OceanBench logo. OceanBench
  • Scores
  • Challengers
  • About
  • Documentation

Open challenger datasets

import oceanbench

oceanbench.__version__
'0.6.0'

Insert here the code that opens the challenger dataset as challenger_dataset: xarray.Dataset

# SPDX-FileCopyrightText: 2025 Mercator Ocean International <https://www.mercator-ocean.eu/>
#
# SPDX-License-Identifier: EUPL-1.2

# Open GLONET forecasts with xarray
import xarray
import oceanbench

challenger_dataset: xarray.Dataset = oceanbench.datasets.challenger.glonet()

challenger_dataset
<xarray.Dataset> Size: 342GB
Dimensions:             (first_day_datetime: 52, lead_day_index: 10, depth: 21,
                         latitude: 672, longitude: 1440)
Coordinates:
  * depth               (depth) float32 84B 0.494 47.37 ... 4.833e+03 5.275e+03
  * latitude            (latitude) float64 5kB -78.0 -77.75 -77.5 ... 89.5 89.75
  * lead_day_index      (lead_day_index) int64 80B 0 1 2 3 4 5 6 7 8 9
  * longitude           (longitude) float64 12kB -180.0 -179.8 ... 179.5 179.8
  * first_day_datetime  (first_day_datetime) datetime64[ns] 416B 2024-01-03 ....
Data variables:
    so                  (first_day_datetime, lead_day_index, depth, latitude, longitude) float64 85GB dask.array<chunksize=(1, 2, 3, 168, 360), meta=np.ndarray>
    thetao              (first_day_datetime, lead_day_index, depth, latitude, longitude) float64 85GB dask.array<chunksize=(1, 2, 3, 168, 360), meta=np.ndarray>
    uo                  (first_day_datetime, lead_day_index, depth, latitude, longitude) float64 85GB dask.array<chunksize=(1, 2, 3, 168, 360), meta=np.ndarray>
    vo                  (first_day_datetime, lead_day_index, depth, latitude, longitude) float64 85GB dask.array<chunksize=(1, 2, 3, 168, 360), meta=np.ndarray>
    zos                 (first_day_datetime, lead_day_index, latitude, longitude) float64 4GB dask.array<chunksize=(1, 2, 168, 360), meta=np.ndarray>
Attributes:
    Conventions:              CF-1.8
    area:                     Global
    challenger:               glonet
    contact:                  glonet@mercator-ocean.eu
    forecast_reference_time:  2024-01-02
    institution:              Mercator Ocean International
    references:               www.edito.eu
    source:                   MOI GLONET
    title:                    Daily mean fields from GLONET 1/4 degree resolu...
    oceanbench_source_kind:   challenger
    oceanbench_source_name:   glonet
xarray.Dataset
    • first_day_datetime: 52
    • lead_day_index: 10
    • depth: 21
    • latitude: 672
    • longitude: 1440
    • depth
      (depth)
      float32
      0.494 47.37 ... 4.833e+03 5.275e+03
      axis :
      Z
      long_name :
      Depth
      positive :
      down
      standard_name :
      depth
      units :
      m
      valid_max :
      5727.917
      valid_min :
      0.494025
      array([4.940250e-01, 4.737369e+01, 9.232607e+01, 1.558507e+02, 2.224752e+02,
             3.181274e+02, 3.802130e+02, 4.539377e+02, 5.410889e+02, 6.435668e+02,
             7.633331e+02, 9.023393e+02, 1.245291e+03, 1.684284e+03, 2.225078e+03,
             3.220820e+03, 3.597032e+03, 3.992484e+03, 4.405224e+03, 4.833291e+03,
             5.274784e+03], dtype=float32)
    • latitude
      (latitude)
      float64
      -78.0 -77.75 -77.5 ... 89.5 89.75
      axis :
      Y
      long_name :
      Latitude
      standard_name :
      latitude
      units :
      degrees_north
      valid_max :
      89.75
      valid_min :
      -78.0
      array([-78.  , -77.75, -77.5 , ...,  89.25,  89.5 ,  89.75], shape=(672,))
    • lead_day_index
      (lead_day_index)
      int64
      0 1 2 3 4 5 6 7 8 9
      array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
    • longitude
      (longitude)
      float64
      -180.0 -179.8 ... 179.5 179.8
      axis :
      X
      long_name :
      Longitude
      standard_name :
      longitude
      units :
      degrees_east
      valid_max :
      179.75
      valid_min :
      -180.0
      array([-180.  , -179.75, -179.5 , ...,  179.25,  179.5 ,  179.75],
            shape=(1440,))
    • first_day_datetime
      (first_day_datetime)
      datetime64[ns]
      2024-01-03 ... 2024-12-25
      array(['2024-01-03T00:00:00.000000000', '2024-01-10T00:00:00.000000000',
             '2024-01-17T00:00:00.000000000', '2024-01-24T00:00:00.000000000',
             '2024-01-31T00:00:00.000000000', '2024-02-07T00:00:00.000000000',
             '2024-02-14T00:00:00.000000000', '2024-02-21T00:00:00.000000000',
             '2024-02-28T00:00:00.000000000', '2024-03-06T00:00:00.000000000',
             '2024-03-13T00:00:00.000000000', '2024-03-20T00:00:00.000000000',
             '2024-03-27T00:00:00.000000000', '2024-04-03T00:00:00.000000000',
             '2024-04-10T00:00:00.000000000', '2024-04-17T00:00:00.000000000',
             '2024-04-24T00:00:00.000000000', '2024-05-01T00:00:00.000000000',
             '2024-05-08T00:00:00.000000000', '2024-05-15T00:00:00.000000000',
             '2024-05-22T00:00:00.000000000', '2024-05-29T00:00:00.000000000',
             '2024-06-05T00:00:00.000000000', '2024-06-12T00:00:00.000000000',
             '2024-06-19T00:00:00.000000000', '2024-06-26T00:00:00.000000000',
             '2024-07-03T00:00:00.000000000', '2024-07-10T00:00:00.000000000',
             '2024-07-17T00:00:00.000000000', '2024-07-24T00:00:00.000000000',
             '2024-07-31T00:00:00.000000000', '2024-08-07T00:00:00.000000000',
             '2024-08-14T00:00:00.000000000', '2024-08-21T00:00:00.000000000',
             '2024-08-28T00:00:00.000000000', '2024-09-04T00:00:00.000000000',
             '2024-09-11T00:00:00.000000000', '2024-09-18T00:00:00.000000000',
             '2024-09-25T00:00:00.000000000', '2024-10-02T00:00:00.000000000',
             '2024-10-09T00:00:00.000000000', '2024-10-16T00:00:00.000000000',
             '2024-10-23T00:00:00.000000000', '2024-10-30T00:00:00.000000000',
             '2024-11-06T00:00:00.000000000', '2024-11-13T00:00:00.000000000',
             '2024-11-20T00:00:00.000000000', '2024-11-27T00:00:00.000000000',
             '2024-12-04T00:00:00.000000000', '2024-12-11T00:00:00.000000000',
             '2024-12-18T00:00:00.000000000', '2024-12-25T00:00:00.000000000'],
            dtype='datetime64[ns]')
    • so
      (first_day_datetime, lead_day_index, depth, latitude, longitude)
      float64
      dask.array<chunksize=(1, 2, 3, 168, 360), meta=np.ndarray>
      cell_methods :
      area: mean
      long_name :
      Salinity
      standard_name :
      sea_water_salinity
      units :
      1e-3
      valid_max :
      50.0
      valid_min :
      0.0
      Array Chunk
      Bytes 78.73 GiB 2.77 MiB
      Shape (52, 10, 21, 672, 1440) (1, 2, 3, 168, 360)
      Dask graph 29120 chunks in 157 graph layers
      Data type float64 numpy.ndarray
      10 52 1440 672 21
    • thetao
      (first_day_datetime, lead_day_index, depth, latitude, longitude)
      float64
      dask.array<chunksize=(1, 2, 3, 168, 360), meta=np.ndarray>
      cell_methods :
      area: mean
      long_name :
      Temperature
      standard_name :
      sea_water_potential_temperature
      units :
      degrees_C
      valid_max :
      40.0
      valid_min :
      -10.0
      Array Chunk
      Bytes 78.73 GiB 2.77 MiB
      Shape (52, 10, 21, 672, 1440) (1, 2, 3, 168, 360)
      Dask graph 29120 chunks in 157 graph layers
      Data type float64 numpy.ndarray
      10 52 1440 672 21
    • uo
      (first_day_datetime, lead_day_index, depth, latitude, longitude)
      float64
      dask.array<chunksize=(1, 2, 3, 168, 360), meta=np.ndarray>
      cell_methods :
      area: mean
      long_name :
      Eastward velocity
      standard_name :
      eastward_sea_water_velocity
      units :
      m s-1
      valid_max :
      5.0
      valid_min :
      -5.0
      Array Chunk
      Bytes 78.73 GiB 2.77 MiB
      Shape (52, 10, 21, 672, 1440) (1, 2, 3, 168, 360)
      Dask graph 29120 chunks in 157 graph layers
      Data type float64 numpy.ndarray
      10 52 1440 672 21
    • vo
      (first_day_datetime, lead_day_index, depth, latitude, longitude)
      float64
      dask.array<chunksize=(1, 2, 3, 168, 360), meta=np.ndarray>
      cell_methods :
      area: mean
      long_name :
      Northward velocity
      standard_name :
      northward_sea_water_velocity
      units :
      m s-1
      valid_max :
      5.0
      valid_min :
      -5.0
      Array Chunk
      Bytes 78.73 GiB 2.77 MiB
      Shape (52, 10, 21, 672, 1440) (1, 2, 3, 168, 360)
      Dask graph 29120 chunks in 157 graph layers
      Data type float64 numpy.ndarray
      10 52 1440 672 21
    • zos
      (first_day_datetime, lead_day_index, latitude, longitude)
      float64
      dask.array<chunksize=(1, 2, 168, 360), meta=np.ndarray>
      cell_methods :
      area: mean
      long_name :
      Sea surface height
      standard_name :
      sea_surface_height_above_geoid
      units :
      m
      valid_max :
      5.0
      valid_min :
      -5.0
      Array Chunk
      Bytes 3.75 GiB 0.92 MiB
      Shape (52, 10, 672, 1440) (1, 2, 168, 360)
      Dask graph 4160 chunks in 157 graph layers
      Data type float64 numpy.ndarray
      52 1 1440 672 10
    • depth
      PandasIndex
      PandasIndex(Index([0.49402499198913574,   47.37369155883789,    92.3260726928711,
              155.85069274902344,  222.47520446777344,   318.1274108886719,
               380.2130126953125,   453.9377136230469,   541.0889282226562,
               643.5667724609375,   763.3331298828125,   902.3392944335938,
                  1245.291015625,  1684.2840576171875,   2225.077880859375,
               3220.820068359375,   3597.031982421875,    3992.48388671875,
                4405.22412109375,      4833.291015625,     5274.7841796875],
            dtype='float32', name='depth'))
    • latitude
      PandasIndex
      PandasIndex(Index([ -78.0, -77.75,  -77.5, -77.25,  -77.0, -76.75,  -76.5, -76.25,  -76.0,
             -75.75,
             ...
               87.5,  87.75,   88.0,  88.25,   88.5,  88.75,   89.0,  89.25,   89.5,
              89.75],
            dtype='float64', name='latitude', length=672))
    • lead_day_index
      PandasIndex
      PandasIndex(Index([0, 1, 2, 3, 4, 5, 6, 7, 8, 9], dtype='int64', name='lead_day_index'))
    • longitude
      PandasIndex
      PandasIndex(Index([ -180.0, -179.75,  -179.5, -179.25,  -179.0, -178.75,  -178.5, -178.25,
              -178.0, -177.75,
             ...
               177.5,  177.75,   178.0,  178.25,   178.5,  178.75,   179.0,  179.25,
               179.5,  179.75],
            dtype='float64', name='longitude', length=1440))
    • first_day_datetime
      PandasIndex
      PandasIndex(DatetimeIndex(['2024-01-03', '2024-01-10', '2024-01-17', '2024-01-24',
                     '2024-01-31', '2024-02-07', '2024-02-14', '2024-02-21',
                     '2024-02-28', '2024-03-06', '2024-03-13', '2024-03-20',
                     '2024-03-27', '2024-04-03', '2024-04-10', '2024-04-17',
                     '2024-04-24', '2024-05-01', '2024-05-08', '2024-05-15',
                     '2024-05-22', '2024-05-29', '2024-06-05', '2024-06-12',
                     '2024-06-19', '2024-06-26', '2024-07-03', '2024-07-10',
                     '2024-07-17', '2024-07-24', '2024-07-31', '2024-08-07',
                     '2024-08-14', '2024-08-21', '2024-08-28', '2024-09-04',
                     '2024-09-11', '2024-09-18', '2024-09-25', '2024-10-02',
                     '2024-10-09', '2024-10-16', '2024-10-23', '2024-10-30',
                     '2024-11-06', '2024-11-13', '2024-11-20', '2024-11-27',
                     '2024-12-04', '2024-12-11', '2024-12-18', '2024-12-25'],
                    dtype='datetime64[ns]', name='first_day_datetime', freq=None))
  • Conventions :
    CF-1.8
    area :
    Global
    challenger :
    glonet
    contact :
    glonet@mercator-ocean.eu
    forecast_reference_time :
    2024-01-02
    institution :
    Mercator Ocean International
    references :
    www.edito.eu
    source :
    MOI GLONET
    title :
    Daily mean fields from GLONET 1/4 degree resolution forecast
    oceanbench_source_kind :
    challenger
    oceanbench_source_name :
    glonet

Evaluation configuration

region = 'global'

Evaluation of challenger dataset using OceanBench

Root Mean Square Deviation (RMSD) of variables compared to GLORYS reanalysis

oceanbench.metrics.rmsd_of_variables_compared_to_glorys_reanalysis(
    challenger_dataset,
    region=region,
)
Lead day 1 Lead day 2 Lead day 3 Lead day 4 Lead day 5 Lead day 6 Lead day 7 Lead day 8 Lead day 9 Lead day 10 Missing fraction
Sea surface height (m) [sea_surface_height_above_geoid]{surface} 0.078212 0.079651 0.079739 0.081586 0.083502 0.085864 0.087867 0.090524 0.092582 0.095031 0.000671
Temperature (°C) [sea_water_potential_temperature]{surface} 0.671305 0.670575 0.701888 0.700506 0.761012 0.763189 0.833383 0.837423 0.906016 0.909487 0.000671
Salinity (PSU) [sea_water_salinity]{surface} 0.560995 0.559306 0.559670 0.557404 0.560255 0.556112 0.563506 0.557935 0.567648 0.560916 0.000671
Meridional current (m/s) [northward_sea_water_velocity]{surface} 0.126109 0.128095 0.131838 0.133239 0.136858 0.138001 0.142269 0.143763 0.147399 0.148204 0.000666
Zonal current (m/s) [eastward_sea_water_velocity]{surface} 0.128883 0.131438 0.135442 0.137320 0.141677 0.143152 0.147471 0.149251 0.153501 0.154654 0.000666
Temperature (°C) [sea_water_potential_temperature]{50m} 1.002910 1.010933 1.047242 1.055807 1.100645 1.113650 1.161149 1.179413 1.224749 1.246463 0.000789
Salinity (PSU) [sea_water_salinity]{50m} 0.245399 0.246167 0.251229 0.252594 0.258187 0.260039 0.265845 0.267895 0.273808 0.275699 0.000789
Meridional current (m/s) [northward_sea_water_velocity]{50m} 0.116766 0.116880 0.117020 0.118228 0.119985 0.121794 0.124585 0.126832 0.129078 0.130584 0.000788
Zonal current (m/s) [eastward_sea_water_velocity]{50m} 0.118752 0.118580 0.118477 0.119574 0.121386 0.123153 0.126082 0.128606 0.131364 0.133428 0.000788
Temperature (°C) [sea_water_potential_temperature]{100m} 1.093666 1.100252 1.117805 1.127543 1.153901 1.167421 1.200661 1.218118 1.251650 1.270490 0.000749
Salinity (PSU) [sea_water_salinity]{100m} 0.196862 0.197301 0.198125 0.198739 0.201700 0.202493 0.206954 0.207828 0.212714 0.213240 0.000749
Meridional current (m/s) [northward_sea_water_velocity]{100m} 0.113582 0.113472 0.112817 0.113741 0.114798 0.116387 0.118417 0.120519 0.122150 0.123587 0.000749
Zonal current (m/s) [eastward_sea_water_velocity]{100m} 0.119604 0.119419 0.118874 0.119596 0.120708 0.122071 0.124197 0.126302 0.128394 0.130074 0.000749
Temperature (°C) [sea_water_potential_temperature]{200m} 0.933166 0.935561 0.953840 0.958212 0.969649 0.978562 0.989235 1.002193 1.010868 1.024616 0.000759
Salinity (PSU) [sea_water_salinity]{200m} 0.161182 0.161412 0.162066 0.162451 0.163575 0.164236 0.165774 0.166612 0.168141 0.168824 0.000759
Meridional current (m/s) [northward_sea_water_velocity]{200m} 0.110361 0.110194 0.108762 0.109113 0.109273 0.109990 0.110909 0.111975 0.112693 0.113341 0.000758
Zonal current (m/s) [eastward_sea_water_velocity]{200m} 0.117576 0.117380 0.116015 0.116141 0.116185 0.116676 0.117438 0.118168 0.118819 0.119209 0.000758
Temperature (°C) [sea_water_potential_temperature]{300m} 0.786652 0.786379 0.796102 0.797889 0.798793 0.804703 0.806945 0.816241 0.819024 0.827816 0.000581
Salinity (PSU) [sea_water_salinity]{300m} 0.133068 0.133143 0.133456 0.133701 0.134250 0.134822 0.135729 0.136578 0.137520 0.138294 0.000581
Meridional current (m/s) [northward_sea_water_velocity]{300m} 0.107724 0.107644 0.106093 0.106290 0.106299 0.106823 0.107563 0.108296 0.108866 0.109216 0.000581
Zonal current (m/s) [eastward_sea_water_velocity]{300m} 0.112852 0.112714 0.111181 0.111211 0.111119 0.111388 0.111991 0.112469 0.113042 0.113271 0.000581
Temperature (°C) [sea_water_potential_temperature]{500m} 0.582565 0.585105 0.574451 0.578207 0.579072 0.584001 0.590658 0.596368 0.604614 0.608656 0.000491
Salinity (PSU) [sea_water_salinity]{500m} 0.098984 0.099088 0.099230 0.099493 0.100254 0.100708 0.101817 0.102394 0.103571 0.104049 0.000491
Meridional current (m/s) [northward_sea_water_velocity]{500m} 0.098541 0.098424 0.096840 0.096834 0.096637 0.096823 0.097223 0.097566 0.097936 0.098039 0.000491
Zonal current (m/s) [eastward_sea_water_velocity]{500m} 0.102831 0.102749 0.100989 0.101014 0.100703 0.100955 0.101250 0.101625 0.101980 0.102194 0.000491

Root Mean Square Deviation (RMSD) of Mixed Layer Depth (MLD) compared to GLORYS reanalysis

oceanbench.metrics.rmsd_of_mixed_layer_depth_compared_to_glorys_reanalysis(
    challenger_dataset,
    region=region,
)
Lead day 1 Lead day 2 Lead day 3 Lead day 4 Lead day 5 Lead day 6 Lead day 7 Lead day 8 Lead day 9 Lead day 10 Missing fraction
Mixed layer depth (m) [ocean_mixed_layer_thickness]{surface} 45.54941 45.405019 47.910058 47.978645 50.600357 50.917583 53.136207 53.524447 55.203666 55.479862 0.000671

Root Mean Square Deviation (RMSD) of geostrophic currents compared to GLORYS reanalysis

oceanbench.metrics.rmsd_of_geostrophic_currents_compared_to_glorys_reanalysis(
    challenger_dataset,
    region=region,
)
Lead day 1 Lead day 2 Lead day 3 Lead day 4 Lead day 5 Lead day 6 Lead day 7 Lead day 8 Lead day 9 Lead day 10 Missing fraction
Meridional geostrophic current (m/s) [geostrophic_northward_sea_water_velocity]{surface} 0.113561 0.114958 0.124546 0.127488 0.135428 0.140118 0.146986 0.153316 0.158548 0.165579 0.00130
Zonal geostrophic current (m/s) [geostrophic_eastward_sea_water_velocity]{surface} 0.105900 0.107422 0.116029 0.119141 0.126296 0.131182 0.137361 0.143901 0.148525 0.155737 0.00124

Root Mean Square Deviation (RMSD) of variables compared to observations

oceanbench.metrics.rmsd_of_variables_compared_to_observations(
    challenger_dataset,
    region=region,
)
Lead day 1 Lead day 2 Lead day 3 Lead day 4 Lead day 5 Lead day 6 Lead day 7 Lead day 8 Lead day 9 Lead day 10 Observations Missing
Temperature (°C) [sea_water_potential_temperature]{surface} 0.806688 0.822411 0.835357 0.847619 0.907410 0.939854 0.971971 0.980053 1.038758 1.011632 150081 0
Temperature (°C) [sea_water_potential_temperature]{0-5m} 0.856148 0.871513 0.915509 0.938800 0.978112 0.984986 1.045921 1.024723 1.092600 1.094428 80763 0
Temperature (°C) [sea_water_potential_temperature]{5-100m} 1.091433 1.113160 1.116544 1.132108 1.177374 1.164472 1.218660 1.240233 1.283961 1.302801 1334564 0
Temperature (°C) [sea_water_potential_temperature]{100-300m} 0.864933 0.886722 0.881532 0.892038 0.922976 0.918527 0.953663 0.953053 0.995588 1.015701 2117343 0
Temperature (°C) [sea_water_potential_temperature]{300-600m} 0.562561 0.577249 0.558515 0.564459 0.577750 0.589280 0.602592 0.609519 0.624670 0.646569 2622487 0
Salinity (PSU) [sea_water_salinity]{0-5m} 0.272634 0.297080 0.292715 0.324847 0.293268 0.307241 0.296862 0.292436 0.331165 0.335958 68940 0
Salinity (PSU) [sea_water_salinity]{5-100m} 0.227862 0.234485 0.237091 0.239308 0.254057 0.264175 0.244736 0.243634 0.264535 0.264418 1136708 0
Salinity (PSU) [sea_water_salinity]{100-300m} 0.133845 0.136138 0.134106 0.134163 0.137014 0.135239 0.143272 0.139352 0.146150 0.153935 1803408 0
Salinity (PSU) [sea_water_salinity]{300-600m} 0.081068 0.081966 0.080791 0.081472 0.083212 0.084896 0.088230 0.088849 0.092431 0.096868 2225476 0
Sea level anomaly (m) [sea_surface_height_above_geoid]{surface} 0.051815 0.052890 0.053196 0.055263 0.057462 0.059915 0.062399 0.064731 0.067340 0.069978 15390586 0
Zonal current (m/s) [eastward_sea_water_velocity]{15m} 0.122166 0.125496 0.129552 0.130928 0.131514 0.131884 0.135374 0.136593 0.139472 0.141860 1202530 0
Meridional current (m/s) [northward_sea_water_velocity]{15m} 0.118430 0.120446 0.123517 0.125667 0.128502 0.129689 0.131768 0.133078 0.134937 0.136422 1202530 0

Deviation of Lagrangian trajectories compared to GLORYS reanalysis

oceanbench.metrics.deviation_of_lagrangian_trajectories_compared_to_glorys_reanalysis(
    challenger_dataset,
    region=region,
)
Lead day 2 Lead day 3 Lead day 4 Lead day 5 Lead day 6 Lead day 7 Lead day 8 Lead day 9 Lead day 10
Lagrangian trajectory deviation (km) []{surface} 10.830428 21.075859 30.966387 40.572414 49.968365 59.150093 68.171188 77.059616 85.822052

Root Mean Square Deviation (RMSD) of variables compared to GLO12 analysis

oceanbench.metrics.rmsd_of_variables_compared_to_glo12_analysis(
    challenger_dataset,
    region=region,
)
Lead day 1 Lead day 2 Lead day 3 Lead day 4 Lead day 5 Lead day 6 Lead day 7 Lead day 8 Lead day 9 Lead day 10 Missing fraction
Sea surface height (m) [sea_surface_height_above_geoid]{surface} 0.030537 0.035089 0.038387 0.042653 0.047666 0.051893 0.056076 0.060377 0.063444 0.066433 0.000000
Temperature (°C) [sea_water_potential_temperature]{surface} 0.461173 0.461212 0.544656 0.548472 0.644156 0.653623 0.744440 0.756151 0.834382 0.842782 0.000000
Salinity (PSU) [sea_water_salinity]{surface} 0.172511 0.182532 0.229039 0.238081 0.272282 0.280444 0.311978 0.320637 0.347616 0.352753 0.000000
Meridional current (m/s) [northward_sea_water_velocity]{surface} 0.051524 0.069434 0.084080 0.094715 0.106109 0.114269 0.124722 0.131591 0.138674 0.142617 0.000004
Zonal current (m/s) [eastward_sea_water_velocity]{surface} 0.051181 0.071210 0.085861 0.097360 0.109257 0.117942 0.128090 0.135470 0.143251 0.147560 0.000004
Temperature (°C) [sea_water_potential_temperature]{50m} 0.737623 0.748008 0.826913 0.843268 0.920001 0.944119 1.019413 1.047792 1.111206 1.137806 0.000239
Salinity (PSU) [sea_water_salinity]{50m} 0.113563 0.114955 0.149535 0.151485 0.175362 0.177991 0.196797 0.199523 0.214629 0.216250 0.000239
Meridional current (m/s) [northward_sea_water_velocity]{50m} 0.044802 0.054460 0.064200 0.071936 0.080438 0.088148 0.096833 0.104167 0.110041 0.114714 0.000239
Zonal current (m/s) [eastward_sea_water_velocity]{50m} 0.045756 0.055988 0.065999 0.074088 0.082789 0.090928 0.100080 0.108046 0.114793 0.120073 0.000239
Temperature (°C) [sea_water_potential_temperature]{100m} 0.563125 0.580493 0.663648 0.690012 0.773138 0.808037 0.888074 0.926391 0.991217 1.022820 0.000233
Salinity (PSU) [sea_water_salinity]{100m} 0.089788 0.090567 0.113985 0.115383 0.133221 0.135282 0.150415 0.152633 0.164556 0.165617 0.000233
Meridional current (m/s) [northward_sea_water_velocity]{100m} 0.039761 0.047412 0.056008 0.063223 0.071295 0.079057 0.087323 0.094525 0.100036 0.104728 0.000233
Zonal current (m/s) [eastward_sea_water_velocity]{100m} 0.040649 0.048871 0.057804 0.065240 0.073406 0.081294 0.089751 0.097455 0.103745 0.109012 0.000233
Temperature (°C) [sea_water_potential_temperature]{200m} 0.421562 0.428431 0.501020 0.516587 0.568604 0.593816 0.641271 0.671121 0.705591 0.729371 0.000185
Salinity (PSU) [sea_water_salinity]{200m} 0.063905 0.064470 0.082412 0.083835 0.096681 0.099016 0.109317 0.111974 0.119481 0.121175 0.000185
Meridional current (m/s) [northward_sea_water_velocity]{200m} 0.031452 0.036890 0.044058 0.050237 0.057170 0.064057 0.071295 0.077815 0.082710 0.086921 0.000185
Zonal current (m/s) [eastward_sea_water_velocity]{200m} 0.030932 0.036444 0.043974 0.050021 0.057083 0.063738 0.070949 0.077284 0.082506 0.086873 0.000185
Temperature (°C) [sea_water_potential_temperature]{300m} 0.362202 0.365532 0.428337 0.440119 0.479425 0.500279 0.537110 0.562148 0.589799 0.607990 0.000211
Salinity (PSU) [sea_water_salinity]{300m} 0.056925 0.057537 0.070752 0.072308 0.081459 0.083944 0.091424 0.094245 0.099785 0.101767 0.000211
Meridional current (m/s) [northward_sea_water_velocity]{300m} 0.028896 0.033721 0.040381 0.046269 0.052786 0.059350 0.066073 0.072293 0.076896 0.080982 0.000211
Zonal current (m/s) [eastward_sea_water_velocity]{300m} 0.028404 0.033052 0.040014 0.045654 0.052142 0.058448 0.065093 0.071119 0.075941 0.080129 0.000211
Temperature (°C) [sea_water_potential_temperature]{500m} 0.235992 0.240834 0.291298 0.301410 0.345211 0.360242 0.400322 0.417188 0.447235 0.458282 0.000197
Salinity (PSU) [sea_water_salinity]{500m} 0.043256 0.043481 0.054688 0.055411 0.063635 0.064888 0.071509 0.072982 0.077979 0.078943 0.000197
Meridional current (m/s) [northward_sea_water_velocity]{500m} 0.025310 0.029398 0.035514 0.040670 0.046390 0.052044 0.057854 0.063226 0.067334 0.070971 0.000199
Zonal current (m/s) [eastward_sea_water_velocity]{500m} 0.024655 0.028681 0.034969 0.039926 0.045533 0.050964 0.056590 0.061796 0.065973 0.069685 0.000199

Root Mean Square Deviation (RMSD) of Mixed Layer Depth (MLD) compared to GLO12 analysis

oceanbench.metrics.rmsd_of_mixed_layer_depth_compared_to_glo12_analysis(
    challenger_dataset,
    region=region,
)
Lead day 1 Lead day 2 Lead day 3 Lead day 4 Lead day 5 Lead day 6 Lead day 7 Lead day 8 Lead day 9 Lead day 10 Missing fraction
Mixed layer depth (m) [ocean_mixed_layer_thickness]{surface} 39.744465 39.588792 43.324254 43.443237 46.972092 47.292208 50.162994 50.396148 52.547539 52.685571 0.0

Root Mean Square Deviation (RMSD) of geostrophic currents compared to GLO12 analysis

oceanbench.metrics.rmsd_of_geostrophic_currents_compared_to_glo12_analysis(
    challenger_dataset,
    region=region,
)
Lead day 1 Lead day 2 Lead day 3 Lead day 4 Lead day 5 Lead day 6 Lead day 7 Lead day 8 Lead day 9 Lead day 10 Missing fraction
Meridional geostrophic current (m/s) [geostrophic_northward_sea_water_velocity]{surface} 0.058497 0.063490 0.082875 0.091221 0.105891 0.116176 0.127993 0.139064 0.146938 0.156744 0.000002
Zonal geostrophic current (m/s) [geostrophic_eastward_sea_water_velocity]{surface} 0.054306 0.059158 0.076851 0.084700 0.098255 0.108167 0.119056 0.129866 0.137089 0.146822 0.000002

Deviation of Lagrangian trajectories compared to GLO12 analysis

oceanbench.metrics.deviation_of_lagrangian_trajectories_compared_to_glo12_analysis(
    challenger_dataset,
    region=region,
)
Lead day 2 Lead day 3 Lead day 4 Lead day 5 Lead day 6 Lead day 7 Lead day 8 Lead day 9 Lead day 10
Lagrangian trajectory deviation (km) []{surface} 4.635766 9.927687 15.687903 21.95052 28.76223 36.089043 43.914936 52.096775 60.52639
 

Powered by: EDITO logo EDITO logo

  • Edit this page
  • View source
  • Report an issue