Spatially inhomogeneous phase change, and its effect on cloud turbulence (part 2)

README: DNS Post-Processing and Plotting Scripts Manuscript Information This repository contains: • Post-processing scripts for DNS model output • Processed data files • Plotting scripts to generate Figures 1–3 in the manuscript: “Spatially inhomogeneous phase change, and its effect on cloud turbulence” Submitted to Geophysical Research Letters (GRL), AGU Repository Structure . ── data_files/ # Processed data used in figures 1 and 2 ── contour_data/ # Processed data used in figures 3 ── re_plots/ # Python scripts to generate manuscript figures ── post_processing_codes/ # Scripts to compute intermediate data from raw DNS output ── README # This documentation Figure Reproducibility Guide The plotting scripts to reproduce Figure 1-3 are available in the plot_scripts/ folder. Figure 1: Correlation and Mean Analysis Use following plotting scripts to regenerate the Figure 1 of the manuscripts: • QT_corr.py: Computes spatial correlation of QT • Qqv_corr.py: Computes correlation between Q and qv • fluc_Tavg.py: Plots average temperature fluctuations • Qavg.py: Domain average of Q • Legends: o (a), (b): legend_corr.py o (c), (d): legend_avg.py Figure 2: TKE and Droplet Radius Analysis Following plotting script to be used to regenerate the Figure 2: • nolegend_tke_spectra.py (set time=0.2 for early time, time=10 for late time) • tke_mean.py: Time evolution of domain-averaged TKE • tke_thresold10.py: TKE above a threshold • rpdf.py: Radius PDF plot • Legends: o (a), (b): legend_spectra.py o (c), (d): legend_tke.py Figure 3: 3D Contours for Different Grid Resolutions 3D contours of the Figure 3 can be reproduced using following scripts: • (256)³ without phase change: 256_np3dcontour_6s.py • (256)³ with phase change: 256_3dcontour_6s.py • (1024)³ without phase change: 1024_np3dcontour_6s.py • (1024)³ with phase change: 1024_3dcontour_6s.py How To Use This repository contains three parts. All three parts are available on Zenodo: Part1: 10.5281/zenodo.17293981 Part 2: 10.5281/zenodo.17309680 Part 3: 10.5281/zenodo.17309818 All three parts are required to access the full dataset. 1. Using following Linux command unzip the dataset zip -s 0 GRL_Data_Repository.zip --out combined_repo.zip mkdir DNS_data_repo unzip combined_repo.zip -d DNS_data_repo which has the complete repository data folder name GRL_Data_Repository 2. The folders named data_files and countour_data contain all processed datasets to reproduce Figures 1–3. 3. Run plotting scripts Ensure Python 3 and required libraries (numpy, matplotlib, xarray) are installed. Example: cd re_plots python QT_corr.py Post-Processing Code Descriptions Located in post_processing_codes/: • TKE Spectra Calculation: tke_high.py — Computes TKE from velocity fields. • Droplet Radius PDF: pdf_cal — Directory containing scripts for radius PDF. • Domain Average Calculations: o 256_avgQT.f90: Domain average of Q and T for 256³ domain o particle_analysis.f90: Particle statistics by averaging over particles • 3D Contour Plot Preparation: o contour.f90: For preparing 3D contour files for 256 and 1024 domain sizes These Fortran codes should be compiled and run within their respective domain folders (e.g., 256/, 512/, 1024/), depending on simulation size. License This dataset is shared under the Creative Commons Attribution 4.0 (CC-BY 4.0) license. Contact For questions or additional data access: Dr. Bipin Kumar Email: [email protected] Affiliation: Indian Institute of Tropical Meteorology, Pune