Research Interests

• Fluid Dynamics

• Turbulent Flows

• Microhydrodynamics

• Cloud Microphysics

Details of My Research Project

Earth's climate is crucially dependent on warm, shallow convective clouds that cover a large portion of the tropics. Limited area models (LAMs), numerical weather predictions (NWPs), and global circulation models (GCMs) have a grid resolution of approximately 50-200 kilometers and do not resolve most cloud scales. The smallest particle length-scale in the atmosphere (sub-micron size aerosol particle) is several orders of magnitude smaller than the GCM grid resolution. Due to the broad spectrum of length scales of atmospheric motions, ranging from 1 millimeter (Kolmogorov length scale in warm cumulus clouds) to thousands of kilometers (tropical cyclones), it is impossible to capture all the physical processes in a single model. Clouds are a leading source of uncertainty in climate models due to the difficulty in accurately parametrizing the macroscale effects of microphysical processes, such as the role of cloud albedos on the energy budget and the effect of the drop size distribution (DSD) on precipitation rates. Warm clouds are dispersions of liquid droplets and aerosol particles embedded in and interacting with a complex turbulent flow. Turbulence in clouds is characterized by large Taylor-microscale Reynolds numbers, relatively small dissipation rates, moderate r.m.s. velocities, and strong intermittency in energy dissipation, Lagrangian acceleration, and scalar gradients at small scales. Cloud droplets initially form on pre-existing aerosol particles that serve as cloud condensation nuclei (CCN). In a supersaturated environment, droplets grow by water vapor condensation up to 15 microns in radius. Droplets larger than 40 microns in radius grow by capturing smaller droplets due to gravitational collision-coalescence. The classical condensation theory predicts that a 15 microns drop will take more than 2 hours to become 40 microns with supersaturation of 0.2% (typical for clouds), whereas, the observed time for the same is around 15 minutes (see Jonas 1996). This rapid growth in droplet size from the condensational to the gravitational regime is an unsolved problem in cloud microphysics, commonly known as the condensation-coalescence bottleneck or size-gap problem. The difficulty in obtaining an accurate rain-forming DSD comes from the lack of physically correct theoretical models for - (1) the condensational growth rate in a turbulent environment with supersaturation fluctuations and (2) the rate of collision-coalescence due to the combined effects of gravity and turbulence with colloidal and hydrodynamic interactions between droplet pairs. Traditional cumulus parameterizations crudely describe cloud microphysics. The need to improve representations of microphysics in large-scale models led to the idea of superparameterization, where microphysical processes are explicitly simulated with a cloud-resolving model (CRM) running in each GCM grid column. Therefore, an explicit study of cloud microphysical processes is important for accurately predicting weather and climate.