Smalley, Kevin (2020-09). A-train Analysis of Low Cloud Structure, Organization, and Warm Rain. Doctoral Dissertation. Thesis uri icon

abstract

  • Low-cloud cover continues to be a dominant source of uncertainty in climate models and past observational-based studies to help constrain this uncertainty have typically been limited in both space and time or by measurements sensitivities. To address this, satellite observations with sensitivities to both cloud and rain are used to analyze the influence of thermodynamics, the environment, and organization on precipitating low clouds. This provides an avenue to sample low clouds both globally and over a longer time period. This analysis shows that both the likelihood of shallow cumulus rainfall and the efficiency of rain production increase as cloud size, environmental moisture, and sea-surface temperature increase. While aerosols hamper rainfall production and require larger clouds than in a clean environment for a similar rain likelihood, they have little influence on rain efficiency once rain begins. This implies that cloud size distributions may be important for improving the simulation of warm rain in climate models. Focusing on the influence of mesoscale organization in raining cells across the transition of stratocumulus to shallow cumulus over the southeast Pacific, analysis shows that cloud fraction is generally lower over the transition region when patches of raining stratocumulus are larger. We attribute this to larger raining patches being more likely to produce more intense rainfall, which may result in stronger cold pools that could drive transitions. This implies that mesoscale organization in precipitation may need to be better captured within climate models to better capture low cloud fraction transitions over the sub-tropical oceans.

publication date

  • September 2020