Abstract
The global cloud-resolving model (GCRM) is based on a holistic approach: the complex interdependences among macro-scale and micro-scale processes are simulated directly. In standard models, the micro-scale phenomena have spatial and time scale smaller than the minimum allowed model-grid resolution; thus, a parameterization is necessary to take into account the important effect that the interaction between phenomena at different length scales produces on weather. Computational meteorological models with higher resolution have a more correct representation of the terrain complex orography and also a more realistic horizontal distribution of the surface characteristics. The focus of the analysis has been placed on the evolution of the quantitative precipitation forecast (QPF), one of the most complex and important meteorological variables. A very special topic of the GCRM is the Yin-Yang grid system, characterized by two partially overlapped volume meshes that cover the Earth surface. The value of the Prandtl number (Pr) is defined by the fluid chemical composition and by its state (temperature and pressure), and is about 0.7 in the atmosphere. The turbulent Pr depends on the horizontal numerical resolution and changes with the turbulence. © 2007
Original language | English |
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Title of host publication | Parallel Computational Fluid Dynamics 2006 |
Publisher | Elsevier Ltd |
Pages | 197-206 |
Number of pages | 10 |
ISBN (Print) | 9780444530356 |
DOIs | |
Publication status | Published - 2007 |
Externally published | Yes |
ASJC Scopus subject areas
- Chemical Engineering(all)