Description:
  Author: V. Agudetse

Analysis:
  Horizon: Seasonal
  Variables:
    name: tas prlr
    freq: monthly_mean
  Datasets:
    System:
      name: Meteo-France-System7
    Multimodel: False
    Reference:
      name: ERA5
  Time:
    sdate: '1101'
    fcst_year: '2020'
    hcst_start: '2000'
    hcst_end: '2016'
    ftime_min: 1
    ftime_max: 3
  Region:
    latmin: -10
    latmax: 10
    lonmin: 0
    lonmax: 20
  Regrid:
    method: bilinear
    type: to_system #to_reference #'r360x181'
  Workflow:
    Anomalies:
      compute: yes # yes/no, default yes
      cross_validation: yes # yes/no, default yes
      save: 'all' # 'all'/'none'/'exp_only'/'fcst_only'
    Calibration:
      method: mse_min
      save: 'none' # 'all'/'none'/'exp_only'/'fcst_only'
    Skill:
      metric: RPS RPSS BSS10 # RPS RPSS CRPS CRPSS FRPSS BSS10 BSS90 EnsCorr Corr mean_bias mean_bias_SS
      save: 'all' # 'all'/'none'
    Probabilities:
      percentiles: [[1/3, 2/3], [1/10, 9/10]]
      save: 'percentiles_only' # 'all'/'none'/'bins_only'/'percentiles_only'
    Visualization:
      plots: skill_metrics, forecast_ensemble_mean
      multi_panel: no
      projection: cylindrical_equidistant
    Indicators:
      index: no
  ncores: 10
  remove_NAs: yes
  Output_format: S2S4E
Run:
  Loglevel: INFO
  Terminal: yes
  output_dir: /esarchive/scratch/aho/tmp/
  code_dir: /esarchive/scratch/aho/git/auto-s2s/
  startR_workflow:
    modules: anomalies calibration skill # Modules to run inside Compute(), in order
    chunk_along: {var: 1, time: 3} # list: {dimension_1: # of chunks, dimension_2, # of chunks, ...}
    run_on: nord3 # options: local (WS), as_machime, nord3
    chunk_wallclock: '01:00:00' # Wallclock for each chunk, hh:mm:ss
    expid: a68e # leave empty to create a new one?
    hpc_user: bsc32734 # your hpc username
    slurm_directives: ['#SBATCH --constraint=medmem', '#SBATCH --exclusive']

