1. PROJECT ------------------- Title: Ocean stratification impedes particulate transport to the plumes of Enceladus: data and software Funding organisation: Science and Technology Facilities Council (STFC) grant ST/W507763/1 2. DATASET ------------------- Description: All data and software supporting (and required to reproduce) the results of Ocean stratification impedes particulate transport to the plumes of Enceladus. The Massachusetts Institute of Technology Ocean General Circulation model (MITgcm) is configured for the study of Enceladus: an ice-covered, ocean-bearing moon of Saturn. Simulations are performed in a 2D latitude-depth configuration to investigate the presence of stratification within Enceladus’ ocean, and explicitly determine the transport timescale of hydrothermally-derived tracers to Enceladus’ south polar ice-ocean interface. Numerical solutions are compared with analytical solutions from a theoretical model. This archive includes: - Raw outputs from the MITgcm simulations, performed across ranges in ocean mean salinity, effective vertical diffusivity and GM (i.e., eddy) diffusivity. - Processed data used to produce all figures in the main text and supplementary material. - A copy of the MITgcm version 68q used to produce the raw data. - Configuration files used to configure the MITgcm for the study of Enceladus. Includes pickup files for one example equilibrated simulation. - Python scripts used to process the MITgcm raw data and to compute the analytical solutions. - Python scripts used to produce all figures presented in the main text and supplementary material. - The conda environment used to successfully run the Python code. See additional README files within subdirectories for further details about their contents. : Cite dataset as: Ames, Flynn (2024): Ocean stratification impedes particulate transport to the plumes of Enceladus: data and software. University of Reading. Dataset. https://researchdata.reading.ac.uk/id/eprint/1308 Publication Year: 2024 Creator(s): Flynn Ames Organisation(s): University of Reading, Department of Meteorology Rights-holder(s): Flynn Ames 3. TERMS OF USE ------------------- Copyright Flynn Ames 2024. This dataset is licensed by the rights-holder under a Creative Commons Attribution 4.0 International Licence: https://creativecommons.org/licenses/by/4.0/ . 4. LIST OF CONTENTS (MASTER DIRECTORY) ------------------- - data: Raw and processed data used to produce figures of Ames et al., 2024. Raw data is in NetCDF format. Processed data are in .npz (compressed numpy) format. See README therein for further details. - envs: Contains Yaml file specifying the conda environment (packages and versions) used to run the python code in this archive. See README therein for instructions to create and activate this environment. - figure\*.py: "Compute" files create and save the data to be plotted. "Plot" files produce and save the plots. - figures: Directory (empty by default) to save figures. - functions_and_constants: Contains JSON files with all parameters/constants used in this code and work, and a python file containing custom python functions used. - MITgcm_checkpoint68q.tar.gz: Compressed copy of the MITgcm version 68q used to perform numerical simulations in Ames et al., 2024. - MITgcm_configuration_setup_files: All files required to configure the MITgcm as done in Ames et al., 2024. See README therein for further details. - process_MITgcm_outputs_main.py: Python script to reproduce processed MITgcm data for the control simulations of Ames et al., 2024. - process_MITgcm_outputs_sensitivity.py: Near identical script to reproduce processed data for sensitivity tests of Ames et al., 2024 - produce_evaluate_T_freeze_approx.py: Script that performs linear regression to non-linear function for freezing temperature, to obtain coefficients for linear approximation for the water freezing temperature - produce_T_crit_data.py: Script to compute the critical temperature T_crit manually, used for fitting a linear approximation, used in analytical solutions. 5. METHODS and PROCESSING ------------------- All outputs are generated with the code provided. The MITgcm is actively maintained at: (https://github.com/MITgcm/MITgcm). Instructions on how to compile and run the MITgcm on a computing cluster, among other details, can be found in the MITgcm documentation: (https://mitgcm.readthedocs.io/en/latest/getting_started/getting_started.html). If the reader is unfamiliar with the MITgcm, yet hoping to use the MITgcm for research, the author recommends completing the first three tutorial experiments found here: (https://mitgcm.readthedocs.io/en/latest/examples/examples.html). NetCDF raw data output can additionally be read and processed with software other than python. Matlab and Python subroutines to read the MITgcm outputs are available within the MITgcm github repository (https://github.com/MITgcm/MITgcm/tree/master/utils).