Open challenger datasets

import oceanbench

oceanbench.__version__

'0.2.0'

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,
                         lat: 672, lon: 1440)
Coordinates:
  * depth               (depth) float32 84B 0.494 47.37 ... 4.833e+03 5.275e+03
  * lat                 (lat) 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
  * lon                 (lon) float64 12kB -180.0 -179.8 -179.5 ... 179.5 179.8
  * first_day_datetime  (first_day_datetime) datetime64[us] 416B 2024-01-03 ....
Data variables:
    so                  (first_day_datetime, lead_day_index, depth, lat, lon) float64 85GB dask.array<chunksize=(1, 10, 1, 672, 1440), meta=np.ndarray>
    thetao              (first_day_datetime, lead_day_index, depth, lat, lon) float64 85GB dask.array<chunksize=(1, 10, 1, 672, 1440), meta=np.ndarray>
    uo                  (first_day_datetime, lead_day_index, depth, lat, lon) float64 85GB dask.array<chunksize=(1, 10, 1, 672, 1440), meta=np.ndarray>
    vo                  (first_day_datetime, lead_day_index, depth, lat, lon) float64 85GB dask.array<chunksize=(1, 10, 1, 672, 1440), meta=np.ndarray>
    zos                 (first_day_datetime, lead_day_index, lat, lon) float64 4GB dask.array<chunksize=(1, 10, 672, 1440), meta=np.ndarray>
Attributes:
    regrid_method:           bilinear
    oceanbench_source_kind:  challenger
    oceanbench_source_name:  glonet

xarray.Dataset

• Dimensions:
  • first_day_datetime: 52
  • lead_day_index: 10
  • depth: 21
  • lat: 672
  • lon: 1440
• Coordinates: (5)
  • depth
    (depth)
    float32
    0.494 47.37 ... 4.833e+03 5.275e+03

    long_name :

    Depth

    standard_name :

    depth

    units :

    m

    units_long :

    Meters

    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)

  • lat
    (lat)
    float64
    -78.0 -77.75 -77.5 ... 89.5 89.75

    axis :

    Y

    long_name :

    Latitude

    standard_name :

    latitude

    units :

    degrees_north

    units_long :

    Degrees North

    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])

  • lon
    (lon)
    float64
    -180.0 -179.8 ... 179.5 179.8

    axis :

    X

    long_name :

    Longitude

    standard_name :

    longitude

    units :

    degrees_east

    units_long :

    Degrees East

    array([-180.  , -179.75, -179.5 , ...,  179.25,  179.5 ,  179.75],
          shape=(1440,))

  • first_day_datetime
    (first_day_datetime)
    datetime64[us]
    2024-01-03 ... 2024-12-25

    array(['2024-01-03T00:00:00.000000', '2024-01-10T00:00:00.000000',
           '2024-01-17T00:00:00.000000', '2024-01-24T00:00:00.000000',
           '2024-01-31T00:00:00.000000', '2024-02-07T00:00:00.000000',
           '2024-02-14T00:00:00.000000', '2024-02-21T00:00:00.000000',
           '2024-02-28T00:00:00.000000', '2024-03-06T00:00:00.000000',
           '2024-03-13T00:00:00.000000', '2024-03-20T00:00:00.000000',
           '2024-03-27T00:00:00.000000', '2024-04-03T00:00:00.000000',
           '2024-04-10T00:00:00.000000', '2024-04-17T00:00:00.000000',
           '2024-04-24T00:00:00.000000', '2024-05-01T00:00:00.000000',
           '2024-05-08T00:00:00.000000', '2024-05-15T00:00:00.000000',
           '2024-05-22T00:00:00.000000', '2024-05-29T00:00:00.000000',
           '2024-06-05T00:00:00.000000', '2024-06-12T00:00:00.000000',
           '2024-06-19T00:00:00.000000', '2024-06-26T00:00:00.000000',
           '2024-07-03T00:00:00.000000', '2024-07-10T00:00:00.000000',
           '2024-07-17T00:00:00.000000', '2024-07-24T00:00:00.000000',
           '2024-07-31T00:00:00.000000', '2024-08-07T00:00:00.000000',
           '2024-08-14T00:00:00.000000', '2024-08-21T00:00:00.000000',
           '2024-08-28T00:00:00.000000', '2024-09-04T00:00:00.000000',
           '2024-09-11T00:00:00.000000', '2024-09-18T00:00:00.000000',
           '2024-09-25T00:00:00.000000', '2024-10-02T00:00:00.000000',
           '2024-10-09T00:00:00.000000', '2024-10-16T00:00:00.000000',
           '2024-10-23T00:00:00.000000', '2024-10-30T00:00:00.000000',
           '2024-11-06T00:00:00.000000', '2024-11-13T00:00:00.000000',
           '2024-11-20T00:00:00.000000', '2024-11-27T00:00:00.000000',
           '2024-12-04T00:00:00.000000', '2024-12-11T00:00:00.000000',
           '2024-12-18T00:00:00.000000', '2024-12-25T00:00:00.000000'],
          dtype='datetime64[us]')

• Data variables: (5)
  • so
    (first_day_datetime, lead_day_index, depth, lat, lon)
    float64
    dask.array<chunksize=(1, 10, 1, 672, 1440), meta=np.ndarray>

    standard_name :

    sea_water_salinity

    Array Chunk Bytes 78.73 GiB 73.83 MiB Shape (52, 10, 21, 672, 1440) (1, 10, 1, 672, 1440) Dask graph 1092 chunks in 157 graph layers Data type float64 numpy.ndarray

  • thetao
    (first_day_datetime, lead_day_index, depth, lat, lon)
    float64
    dask.array<chunksize=(1, 10, 1, 672, 1440), meta=np.ndarray>

    standard_name :

    sea_water_potential_temperature

    Array Chunk Bytes 78.73 GiB 73.83 MiB Shape (52, 10, 21, 672, 1440) (1, 10, 1, 672, 1440) Dask graph 1092 chunks in 157 graph layers Data type float64 numpy.ndarray

  • uo
    (first_day_datetime, lead_day_index, depth, lat, lon)
    float64
    dask.array<chunksize=(1, 10, 1, 672, 1440), meta=np.ndarray>

    standard_name :

    eastward_sea_water_velocity

    Array Chunk Bytes 78.73 GiB 73.83 MiB Shape (52, 10, 21, 672, 1440) (1, 10, 1, 672, 1440) Dask graph 1092 chunks in 157 graph layers Data type float64 numpy.ndarray

  • vo
    (first_day_datetime, lead_day_index, depth, lat, lon)
    float64
    dask.array<chunksize=(1, 10, 1, 672, 1440), meta=np.ndarray>

    standard_name :

    northward_sea_water_velocity

    Array Chunk Bytes 78.73 GiB 73.83 MiB Shape (52, 10, 21, 672, 1440) (1, 10, 1, 672, 1440) Dask graph 1092 chunks in 157 graph layers Data type float64 numpy.ndarray

  • zos
    (first_day_datetime, lead_day_index, lat, lon)
    float64
    dask.array<chunksize=(1, 10, 672, 1440), meta=np.ndarray>

    standard_name :

    sea_surface_height_above_geoid

    Array Chunk Bytes 3.75 GiB 73.83 MiB Shape (52, 10, 672, 1440) (1, 10, 672, 1440) Dask graph 52 chunks in 157 graph layers Data type float64 numpy.ndarray

• Indexes: (5)
  • 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'))

  • lat
    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='lat', length=672))

  • lead_day_index
    PandasIndex

    PandasIndex(Index([0, 1, 2, 3, 4, 5, 6, 7, 8, 9], dtype='int64', name='lead_day_index'))

  • lon
    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='lon', 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[us]', name='first_day_datetime', freq=None))

• Attributes: (3)

  regrid_method :

  bilinear

  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
Sea surface height (m) [sea_surface_height_above_geoid]{surface}	0.074917	0.075609	0.076512	0.077164	0.081231	0.081356	0.083916	0.083968	0.088193	0.088645
Temperature (°C) [sea_water_potential_temperature]{surface}	0.653493	0.668673	0.684687	0.689508	0.745070	0.757647	0.823643	0.825621	0.897667	0.913006
Salinity (PSU) [sea_water_salinity]{surface}	0.784364	0.779122	0.789065	0.784865	0.794788	0.786468	0.800714	0.793921	0.808190	0.794032
Meridional current (m/s) [northward_sea_water_velocity]{surface}	0.123780	0.123123	0.123664	0.124188	0.127241	0.127934	0.131073	0.133070	0.136927	0.138057
Zonal current (m/s) [eastward_sea_water_velocity]{surface}	0.124898	0.124549	0.125849	0.126905	0.130907	0.131856	0.134816	0.137345	0.141916	0.143689
Temperature (°C) [sea_water_potential_temperature]{50m}	0.950838	0.960983	0.979252	0.997108	1.033280	1.069808	1.106541	1.161922	1.192329	1.262406
Salinity (PSU) [sea_water_salinity]{50m}	0.359301	0.358292	0.366537	0.366240	0.372034	0.372357	0.377904	0.378843	0.384317	0.385659
Meridional current (m/s) [northward_sea_water_velocity]{50m}	0.109348	0.109203	0.108095	0.109004	0.110015	0.112219	0.114789	0.118052	0.120380	0.122990
Zonal current (m/s) [eastward_sea_water_velocity]{50m}	0.110953	0.110641	0.109742	0.110467	0.111442	0.113338	0.115688	0.118729	0.121339	0.124503
Temperature (°C) [sea_water_potential_temperature]{100m}	1.013975	1.018525	1.032025	1.046868	1.063016	1.092178	1.111447	1.153763	1.171003	1.223978
Salinity (PSU) [sea_water_salinity]{100m}	0.246523	0.246794	0.249711	0.250683	0.253024	0.254625	0.256996	0.259219	0.261306	0.263804
Meridional current (m/s) [northward_sea_water_velocity]{100m}	0.105945	0.105855	0.104525	0.105061	0.105411	0.106600	0.107987	0.109739	0.110915	0.112193
Zonal current (m/s) [eastward_sea_water_velocity]{100m}	0.110722	0.110734	0.109617	0.110044	0.110426	0.111623	0.113112	0.115188	0.116817	0.118635
Temperature (°C) [sea_water_potential_temperature]{200m}	0.866920	0.870845	0.878681	0.883483	0.887908	0.895494	0.904180	0.914545	0.925264	0.936120
Salinity (PSU) [sea_water_salinity]{200m}	0.159622	0.159799	0.159967	0.160373	0.161090	0.161860	0.162948	0.164007	0.165058	0.166200
Meridional current (m/s) [northward_sea_water_velocity]{200m}	0.102400	0.102331	0.100579	0.100846	0.100593	0.101262	0.101794	0.102904	0.103303	0.104081
Zonal current (m/s) [eastward_sea_water_velocity]{200m}	0.108217	0.108135	0.106812	0.107002	0.107012	0.107686	0.108416	0.109504	0.110157	0.110961
Temperature (°C) [sea_water_potential_temperature]{300m}	0.734778	0.735396	0.736325	0.737507	0.732311	0.736063	0.735859	0.742506	0.745704	0.752214
Salinity (PSU) [sea_water_salinity]{300m}	0.124912	0.124815	0.125415	0.125307	0.125971	0.126063	0.126989	0.127309	0.128231	0.128575
Meridional current (m/s) [northward_sea_water_velocity]{300m}	0.099826	0.099794	0.097926	0.098095	0.097691	0.098238	0.098607	0.099522	0.099780	0.100428
Zonal current (m/s) [eastward_sea_water_velocity]{300m}	0.103930	0.103870	0.102214	0.102310	0.102022	0.102456	0.102838	0.103591	0.103985	0.104548
Temperature (°C) [sea_water_potential_temperature]{500m}	0.545585	0.547753	0.537034	0.539727	0.540524	0.544230	0.550843	0.555686	0.564125	0.568008
Salinity (PSU) [sea_water_salinity]{500m}	0.091974	0.091945	0.092292	0.092268	0.093319	0.093435	0.094779	0.095063	0.096352	0.096659
Meridional current (m/s) [northward_sea_water_velocity]{500m}	0.091398	0.091301	0.089504	0.089491	0.089009	0.089284	0.089434	0.089950	0.090080	0.090419
Zonal current (m/s) [eastward_sea_water_velocity]{500m}	0.095011	0.094899	0.093237	0.093249	0.092929	0.093205	0.093467	0.093983	0.094280	0.094677

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}	47.418571	48.142452	51.06374	52.124054	54.746792	56.308804	57.909355	59.070194	60.091621	61.383015

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}	0.17652	0.173261	0.221775	0.217936	0.259315	0.257165	0.288926	0.291178	0.316608	0.323794
Zonal geostrophic current (m/s) [geostrophic_eastward_sea_water_velocity]{surface}	0.15148	0.157602	0.181300	0.186301	0.209260	0.218171	0.234063	0.247203	0.260786	0.276664

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}	0.759423	0.790359	0.798785	0.816417	0.874569	0.908491	0.949588	0.954193	1.016967	0.995746
Temperature (°C) [sea_water_potential_temperature]{0-5m}	0.807080	0.837448	0.885974	0.913160	0.949393	0.952410	1.016724	1.004103	1.059881	1.085458
Temperature (°C) [sea_water_potential_temperature]{5-100m}	1.075647	1.097325	1.094423	1.105662	1.162849	1.156355	1.205210	1.251955	1.291900	1.316694
Temperature (°C) [sea_water_potential_temperature]{100-300m}	0.854673	0.878838	0.865922	0.881164	0.918363	0.908868	0.950205	0.966040	0.995139	1.007091
Temperature (°C) [sea_water_potential_temperature]{300-600m}	0.551765	0.569757	0.538838	0.547484	0.557455	0.560584	0.576611	0.587564	0.600256	0.593927
Salinity (PSU) [sea_water_salinity]{0-5m}	0.243836	0.250048	0.257300	0.290257	0.260298	0.272441	0.265854	0.256418	0.279985	0.291157
Salinity (PSU) [sea_water_salinity]{5-100m}	0.202617	0.202967	0.213884	0.207096	0.223777	0.222545	0.223054	0.216173	0.234219	0.238673
Salinity (PSU) [sea_water_salinity]{100-300m}	0.133262	0.134733	0.133302	0.132093	0.137895	0.133888	0.143620	0.139588	0.145275	0.145401
Salinity (PSU) [sea_water_salinity]{300-600m}	0.082012	0.082092	0.081161	0.081172	0.083652	0.084656	0.086940	0.088770	0.090271	0.091540
Sea level anomaly (m) [sea_surface_height_above_geoid]{surface}	0.108831	0.109502	0.109876	0.112825	0.111972	0.115381	0.114805	0.120185	0.118330	0.123063
Zonal current (m/s) [eastward_sea_water_velocity]{15m}	0.207896	0.207350	0.209468	0.210460	0.209568	0.210414	0.214402	0.215575	0.216117	0.217876
Meridional current (m/s) [northward_sea_water_velocity]{15m}	0.192585	0.191873	0.192831	0.194819	0.196243	0.197425	0.197650	0.199064	0.199674	0.200648

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}	9.892875	18.954	27.544943	35.931477	44.125797	52.09251	59.901028	67.644791

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}	0.025583	0.029117	0.033383	0.039416	0.045627	0.050024	0.053732	0.058930	0.062251	0.066121
Temperature (°C) [sea_water_potential_temperature]{surface}	0.389471	0.412645	0.485869	0.501431	0.596709	0.623799	0.711621	0.725284	0.806660	0.833109
Salinity (PSU) [sea_water_salinity]{surface}	0.140916	0.146462	0.203252	0.213358	0.255208	0.267359	0.299953	0.311225	0.340455	0.348861
Meridional current (m/s) [northward_sea_water_velocity]{surface}	0.068325	0.071976	0.071801	0.080378	0.089814	0.097945	0.107000	0.114935	0.122532	0.127399
Zonal current (m/s) [eastward_sea_water_velocity]{surface}	0.064771	0.068845	0.071855	0.081153	0.092060	0.100413	0.109362	0.117794	0.126338	0.131918
Temperature (°C) [sea_water_potential_temperature]{50m}	0.699391	0.707628	0.751990	0.774050	0.837430	0.881586	0.945383	1.008628	1.058448	1.130846
Salinity (PSU) [sea_water_salinity]{50m}	0.095831	0.097780	0.134589	0.137478	0.161834	0.165318	0.183895	0.187332	0.202354	0.204958
Meridional current (m/s) [northward_sea_water_velocity]{50m}	0.047667	0.049887	0.054347	0.059318	0.065700	0.073517	0.081940	0.090480	0.097023	0.103440
Zonal current (m/s) [eastward_sea_water_velocity]{50m}	0.046523	0.048657	0.054857	0.060122	0.066536	0.074113	0.082604	0.091420	0.098710	0.106063
Temperature (°C) [sea_water_potential_temperature]{100m}	0.522847	0.526607	0.597924	0.622630	0.699546	0.745729	0.819989	0.879932	0.940328	1.003553
Salinity (PSU) [sea_water_salinity]{100m}	0.076010	0.076386	0.101227	0.102202	0.120608	0.121995	0.136997	0.138382	0.150349	0.150559
Meridional current (m/s) [northward_sea_water_velocity]{100m}	0.041927	0.043163	0.047638	0.052058	0.058009	0.064603	0.072090	0.079123	0.084788	0.089849
Zonal current (m/s) [eastward_sea_water_velocity]{100m}	0.040480	0.042029	0.047628	0.052504	0.058703	0.065680	0.073285	0.080929	0.087185	0.093154
Temperature (°C) [sea_water_potential_temperature]{200m}	0.391056	0.395777	0.448494	0.464096	0.501701	0.528645	0.566811	0.600517	0.630811	0.661304
Salinity (PSU) [sea_water_salinity]{200m}	0.050008	0.050174	0.068537	0.069837	0.082666	0.085043	0.094954	0.097859	0.104946	0.107253
Meridional current (m/s) [northward_sea_water_velocity]{200m}	0.032637	0.033100	0.037202	0.041037	0.046489	0.052556	0.059295	0.065895	0.071006	0.075811
Zonal current (m/s) [eastward_sea_water_velocity]{200m}	0.031223	0.031808	0.036427	0.040388	0.045863	0.052014	0.058707	0.065364	0.070606	0.075691
Temperature (°C) [sea_water_potential_temperature]{300m}	0.335492	0.339912	0.385208	0.399240	0.423070	0.448178	0.473117	0.504798	0.524609	0.553017
Salinity (PSU) [sea_water_salinity]{300m}	0.047760	0.047986	0.061836	0.063108	0.072131	0.074458	0.081321	0.084229	0.089002	0.091470
Meridional current (m/s) [northward_sea_water_velocity]{300m}	0.029454	0.029799	0.033865	0.037525	0.042764	0.048551	0.054930	0.061215	0.066083	0.070746
Zonal current (m/s) [eastward_sea_water_velocity]{300m}	0.028196	0.028568	0.033104	0.036841	0.042032	0.047872	0.054154	0.060437	0.065377	0.070208
Temperature (°C) [sea_water_potential_temperature]{500m}	0.194694	0.196094	0.246721	0.253839	0.297452	0.310491	0.349549	0.366145	0.395775	0.408791
Salinity (PSU) [sea_water_salinity]{500m}	0.035103	0.035132	0.046463	0.047006	0.055479	0.056580	0.063143	0.064618	0.069374	0.070598
Meridional current (m/s) [northward_sea_water_velocity]{500m}	0.025072	0.025466	0.029436	0.033001	0.037819	0.043030	0.048634	0.054128	0.058452	0.062577
Zonal current (m/s) [eastward_sea_water_velocity]{500m}	0.023865	0.024272	0.028673	0.032207	0.036947	0.042087	0.047549	0.053015	0.057399	0.061678

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}	41.05304	41.929909	46.365082	47.648685	51.052643	52.725246	54.690037	55.902821	57.099098	58.441353

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}	0.147910	0.145386	0.202040	0.200165	0.245076	0.24578	0.279598	0.284404	0.310714	0.319720
Zonal geostrophic current (m/s) [geostrophic_eastward_sea_water_velocity]{surface}	0.119306	0.128457	0.159862	0.168571	0.194220	0.20682	0.225022	0.241146	0.255697	0.272815

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}	4.453069	8.62245	12.893026	17.849806	23.46216	29.620039	36.278549	43.364353