud size distributions, key for evaluating the observational impact of exoplanet clouds.
In Chapter 3, I study how clouds affect the detectability of biosignatures using direct imaging surveys. I use the Planetary Spectrum Generator (PSG), a radiative transfer model, to evaluate observability of O$_2$ and O$_3$ with the planned Habitable Worlds Observatory (HWO). Cloud microphysics is derived from 1D CARMA output, sensitivity tests, and an analytical model. I find that clouds are likely to increase the signal-to-noise ratio for O$_2$ and O$ _3$ detection in direct imaging—a contrast to transmission spectroscopy, where clouds usually obscure gas signals.
In Chapter 4, I investigate how cloud microphysics interacts with 3D atmospheric circulation by varying the planetary rotation period, a key 3D parameter. I use CESM2-CAM6, a Global Climate Model (GCM), coupled with CARMA, and compare the results with those from the Morrison-Gettelman (MG) parameterized scheme. CARMA produces less shortwave and more longwave cloud forcing, and significantly different ice cloud size distributions. This reduces the net CRE by $4–10$ $W/m^2$, which is unlikely to alter climate-based habitability assessment. However, the difference in particle sizes can significantly impact transmission spectra and retrievals.
This thesis evaluates the effect of cloud microphysics on exoplanet climate and observability using CARMA. I present a methodology to assess parameterized schemes under extrapolated conditions and show that sophisticated schemes can perform well in some cases. Overall, resolving cloud microphysics may not change habitability conclusions but could substantially affect observational interpretation.