This component contains postprocess scripts that can be used to basically validate the model components.
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Sven Karsten 1fc3a9d469 Release version 1.03.00 2 months ago
CCLM Renamed global_settings.py to global_settings.example to avoid potential overwriting of deployed setup 2 months ago
MOM5 Renamed global_settings.py to global_settings.example to avoid potential overwriting of deployed setup 2 months ago
auxiliary Added percentile task and cleaned up 3 months ago
.gitignore Added .gitignore 2 years ago
Readme.md Release version 1.03.00 2 months ago
load_modules_haumea.sh Changed permissions to executable 2 years ago
load_modules_hlrnb.sh Added generate_mom_forcing task. 2 years ago
load_modules_hlrng.sh Added generate_mom_forcing task. 2 years ago
load_modules_phy-4.sh Added new phy-4 to accepted machines 1 year ago
load_modules_phy-10.sh Added generate_mom_forcing task. 2 years ago
load_modules_target.template Added template for new targets 3 months ago

Readme.md

Purpose, Description

This is the repository for basic postprocess tasks for the individual models. The goal is to provide scripts for

Each user can add his/her own customized postprocess tasks as described at https://sven-karsten.github.io/iow_esm/usage/create_postprocess_task.html.

Authors

Versions

1.03.00 (latest release)

date author(s) link
2023-07-24 SK 1.03.00

changes

  • reactivated seasonal_percentile task
  • added process_raw_output_and_compress task
    • this task creates monthly means for the output and compresses the raw (postprocessed) data into a .tar.gz archive
  • a lot of polishing of the created plots and reports
  • added load_modules_target.sh template

dependencies

  • python environment as anaconda3 or miniconda3
  • cdo, nco, see load module scripts for your target

known issues

  • None

tested with

  • intensively tested on IOW servers, Berlin's and on Göttingen's HLRN machine on MOM5 and CCLM output
older versions

1.02.00

date author(s) link
2022-12-22 SK 1.02.00

changes

  • main task is now create_validation_report
    • validation report is Jupyter notebook containing figures and links to other notebooks that create these figures
  • obsolete tasks plot, plot_time_series, test have been removed
  • result directories can have prefix that is defined as "name" in global_settings.py
  • fixed bug with empty stations and regions
  • regions can be specified by giving mask files
    • mask should contain one variable "mask" that is one in the specific region and undefined elsewhere
  • ice extent is calculated during processing of raw output
  • plotting of seasonally averaged vertical profiles has been added
    • variable must be a 4D (3 space + 1 time) variable
    • dimension must be marked in global_settings.py as dicitonary entry "dimension" with integer value, e.g 3 or 4 for 3- or 4-dimensional field, respectively
    • default dimension is assumed to be 3 (backward compatible)
  • seasonal means provide now standard deviation variables
  • added Taylor diagrams
  • other model data can be added to plots (work in progress)

dependencies

  • python environment as anaconda3 or miniconda3
  • cdo, nco, see load module scripts for your target

known issues

  • None

tested with

  • intensively tested on IOW servers, Berlin's and on Göttingen's HLRN machine on MOM5 and CCLM output

1.01.02

date author(s) link
2022-05-31 SK 1.01.02

changes

  • fixed bug in using the cdo showname operator
  • allow for mean over total time period by using empty month list
  • committed more general global settings

dependencies

  • python environment as anaconda3 or miniconda3
  • cdo, nco, (texlive), see load module scripts for your target

known issues

  • plotting on HLRN Berlin not yet possible due to missing python module basemap
    • can be circumvented by creating own conda environment via
    module load anaconda3/2019.10
    conda init bash
    conda create --name plotting
    conda activate plotting
    conda install basemap
    conda install netCDF4
    conda install xarray
    
    and adding conda activate plotting to your local load_modules.sh on blogin
  • plotting time series sporadically fails due to yet unknown reason

tested with

  • intensively tested on Berlin's (with workaround) and on Göttingen's HLRN machine on MOM5 and CCLM output

1.01.01

date author(s) link
2022-05-04 SK 1.01.01

changes

  • fixed bug in using the mppncombine tool in MOM5/mppncombine/mppncombine.py
    • the first IO rectangle was not merged to the others
    • was not visible with 8nm MOM5 setup since this there was no data in this rectangle

dependencies

  • python environment as anaconda3 or miniconda3
  • cdo, nco, (texlive), see load module scripts for your target

known issues

  • plotting on HLRN Berlin not yet possible due to missing python module basemap
    • can be circumvented by creating own conda environment via
    module load anaconda3/2019.10
    conda init bash
    conda create --name plotting
    conda activate plotting
    conda install basemap
    conda install netCDF4
    conda install xarray
    
    and adding conda activate plotting to your local load_modules.sh on blogin

tested with

  • intensively tested on Berlin's (with workaround) and on Göttingen's HLRN machine on MOM5 and CCLM output

1.01.00

date author(s) link
2022-04-27 SK 1.01.00

changes

  • added task generate_mom_forcing to CCLM's tasks
    • task creates forcing for the MOM5 ocean model according to transformation given Thomas Neumann's scripts
    • splitted process_raw_output task for MOM5
      • mppncombine does merging of MOM's output
      • split_files generates subsequently "1 file per variable" pattern
  • fixed file ending .nc in CCLM/process_raw_output for total rain variable
  • fixed plotting of standard deviation in time series
  • remove results directory when rerunning a task
  • if no units are specified, arbitrary units "a.u." appear in the plot

dependencies

  • python environment as anaconda3 or miniconda3
  • cdo, nco, (texlive), see load module scripts for your target

known issues

  • plotting on HLRN Berlin not yet possible due to missing python module basemap
    • can be circumvented by creating own conda environment via
    module load anaconda3/2019.10
    conda init bash
    conda create --name plotting
    conda activate plotting
    conda install basemap
    conda install netCDF4
    conda install xarray
    
    and adding conda activate plotting to your local load_modules.sh on blogin

tested with

  • intensively tested on Berlin's (with workaround) and on Göttingen's HLRN machine on MOM5 and CCLM output

1.00.00

date author(s) link
2022-01-31 SK 1.00.00

changes

  • initital release
    • configured variables can be plotted and compared to a reference via seasonal means and time series for stations and regions

dependencies

  • python environment as anaconda3 or miniconda3
  • cdo, nco, (texlive), see load module scripts for your target

known issues

  • plotting on HLRN Berlin not yet possible due to missing python module basemap

tested with

  • intensively tested on Göttingen's HLRN machine on MOM5 and CCLM output