Abstract
Abstract. As far as the representation of deep moist convection is concerned, only two kinds of model physics are used at present: highly parameterized as in the conventional general circulation models (GCMs) and explicitly simulated as in the cloud-resolving models (CRMs). Ideally, these two kinds of model physics should be unified so that a continuous transition of model physics from one kind to the other takes place as the resolution changes. With such unification, the GCM can converge to a global CRM (GCRM) as the grid size is refined. This paper suggests two possible routes to achieve the unification. ROUTE I continues to follow the parameterization approach, but uses a unified parameterization that is applicable to any horizontal resolutions between those typically used by GCMs and CRMs. It is shown that a key to construct such a unified parameterization is to eliminate the assumption of small fractional area covered by convective clouds, which is commonly used in the conventional cumulus parameterizations either explicitly or implicitly. A preliminary design of the unified parameterization is presented, which demonstrates that such an assumption can be eliminated through a relatively minor modification of the existing mass-flux based parameterizations. Partial evaluations of the unified parameterization are also presented. ROUTE II follows the "multi-scale modeling framework (MMF)" approach, which takes advantage of explicit representation of deep moist convection and associated cloud-scale processes by CRMs. The Quasi-3-D (Q3-D) MMF is an attempt to broaden the applicability of MMF without necessarily using a fully three-dimensional CRM. This is accomplished using a network of cloud-resolving grids with large gaps. An outline of the Q3-D algorithm and highlights of preliminary results are reviewed.
Highlights
In his landmark paper published near the beginning of the 20th century, Vilhelm Bjerknes (Fig. 1) pointed out that necessary and sufficient conditions for the rational solution of the forecasting problem are the following (Bjerknes, 1904): 1. One has to know with sufficient accuracy the state of the atmosphere at a given time; 2
Route II with the Q3-D cloud-resolving models (CRMs) is extremely promising since its results are close to those of a 3-D CRM while computationally it is more efficient by almost two orders of magnitude
As far as the representation of deep moist convection is concerned, conventional general circulation models (GCMs) and CRMs have quite different formulations of model physics, each of which is applicable to only a limited range of horizontal resolution
Summary
In his landmark paper published near the beginning of the 20th century, Vilhelm Bjerknes (Fig. 1) pointed out that necessary and sufficient conditions for the rational solution of the forecasting problem are the following (Bjerknes, 1904): 1. One has to know with sufficient accuracy the state of the atmosphere at a given time; 2. The rationale for the main theme of the paper is the following assessment of the current status of numerical modeling of the atmosphere: As far as the representation of deep moist convection is concerned, only two kinds of model physics are used at present: highly parameterized and explicitly simulated Besides those models that explicitly simulate turbulence such as Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES) models, we have two discrete families of atmospheric models as shown in Fig. 2: one is represented by the conventional general circulation models (GCMs) and the other by the cloud-resolving models (CRMs).
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