Description:
  Author: nperez
  Info: ECVs Oper ESS ECMWF SEAS5 Seasonal Forecast recipe (monthly mean, tas)

Analysis:
  Horizon: seasonal # Mandatory, str: either subseasonal, seasonal, or decadal
  Variables:
    - {name: 'prlr', freq: 'monthly_mean', units: 'C'}
      #- {name: 'prlr', freq: 'monthly_mean', units: 'mm', flux: yes}
  Datasets:
    System:
      #- {name: 'Meteo-France-System8'}
      #- {name: 'CMCC-SPS3.5'}
     - {name: 'ECMWF-SEAS5.1'}
      # - {name: 'UK-MetOffice-Glosea602'}
        ##- {name: 'NCEP-CFSv2'}
        #- {name: 'DWD-GCFS2.1'}
        #- {name: 'ECCC-GEM5.2-NEMO'}
    # name: Meteo-France-System7 #ECMWF-SEAS5.1 #ECMWF-i2o2 #UKMO-System602 #Meteo-France-System8
    Multimodel: 
      execute: no
      approach: pooled # Mandatory, bool: Either yes/true or no/false
      createFrom: Anomalies
    Reference:
      name: ERA5 # Mandatory, str: Reference codename. See docu.
  Time:
    sdate: '0101'
    fcst_year: # '2024' 
    hcst_start: '1993' # Mandatory, int: Hindcast start year 'YYYY'
    hcst_end: '1996' # Mandatory, int: Hindcast end year 'YYYY'
    ftime_min: 1 # Mandatory, int: First leadtime time step in months 
    ftime_max: 6 # Mandatory, int: Last leadtime time step in months
  Region:
    - {name: 'Global', latmin: -90, latmax: 90,  lonmin: -180, lonmax: 179.9}
      # - {name: 'Global', latmin: 0, latmax: 10, lonmin: 0, lonmax: 10}
  Regrid:
    method: conservative # Mandatory, str: Interpolation method. See docu.
    type: to_system
  Workflow:
    Anomalies:
      compute: yes
      cross_validation: no
      save: none
    Time_aggregation:
      execute: yes
      method: average
      ini: [1, 2, 3, 4]
      end: [3, 4, 5, 6]
    Calibration:
      method: raw #crps_min #evmos # Mandatory, str: Calibration method. See docu.
      cross_validation: yes
      save: none
    Skill:
      metric: rpss
      save: 'all'
      cross_validation: yes
    Probabilities:
      percentiles: [[1/3, 2/3]] # frac: Quantile thresholds.
      save: 'all'
    Indicators:
      index: no
    Visualization:
      plots: skill_metrics forecast_ensemble_mean most_likely_terciles
      multi_panel: no
      mask_terciles: 'both'
      mask_ens: 'both'
      projection: Robinson
      file_format: 'PNG'
    Scorecards:
      execute: no # yes/no 
      regions:
        Extra-tropical NH:  {lon.min: 0,  lon.max: 360, lat.min: 30, lat.max: 90}
        Tropics: {lon.min: 0,  lon.max: 360, lat.min: -30, lat.max: 30}
        Extra-tropical SH : {lon.min: 0,  lon.max: 360, lat.min: -90, lat.max: -30}
      start_months: NULL
      metric: rpss
      metric_aggregation: 'skill'
      #inf_to_na: yes
      table_label: NULL
      fileout_label: NULL
      col1_width: NULL
      col2_width: NULL
      calculate_diff: FALSE
  ncores: 30 # Optional, int: number of cores, defaults to 1
  remove_NAs: yes # Optional, bool: Whether NAs are removed, defaults to FALSE
  alpha: 0.05
  Output_format: scorecards
  logo: yes
Run:
  Loglevel: INFO
  Terminal: yes
  filesystem: esarchive
  output_dir: /home/Earth/vagudets/sunset-outputs/  # replace with the directory where you want to save the outputs
  code_dir: /home/bsc/bsc032339/sunset/ # replace with the directory where your code is
  autosubmit: no
  # fill only if using autosubmit
  auto_conf:
    script: /esarchive/scratch/nperez/git3/sunset/full_ecvs_scorecards.R # replace with the path to your script
    expid: a68v # replace with your EXPID
    hpc_user: bsc32339 # replace with your hpc username
    wallclock: 02:00 # hh:mm
    processors_per_job: 4 
    platform: nord3v2 
    email_notifications: yes # enable/disable email notifications. Change it if you want to.
    email_address: nuria.perez@bsc.es # replace with your email address
    notify_completed: yes # notify me by email when a job finishes
    notify_failed: yes # notify me by email when a job fails

