Collaborative Research: Integrating Models and Observations to Assess Effects of Turbulence on Warm Rain Initiation

University Of California-Santa Cruz, Santa Cruz CA

Investigators

Abstract

While the "warm rain" process--in which ice-phase microphysics play little or no role in development of precipitation-size particles--is thought to account for as much as one-third of all tropical precipitation, yet a number of uncertainties remain regarding its exact mechanisms. In particular, the classic theory of condensational growth followed by collision-coalescence accompanying gravitational settling is unable to explain the oft-observed rapid development of rain in clouds confined to temperatures warmer than 0 degC. It has gradually become recognized that turbulence could play a critical role in accelerating this process, but realizable predictions have been difficult to achieve because quantitative research approaches are lacking. Recent advances in theory and computational capacity have enabled more quantitative assessment of turbulence effects on the collision-coalescence rate, and several preliminary parameterizations of turbulent collection have been developed. The goals of this research are to (a) incorporate representation of realistic turbulence-driven collection (i.e. droplet growth) in a large-eddy simulation (LES) model of cloud behavior using a bin microphysical scheme, and subsequently (b) to evaluate resulting predictions using existing in situ observations of real clouds to identify those conditions under which this newly-represented process affects and improves model predictions. Owing to their long lifecycle and a large amount of high-quality observational data available to facilitate real world-model comparisons, marine stratocumulus clouds will be emphasized. A hybrid direct numerical simulation (DNS) approach will be used to develop more accurate parameterization of turbulent collision-coalescence in conditions of low-to-intermediate mean flow dissipation rates, and statistical methods to incorporate such a parameterization into the LES framework will be explored. This approach will be complemented by phenomenological modeling of Reynolds number effects on airflow, and in so doing the LES model will be improved to allow for differing cloud entrainment mixing scenarios. The intellectual merit of this study will center on a more accurate and systematic evolution of the effects of turbulence on realistic stratocumulus conditions and improved assessment of our current ability to represent such effects quantitatively in a predictive mode. Broader Impacts of the effort will include development of findings that should ultimately be applicable to other types of clouds (e.g., more vigorous cumulus) and improved quantitative representation for warm-rain development in more coarse-grained numerical weather prediction and climate models, as well as through enhanced collaboration across the cloud microphysics and computational sciences. This setting will provide a vibrant and multifaceted education and training ground for a mix of undergraduate and graduate students at the two involved institutions.