31 May 2023
 | 31 May 2023

Technical note: Emulation of a large-eddy simulator for stratocumulus clouds in a general circulation model

Kalle Nordling, Jukka-Pekka Keskinen, Sami Romakkaniemi, Harri Kokkola, Petri Räisänen, Antti Lipponen, Antti-Ilari Partanen, Jaakko Ahola, Juha Tonttila, Muzaffer Ege Alper, Hannele Korhonen, and Tomi Raatikainen

Abstract. Here we present for the first time a proof of concept for an emulation-based method that uses a large-eddy simulations (LES) to present sub-grid cloud processes in a general circulation model (GCM). We focus on two key variables affecting the properties of shallow marine clouds: updraft velocity and precipitation formation. The LES is able to describe these processes with high resolution accounting for the realistic variability in cloud properties. We show that the selected emulation method is 5 able to represent the LES outcome with relatively good accuracy and that the updraft velocity and precipitation emulators can be coupled with the GCM practically without increasing the computational costs. We also show that the emulators influence the climate simulated by the GCM, but do not consistently improve or worsen the agreement with observations on cloud related properties. Although especially the updraft velocity at cloud base is better captured. A more quantitative evaluation of the emulator impacts against observations would, however, have required model re-tuning, which is a significant task and thus could 10 not be included in this proof-of-concept study. All in all, the approach introduced here is a promising candidate for representing detailed cloud and aerosol related sub-grid processes in GCMs. Further development work together with increasing computing capacity can be expected to improve the accuracy and the applicability of the approach in climate simulations.

Kalle Nordling et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-912', Anonymous Referee #1, 05 Jul 2023
  • RC2: 'Comment on egusphere-2023-912', Anonymous Referee #2, 11 Aug 2023
  • RC3: 'Comment on egusphere-2023-912', Anonymous Referee #3, 21 Aug 2023

Kalle Nordling et al.

Kalle Nordling et al.


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Short summary
This paper shows how use machine learning methods to for model of small scale atmospherics physics model (large eddy simulation) which cover physics to the 100 m scale and implement that model to global large scale model. Our results shows that the global model is stable and it provides meaningful results. This way we can include physic based presentation of sub-grid (physics which happens in 100 m scale) physics to the global model which resolution is in 100 km scale.