HR: 11:30h
AN: A42A-05    [Abstracts]
TI: Explicit Simulation of Ice Crystal Habits in 3D Eulerean Numerical Weather Prediction Model
AU: * Hashino, T
EM: hashino@wisc.edu
AF: Department of Atmospheric and 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 and Oceanic Sciences, University of Wisconsin - Madison, 1225 W. Dayton Street, Madison, WI 53706 United States
AB: Current operational weather prediction models simulate the ice microphysics based on Kessler/Orville approach, or categorization of solid hydrometeors, for its computational efficiency. The scheme may not be appropriate to study cloud microphysics not only due to the prescribed decision tree and arbitrary categories, but also the inability to reflect the growth history of solid hydrometeors. In addition, along with more available computational power, recent remote sensing technology needs proper representation of phase, distribution, shape, and density of solid hydrometeors in radiation transfer calculation. This research describes a methodology to simulate ice crystal habit (or shape), and density of frozen hydrometeors explicitly which can be used in 3D Eulerean Numerical Weather Prediction (NWP) Model. In Eulerean NWP model the prognostic variables are predicted using a mass conservation equation requiring the predictive variable to be extensive. To predict the evolving habit structure of cloud physics variables in such a model framework, we introduce extensive variables that contain the essential information necessary to reconstruct the probable geometry of the ice crystals: mass components and concentration-weighted length. At any given point, we can retrieve the geometry of ice crystals, such as dendrite, plate, column, needle or rosette from these variables. This method will be implemented in a bin model which represents all the solid hydrometeors by one mass distribution. Idealized orographic storms will be simulated by University of Wisconsin Nonhydrostatic Modeling System with the bin model. The result will be discussed in the presentation.
DE: 0320 Cloud physics and chemistry
SC: Atmospheric Sciences [A]
MN: 2005 Joint Assembly