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Open challenger datasets

import oceanbench

oceanbench.__version__
'0.5.0'

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 XiHe forecasts with xarray
import xarray
import oceanbench

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

challenger_dataset
Remote data read failed during challenger dataset open (1/12): 502, message='Bad Gateway', url='https://s3.waw3-1.cloudferro.com/oceanbench-bucket/public/ml-forecast-outputs/xihe/20241211.zarr/thetao/0.3.0.0'. Retrying in 2s.
<xarray.Dataset> Size: 2TB
Dimensions:             (first_day_datetime: 52, lead_day_index: 10, depth: 23,
                         latitude: 2041, longitude: 4320)
Coordinates:
  * depth               (depth) float32 92B 0.494 2.646 5.078 ... 541.1 643.6
  * latitude            (latitude) float32 8kB -80.0 -79.92 ... 89.92 90.0
  * lead_day_index      (lead_day_index) int64 80B 0 1 2 3 4 5 6 7 8 9
  * longitude           (longitude) float32 17kB -180.0 -179.9 ... 179.8 179.9
  * first_day_datetime  (first_day_datetime) datetime64[ns] 416B 2024-01-03 ....
Data variables:
    so                  (first_day_datetime, lead_day_index, depth, latitude, longitude) float32 422GB dask.array<chunksize=(1, 1, 1, 256, 512), meta=np.ndarray>
    thetao              (first_day_datetime, lead_day_index, depth, latitude, longitude) float32 422GB dask.array<chunksize=(1, 1, 1, 256, 512), meta=np.ndarray>
    uo                  (first_day_datetime, lead_day_index, depth, latitude, longitude) float32 422GB dask.array<chunksize=(1, 1, 1, 256, 512), meta=np.ndarray>
    vo                  (first_day_datetime, lead_day_index, depth, latitude, longitude) float32 422GB dask.array<chunksize=(1, 1, 1, 256, 512), meta=np.ndarray>
    zos                 (first_day_datetime, lead_day_index, latitude, longitude) float32 18GB dask.array<chunksize=(1, 1, 256, 512), meta=np.ndarray>
Attributes:
    Conventions:              CF-1.8
    challenger:               xihe
    forecast_reference_time:  2024-01-02
    oceanbench_source_kind:   challenger
    oceanbench_source_name:   xihe
xarray.Dataset
    • first_day_datetime: 52
    • lead_day_index: 10
    • depth: 23
    • latitude: 2041
    • longitude: 4320
    • depth
      (depth)
      float32
      0.494 2.646 5.078 ... 541.1 643.6
      axis :
      Z
      long_name :
      Depth
      positive :
      down
      standard_name :
      depth
      units :
      m
      array([4.940000e-01, 2.645700e+00, 5.078200e+00, 7.929600e+00, 1.140500e+01,
             1.581010e+01, 2.159880e+01, 2.944470e+01, 4.034410e+01, 5.576430e+01,
             7.785390e+01, 9.232610e+01, 1.097293e+02, 1.306660e+02, 1.558507e+02,
             1.861256e+02, 2.224752e+02, 2.660403e+02, 3.181274e+02, 3.802130e+02,
             4.539377e+02, 5.410889e+02, 6.435668e+02], dtype=float32)
    • latitude
      (latitude)
      float32
      -80.0 -79.92 -79.83 ... 89.92 90.0
      axis :
      Y
      long_name :
      Latitude
      standard_name :
      latitude
      units :
      degrees_north
      array([-80.      , -79.916664, -79.833336, ...,  89.83334 ,  89.91667 ,
              90.      ], shape=(2041,), dtype=float32)
    • 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)
      float32
      -180.0 -179.9 ... 179.8 179.9
      axis :
      X
      long_name :
      Longitude
      standard_name :
      longitude
      units :
      degrees_east
      array([-180.     , -179.91667, -179.83333, ...,  179.75   ,  179.83334,
              179.91669], shape=(4320,), dtype=float32)
    • 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)
      float32
      dask.array<chunksize=(1, 1, 1, 256, 512), meta=np.ndarray>
      long_name :
      Salinity
      standard_name :
      sea_water_salinity
      units :
      1e-3
      Array Chunk
      Bytes 392.84 GiB 512.00 kiB
      Shape (52, 10, 23, 2041, 4320) (1, 1, 1, 256, 512)
      Dask graph 861120 chunks in 157 graph layers
      Data type float32 numpy.ndarray
      10 52 4320 2041 23
    • thetao
      (first_day_datetime, lead_day_index, depth, latitude, longitude)
      float32
      dask.array<chunksize=(1, 1, 1, 256, 512), meta=np.ndarray>
      long_name :
      Temperature
      standard_name :
      sea_water_potential_temperature
      units :
      degrees_C
      Array Chunk
      Bytes 392.84 GiB 512.00 kiB
      Shape (52, 10, 23, 2041, 4320) (1, 1, 1, 256, 512)
      Dask graph 861120 chunks in 157 graph layers
      Data type float32 numpy.ndarray
      10 52 4320 2041 23
    • uo
      (first_day_datetime, lead_day_index, depth, latitude, longitude)
      float32
      dask.array<chunksize=(1, 1, 1, 256, 512), meta=np.ndarray>
      long_name :
      Eastward velocity
      standard_name :
      eastward_sea_water_velocity
      units :
      m s-1
      Array Chunk
      Bytes 392.84 GiB 512.00 kiB
      Shape (52, 10, 23, 2041, 4320) (1, 1, 1, 256, 512)
      Dask graph 861120 chunks in 157 graph layers
      Data type float32 numpy.ndarray
      10 52 4320 2041 23
    • vo
      (first_day_datetime, lead_day_index, depth, latitude, longitude)
      float32
      dask.array<chunksize=(1, 1, 1, 256, 512), meta=np.ndarray>
      long_name :
      Northward velocity
      standard_name :
      northward_sea_water_velocity
      units :
      m s-1
      Array Chunk
      Bytes 392.84 GiB 512.00 kiB
      Shape (52, 10, 23, 2041, 4320) (1, 1, 1, 256, 512)
      Dask graph 861120 chunks in 157 graph layers
      Data type float32 numpy.ndarray
      10 52 4320 2041 23
    • zos
      (first_day_datetime, lead_day_index, latitude, longitude)
      float32
      dask.array<chunksize=(1, 1, 256, 512), meta=np.ndarray>
      long_name :
      Sea surface height
      standard_name :
      sea_surface_height_above_geoid
      units :
      m
      Array Chunk
      Bytes 17.08 GiB 512.00 kiB
      Shape (52, 10, 2041, 4320) (1, 1, 256, 512)
      Dask graph 37440 chunks in 157 graph layers
      Data type float32 numpy.ndarray
      52 1 4320 2041 10
    • depth
      PandasIndex
      PandasIndex(Index([0.49399998784065247,   2.645699977874756,   5.078199863433838,
               7.929599761962891,  11.404999732971191,  15.810099601745605,
              21.598800659179688,  29.444700241088867,   40.34410095214844,
               55.76430130004883,   77.85389709472656,   92.32610321044922,
              109.72930145263672,  130.66600036621094,  155.85069274902344,
              186.12559509277344,  222.47520446777344,   266.0403137207031,
               318.1274108886719,   380.2130126953125,   453.9377136230469,
               541.0889282226562,   643.5667724609375],
            dtype='float32', name='depth'))
    • latitude
      PandasIndex
      PandasIndex(Index([             -80.0, -79.91666412353516, -79.83333587646484,
                         -79.75, -79.66666412353516, -79.58333587646484,
                          -79.5, -79.41666412353516, -79.33333587646484,
                         -79.25,
             ...
                          89.25,  89.33334350585938,  89.41667175292969,
                           89.5,  89.58334350585938,  89.66667175292969,
                          89.75,  89.83334350585938,  89.91667175292969,
                           90.0],
            dtype='float32', name='latitude', length=2041))
    • 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, -179.9166717529297, -179.8333282470703,
                        -179.75, -179.6666717529297, -179.5833282470703,
                         -179.5, -179.4166717529297, -179.3333282470703,
                        -179.25,
             ...
             179.16668701171875,             179.25, 179.33334350585938,
             179.41668701171875,              179.5, 179.58334350585938,
             179.66668701171875,             179.75, 179.83334350585938,
             179.91668701171875],
            dtype='float32', name='longitude', length=4320))
    • 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
    challenger :
    xihe
    forecast_reference_time :
    2024-01-02
    oceanbench_source_kind :
    challenger
    oceanbench_source_name :
    xihe

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
Sea surface height (m) [sea_surface_height_above_geoid]{surface} 0.076726 0.083929 0.083576 0.082502 0.082190 0.087093 0.086212 0.085571 0.089102 0.089900
Temperature (°C) [sea_water_potential_temperature]{surface} 0.629868 0.636551 0.644635 0.672039 0.676311 0.703092 0.676269 0.742477 0.771685 0.793318
Salinity (PSU) [sea_water_salinity]{surface} 0.524505 0.514574 0.525958 0.526858 0.526786 0.516250 0.514341 0.515909 0.520586 0.504334
Meridional current (m/s) [northward_sea_water_velocity]{surface} 0.132223 0.129777 0.130181 0.130182 0.131323 0.131526 0.130368 0.131253 0.130856 0.131282
Zonal current (m/s) [eastward_sea_water_velocity]{surface} 0.135432 0.132321 0.133001 0.133917 0.135529 0.135583 0.134536 0.136210 0.136189 0.136189
Temperature (°C) [sea_water_potential_temperature]{50m} 0.861334 0.886597 0.881886 0.889478 0.892242 0.931173 0.864874 0.926561 0.949899 0.994700
Salinity (PSU) [sea_water_salinity]{50m} 0.252755 0.254781 0.253308 0.253052 0.255919 0.254125 0.253929 0.255163 0.256527 0.258861
Meridional current (m/s) [northward_sea_water_velocity]{50m} 0.121529 0.118999 0.118881 0.117899 0.118788 0.118759 0.117383 0.118371 0.117861 0.117701
Zonal current (m/s) [eastward_sea_water_velocity]{50m} 0.123306 0.120053 0.119727 0.118752 0.120193 0.119677 0.118454 0.119691 0.119571 0.119781
Temperature (°C) [sea_water_potential_temperature]{100m} 1.030896 1.063704 1.081340 1.093890 1.074241 1.100504 1.090984 1.112177 1.133298 1.163074
Salinity (PSU) [sea_water_salinity]{100m} 0.183027 0.184078 0.182609 0.183703 0.184056 0.182786 0.185215 0.184004 0.187482 0.186837
Meridional current (m/s) [northward_sea_water_velocity]{100m} 0.117458 0.114270 0.113489 0.111356 0.111678 0.111430 0.109546 0.110331 0.109601 0.109157
Zonal current (m/s) [eastward_sea_water_velocity]{100m} 0.122811 0.119426 0.118580 0.116469 0.116724 0.115893 0.114647 0.115533 0.114942 0.114928
Temperature (°C) [sea_water_potential_temperature]{200m} 0.880264 0.849661 0.873729 0.831915 0.870122 0.861051 0.857930 0.887938 0.867277 0.878264
Salinity (PSU) [sea_water_salinity]{200m} 0.145038 0.146706 0.147371 0.143928 0.144623 0.144112 0.141210 0.142404 0.140690 0.142278
Meridional current (m/s) [northward_sea_water_velocity]{200m} 0.112848 0.116040 0.113975 0.110626 0.110795 0.110346 0.110289 0.110393 0.108942 0.108167
Zonal current (m/s) [eastward_sea_water_velocity]{200m} 0.119335 0.122393 0.120595 0.117599 0.118125 0.117228 0.116415 0.116953 0.115789 0.114786
Temperature (°C) [sea_water_potential_temperature]{300m} 0.748191 0.708310 0.730090 0.700148 0.729757 0.729461 0.714173 0.740630 0.731924 0.731412
Salinity (PSU) [sea_water_salinity]{300m} 0.118126 0.119155 0.121995 0.118139 0.118841 0.119253 0.115318 0.117926 0.115148 0.118110
Meridional current (m/s) [northward_sea_water_velocity]{300m} 0.109681 0.113194 0.111282 0.107941 0.108060 0.107670 0.107527 0.107343 0.106009 0.105061
Zonal current (m/s) [eastward_sea_water_velocity]{300m} 0.114999 0.118220 0.116693 0.113402 0.113901 0.113263 0.112870 0.113036 0.111723 0.110587
Temperature (°C) [sea_water_potential_temperature]{500m} 0.556726 0.536028 0.545908 0.528926 0.551378 0.545784 0.536114 0.552942 0.549364 0.548260
Salinity (PSU) [sea_water_salinity]{500m} 0.087459 0.089790 0.089289 0.088168 0.087352 0.089140 0.085900 0.087570 0.086417 0.088109
Meridional current (m/s) [northward_sea_water_velocity]{500m} 0.100228 0.103875 0.102240 0.098887 0.098821 0.098368 0.098056 0.097381 0.096466 0.095566
Zonal current (m/s) [eastward_sea_water_velocity]{500m} 0.104538 0.108192 0.106845 0.103578 0.103825 0.103267 0.102734 0.102520 0.101651 0.100741

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
Mixed layer depth (m) [ocean_mixed_layer_thickness]{surface} 66.613197 62.938297 64.006264 66.532356 62.059383 62.941429 66.68856 67.936646 69.876205 61.211857

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
Meridional geostrophic current (m/s) [geostrophic_northward_sea_water_velocity]{surface} 0.666276 0.690856 0.681229 0.681595 0.674515 0.666056 0.641394 0.670328 0.679011 0.656072
Zonal geostrophic current (m/s) [geostrophic_eastward_sea_water_velocity]{surface} 0.791730 0.803465 0.786177 0.769088 0.778899 0.769588 0.715272 0.737638 0.752962 0.746820

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
Temperature (°C) [sea_water_potential_temperature]{surface} 0.827681 0.850135 0.825018 0.864820 0.886349 0.935867 0.915200 0.942167 0.982418 0.959814
Temperature (°C) [sea_water_potential_temperature]{0-5m} 0.790706 0.826710 0.847602 0.887060 0.912828 0.922657 0.921889 0.919485 0.966517 0.998555
Temperature (°C) [sea_water_potential_temperature]{5-100m} 0.918791 0.942303 0.917347 0.968459 0.973882 0.990037 0.984000 1.011819 1.019024 1.050631
Temperature (°C) [sea_water_potential_temperature]{100-300m} 0.809930 0.824450 0.795232 0.831337 0.837570 0.821245 0.841779 0.836520 0.855257 0.855931
Temperature (°C) [sea_water_potential_temperature]{300-600m} 0.543093 0.538368 0.528825 0.538841 0.543478 0.550186 0.560908 0.566489 0.584120 0.570380
Salinity (PSU) [sea_water_salinity]{0-5m} 0.269382 0.293226 0.293964 0.304462 0.287155 0.299249 0.272486 0.278354 0.305268 0.303121
Salinity (PSU) [sea_water_salinity]{5-100m} 0.248634 0.250597 0.249743 0.255119 0.267397 0.250162 0.254363 0.252794 0.259799 0.261310
Salinity (PSU) [sea_water_salinity]{100-300m} 0.137681 0.135892 0.131146 0.140599 0.136592 0.132864 0.142001 0.136247 0.134200 0.137226
Salinity (PSU) [sea_water_salinity]{300-600m} 0.080870 0.082628 0.079516 0.081017 0.079216 0.079789 0.082040 0.082919 0.083415 0.083495
Sea level anomaly (m) [sea_surface_height_above_geoid]{surface} 0.054363 0.055488 0.056390 0.059203 0.060995 0.063485 0.065997 0.065554 0.067905 0.069092
Zonal current (m/s) [eastward_sea_water_velocity]{15m} 0.218455 0.215305 0.217684 0.217741 0.216582 0.216584 0.218436 0.219323 0.218594 0.220536
Meridional current (m/s) [northward_sea_water_velocity]{15m} 0.199061 0.196908 0.197786 0.199661 0.199683 0.200544 0.199650 0.200301 0.199249 0.200112

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
Lagrangian trajectory deviation (km) []{surface} 11.914344 23.026192 33.362679 43.126549 52.474358 61.364708 69.865959 78.120132

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
Sea surface height (m) [sea_surface_height_above_geoid]{surface} 0.035551 0.043190 0.045651 0.048727 0.052177 0.056301 0.059414 0.060321 0.062903 0.064329
Temperature (°C) [sea_water_potential_temperature]{surface} 0.454202 0.486987 0.497021 0.547273 0.570087 0.612887 0.604224 0.672931 0.692320 0.720710
Salinity (PSU) [sea_water_salinity]{surface} 0.259571 0.308280 0.298078 0.316531 0.325396 0.349453 0.360162 0.375083 0.387104 0.405881
Meridional current (m/s) [northward_sea_water_velocity]{surface} 0.060879 0.073777 0.083883 0.092683 0.101338 0.108449 0.115101 0.121287 0.124526 0.127748
Zonal current (m/s) [eastward_sea_water_velocity]{surface} 0.065079 0.076587 0.086170 0.095918 0.104602 0.112450 0.118844 0.125851 0.129877 0.132720
Temperature (°C) [sea_water_potential_temperature]{50m} 0.547107 0.604393 0.608878 0.653831 0.681978 0.735985 0.721259 0.773058 0.791627 0.842497
Salinity (PSU) [sea_water_salinity]{50m} 0.112799 0.128895 0.129270 0.142911 0.147995 0.153805 0.158284 0.163890 0.170335 0.169095
Meridional current (m/s) [northward_sea_water_velocity]{50m} 0.047347 0.057714 0.066332 0.073866 0.082299 0.089716 0.096668 0.103518 0.106983 0.110337
Zonal current (m/s) [eastward_sea_water_velocity]{50m} 0.048232 0.058225 0.066741 0.075343 0.083408 0.091131 0.098781 0.105549 0.109719 0.113530
Temperature (°C) [sea_water_potential_temperature]{100m} 0.561607 0.603770 0.623086 0.673661 0.700415 0.745735 0.772834 0.815991 0.842215 0.872446
Salinity (PSU) [sea_water_salinity]{100m} 0.096557 0.108344 0.108355 0.120298 0.121426 0.126584 0.130387 0.134046 0.138397 0.137320
Meridional current (m/s) [northward_sea_water_velocity]{100m} 0.042023 0.052609 0.060562 0.067902 0.075620 0.082854 0.089248 0.095467 0.098813 0.101693
Zonal current (m/s) [eastward_sea_water_velocity]{100m} 0.042201 0.054010 0.062155 0.069973 0.077628 0.084793 0.091232 0.097486 0.101231 0.104175
Temperature (°C) [sea_water_potential_temperature]{200m} 0.450583 0.414833 0.422731 0.480147 0.492359 0.515109 0.553035 0.581673 0.581170 0.595240
Salinity (PSU) [sea_water_salinity]{200m} 0.075169 0.074562 0.073735 0.083805 0.084987 0.088828 0.095038 0.098577 0.100267 0.101284
Meridional current (m/s) [northward_sea_water_velocity]{200m} 0.063987 0.040038 0.044957 0.052811 0.057689 0.064314 0.070551 0.075851 0.078556 0.081415
Zonal current (m/s) [eastward_sea_water_velocity]{200m} 0.058770 0.039496 0.044433 0.052433 0.057078 0.063328 0.069573 0.074598 0.077434 0.080275
Temperature (°C) [sea_water_potential_temperature]{300m} 0.398476 0.350897 0.359088 0.404292 0.420920 0.440538 0.471224 0.500090 0.504076 0.513400
Salinity (PSU) [sea_water_salinity]{300m} 0.065255 0.062836 0.064310 0.071046 0.072948 0.076795 0.081262 0.084431 0.085381 0.087187
Meridional current (m/s) [northward_sea_water_velocity]{300m} 0.058759 0.037033 0.041760 0.049300 0.053811 0.059927 0.065901 0.070987 0.073615 0.076403
Zonal current (m/s) [eastward_sea_water_velocity]{300m} 0.053356 0.035994 0.040882 0.048322 0.052820 0.058552 0.064537 0.069319 0.072076 0.074811
Temperature (°C) [sea_water_potential_temperature]{500m} 0.314704 0.285983 0.283610 0.325199 0.333044 0.343778 0.370636 0.390765 0.395176 0.401020
Salinity (PSU) [sea_water_salinity]{500m} 0.053945 0.053107 0.052125 0.057572 0.057600 0.061271 0.063637 0.065531 0.065629 0.067448
Meridional current (m/s) [northward_sea_water_velocity]{500m} 0.049193 0.033147 0.037709 0.044652 0.048497 0.053562 0.058969 0.063243 0.065622 0.068080
Zonal current (m/s) [eastward_sea_water_velocity]{500m} 0.044174 0.032260 0.036767 0.043803 0.047444 0.052221 0.057476 0.061622 0.064023 0.066487

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
Mixed layer depth (m) [ocean_mixed_layer_thickness]{surface} 62.709129 57.64518 59.842758 62.855507 57.727131 58.787022 63.137215 64.407211 66.715134 56.990421

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
Meridional geostrophic current (m/s) [geostrophic_northward_sea_water_velocity]{surface} 0.661467 0.686062 0.677284 0.678250 0.672306 0.664370 0.640532 0.669968 0.679082 0.656538
Zonal geostrophic current (m/s) [geostrophic_eastward_sea_water_velocity]{surface} 0.788226 0.799893 0.783338 0.766771 0.778300 0.769611 0.715821 0.739305 0.754964 0.748757

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
Lagrangian trajectory deviation (km) []{surface} 5.652573 11.56456 17.548149 23.808969 30.475452 37.451015 44.686951 52.148106
 

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