Diurnal Variation of Simulated Cumulus Convection in Radiative-Convective Equilibrium

Abstract

This study investigates the representation of the diurnal variation of cumulus convection in radiative-convective equilibrium states in an area of 200 km by 200 km without large-scale forcing by using a non-hydrostatic model with sub-kilometer horizontal resolutions. The experiment with the horizontal resolution of 200 m successfully reproduced the diurnal variability of the trimodal characteristics of cumulus convection. We demonstrated that the horizontal resolution dependence largely affects the trimodal structure of clouds and the characteristics of precipitation and its diurnal variation. With the coarse resolution of 1600 m, a signature of convective aggregation appeared and the diurnal variation of convection was not clearly seen. We further examined the mechanisms for the diurnal variation of cumulus convection by focusing on the temporal and vertical variations of radiative and latent heating anomalies. The diurnal variability of the static stability caused by both radiative and latent heating plays a role in characterizing the diurnal variation of the cumulus convection.(Citation: Yanase, T., and T. Takemi, 2018: Diurnal variation of simulated cumulus convection in radiative-convective equilibrium. SOLA, 14, 116−120,

New Critical Length for the Onset of Self‐Aggregation of Moist Convection

“…This issue can be discussed by comparing H2000L384 (aggregated case) with H1000L384 (scattered case). We found that the low‐cloud amount in the subsidence region during Days 11–20 was larger in H2000L384 than in H1000L384 (Figures S4d and S4c), which is consistent with the results of MB15 and Yanase and Takemi (2018). This suggests that the low‐resolution experiments represent a larger amount of low cloud, the enhanced radiative cooling strengthens the positive feedback and u s , and the critical length becomes smaller than that of high‐resolution experiments.…”

“…In numerical simulations under the RCE framework, moist convection was organized into an aggregated cloud system even under constant sea surface conditions (Held et al, 1993; Tompkins & Craig, 1998a). This organization process is called convective self‐aggregation (CSA) and has been intensively studied using a wide variety of models in recent years (Arnold & Randall, 2015; Bretherton et al, 2005, hereafter BBK05; Emanuel et al, 2014; Haerter, 2019; Hohenegger & Stevens, 2016; Khairoutdinov & Emanuel, 2013; Satoh & Matsuda, 2009; Tompkins, 2001b; Windmiller & Craig, 2019; Yanase & Takemi, 2018). It has recently been pointed out that CSA alters even mean fields (BBK05; Bony et al, 2015, 2016; Cronin & Wing, 2017; Drotos et al, 2020; Holloway et al, 2017; Mauritsen & Stevens, 2015; Noda et al, 2019; Tobin et al, 2012; Wing, 2019).…”

The Diurnal Path to Persistent Convective Self‐Aggregation

“…Several studies mimic diurnal variation through oscillating surface temperatures (Cronin et al., 2015 ; Liu & Moncrieff, 1998 ; Ruppert & Hohenegger, 2018 ; Ruppert & O’Neill, 2019 ; Tian et al., 2006 ; Yanase & Takemi, 2018 ). Under such conditions, recent simulations demonstrated the spontaneous formation of MCS‐like clusters (Haerter et al., 2020 ), which appeared only when the surface temperature amplitude was sufficiently large (≳3.5 K).…”

“…Our study reaches three main conclusions: (a) Fine resolution accelerates the emergence of persistent dry patches when the surface temperature oscillates. This identifies a key difference to classical RCE setups, where it is known that fine model resolution can hamper CSA (Jeevanjee & Romps, 2013 ; Muller & Bony, 2015 ; Muller & Held, 2012 ), whereas coarse resolution can support it and even mask the diurnal cycle (Yanase & Takemi, 2018 ). (b) For oscillating surface temperatures high resolution gives rise to mesoscale cold pools that are larger and travel faster.…”

Characteristic Form and Distance in High‐Level Hierarchical Structure of Self‐Aggregated Clouds in Radiative‐Convective Equilibrium

“…To understand cloud systems modulated by the external environment, it is necessary to investigate the intrinsic characteristics of cloud organization, which have been studied by simulating radiative‐convective equilibrium (RCE) using explicitly represented convection models (Bretherton et al., 2005; Held et al., 1993; C. J. Muller & Held, 2012; Patrizio & Randall, 2019, hereafter PR19; Tompkins & Craig, 1998; Yanase & Takemi, 2018; Yanase et al., 2020). The spontaneous organization of clouds in the RCE, commonly referred to as convective self‐aggregation (CSA), has received increasing attention in recent years (C. Muller et al., 2022; Wing et al., 2017).…”