HR: 14:25h
AN: H53J-04    [Abstracts]
TI: Explicit Simulation Of Ice Crystal Habits In 3D Eulerean Numerical Weather Prediction Model - Sensitivities On Aggregation And Riming Processes
AU: * Hashino, T
EM: hashino@wisc.edu
AF: Department of Atmospheric & Oceanic Sciences, University of Wisconsin - Madison, 1225 W. Dayton Street, Madison, WI 53706 United States
AU: Tripoli, G J
EM: tripoli@aos.wisc.edu
AF: Department of Atmospheric & Oceanic Sciences, University of Wisconsin - Madison, 1225 W. Dayton Street, Madison, WI 53706 United States
AB: The Spectral Habit Ice Prediction System (SHIPS) developed by the authors provides a methodology to explicitly simulate ice crystal habit (or shape), and density of frozen hydrometeors in a 3D Eulerian Numerical Weather Prediction (NWP) Model. It enables the prediction model to reflect the atmospheric conditions encountered during their growth history through concentration, mass, length, and volume components. With this method, categorization of frozen hydrometeors into idealized habits such as plates, columns, graupels etc is not necessary. This is a departure from other microphysical models based on categorization techniques which are widely used in operational weather prediction models today. This presentation focuses on aggregation and riming processes in 2D idealized simulation of orographic snow storm that occurred during the IMPROVE-2 campaign. It is well known that aggregation efficiency is dependent on habit or shape of ice crystals as well as stickiness. Density of graupel and the melt water on the surface reflects the growth history of frozen hydrometeors. It is important to simulate correct efficiencies of those processes because they determine the amount of precipitation that reaches the ground. Modeling of those processes and the sensitivities of ice crystal habits on those processes will be discussed.
DE: 0320 Cloud physics and chemistry
DE: 3354 Precipitation (1854)
SC: Hydrology [H]
MN: Fall Meeting 2005