Winderlich.yaml

- key: Winderlich SCQS
  doi: [pers_comm, K. Winderlich, DWD]
  metric:
    name: SCQS 
    long_name: Synoptic Circulation Quality Score 
    units: 1
    variables: z500
    comment: |
      Domain is CORDEX-EUR. Data z500 is converted to daily anomalies and
      normalized by daily standard deviation. Data are then attributed to
      previously obtained Synoptic Circulation (SP) classes. Number of
      Synoptic Circulation classes is 43 (derived on daily ERA-Interim data,
      1979-2018). For each model, 7 variables are computed from the
      attributed daily data.

      1) HIST - frequency of each SP-class (year through)
      2) HIST_JFD - frequency of each SP-class (winter)
      3) HIST_MAM - frequency of each SP-class (spring)
      4) HIST_JJA - frequency of each SP-class (summer)
      5) HIST_SON - frequency of each SP-class (autumn)
      6) SEQUENCE - matrix of frequencies for the subsequent occurrence
                    of the pair of two synoptic patterns SPi?SPj.
      7) PERSISTENCE - matrix of frequency for persistence of each
                       SP-class for 1,2,3,.. N days in a row. 

      The SCQS is computed as the mean of 7 individual Quality Scores
      computed on each of these variables.              
    best: 1
    worst: 0
  type: performance
  spatial_scope: EUR
  temporal_scope: Annual
  plausible_values:
    - min: 0
      max: 1
      source: author
      comment: >
        The higher the better, SCQS between reference reanalysis (ERA-Interim)
        and an alternative reanalysis (NCAR-NCEP1) is in the table for comparison.
  data_source: author 
  data: 
    ACCESS-CM2_r1i1p1f1: 0.84
    AWI-ESM-1-1-LR_r1i1p1f1: 0.79
    BCC-CSM2-MR_r1i1p1f1: 0.83
    BCC-ESM1_r1i1p1f1: 0.84
    CanESM5_r1i1p1f1: 0.82
    CESM2_r1i1p1f1: 0.83
    CESM2-FV2_r1i1p1f1: 0.82
    CESM2-WACCM-FV2_r1i1p1f1: 0.81
    CMCC-CM2-SR5_r1i1p1f1: 0.85
    CNRM-CM6-1_r1i1p1f2: 0.79
    CNRM-ESM2-1_r1i1p1f2: 0.79
    EC-Earth3_r1i1p1f1: 0.82
    EC-Earth3-Veg_r1i1p1f1: 0.82
    FGOALS-f3-L_r1i1p1f1: 0.79
    FGOALS-g3_r1i1p1f1: 0.80
    GISS-E2-1-G_r1i1p1f1: 0.79
    HadGEM3-GC31-LL_r1i1p1f3: 0.83
    HadGEM3-GC31-MM_r1i1p1f3: 0.84
    INM-CM4-8_r1i1p1f1: 0.81
    INM-CM5-0_r1i1p1f1: 0.84
    IPSL-CM6A-LR_r1i1p1f1: 0.79
    IPSL-CM6A-LR-INCA_r1i1p1f1: 0.76
    KACE-1-0-G_r1i1p1f1: 0.85
    MIROC6_r1i1p1f1: 0.81
    MPI-ESM-1-2-HAM_r1i1p1f1: 0.83
    MPI-ESM1-2-HR_r1i1p1f1: 0.87
    MPI-ESM1-2-LR_r1i1p1f1: 0.82
    MRI-ESM2-0_r1i1p1f1: 0.85
    NorESM2-LM_r1i1p1f1: 0.80
    NorESM2-MM_r1i1p1f1: 0.84
    TaiESM1_r1i1p1f1: 0.83
    UKESM1-0-LL_r1i1p1f2: 0.83
  data_other: 
    ERA-Interim: 1.00 # reference reanalysis
    NCAR-NCEP1: 0.90