10:15 〜 10:30
[AAS08-06] A Force-Response Framework for Convective Aggregation: Insights from VVM, SCALE, and CM1
★Invited Papers
キーワード:Forced-response Framework, Convective aggregation, Radiative-convective equilibrium
This study investigates convective aggregation (CA) among three cloud-resolving models (VVM, SCALE, and CM1) based on a modeling framework proposed by Huang and Wu (2022). The modeling framework introduces the competing effects between the convection-SST feedback (CSF) and the moisture-convection feedback (MCF) using the VVM coupled to a mixed-layer slab ocean. The initial SST gradient is imposed to force the development of CA, and convection could respond differently depending on the mixed layer depth. We refer to this as a Force-response Framework (FF) and formulate it as a nonlinear system incorporating the growth and dissipation rates of subsidence fraction. Using FF, we compare the growth rate of subsidence fraction among VVM, SCALE, and CM1. Our results show that VVM and CM1 exhibit similar growth rates, whereas SCALE has a smaller growth rate. However, the equilibrium of subsidence fraction differs among the models. CM1 has the smallest fraction, while it is greatest in VVM. Huang and Wu (2022) also reported that larger convective clouds can efficiently drive CA circulation, which can be reflected in the subsidence. Thus, we hypothesize that differences in convective aggregation arise from differences in convective system structures. To investigate this, we will analyze the evolution of cloud size distributions among the three models to understand the role of convective systems in driving CA circulation. Additionally, we will further use an intermediate model that allows predefined convective cloud sizes to explore their impact on large-scale circulations.