Implementing the HYbrid MAss flux Convection Scheme (HYMACS) in ICON – First idealized tests and adaptions to the dynamical core for local mass sources

Abstract

In this study, the Hybrid MAss flux Convection Scheme (HYMACS) is implemented in the ICOsahedral Non‐hydrostatic (ICON) weather prediction model. In contrast to conventional convection parametrization schemes, the convective up‐ and downdraughts are solely treated as subgrid‐scale processes in HYMACS, whereas the environmental subsidence is passed to the grid‐scale dynamics of the hosting model. It is shown that the operational anisotropic divergence damping in ICON distorts the grid‐scale dynamical response on the net mass transport parametrized by HYMACS. Thus, a revised numerical filter configuration is developed which focuses on both the compatibility to local mass sources (sinks) and the effective suppression of numerical modes inherent from the model's triangular grid. Evaluation of Jablonowski–Williamson dynamical core experiments reveal that the combination of an isotropic second‐order divergence damping with a modified version of the fourth‐order divergence damping outperforms against numerical filters based on diffusion. The obtained results are similar to the operational set‐up indicating just a minor effect on the properties of the dynamical core. Moreover, a series of dry mass lifting experiments with the revised numerical filter confirms its compatability with HYMACS. The distortion of the grid‐scale circulation is removed while gravity waves are still retained despite the potentially degenerative effect of the fourth‐order divergence damping. Analyses of kinetic energy spectra confirm the effective suppression of checkerboard noise for a wide range of different situations. The present study may be understood as a base for future applications of HYMACS with a full cloud model in real‐case studies.

Generalized eddy-diffusivity mass-flux (GEM) formulation for the parameterization of atmospheric convection and turbulence

“…Although parameterizations with relaxed fractional area occupied by the convection have been formulated (e.g. Arakawa and Wu, 2013;Grell and Freitas, 2014;Fan et al, 2015;Gerard, 2015;Zheng et al, 2016;Kwon and Hong, 2017;Malardel and Bechtold, 2019;Langguth et al, 2020;Wang, 2022), they still assume top-hat profiles as in the mass-flux formulation, and as is going to be seen in Section 4.3.1, such development is valid only if the convective radial velocity is assumed to be very small, and thus, the subgrid fluxes containing subgrid horizontal wind components, such as the subgrid horizontal transport, are neglected. However, at high resolutions, there might be a large variability between two consecutive grid cells (for example, in a grid cell a cumulonimbus cloud may develop, while in the neighbor one only shallow convection is present), and thus, neglecting the subgrid horizontal transport terms might result in large errors.…”

Generalized eddy‐diffusivity mass‐flux formulation for the parametrization of atmospheric convection and turbulence

“…However, the assumption of a very small fractional area occupied by the convection in every grid box of the numerical model is still a very important assumption in all mass‐flux formations (Arakawa & Wu, 2015; Yano, 2014b), which means that the grid spacing of the numerical models must be large enough such that this condition is respected regardless of the spatial variability of the convective elements. Although parametrizations with relaxed fractional area occupied by the convection have been formulated (e.g., Arakawa & Wu, 2013; Fan, 2015; Gerard, 2015; Grell & Freitas, 2014; Kwon & Hong, 2017; Langguth et al, 2020; Malardel & Bechtold, 2019; Wang, 2022; Zheng et al, 2016), they still assume top‐hat profiles as in the mass‐flux formulation; and as is going to be seen in Section 4.3.1, such development is valid only if the convective radial velocity is assumed to be very small, and thus the subgrid fluxes containing subgrid horizontal wind components, such as the subgrid horizontal transport, are neglected. However, at high resolutions, there might be a large variability between two consecutive grid cells (e.g., in a grid cell a cumulonimbus cloud may develop, whereas in the neighbor cell only shallow convection is present), and thus neglecting the subgrid horizontal transport terms might result in large errors.…”