A Low Mach Number Model for Moist Atmospheric Flows

Journal Article · Wed Apr 01 00:00:00 EDT 2015 · Journal of the Atmospheric Sciences

DOI:https://doi.org/10.1175/JAS-D-14-0248.1· OSTI ID:1407268

Duarte, Max ^[1]; Almgren, Ann S. ^[1]; Bell, John B. ^[1]

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1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Center for Computational Sciences and Engineering

A low Mach number model for moist atmospheric flows is introduced that accurately incorporates reversible moist processes in flows whose features of interest occur on advective rather than acoustic time scales. Total water is used as a prognostic variable, so that water vapor and liquid water are diagnostically recovered as needed from an exact Clausius–Clapeyron formula for moist thermodynamics. Low Mach number models can be computationally more efficient than a fully compressible model, but the low Mach number formulation introduces additional mathematical and computational complexity because of the divergence constraint imposed on the velocity field. Here in this paper, latent heat release is accounted for in the source term of the constraint by estimating the rate of phase change based on the time variation of saturated water vapor subject to the thermodynamic equilibrium constraint. Finally, the authors numerically assess the validity of the low Mach number approximation for moist atmospheric flows by contrasting the low Mach number solution to reference solutions computed with a fully compressible formulation for a variety of test problems.

• Research Organization: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
• Grant/Contract Number: AC02-05CH11231
• OSTI ID: 1407268
• Journal Information: Journal of the Atmospheric Sciences, Vol. 72, Issue 4; ISSN 0022-4928
• Publisher: American Meteorological Society
• Country of Publication: United States
• Language: English

Related Subjects

54 ENVIRONMENTAL SCIENCES
Model comparison
Nonhydrostatic models
Numerical analysis/modeling