https://github.com/dennissergeev/stretched_mesh_code
Scripts to reproduce figures for the paper
https://github.com/dennissergeev/stretched_mesh_code
atmospheric-modelling atmospheric-science climate-model exoplanets idealized-numerical-simulations numerical-modelling planetary-science unstructured-meshes
Last synced: 8 months ago
JSON representation
Scripts to reproduce figures for the paper
- Host: GitHub
- URL: https://github.com/dennissergeev/stretched_mesh_code
- Owner: dennissergeev
- License: mit
- Created: 2023-05-22T12:08:55.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2024-05-23T12:34:18.000Z (about 2 years ago)
- Last Synced: 2024-06-13T16:38:37.178Z (almost 2 years ago)
- Topics: atmospheric-modelling, atmospheric-science, climate-model, exoplanets, idealized-numerical-simulations, numerical-modelling, planetary-science, unstructured-meshes
- Language: Jupyter Notebook
- Homepage:
- Size: 27.2 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
The impact of the explicit representation of convection on the climate of a tidally locked planet in global stretched-mesh simulations.
Repository contents
Notebooks and Python scripts are in the [`src/scripts/`](src/scripts/) directory, while the figures are in the [`src/figures/`](src/figures/) directory.
| # | Figure | Notebook |
|:---:|:-------|:---------|
| 1 | [Summary of the simulation setup](src/figures/regr__hab1_mod_c192_s10e_s10r_s10p_p__cell_width__c12_mesh__summary.pdf) | [Show-Mesh-And-Cell-Sizes.ipynb](https://nbviewer.jupyter.org/github/dennissergeev/stretched_mesh_code/blob/main/src/scripts/Show-Mesh-And-Cell-Sizes.ipynb) |
| 2 | [Clouds and precipitation in the simulations with stretched and quasi-uniform mesh](src/figures/combi_hab1_mod_c192_s10e_s10r_s10p_p__inst_diag__tot_col_m_c_tot_prec__grat__precip_sum_hist__cloud_types.pdf) | [Cloud-Precip-Snap-Hist.ipynb](https://nbviewer.jupyter.org/github/dennissergeev/stretched_mesh_code/blob/main/src/scripts/Cloud-Precip-Snap-Hist.ipynb) |
| 3 | [Meridional and time mean profiles of vertically integrated moisture diagnostics](src/figures/regr__hab1_mod_c192_s10e_s10r_s10p_p__tot_col_m_v_tot_col_m_c_tot_col_m_cl_tot_col_m_ci__tmm.pdf) | [Meridional-Mean-Cloud-Profiles.ipynb](https://nbviewer.jupyter.org/github/dennissergeev/stretched_mesh_code/blob/main/src/scripts/Meridional-Mean-Cloud-Profiles.ipynb) |
| 4 | [Vertical profiles of time mean diagnostics in the substellar region](src/figures/regr__hab1_mod_c192_s10e_s10r_s10p_p__tot_col_m_v_tot_col_m_c_tot_col_m_cl_tot_col_m_ci__tmm.pdf) | [Substellar-Vertical-Profiles.ipynb](https://nbviewer.jupyter.org/github/dennissergeev/stretched_mesh_code/blob/main/src/scripts/Substellar-Vertical-Profiles.ipynb) |
| 5 | [Thermodynamic and circulation regime](src/figures/regr__hab1_mod_c192_s10e_s10r_s10p_p__t_sfc_toa_olr_u_zm__w_zm_day__tm_map.pdf) | [Thermodynamic-And-Circulation-Regime.ipynb](https://nbviewer.jupyter.org/github/dennissergeev/stretched_mesh_code/blob/main/src/scripts/Thermodynamic-And-Circulation-Regime.ipynb) |
| 6 | [Maps of precipitation rate](src/figures/regr__hab1_mod_c192_s10e_s10r_s10p_p__tot_prec_ls_prec_conv_prec__tm_map.pdf) | [Precipitation-Maps.ipynb](https://nbviewer.jupyter.org/github/dennissergeev/stretched_mesh_code/blob/main/src/scripts/Precipitation-Maps.ipynb) |
| 7 | [Circulation regime bistability](src/figures/thai_hab1__c192_s10e_s10r_s10p_p__inst_diag__toa_osr__t_sfc__wind_08160m.pdf) | [Show-Bistability.ipynb](https://nbviewer.jupyter.org/github/dennissergeev/stretched_mesh_code/blob/main/src/scripts/Show-Bistability.ipynb) |
How to reproduce figures
Set up environment
To recreate the required environment for running Python code, follow these steps. (Skip the first two steps if you have Jupyter with `nb_conda_kernels` installed already.)
1. Install conda or mamba, e.g. using [miniforge](https://github.com/conda-forge/miniforge).
2. Install necessary packages to the `base` environment. Make sure you are installing them from the `conda-forge` channel.
```bash
mamba install -c conda-forge jupyterlab nb_conda_kernels conda-lock
```
3. Git-clone or download this repository to your computer.
4. In the command line, navigate to the downloaded folder, e.g.
```bash
cd /path/to/downloaded/repository
```
5. Create a conda environment from the lock file.
```
conda-lock install --name stretched_mesh_env conda-lock.yml
```
Open the code
1. Start the Jupyter Lab, for example from the command line (from the `base` environment).
```bash
jupyter lab
```
2. Open notebooks in the `stretched_mesh_env` environment start running the code.
System information
--------------------------------------------------------------------------------
Date: Tue Apr 30 11:43:52 2024 BST
OS : Linux
CPU(s) : 56
Machine : x86_64
Architecture : 64bit
RAM : 502.6 GiB
Environment : Python
File system : ext4
Python 3.12.3 | packaged by conda-forge | (main, Apr 15 2024, 18:38:13) [GCC
12.3.0]
numpy : 1.26.4
scipy : 1.13.0
IPython : 8.22.2
matplotlib : 3.8.4
scooby : 0.9.2
--------------------------------------------------------------------------------
```bash
python -c 'import scooby; print(scooby.Report())'
```