# ESMValTool
# recipe_toymodel.yml
---
documentation:
  title: Generate artificial forecasts from observations
  description: |
    Tool for generating synthetic observations based on the model presented
    in Weigel et al. (2008) QJRS with an extension to consider non-stationary
    (2008) QJRS with an extension to consider non-stationary distributions
    distributions prescribing a linear trend. The toymodel allows to
    generate an artificial forecast based on observations provided as input.

  authors:
    - bellprat_omar

  maintainer:
    - unmaintained

  projects:
    - c3s-magic

  references:
    - weigel08qjrms


datasets:
  # - {dataset: IPSL-CM5A-LR, type: exp, project: CMIP5,  exp: historical,  ensemble: r1i1p1,  start_year: 1999,  end_year: 2000}
  # - {dataset: MPI-ESM-LR, type: exp, project: CMIP5, exp: rcp85, ensemble: r1i1p1, start_year: 2020, end_year: 2050}
  - {dataset: bcc-csm1-1, type: exp, project: CMIP5, exp: rcp45, ensemble: r1i1p1, start_year: 2051, end_year: 2060}

preprocessors:
  preproc:
    regrid:
      target_grid: bcc-csm1-1
      scheme: linear
    mask_fillvalues:
      threshold_fraction: 0.95
    extract_region:
      start_longitude: -40
      end_longitude: 40
      start_latitude: 30
      end_latitude: 50


diagnostics:
  toymodel:
    description: Generate synthetic observations.
    variables:
      psl:
        preprocessor: preproc
        mip: Amon

    scripts:
      main:
        script: magic_bsc/toymodel.R
        beta: 500
        number_of_members: 20