Convergence of Convective Updraft Ensembles With Respect to the Grid Spacing of Atmospheric Models

• Published in: Geophysical research letters 2019-12, Vol.46 (24), p.14817-14825
• Main Authors: Sueki, Kenta, Yamaura, Tsuyoshi, Yashiro, Hisashi, Nishizawa, Seiya, Yoshida, Ryuji, Kajikawa, Yoshiyuki, Tomita, Hirofumi
• Format: Article
• Language: English
• Subjects: Atmosphere; Atmospheric models; Boxes; Climate; Climate system; Cloud systems; Computational fluid dynamics; Computer applications; Computer simulation; Convection; Convergence; Cumulonimbus clouds; deep moist convection; Distance; Earth; grid‐refinement experiments; high‐resolution simulations; Large eddy simulation; Large eddy simulations; Mathematical models; Meteorologists; Moist convection; numerical convergence; Resolution; Simulation; terra incognita; Updraft; Width; Wind speed
• ISSN: 0094-8276; 1944-8007
• DOI: 10.1029/2019GL084491

Atmospheric deep moist convection can organize into cloud systems, which impact the Earth's climate significantly. High‐resolution simulations that correctly reproduce organized cloud systems are necessary to understand the role of deep convection in the Earth's climate system. However, there remain issues regarding convergence with respect to grid spacing. To investigate the resolution necessary for a reasonable simulation of deep convection, we conducted grid‐refinement experiments using state‐of‐the‐art atmospheric models. We found that the structure of an updraft ensemble in an organized cloud system converges at progressively smaller scales as the grid spacing is reduced. The gap between two adjacent updrafts converges to a particular distance when the grid spacing becomes as small as 1/20–1/40 of the updraft radius. We also found that the converged inter‐updraft distance value is not significantly different between Reynolds‐averaged Navier–Stokes simulations and large eddy simulations for grid spacings in the terra incognita range. Plain Language Summary Meteorologists use computer simulations to predict atmospheric phenomena. When simulating the atmosphere, they divide it into small boxes and calculate the changes in wind speed, amounts of moisture and precipitation, and other important variables in each box. Here, our question is how finely we should divide the atmosphere to obtain the correct “answer” in the simulations; we call this the convergence problem. The more finely we divide the atmosphere, the more closely the simulation results approach the correct answer, but the more computational resources we need. The convergence problem is an important topic for us when carrying out accurate atmospheric simulations with limited computational power. This paper has addressed this problem. The target of our simulation is a group of cumulonimbus clouds. We performed several simulations with progressively smaller boxes to investigate how finely we should divide the atmosphere to reach convergence. We found that we should divide the atmosphere so that the width of each box is as small as 1/20 to 1/40 of the width of an upward current in an individual cumulonimbus cloud. We believe that this paper provides a new guideline for accurate atmospheric simulations. Key Points We conducted grid refinement experiments with convection‐permitting atmospheric models to assess convergence of deep convective updrafts The experiments reveal that the statistics of conve