Joon-Hee Jung

The Resolution Dependence of Model Physics: Illustrations from Nonhydrostatic Model Experiments

The goal of this paper is to gain insight into the resolution dependence of model physics, the parameterization of moist convection in particular, which is required for accurately predicting large-scale features of the atmosphere. To achieve this goal, experiments using a two-dimensional nonhydrostatic model with different resolutions are conducted under various idealized tropical conditions. For control experiments (CONTROL), the model is run as a cloud-system-resolving model (CSRM). Next, a ‘‘large-scale dynamics model’’ (LSDM) is introduced as a diagnostic tool, which is a coarser-resolution version of the same model but with only partial or no physics. Then, the LSDM is applied to an ensemble of realizations selected from CONTROL and a ‘‘required parameterized source’’ (RPS) is identified for the results of the LSDM to become consistent with CONTROL as far as the resolvable scales are concerned. The analysis of RPS diagnosed in this way confirms that RPS is highly resolution dependent in the range of typical resolutions of mesoscale models even in ensemble/space averages, while ‘‘real source’’ (RS) is not. The time interval of implementing model physics also matters for RPS. It is emphasized that model physics in future prediction models should automatically produce these resolution dependencies so that the need for retuning parameterizations as resolution changes can be minimized.

A Three-Dimensional Anelastic Model Based on the Vorticity Equation

Abstract A three-dimensional anelastic model has been developed using the vorticity equation, in which the pressure gradient force is eliminated. The prognostic variables of the model dynamics are the horizontal components of vorticity at all heights and the vertical component of vorticity and the horizontally uniform part of the horizontal velocity at a selected height. To implement the anelastic approximation, vertical velocity is diagnostically determined from the predicted horizontal components of vorticity by solving an elliptic equation. This procedure replaces solving the elliptic equation for pressure in anelastic models based on the momentum equation. Discretization of the advection terms uses an upstream-weighted partially third-order scheme. When time is continuous, the solution of this scheme is quadratically bounded. As an application of the model, interactions between convection and its environment with vertical shear are studied without and with model physics from the viewpoint of vorticity...

Preliminary Tests of Multiscale Modeling with a Two-Dimensional Framework: Sensitivity to Coupling Methods

Preliminary tests of the multiscale modeling approach, also known as the cloud-resolving convective parameterization, or superparameterization, are performed using an idealized framework. In this approach, a two-dimensional cloud-system resolving model (CSRM) is embedded within each vertical column of a general circulation model (GCM) replacing conventional cloud parameterization. The purpose of this study is to investigate the coupling between the GCM and CSRMs and suggest a revised method of coupling that abandons the cyclic lateral boundary condition for each CSRM used in the original cloud-resolving convective parameterization. In this way, the CSRM extends into neighboring GCM grid boxes while sharing approximately the same mass fluxes with the GCM at the borders of the grid boxes. With the original and revised methods of coupling, numerical simulations of the evolution of cloud systems are conducted using a two-dimensional model that couples CSRMs with a lower-resolution version of the CSRM with no physics [large-scale dynamics model (LSDM)]. The results with the revised method show that cloud systems can propagate from one LSDM grid column to the next as expected. Comparisons with a straightforward application of a single CSRM to the entire domain (CONTROL) show that the biases of the large-scale thermodynamic fields simulated by the coupled model are significantly smaller with the revised method. The results also show that the biases are near the smallest when the velocity fields of the LSDM and CSRM are nudged to each other with the time scale of a few hours and the thermodynamic field of the LSDM is instantaneously updated at each time step with the domain-averaged CSRM field.

Modeling the moist‐convective atmosphere with a Quasi‐3‐D Multiscale Modeling Framework (Q3D MMF)

The Q3D MMF (Quasi-Three-Dimensional Multiscale Modeling Framework) is a new generation of MMF that replaces the conventional subgrid-scale parameterizations in general circulation models (GCMs) with explicit simulations of cloud and associated processes by cloud-resolving models (CRMs). In the Q3D MMF, 3-D CRMs are applied to the channel domains that extend over GCM grid cells. To avoid “double counting” of the large-scale effects, only the eddy effects simulated by the CRMs are implemented into the GCM as far as the transports are concerned, while the total effects are implemented for diabatic processes. The CRMs recognize the large-scale horizontal inhomogeneity through the lateral boundary conditions obtained from the GCM through interpolation. To maintain compatibility between the GCM and CRMs, the averages of CRM variables over the GCM grid spacing are relaxed to the corresponding GCM variables with the advective time scale. To evaluate the Q3D MMF, a transition from a wave to strong vortices is simulated in an idealized horizontal domain. Comparison with a fully 3-D benchmark simulation shows that the Q3D MMF successfully predicts the evolution of the vortices. It also captures important statistics such as the domain-averaged surface precipitation rate, turbulent fluxes and subgrid-scale (co)variances. From tests with 3-D and 2-D CRMs, respectively, it is concluded that the ability to recognize large-scale inhomogeneities is primarily responsible for the successful performance of the Q3D MMF. It is also demonstrated that the use of two perpendicular sets of CRMs has positive impacts on the simulation.

A Study of the Stratospheric Major Warming and Subsequent Flow Recovery during the Winter of 1979 with an Isentropic Vertical Coordinate Model

Abstract The principal goal of this paper is to gain further insight into the dynamical processes during the stratospheric major warming of February and early March 1979, with a special emphasis on the recovery stage. To achieve this goal, first the entire evolution of the warming event is numerically simulated using an isentropic vertical coordinate model. Then the results from the following complementary points of view are quantitatively analyzed: wave effects on the mean flow, potential enstrophy conversion and transport, and potential vorticity redistribution on a synoptic chart. There is an indication that wavenumber 1 during the recovery stage amplifies through a mechanism within the stratosphere and propagates downward. The simulated Eliassen–Palm flux field shows that the amplified wave 1 is responsible for the mean flow acceleration in the recovery stage. It is therefore concluded that the in situ amplification mechanism for wave 1 plays a crucial role in the dynamics of the flow recovery. In ord...

Multiscale Modeling of the Moist-Convective Atmosphere

AbstractOne of the most important contributions of Michio Yanai to tropical meteorology is the introduction of the concepts of apparent heat source Q1 and apparent moisture sink Q2 in the large-scale heat and moisture budgets of the atmosphere. Through the inclusion of unresolved eddy effects, the vertical profiles of apparent sources (and sinks) are generally quite different from those of true sources taking place locally. In low-resolution models, such as the conventional general circulation models (GCMs), cumulus parameterization is supposed to determine the apparent sources for each grid cell from the explicitly predicted grid-scale processes. Because of the recent advancement of computer technology, however, increasingly higher horizontal resolutions are being used even for studying the global climate, and, therefore, the concept of apparent sources must be expanded rather drastically. Specifically, the simulated apparent sources should approach and eventually converge to the true sources as the hori...

Simulation of subgrid orographic precipitation with an embedded 2‐D cloud‐resolving model

By explicitly resolving cloud-scale processes with embedded two-dimensional (2-D) cloud-resolving models (CRMs), superparameterized global atmospheric models have successfully simulated various atmospheric events over a wide range of time scales. Up to now, however, such models have not included the effects of topography on the CRM grid scale. We have used both 3-D and 2-D CRMs to simulate the effects of topography with prescribed “large-scale” winds. The 3-D CRM is used as a benchmark. The results show that the mean precipitation can be simulated reasonably well by using a 2-D representation of topography as long as the statistics of the topography such as the mean and standard deviation are closely represented. It is also shown that the use of a set of two perpendicular 2-D grids can significantly reduce the error due to a 2-D representation of topography.