ERF-SDM Simulations of a Convection Cloud Chamber: Model Development, Benchmark Evaluation, and Aerosol-Cloud-Turbulence Interactions
Abstract. Convection cloud chambers provide a unique platform for investigating aerosol cloud turbulence interactions under well controlled laboratory conditions and for evaluating numerical cloud microphysics models. This study extends the Energy Research and Forecasting model coupled with the Super Droplet Method (ERF-SDM) to simulate statistically stationary cloud chamber experiments through the implementation of Monin Obukhov similarity theory on all chamber walls, continuous aerosol injection, and wall deposition of super droplets. The model is evaluated using the recent Pi Chamber benchmark configuration from the cloud chamber modeling community and laboratory measurements from the Michigan Technological University Pi Chamber. ERF-SDM successfully represents characteristic chamber circulation and qualitative aerosol-dependent microphysical responses under the prescribed boundary conditions. Process-oriented analyses show that increasing aerosol injection strongly reduces mean and root-mean-square supersaturation, with most of the adjustment occurring between injection rates of 1 and 50 cm⁻³ min⁻¹. Higher injection rates also produce smaller cloud droplets and narrower droplet size distributions. However, the spatial standard deviation of supersaturation does not decrease monotonically, indicating that regulation of the mean thermodynamic state is not accompanied by a corresponding reduction in centered spatial variability. The simulations further demonstrate a transition from an aerosol limited regime at low aerosol injection rates to a vapor limited regime at higher aerosol loading, where competition for available water vapor increasingly limits aerosol activation. These results demonstrate that ERF-SDM, with the new cloud chamber capabilities, can effectively simulate laboratory cloud chamber experiments and investigate the coupled interactions among turbulence, supersaturation fluctuations, aerosol activation, and cloud microphysical evolution, providing valuable insights for understanding aerosol and cloud interactions in Earth system models.
Dear authors,
Unfortunately, after checking your manuscript, it has come to our attention that it does not comply with our "Code and Data Policy".
https://www.geoscientific-model-development.net/policies/code_and_data_policy.html
Namely, your manuscript does not contain a Data Availability section. The GMD review and publication process depends on reviewers and community commentators being able to access, during the discussion phase, the code and data on which a manuscript depends, and on ensuring the provenance of replicability of the published papers for years after their publication. Please, therefore, publish all the data used to produce your work in one of the appropriate repositories and reply to this comment with the relevant information (link and a permanent identifier for it (e.g. DOI)) as soon as possible. We cannot have manuscripts under discussion that do not comply with our policy.
Later, if the Topical Editor decides to continue with the review or publication process of your manuscript and you are requested to upload a new version of it, then Data Availability section must be included citing the repository locations, and corresponding references added to the bibliography.
I must note that if you do not fix this problem, we cannot continue with the peer-review process or accept your manuscript for publication in GMD.
Juan A. Añel
Geosci. Model Dev. Executive Editor