Improved Climate Simulation by Using a Double‐Plume Convection Scheme in a Global Model

Abstract

General circulation models (GCMs) are widely used for global weather forecasting and climate modeling. In a GCM, the convective parameterization, which represents the bulk effects of convection, is typically regarded as a large source of model uncertainty (Arakawa, 2004;Rybka & Tost, 2014;Tost et al., 2006). Cumulus convection interacts with other processes in complex ways. Heat and moisture are pumped out of the planetary boundary layer (PBL) by subgrid-scale cumulus cells in response to surface solar heating. Detrainment and/or re-evaporation from convective condensate and precipitation moisten the grid-scale environment, favoring large-scale condensation. Convective parameterizations also strongly regulate the partition of convective and large-scale precipitation over the tropics with resultant effects on clouds and tropical transients (Kim et al., 2012;Lin et al., 2013). The interdependency between subgrid-and grid-scale processes further influences the hydrological processes, cloud types, and thus cloud radiative forcing and its feedback (Arakawa, 2004;Hourdin et al., 2006).Apart from the mean states, the impact of convective parameterization on tropical variabilities has also been reported in some previous studies (

Resolution Sensitivity of the GRIST Nonhydrostatic Model From 120 to 5 km (3.75 km) During the DYAMOND Winter

“…This configuration is mainly targeted at high‐resolution applications due to physical and computational reasons. It differs from another model configuration of GRIST (Li et al., 2022) in aspects of the physics suite and physics–dynamics coupling.…”

“…This so‐called explicit dynamics–microphysics coupling differs from the fractional cloudiness parameterization typically used in large‐scale global models, in which the cloud microphysics is used for computing the “in‐cloud” process rates and does not have a direct interaction with the resolved‐scale model dynamics. The definition of “in‐cloud” introduces some additional assumptions for evaluating the sub‐grid cloud macrophysical properties (cf., Li et al., 2022).…”

“…In practice, because global weather and climate modeling differ significantly in terms of their spatial and temporal scales, the so‐called unification is pursued following two routes: (a) to maximize the possibility of constructing weather and climate models using a single model framework and dynamical core; and (b) to maximize the possibility of using a unified model formulation with minimum application‐specific changes for weather‐to‐climate forecast applications that are relevant to most operational business demands. Global weather and climate modeling research applications based on GRIST have been continuously pushed forward (e.g., Li & Zhang, 2022; Li et al., 2022; Zhang et al., 2021).…”

“…The Global‐to‐Regional Integrated forecast SysTem (GRIST; Li et al., 2022; Liu et al., 2020; Wang et al., 2019; Zhang et al., 2019, 2020, 2021; Zhou et al., 2020) has been developed to explore unified global weather and climate modeling. Many reasons have motivated the development of GRIST.…”

Impact of Convective Parameterizations on Atmospheric Mesoscale Kinetic Energy Spectra in Global High‐Resolution Simulations

“…The current operational weather and climate model configurations still do not entirely resolve the meso‐ and small‐scale convections and thus the forecast results largely depend on the CP. CP can drastically regulate the mean climate and tropical transient activity of a general circulation model (Li et al., 2022). Many studies have focused on the sensitivity of the simulations to different CP schemes (e.g., Fowler et al., 2020; Li et al., 2022).…”