https://github.com/e3sm-project/a-prime

ACME Priority Metrics
https://github.com/e3sm-project/a-prime

climate climate-science

Last synced: 9 months ago
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ACME Priority Metrics

• Host: GitHub
• URL: https://github.com/e3sm-project/a-prime
• Owner: E3SM-Project
• License: bsd-3-clause
• Created: 2017-05-31T23:28:20.000Z (about 9 years ago)
• Default Branch: master
• Last Pushed: 2019-11-04T16:25:45.000Z (over 6 years ago)
• Last Synced: 2025-06-04T03:21:02.815Z (about 1 year ago)
• Topics: climate, climate-science
• Language: Python
• Size: 709 KB
• Stars: 1
• Watchers: 129
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README
  • License: LICENSE

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README

          
Python based scripts to generate E3SM Coupled Priority Metrics 

Basic pre-steps:

   Clone E3SMM a-prime repository:

     git clone https://github.com/E3SM-Project/a-prime

About MPAS-Analysis:

   MPAS-Analysis is loaded as a git submodule and this is done

   for the user in the run_aprime driver. There is only one

   circumstance in which the user has to load the submodule

   manually, and that is when he/she wants to run aprime in

   batch mode *and* the submodule has never been cloned before.

   In that case, do the following:

     cd a-prime/python/MPAS-Analysis

     git submodule update --init

   An alternative to this is to run a-prime on the login node

   for the first time, so that the git submodule is initialized

   for the user inside the driver.

About conda and other environment issues:

   The system is set up to load its own environment within the

   driver, therefore the user needs to do *nothing* in that sense.

   The e3sm-unified conda environment specific for a particular

   machine is loaded properly inside run_aprime, and that includes

   the updated version of nco.

Supported machines as of September 2017:

   1) edison/cori

   2) titan/rhea

   3) acme1/aims4

About batch mode:

   As of September 2017, it is available on edison and titan.

Main steps to run aprime:

I. Copy the template script run_aprime.bash to a user version

   (e.g. run_aprime_$user.bash)

II. Set case specific variables in driver (run_aprime_$user.bash)

    script. See driver for more instructions on this.

III. Execute driver script (e.g. "run_aprime_$user.bash") to run

     the diagnostics and create an html file.

NOTES ABOUT SOFTWARE DESIGN:

1. The script is flexible and extensible, meaning it is easy to add 

   more variables and observational datasets to the current set.

2. Climatology diagnostics variables and their details are listed in the bash_scripts/ files:

	 var_list_model_vs_model_climo.bash	For model vs. model comparisons

	 var_list_model_vs_obs_climo.bash	For model vs. obs comparisons

   Time Series diagnostics variables and their details are listed in the files:

	 var_list_model_vs_model_time_series.bash	For model vs. model comparisons

	 var_list_model_vs_obs_time_series.bash		For model vs. model comparisons

	

   These lists can be easily extended to include other variables as needed,

   simply by adding their details in the format used in the files. 

3. Multiple cases can be compared against a ref_case simultaneously, each comparison generating its own webpage.

   In the works!

4. The scripts generate separate log files for each step, making it easy to debug

5. Several intermediary data files are written at various steps, making it easy to debugs

6. The data files used for making the plots are also saved.

Things to do:

1. Accelerate code by harnessing parallelism further by submitting more jobs in the background

2. Remove redundancies

3. Generate mapping files for T85 and T341 (high res project) runs.