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Multiple research assistantship (RA) positions are available for M.S. or PhD students applying for the 2020 Fall admission. Interested students are welcome to email me at email@example.com for more information.
#1: The overarching goal of this project is to obtain a deeper understanding of microphysical processes governing the evolution of drop size distributions (DSDs) using a synergistic combination of dual-polarization radar retrievals of DSD moments and one-dimensional (1D) model-predictions of moments and process rates for cases well-observed by the scanning polarimetric ARMOR radar and the University of Alabama at Huntsville (UAH) Mobile Integrated Profiling System (MIPS). The proposed simulations are based on two new numerical models, (i) the cloud particle model (CPM) which explicitly accounts for the evolution of all the cloud particles under warm rain microphysical processes, and (ii) a novel Monte-Carlo microphysics model (McSnow) that simulates the evolution of ice, mixed phase and rain based on the physical properties of super-particles using the super droplet method (SDM, or Lagrangian Cloud Model interchangeably). The coupling between ice processes above the melting level to rain processes below the melting level to the surface needs to be better understood. McSnow-predicted profiles and slopes of dual-pol variables with height from above the bright-band to the surface will be compared with radar observations to infer the dominant processes as well as rain types. The explicit cloud particle model (CPM) will be used to predict if there is a significant impact of observed fall speed on collisional processes and subsequently on DSD evolution.
The student will be in charge of the modeling component using the SDM (or LCM) to simulate the rain microphysical processes in the stratiform cloud or tropical cyclone rainbands. SDM (or LCM), unlike bulk microphysics and bin microphysics, is an emerging cloud modeling approach that directly simulates the clouds at the cloud particle level. Students with programming (Fortran or other language), data analysis (using Python or Matlab or NCL), and numerical models (WRF or others) experiences/skills, are encouraged to contact Wei Wu for the Research Assistantship (RA) opportunity through email: firstname.lastname@example.org.
#2: Microphysical processes leading to the formation of drizzle and rain in warm (ice-free) cumulus clouds are still not well understood, and their representation is a key uncertainty in climate models. From a theoretical point of view, cloud droplets can grow by water vapor diffusion only to sizes where collisional growth is still inefficient. This is often referred to as the condensation-coalescence bottleneck, between approximately 15 and 40 microns in droplet radius. In this project, we will apply theory, observations, and numerical modeling to study processes occurring in natural clouds that push droplet growth through the condensation-coalescence bottleneck.
In-situ high- resolution observations from recent ARM field campaigns targeting convective clouds, including RACORO and HI-SCALE over the SGP site and the recent CACTI project in north-central Argentina will be analyzed. Cloud particle probes will be analyzed at the highest resolution possible, up to 10 Hz sampling (CAS, FSSP, CIP and 2D-S) on a slowly flying Twin Otter aircraft during RACORO and on a particle-by- particle basis (FCDP, 2D-S and HVPS) on ARM Aerial Facility’s Gulfstream 1 (G-1) aircraft in HI- SCALE and CACTI. The focus will be on droplet spectral width and its relationship to cloud parameters (e.g., mean radius, adiabatic fraction, local turbulence intensity, and presence or absence of droplets in the bottleneck size range, as well as the spatial variability of these parameters along-the-flight-path vicinity of the observation location) and environmental conditions (location in cloud, vertical velocity, synoptic conditions and origins of air masses). We will also combine high-resolution droplet spectral information with scale-dependent estimates of the vertical velocity fluctuations derived from the turbulent kinetic energy scaling and aircraft gust probe data to provide for the first time estimates of the supersaturation fluctuation at scales of meters to tens of meters within convective clouds. These fluctuations have been argued in the past to play a critical role in the evolution of the droplet spectra.
On the modeling side, we will apply a novel Lagrangian modeling approach referred to as the “super-droplet method” that allows unprecedented fidelity for simulating cloud microphysics. This novel approach mitigates numerical problems facing traditional Eulerian bin microphysics that lead to artificial droplet spectral broadening. Moreover, the Lagrangian approach allows truly multiscale cloud simulations by incorporating a physically-based stochastic subgrid-scale droplet growth scheme. These simulations will employ the Weather Research and Forecasting model in large eddy simulation mode with environmental conditions obtained from field observations. Statistical techniques developed with our previous ASR funding will be used to evaluate model simulations with the observational data.
Students with programming (Fortran or other language), data analysis (using Python or Matlab or NCL), and numerical models (WRF or others) experiences/skills, are encouraged to contact Wei Wu for the Research Assistantship (RA) opportunity through email: email@example.com.
Wei Wu Research Scientist Cooperative Institute for Mesoscale Meteorological Studies (CIMMS) The University of Oklahoma 120 David L. Boren Blvd. Norman, OK 73072-7304 Phone: 405-325-4637 Email: firstname.lastname@example.org