Running ADF on NIRD

[adagj]

The new atmospheric diagnostics package can be installed using conda. However, using a more recent conda version can lead to extended time (i.e. days) resolving dependencies. A more efficient approach is utilizing the conda module on NIRD. This method bypasses the need for personal conda installation and bashrc modifications, aligning with sigma2's recommendation against adding conda configurations to bashrc. I tested this method by removing my conda installation, and it proved efficient and effective:

1. On NIRD, load the conda module: $ module load Anaconda3/2022.05
2. create a directory where the conda files can be stored:
   $ mkdir /projects/NS____K/user/conda
3. set that as your conda storage space:
   $ my_conda_storage=/cluster/projects/NS____K/user/conda
$ export CONDA_PKGS_DIRS=${my_conda_storage}/package-cache
4. Clone the ADF repository:
   $ git clone https://github.com/NCAR/ADF ADF
$ cd ADF
5. create the conda environment (this will probably take some time):
   $ conda env create -f env/conda_environment.yaml
6. I needed to do a new git pull at this point:
   $ git pull

Steps 1 through 5 are necessary only once. Each subsequent time you want to run the ADF diagnostics, you can skip these steps.

For each time you want to run the ADF diagnostics:
7. Activate the environment. The first time you need to log out and in of NIRD. Then:
$ module load Anaconda3/2022.05
$ source ${EBROOTANACONDA3}/bin/activate
$ conda activate adf_v0.11

8. Running the diagnostics: ./run_adf_diag config_yourconfigname.yaml

9. To see some examples of the config_yourconfigname.yaml file, please have a look at /datalake/NS2345K/adagj/ADFout/config_ada_test.yaml or /datalake/NS2345K/mvertens/ADF/input_file//config_test_ghgmam4.yaml

10. For making the diagnostics available for all, please use the folder /nird/datapeak/NS9560K/www/diagnostics/. To be set in cam_diag_plot_loc in the config file. Output can be view from https://ns9560k.web.sigma2.no/datapeak/diagnostics/.

We recommend to run on the ipcc node in order to have sufficient available memory.

Useful links:

• https://justin-richling.github.io/ADF-Tutorial/README.html
• https://github.com/NCAR/ADF
• https://documentation.sigma2.no/software/userinstallsw/conda.html

[adagj]

Improvements might involve:

• Shared directory for observations. The observations used by the ADF diagnostics are located here at the moment: /projects/NS9560K/mvertens/obs_data/ADF_obs
• ADF repository for NorESM including specific variables from Oslo-Aero. Is the best option to make a fork?
• Add additional observations

[oyvindseland]

Does the diagnostics require the use of one specific variable or can it be a sum of variables. One example both for MAM4 and Oslo-Aero is the total amount of a chemical compound, e.g. sulfate. This can be found by summing up several tracers.

[Ovewh]

Cool Thanks Ada. Just, a comment no need for everyone install their own conda environment for running ADF. Just load the Anaconda module as you described and then if we agree on a location for the ADF conda environment one can just do, conda activate /path/to/adf/environment/. Having many conda environments can easily fill up the project space with too many files.

Also might be worth looking into running the diagnostics directly on the preproc queue on betzy and then copy output to nird? Atleast then there should be enough memory.

[adagj]

Tomas Torsvik is preparing the common conda environment, so that will be ready over the summer.

[Ovewh]

Sounds good, ok until that is ready, i think it is better to install conda environments under /nird/scratch/username. Not in a project directory.