Japan Geoscience Union Meeting 2021

Presentation information

[E] Oral

A (Atmospheric and Hydrospheric Sciences ) » A-AS Atmospheric Sciences, Meteorology & Atmospheric Environment

[A-AS01] Large-scale moisture and organized cloud systems

Fri. Jun 4, 2021 1:45 PM - 3:10 PM Ch.07 (Zoom Room 07)

convener:Satoru Yokoi(Japan Agency for Marine-Earth Science and Technology), Hiroaki Miura(The University of Tokyo), Atsushi Hamada(University of Toyama), Masaki Satoh(Atmosphere and Ocean Research Institute, The University of Tokyo), Chairperson:Satoru Yokoi(Japan Agency for Marine-Earth Science and Technology), Atsushi Hamada(University of Toyama)

2:55 PM - 3:10 PM

[AAS01-06] Statistical Analysis of Cumulus Convection in Radiative-Convective Equilibrium Based on Canonical Ensemble Framework

*Takuya Jinno1, Hiroaki Miura1 (1.Graduate School of Science, The University of Tokyo)

Keywords:radiative-convective equilibrium, cumulus convection, canonical ensemble

The collective characteristics of cumulus convection in statistical equilibrium vary in response to environmental large-scale forcing. Here we view the population of weakly interacting deep cumulus clouds under ideal conditions as a Gibbs canonical ensemble with convective kinetic energy as a reference quantity. With this as a starting point, we assess theoretical frameworks based on equilibrium statistical mechanics that relates the macroscopic state of the system to the probability distribution of individual cumulus convection. From these considerations, the form of the parameter representing the macroscopic state, which corresponds to the inverse temperature in statistical mechanics, can be inferred from the bulk thermodynamic quantities for the troposphere. The analysis of the cumulus convection ensemble generated by cloud-resolving simulations in radiative-convective equilibrium shows that the frequency distribution of convective cores calculated from the updraft kinetic energy follows a negative exponential (figure 1). Comparison between area-averaged thermodynamic quantities and the scaling exponent of cumulus probability distribution is also discussed.