Dataset for Supersaturation in the Wake of a Precipitating Hydrometeor and its Impact on Aerosol Activation

******************Dataset Details****************** 1. Article Title: Supersaturation in the Wake of a Precipitating Hydrometeor and its Impact on Aerosol Activation 2. Journal: Geophysical Research Letters, 47(22),  e2020GL091179, https://doi.org/10.1029/2020GL091179, 2020 3. Name and contact information:     Eberhard Bodenschatz,     Laboratory for Fluid Physics, Pattern Formation and Biocomplexity,     Max Planck Institute for Dynamics and Self-Organization,     Am Faßberg 17,     37077 Göttingen, Germany 4. Email: eberhard.bodenschatz@ds.mpg.de 5. Funding: This research was funded by the Marie - Sk lodowska Curie Actions (MSCA) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 675675), and an extension to programme COMPLETE by Department of Applied Science and Technology, Politecnico di Torino. 6. Abstract: The activation of aerosols impacts the life cycle of a cloud. A detailed understanding is necessary for reliable climate prediction. Recent laboratory experiments demonstrate that aerosols can be activated in the wake of precipitating hydrometeors. However, many quantitative aspects of this wake‐induced activation of aerosols remain unclear. Here, we report a detailed numerical investigation of the activation potential of wake‐induced supersaturation. By Lagrangian tracking of aerosols, we show that a significant fraction of aerosols are activated in the supersaturated wake. These “lucky aerosols” are entrained in the wake's vortices and reside in the supersaturated environment sufficiently long to be activated. Our analyses show that this wake‐induced activation of aerosols can contribute to the life cycle of the clouds. ******************Dataset Organization****************** 1. Datasets are organized in folders which correspond to Figures in the Letter or in the Supporting Information (e.g., Figure 1 or Figure S2). 2. Details of the entries can be found in the header of each dataset. 3. Details of the simulation setup can be found in the text of each Figure. ******************Software Details****************** 1. Open-source  LBM  library  Palabos  (Latt  et al., 2020). Link: https://palabos.unige.ch/ 2. Data visualization is achieved using open-source library ParaView version 5.7 and Gnuplot Version 5.2.