# ESMValTool
# recipe_validation.yml
---
documentation:
  description: |
    Validation of CONTROL and EXPERIMENT datasets.
    This recipe produces standard comparison plots for two models
    and may include observational data. The standard comparison
    metrics are 2D lat-lon differences (between control and experiment),
    plain 2D lat-lon for each model, 1D (coordinate vs time)
    zonal and meridional means for both control and experiment models.
    Plots are produced for each season (winter DJF, spring MAM, summer JJA,
    autumn SON) and for the entire year.
    There are no restrictions in terms of data.

  authors:
    - predoi_valeriu

  title: Standard comparison between two models (control and experiment, CMIP5 data).

  maintainer:
    - predoi_valeriu

datasets:
  - {dataset: MPI-ESM-LR,  project: CMIP5,  mip: Amon,  exp: historical,  ensemble: r1i1p1,  start_year: 2001,  end_year: 2005}
  - {dataset: NorESM1-M,   project: CMIP5,  mip: Amon,  exp: historical,  ensemble: r1i1p1,  start_year: 2001,  end_year: 2005}

preprocessors:
  pp_rad:
    regrid:
      target_grid: 1x1
      scheme: linear
  pp_rad_derive_var:
    # use this not to overwrite variables that are used both
    # for derivation and as standalone diag vars
    regrid:
      target_grid: 1x1
      scheme: linear

diagnostics:
  validation_with_CERES-EBAF:
    description: "CMIP5 vs CERES-EBAF"
    variables:
      rtnt: # TOA TOT net
        preprocessor: pp_rad_derive_var
        derive: true
        force_derivation: false
      rsut: # TOA SW up all sky
        preprocessor: pp_rad
    additional_datasets:
      - {dataset: CERES-EBAF,  project: obs4MIPs, mip: Amon, level: L3B,  version: v20160610,  start_year: 2001,  end_year: 2012, tier: 1}
    scripts:
      lat_lon:
        script: validation.py
        title: ""
        cmip_era: CMIP5
        control_model: MPI-ESM-LR
        exper_model: NorESM1-M
        observational_datasets: ['CERES-EBAF'] # list of at least one element; if no OBS wanted comment out
        analysis_type: lat_lon  # use any of: lat_lon, meridional_mean, zonal_mean, vertical_mean[not implemented]
        seasonal_analysis: false  # turn on to output per season
        save_cubes: true  # save each plotted cube in work
      zonal_mean:
        script: validation.py
        title: ""
        cmip_era: CMIP5
        control_model: MPI-ESM-LR
        exper_model: NorESM1-M
        observational_datasets: ['CERES-EBAF'] # list of at least one element; if no OBS wanted comment out
        analysis_type: zonal_mean  # use any of: lat_lon, meridional_mean, zonal_mean, vertical_mean[not implemented]
        seasonal_analysis: true  # turn on to output per season
        save_cubes: true  # save each plotted cube in work
      meridional_mean:
        script: validation.py
        title: ""
        cmip_era: CMIP5
        control_model: MPI-ESM-LR
        exper_model: NorESM1-M
        observational_datasets: ['CERES-EBAF'] # list of at least one element; if no OBS wanted comment out
        analysis_type: meridional_mean  # use any of: lat_lon, meridional_mean, zonal_mean, vertical_mean[not implemented]
        seasonal_analysis: true  # turn on to output per season
        save_cubes: true  # save each plotted cube in work