Development of a Quasi‐3D Multiscale Modeling Framework: Motivation, Basic Algorithm and Preliminary results

Abstract

A new framework for modeling the atmosphere, which we call the quasi-3D (Q3D) multi-scale modeling framework (MMF), is developed with the objective of including cloud-scale three-dimensional effects in a GCM without necessarily using a global cloud-resolving model (CRM). It combines a GCM with a Q3D CRM that has the horizontal domain consisting of two perpendicular sets of channels, each of which contains a locally 3D grid-point array. For computing efficiency, the widths of the channels are chosen to be narrow. Thus, it is crucial to select a proper lateral boundary condition to realistically simulate the statistics of cloud and cloud-associated processes. Among the various possibilities, a periodic lateral boundary condition is chosen for the deviations from background fields that are obtained by interpolations from the GCM grid points. Since the deviations tend to vanish as the GCM grid size approaches that of the CRM, the whole system of the Q3D MMF can converge to a fully 3D global CRM. Consequently, the horizontal resolution of the GCM can be freely chosen depending on the objective of application, without changing the formulation of model physics.To evaluate the newly developed Q3D CRM in an efficient way, idealized experiments have been performed using a small horizontal domain. In these tests, the Q3D CRM uses only one pair of perpendicular channels with only two grid points across each channel. Comparing the simulation results with those of a fully 3D CRM, it is concluded that the Q3D CRM can reproduce most of the important statistics of the 3D solutions, including the vertical distributions of cloud water and precipitants, vertical transports of potential temperature and water vapor, and the variances and covariances of dynamical variables. The main improvement from a corresponding 2D simulation appears in the surface fluxes and the vorticity transports that cause the mean wind to change. A comparison with a simulation using a coarse-resolution 3D CRM is also made.

A Community Atmosphere Model With Superparameterized Clouds

“…As the outer grid size of Jung and Arakawa's [2010] MMF is refined to that of CRM, their MMF naturally converges to a GCRM.…”

Toward unification of the multiscale modeling of the atmosphere

“…AS and many other mass-flux based parameterizations (e.g., Tiedtke, 1989;Kain and Fritsch, 1990;Emanuel, 1991;Gregory and Rowntree, 1990;Zhang and McFarlane, 1995) exclude this possibility by assuming σ 1, either explicitly or implicitly, where σ is the fractional area covered by all convective clouds in the grid cell. With this assumption, the temperature and water vapor to be predicted are essentially those for the cloud environment.…”

“…The simulations are performed by applying the 3-D anelastic vorticity equation model of Jung and Arakawa (2008) to a horizontal domain of 512 km×512 km with a 2 km grid size. Other experimental settings are similar to the benchmark simulations used by Jung and Arakawa (2010). Two 24-h simulations are made, one with and the other without background shear.…”

“…It is a complement of ROUTE I, simulating the details of cloud processes at least partially. The Q3-D MMF is described in detail by Jung and Arakawa (2010) so that this paper gives only a brief outline of the framework and some highlights of its preliminary results.…”

“…Consequently, the horizontal resolution of the GCM can be freely chosen depending on the objective of application without changing the formulation of model physics. For more details of the Q3-D algorithm, see Jung and Arakawa (2010).…”