Articles | Volume 9, issue 6
Model description paper
10 Jun 2016
Model description paper |  | 10 Jun 2016

Generalization and application of the flux-conservative thermodynamic equations in the AROME model of the ALADIN system

Daan Degrauwe, Yann Seity, François Bouyssel, and Piet Termonia

Abstract. General yet compact equations are presented to express the thermodynamic impact of physical parameterizations in a NWP or climate model. By expressing the equations in a flux-conservative formulation, the conservation of mass and energy by the physics parameterizations is a built-in feature of the system. Moreover, the centralization of all thermodynamic calculations guarantees a consistent thermodynamical treatment of the different processes. The generality of this physics–dynamics interface is illustrated by applying it in the AROME NWP model. The physics–dynamics interface of this model currently makes some approximations, which typically consist of neglecting some terms in the total energy budget, such as the transport of heat by falling precipitation, or the effect of diffusive moisture transport. Although these terms are usually quite small, omitting them from the energy budget breaks the constraint of energy conservation. The presented set of equations provides the opportunity to get rid of these approximations, in order to arrive at a consistent and energy-conservative model. A verification in an operational setting shows that the impact on monthly-averaged, domain-wide meteorological scores is quite neutral. However, under specific circumstances, the supposedly small terms may turn out not to be entirely negligible. A detailed study of a case with heavy precipitation shows that the heat transport by precipitation contributes to the formation of a region of relatively cold air near the surface, the so-called cold pool. Given the importance of this cold pool mechanism in the life cycle of convective events, it is advisable not to neglect phenomena that may enhance it.

Short summary
In its purest essence, numerical weather prediction boils down to solving the fundamental laws of nature with computers. Such fundamental laws are the conservation of energy and the conservation of mass. In this paper, a framework is presented that allows to respect these laws more accurately, which should lead to weather forecasts that correspond better to reality. Under specific circumstances, such as heavy precipitation, the proposed framework has a significant impact on the forecast.