# ESMValTool
# recipe_modes_of_variability.yml
---
documentation:
  title: |
    Root Mean Square Error (RMSE) between observed and modelled patterns of
    variability.

  description: |
    Tool to compute the RMSE between the observed and modelled patterns of
    variability obtained through classification and their relative relative
    bias (percentage) in the frequency of occurrence and the persistence of
    each mode.

  authors:
    - torralba_veronica
    - fuckar_neven
    - cortesi_nicola
    - guemas_virginie
    - hunter_alasdair
    - perez-zanon_nuria
    - manubens_nicolau

  maintainer:
    - unmaintained

  projects:
    - c3s-magic

  references:
    - fuckar15cd

datasets:
  - {dataset: CNRM-CM5, project: CMIP5, start_year: 1971, end_year: 2000, ensemble: r1i1p1, exp: historical}
  - {dataset: CNRM-CM5, project: CMIP5, start_year: 2020, end_year: 2075, ensemble: r1i1p1, exp: rcp85}

preprocessors:
  preproc:
    extract_region:
      start_longitude: 0
      end_longitude: 360
      start_latitude: 50
      end_latitude: 90
    extract_levels:
      levels: 50000
      scheme: nearest
diagnostics:
  weather_regime:
    description: Compute modes of variability.
    variables:
      zg:
        preprocessor: preproc
        mip: Amon
    scripts:
      main:
        script: magic_bsc/weather_regime.R
        plot_type: polar  # rectangular or polar

        ncenters: 3
        detrend_order: 2  # 0, 1 or 2 for daily data
        cluster_method: "kmeans"  # select hclust or kmeans
        EOFS: false
        frequency: 'SON'  # Select a month (format: JAN, FEB, ...) or season (JJA, SON, MAM(only monthly), DJF)