Simulating Non-hydrostatic atmospheres on Planets (SNAP): formulation, validation and application to the Jovian atmosphere. (arXiv:1901.02955v1 [astro-ph.EP])
<a href="http://arxiv.org/find/astro-ph/1/au:+Li_C/0/1/0/all/0/1">Cheng Li</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Chen_X/0/1/0/all/0/1">Xi Chen</a>
A new non-hydrostatic and cloud-resolving atmospheric model is developed for
studying moist convection and cloud formation in planetary atmospheres. It is
built on top of the Athena++ framework, utilizing its static/adaptive
mesh-refinement, parallelization, curvilinear geometry, and dynamic task
scheduling. We extend the original hydrodynamic solver to vapors, clouds, and
precipitation. Microphysics is formulated generically so that it can be applied
to both Earth and Jovian planets. We implemented the Low Mach number
Approximate Riemann Solver (LMARS) for simulating low speed atmospheric flows
in addition to the usual Roe and HLLC Riemann solvers. Coupled with a
fifth-order Weighted Essentially Nonoscillatory (WENO) subgrid-reconstruction
method, the sharpness of critical fields such as clouds is well-preserved, and
no extra hyperviscosity or spatial filter is needed to stabilize the model.
Unlike many atmospheric models, total energy is used as the prognostic variable
of the thermodynamic equation. One significant advantage of using total energy
as a prognostic variable is that the entropy production due to irreversible
mixing process can be properly captured. The model is designed to provide a
unified framework for exploring planetary atmospheres across various
conditions, both terrestrial and Jovian. First, a series of standard numerical
tests for Earth’s atmosphere is carried out to demonstrate the performance and
robustness of the new model. Second, simulation of an idealized Jovian
atmosphere in radiative-convective equilibrium shows that 1) the temperature
gradient is superadiabatic near the water condensation level because of the
changing of the mean molecular weight, and 2) the mean profile of ammonia gas
shows a depletion in the subcloud layer down to nearly 10 bars. Relevance to
the recent Juno observations is discussed.
A new non-hydrostatic and cloud-resolving atmospheric model is developed for
studying moist convection and cloud formation in planetary atmospheres. It is
built on top of the Athena++ framework, utilizing its static/adaptive
mesh-refinement, parallelization, curvilinear geometry, and dynamic task
scheduling. We extend the original hydrodynamic solver to vapors, clouds, and
precipitation. Microphysics is formulated generically so that it can be applied
to both Earth and Jovian planets. We implemented the Low Mach number
Approximate Riemann Solver (LMARS) for simulating low speed atmospheric flows
in addition to the usual Roe and HLLC Riemann solvers. Coupled with a
fifth-order Weighted Essentially Nonoscillatory (WENO) subgrid-reconstruction
method, the sharpness of critical fields such as clouds is well-preserved, and
no extra hyperviscosity or spatial filter is needed to stabilize the model.
Unlike many atmospheric models, total energy is used as the prognostic variable
of the thermodynamic equation. One significant advantage of using total energy
as a prognostic variable is that the entropy production due to irreversible
mixing process can be properly captured. The model is designed to provide a
unified framework for exploring planetary atmospheres across various
conditions, both terrestrial and Jovian. First, a series of standard numerical
tests for Earth’s atmosphere is carried out to demonstrate the performance and
robustness of the new model. Second, simulation of an idealized Jovian
atmosphere in radiative-convective equilibrium shows that 1) the temperature
gradient is superadiabatic near the water condensation level because of the
changing of the mean molecular weight, and 2) the mean profile of ammonia gas
shows a depletion in the subcloud layer down to nearly 10 bars. Relevance to
the recent Juno observations is discussed.
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