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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 XiHe forecasts with xarray
import xarray
import oceanbench

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

challenger_dataset
<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 Missing fraction
Sea surface height (m) [sea_surface_height_above_geoid]{surface} 0.076716 0.083912 0.083560 0.082479 0.082172 0.087070 0.086192 0.085548 0.089080 0.089884 0.000001
Temperature (°C) [sea_water_potential_temperature]{surface} 0.628932 0.635523 0.643679 0.671238 0.675221 0.702141 0.675301 0.741300 0.770586 0.792358 0.000000
Salinity (PSU) [sea_water_salinity]{surface} 0.520520 0.510803 0.521688 0.522537 0.522109 0.512183 0.510562 0.512113 0.516930 0.500890 0.000000
Meridional current (m/s) [northward_sea_water_velocity]{surface} 0.132252 0.129803 0.130207 0.130207 0.131349 0.131553 0.130394 0.131278 0.130881 0.131307 0.000000
Zonal current (m/s) [eastward_sea_water_velocity]{surface} 0.135460 0.132346 0.133026 0.133942 0.135554 0.135608 0.134561 0.136234 0.136213 0.136215 0.000000
Temperature (°C) [sea_water_potential_temperature]{50m} 0.857714 0.881721 0.876566 0.884869 0.887508 0.926433 0.859843 0.921232 0.944891 0.989729 0.000000
Salinity (PSU) [sea_water_salinity]{50m} 0.249008 0.250927 0.249369 0.248872 0.251614 0.249819 0.249851 0.250866 0.252216 0.254360 0.000000
Meridional current (m/s) [northward_sea_water_velocity]{50m} 0.121778 0.119225 0.119102 0.118110 0.118993 0.118964 0.117583 0.118573 0.118059 0.117900 0.000000
Zonal current (m/s) [eastward_sea_water_velocity]{50m} 0.123560 0.120281 0.119952 0.118966 0.120407 0.119888 0.118659 0.119899 0.119777 0.119992 0.000000
Temperature (°C) [sea_water_potential_temperature]{100m} 1.029823 1.062367 1.079988 1.092654 1.072968 1.099261 1.089853 1.111051 1.132234 1.162044 0.000000
Salinity (PSU) [sea_water_salinity]{100m} 0.182395 0.183335 0.181853 0.182873 0.183234 0.181947 0.184420 0.183161 0.186629 0.185948 0.000000
Meridional current (m/s) [northward_sea_water_velocity]{100m} 0.117488 0.114297 0.113516 0.111381 0.111703 0.111455 0.109570 0.110355 0.109624 0.109180 0.000000
Zonal current (m/s) [eastward_sea_water_velocity]{100m} 0.122841 0.119453 0.118607 0.116494 0.116749 0.115917 0.114671 0.115557 0.114966 0.114953 0.000000
Temperature (°C) [sea_water_potential_temperature]{200m} 0.879564 0.848807 0.873122 0.831051 0.869456 0.860513 0.857318 0.887391 0.866753 0.877782 0.000000
Salinity (PSU) [sea_water_salinity]{200m} 0.144886 0.146537 0.147237 0.143759 0.144492 0.144007 0.141081 0.142290 0.140584 0.142185 0.000000
Meridional current (m/s) [northward_sea_water_velocity]{200m} 0.112874 0.116067 0.114002 0.110650 0.110821 0.110371 0.110314 0.110418 0.108966 0.108191 0.000000
Zonal current (m/s) [eastward_sea_water_velocity]{200m} 0.119359 0.122416 0.120619 0.117620 0.118148 0.117250 0.116437 0.116976 0.115812 0.114809 0.000000
Temperature (°C) [sea_water_potential_temperature]{300m} 0.747584 0.707606 0.729574 0.699427 0.729172 0.728978 0.713608 0.740109 0.731435 0.730972 0.000000
Salinity (PSU) [sea_water_salinity]{300m} 0.117917 0.118938 0.121810 0.117926 0.118661 0.119098 0.115139 0.117759 0.114988 0.117966 0.000000
Meridional current (m/s) [northward_sea_water_velocity]{300m} 0.109701 0.113215 0.111303 0.107960 0.108080 0.107690 0.107547 0.107362 0.106028 0.105080 0.000000
Zonal current (m/s) [eastward_sea_water_velocity]{300m} 0.115017 0.118239 0.116712 0.113418 0.113919 0.113280 0.112887 0.113054 0.111741 0.110604 0.000000
Temperature (°C) [sea_water_potential_temperature]{500m} 0.556377 0.535637 0.545630 0.528542 0.551081 0.545530 0.535822 0.552665 0.549097 0.548028 0.000000
Salinity (PSU) [sea_water_salinity]{500m} 0.087385 0.089715 0.089224 0.088093 0.087289 0.089082 0.085835 0.087509 0.086355 0.088049 0.000000
Meridional current (m/s) [northward_sea_water_velocity]{500m} 0.100242 0.103891 0.102255 0.098901 0.098835 0.098381 0.098069 0.097394 0.096479 0.095578 0.000000
Zonal current (m/s) [eastward_sea_water_velocity]{500m} 0.104551 0.108207 0.106859 0.103590 0.103838 0.103280 0.102746 0.102533 0.101664 0.100753 0.000000

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} 66.635735 62.959354 64.027695 66.554794 62.080173 62.96244 66.711044 67.959686 69.899849 61.232536 0.0

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} 0.221379 0.229024 0.224693 0.229759 0.228288 0.233274 0.225284 0.232865 0.231600 0.230305 0.000004
Zonal geostrophic current (m/s) [geostrophic_eastward_sea_water_velocity]{surface} 0.223201 0.226724 0.223528 0.223758 0.222158 0.227557 0.217188 0.224061 0.226163 0.229656 0.000007

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} 0.801163 0.819833 0.794863 0.839350 0.856272 0.911393 0.892356 0.917092 0.955537 0.931938 150081 0
Temperature (°C) [sea_water_potential_temperature]{0-5m} 0.786284 0.823444 0.847882 0.887209 0.901378 0.914403 0.916298 0.917083 0.961890 0.992129 80763 0
Temperature (°C) [sea_water_potential_temperature]{5-100m} 0.909281 0.932653 0.907360 0.959584 0.960222 0.976426 0.973279 1.003122 1.009505 1.041286 1334564 0
Temperature (°C) [sea_water_potential_temperature]{100-300m} 0.807857 0.822879 0.796891 0.827828 0.835336 0.816845 0.840951 0.836716 0.857515 0.859511 2117343 0
Temperature (°C) [sea_water_potential_temperature]{300-600m} 0.541661 0.536868 0.529253 0.537184 0.541725 0.548466 0.559379 0.566445 0.584526 0.571844 2622487 0
Salinity (PSU) [sea_water_salinity]{0-5m} 0.259201 0.285479 0.281679 0.306581 0.277629 0.285114 0.271660 0.268460 0.303587 0.297807 68940 0
Salinity (PSU) [sea_water_salinity]{5-100m} 0.200856 0.213184 0.212412 0.221731 0.219871 0.215361 0.217634 0.213976 0.227629 0.225870 1136708 0
Salinity (PSU) [sea_water_salinity]{100-300m} 0.128446 0.131361 0.129056 0.133257 0.131669 0.126038 0.134569 0.129580 0.132140 0.135147 1803408 0
Salinity (PSU) [sea_water_salinity]{300-600m} 0.080013 0.082092 0.078658 0.080084 0.078222 0.078688 0.081220 0.082064 0.082852 0.082645 2225476 0
Sea level anomaly (m) [sea_surface_height_above_geoid]{surface} 0.053811 0.054881 0.055895 0.058740 0.060547 0.062969 0.065486 0.065036 0.067346 0.068601 15390586 0
Zonal current (m/s) [eastward_sea_water_velocity]{15m} 0.137079 0.135405 0.137066 0.136784 0.136837 0.135617 0.136133 0.137290 0.138134 0.139549 1202530 0
Meridional current (m/s) [northward_sea_water_velocity]{15m} 0.131117 0.128724 0.129884 0.130439 0.132086 0.131964 0.130296 0.130467 0.130408 0.132279 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} 11.915425 23.030924 33.370186 43.134529 52.483212 61.371029 69.877106 78.134804 86.133629

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} 0.035551 0.043190 0.045651 0.048727 0.052177 0.056301 0.059414 0.060321 0.062903 0.064329 1.072749e-06
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 0.000000e+00
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 0.000000e+00
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 1.072749e-06
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 1.072749e-06
Temperature (°C) [sea_water_potential_temperature]{50m} 0.541243 0.597533 0.601638 0.648146 0.676280 0.730540 0.715868 0.767415 0.786290 0.837329 0.000000e+00
Salinity (PSU) [sea_water_salinity]{50m} 0.109297 0.124944 0.126104 0.139459 0.145220 0.151050 0.155193 0.161162 0.167556 0.166540 0.000000e+00
Meridional current (m/s) [northward_sea_water_velocity]{50m} 0.047345 0.057719 0.066361 0.073914 0.082371 0.089813 0.096779 0.103651 0.107124 0.110493 8.514015e-07
Zonal current (m/s) [eastward_sea_water_velocity]{50m} 0.048241 0.058237 0.066777 0.075399 0.083491 0.091239 0.098905 0.105693 0.109875 0.113700 8.514015e-07
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 0.000000e+00
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 0.000000e+00
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 6.023157e-06
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 6.023157e-06
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 0.000000e+00
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 0.000000e+00
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 2.812068e-06
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 2.812068e-06
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 0.000000e+00
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 0.000000e+00
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 2.340138e-06
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 2.340138e-06
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 0.000000e+00
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 0.000000e+00
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 2.798286e-06
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 2.798286e-06

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} 62.709129 57.64518 59.842758 62.855507 57.727131 58.787022 63.137215 64.407211 66.715134 56.990421 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} 0.204580 0.214278 0.210426 0.217324 0.217247 0.224261 0.218421 0.227418 0.227417 0.226908 0.000003
Zonal geostrophic current (m/s) [geostrophic_eastward_sea_water_velocity]{surface} 0.207338 0.212737 0.209980 0.211711 0.211914 0.219368 0.210705 0.219003 0.222359 0.226737 0.000001

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} 5.653659 11.56801 17.554674 23.817381 30.485514 37.461853 44.698421 52.16349 59.688107
 

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