UC Berkeley

The technology used to observe solar system planets continues to advance, increasing the spatial resolution, time cadence, and spectral coverage of observations and permitting the discovery of new phenomena in the atmospheres of worlds near and far. Comparative planetology is a powerful framework to help characterize and explain these newly-discovered phenomena: the similarities and differences between the composition, structure, and dynamics of planetary atmospheres test the robustness of the theories we use to understand and predict the weather and climate of atmospheres. This dissertation uses a comparative planetology framework to understand the physical processes underlying new observations of the atmospheres of Uranus and Neptune and new statistical analyses of observed storms on Earth. Although qualitatively dissimilar, the atmospheres of Uranus, Neptune, and Earth lie in a similar fluid-dynamical regime in many respects, allowing much of our physical intuition to translate across those three atmospheres. In particular, this dissertation focuses on using remote-sensing data to probe processes relevant to cloud formation and precipitation.

Higher bulk densities and strong enrichment in carbon and oxygen distinguish Uranus and Neptune from the gas giants Jupiter and Saturn, placing them into their own category, the ice giants. Exoplanet statistics reinforce this distinction: a gap in the size distribution of known exoplanets has been observed between the Jupiter-sized and Neptune-sized exoplanets. Uranus and Neptune are therefore of primary importance for understanding the different types of worlds that fill our galaxy; however, their distance from Earth also makes them very challenging to study in detail. The first three chapters of this dissertation tackle that observational challenge.Using near-infrared data from Keck Observatory and optical data from the Hubble Space Telescope (HST), I characterize a newly-observed storm at the equator of Neptune, including derivations of drift rates from cloud tracking and cloud-top pressures from radiative transfer modeling. I then apply the physics of deep convection and planetary waves to infer the drivers of the storm. Making use of millimeter-wavelength observations from the Atacama Large (sub)-Millimeter Array (ALMA) and mid-infrared observations from the Very Large Telescope (VLT), I observe the thermal component of the Uranian ring system for the first time. I apply the radiative transfer equation to the ring particles to derive their surface temperature and show that they rotate slowly compared to their radiative cooling time. I use the same dataset in conjunction with centimeter-wavelength Very Large Array (VLA) data to study the deep troposphere of Uranus from 1-50 bar. Applying intuition based on Earth's Hadley-Walker circulation, I link the observed enrichment and depletion of volatile species in Uranus's deep troposphere to Uranus's planetary-scale circulation.

Although the instrumentation and radiative transfer models are similar between observations of Earth and the ice giants, the technical challenges that arise in observing these bodies are somewhat opposite. Earth observations exemplify a data-rich regime in which millions of new data points are recorded every hour at spatial resolutions of order 1 kilometer, whereas ice giant studies are comparatively data-starved: $\sim$10 images at 100-kilometer resolution may constitute a full dataset. The second half of this dissertation tackles the data-rich observational challenge, concerning itself with the observed statistics of extratropical extreme storms on Earth from remote-sensing data. Using Doppler radar data, I show that the return values of extreme precipitation are strongly autocorrelated over the Eastern and Midwestern United States up to scales of $\gtrsim$100 kilometers, and that rain gauges can accurately estimate extreme precipitation only if interpolated with a particular eye toward capturing extremes. I then compile a suite of hourly data at 8-km resolution over the Eastern and Midwestern United States that simultaneously probes the synoptic-scale dynamical context of storms, the structure of clouds within storms, and the precipitation produced by storms. I demonstrate the utility of this unique data combination by examining the precipitation efficiency of storms, showing that precipitation efficiency increases with equivalent potential temperature over the contiguous United States (CONUS) in both the warm and cool seasons.

Taken as a whole, this dissertation showcases the ways in which recent advances in remote sensing technology and computational power can be applied to study atmospheres across the solar system, with a particular focus on cloud and precipitation processes.The types of questions that can be answered in the data-rich regime underscore the massive potential for advances in our understanding of the Solar System planets (and exoplanets) as data from new observatories and missions arrive in the next decades.