An adaptive discontinuous Galerkin method for modeling cumulus clouds
Author
Müller, Andreas
Behrens, Jörn
Giraldo, Francis X.
Wirth, Volkmar
Date
2010-06Metadata
Show full item recordAbstract
Theoretical understanding and numerical modeling of atmospheric moist convection
still pose great challenges to meteorological research. The present work addresses
the following question: How important is mixing between cloudy and environmental air
for the development of a cumulus cloud? A Direct Numerical Simulation of a single cloud
is way beyond the capacity of today’s computing power. The use of a Large Eddy Simulation
in combination with semi-implicit time-integration and adaptive techniques offers a
significant reduction of complexity.
So far this work is restricted to dry flow in two-dimensional geometry. The compressible
Navier-Stokes equations are discretized using a discontinuous Galerkin method introduced
by Giraldo and Warburton in 2008. Time integration is done by a semi-implicit backward
difference. For the first time we combine these numerical methods with an h-adaptive
grid refinement. This refinement of our triangular grid is implemented with the function
library AMATOS and uses a space filling curve approach.
Validation through different test cases shows very good agreement between the current
results and those from the literature. For comparing different adaptivity setups we developed
a new qualitative error measure for the simulation of warm air bubbles. With the
help of this criterion we show that the simulation of a rising warm air bubble on a locally
refined grid can be more than six times faster than a similar computation on a uniform
mesh with the same accuracy.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.Collections
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