# Main Page

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== ASAM (CPU) == | == ASAM (CPU) == | ||

- | ASAM is a numerical solver for atmospheric applications at all scales ranging from the globe up to building resolving simulations. ASAM stands for '''A'''ll '''S'''cale '''A'''tmsopheric '''M'''odel. The underlying compressible Euler equations in flux form are solved in an Eulerian framework. ASAM was at first designed for CFD simulation around buildings where the obstacles are includes within a Cartesian grid by a cut cell approach. This approach is now extended to other orthogonal grids like the | + | ASAM is a numerical solver for atmospheric applications at all scales ranging from the globe up to building resolving simulations. ASAM stands for '''A'''ll '''S'''cale '''A'''tmsopheric '''M'''odel. The underlying compressible Euler equations in flux form are solved in an Eulerian framework. ASAM was at first designed for CFD simulation around buildings where the obstacles are includes within a Cartesian grid by a cut cell approach. This approach is now extended to other orthogonal grids like the lat-lon grid. Due to the implicit time integration scheme there are no stability problems with small grid cells resulting from cut cells or cells near the poles. ASAM requires that physical processes can be prescribed as a time continuous process with respect the model variables and is not dependent from the time step. ASAM is a developing research code and has a lot of different options to choose numerical methods, number of variables and physical processes. The code is used for testing new numerical approaches but is also for process studies on different scales. Examples are LES simulations of stratiform clouds, vortex generation in street canyons, moist bubble experiments, orographic rainfall and so on. ASAM is a fully parallelized code and is easily portable between different platforms. The following links provide more detailed information about the model content: |

* [[Equations]] | * [[Equations]] |

## Current revision

## Contents |

# Content

## ASAM (CPU)

ASAM is a numerical solver for atmospheric applications at all scales ranging from the globe up to building resolving simulations. ASAM stands for **A**ll **S**cale **A**tmsopheric **M**odel. The underlying compressible Euler equations in flux form are solved in an Eulerian framework. ASAM was at first designed for CFD simulation around buildings where the obstacles are includes within a Cartesian grid by a cut cell approach. This approach is now extended to other orthogonal grids like the lat-lon grid. Due to the implicit time integration scheme there are no stability problems with small grid cells resulting from cut cells or cells near the poles. ASAM requires that physical processes can be prescribed as a time continuous process with respect the model variables and is not dependent from the time step. ASAM is a developing research code and has a lot of different options to choose numerical methods, number of variables and physical processes. The code is used for testing new numerical approaches but is also for process studies on different scales. Examples are LES simulations of stratiform clouds, vortex generation in street canyons, moist bubble experiments, orographic rainfall and so on. ASAM is a fully parallelized code and is easily portable between different platforms. The following links provide more detailed information about the model content:

## ASAMgpu

ASAMgpu is a model for three dimensional atmospheric simulations. It uses GPU's to provide a maximum performance that enables 3D-LES on architectures ranging from a notebook, an ordinary gaming pc up to one or more high performance MultiGPU Nodes.

- LES running on GPU's using OpenGL + GLSL (see ASAMgpu)

# References

- George H. Bryan and J. Michael Fritsch (December 2002). A Benchmark Simulation for Moist Nonhydrostatic Numerical Models.
*Monthly Weather Review. Volume 130. Issue 12*, 2917–2928. (back) - Lanser, D., J. G. Blom, and J. G. Verwer (2001). Time integration of the shallow water equations in spherical geometry.
*Journal of Computational Physics 171*, 373–393. (back) - William A. Gallus Jr. and Joseph B. Klemp (April 2000). Behavior of Flow over Step Orography.
*Monthly Weather Review. Volume 128. Issue 4*, 1153–1164. (back) - Christoph Schär (December 1990). Quasi-geostrophic Lee Cyclogenesis.
*Journal of the Atmospheric Sciences, Volume 47. Issue 24*, 3044–3066. (back) - Straka, J., R. Wilhelmson, L. Wicker, J. Anderson, and K. Droegemeier (1993). Numerical solutions of a nonlinear density-current - a benchmark solution and comparisons.
*International Journal of Numerical Methods in Fluids 17*, 1–22. (back) - H. Tomita and M. Satoh (2004). A new dynamical framework of nonhydrostatic global model using the icosahedral grid.
*Fluid Dynamics Research 34*, 357-400. (back) - Hodyss, Nolan (August 2007). Linear Anelastic Equations for Atmospheric Vortices.
*American Meteorological Society. Volume 64*, 2947-2959. (back) - Schmidli, Juerg (2008). The T-REX valley wind intercomparison project. Conference. Presented at: 13th Conference on Mountain Meteorology, Whistler, Canada, Aug 11 - Aug 15, 2008 (back)