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 WenHai forecasts with xarray
import xarray
import oceanbench

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

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[us] 416B 2024-01-03 ....
Data variables:
    so                  (first_day_datetime, lead_day_index, depth, latitude, longitude) float32 422GB dask.array<chunksize=(1, 1, 1, 75, 4320), meta=np.ndarray>
    thetao              (first_day_datetime, lead_day_index, depth, latitude, longitude) float32 422GB dask.array<chunksize=(1, 1, 1, 75, 4320), meta=np.ndarray>
    uo                  (first_day_datetime, lead_day_index, depth, latitude, longitude) float32 422GB dask.array<chunksize=(1, 1, 1, 75, 4320), meta=np.ndarray>
    vo                  (first_day_datetime, lead_day_index, depth, latitude, longitude) float32 422GB dask.array<chunksize=(1, 1, 1, 75, 4320), meta=np.ndarray>
    zos                 (first_day_datetime, lead_day_index, latitude, longitude) float32 18GB dask.array<chunksize=(1, 1, 75, 4320), meta=np.ndarray>
Attributes:
    oceanbench_source_kind:  challenger
    oceanbench_source_name:  wenhai

xarray.Dataset

• Dimensions:
  • first_day_datetime: 52
  • lead_day_index: 10
  • depth: 23
  • latitude: 2041
  • longitude: 4320
• Coordinates: (5)
  • depth
    (depth)
    float32
    0.494 2.646 5.078 ... 541.1 643.6

    long_name :

    Depth

    standard_name :

    depth

    units :

    m

    units_long :

    Meters

    array([4.940250e-01, 2.645669e+00, 5.078224e+00, 7.929560e+00, 1.140500e+01,
           1.581007e+01, 2.159882e+01, 2.944473e+01, 4.034405e+01, 5.576429e+01,
           7.785385e+01, 9.232607e+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

    units_long :

    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

    units_long :

    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[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, latitude, longitude)
    float32
    dask.array<chunksize=(1, 1, 1, 75, 4320), meta=np.ndarray>

    standard_name :

    sea_water_salinity

    Array Chunk Bytes 392.84 GiB 1.24 MiB Shape (52, 10, 23, 2041, 4320) (1, 1, 1, 75, 4320) Dask graph 334880 chunks in 157 graph layers Data type float32 numpy.ndarray

  • thetao
    (first_day_datetime, lead_day_index, depth, latitude, longitude)
    float32
    dask.array<chunksize=(1, 1, 1, 75, 4320), meta=np.ndarray>

    standard_name :

    sea_water_potential_temperature

    Array Chunk Bytes 392.84 GiB 1.24 MiB Shape (52, 10, 23, 2041, 4320) (1, 1, 1, 75, 4320) Dask graph 334880 chunks in 157 graph layers Data type float32 numpy.ndarray

  • uo
    (first_day_datetime, lead_day_index, depth, latitude, longitude)
    float32
    dask.array<chunksize=(1, 1, 1, 75, 4320), meta=np.ndarray>

    standard_name :

    eastward_sea_water_velocity

    Array Chunk Bytes 392.84 GiB 1.24 MiB Shape (52, 10, 23, 2041, 4320) (1, 1, 1, 75, 4320) Dask graph 334880 chunks in 157 graph layers Data type float32 numpy.ndarray

  • vo
    (first_day_datetime, lead_day_index, depth, latitude, longitude)
    float32
    dask.array<chunksize=(1, 1, 1, 75, 4320), meta=np.ndarray>

    standard_name :

    northward_sea_water_velocity

    Array Chunk Bytes 392.84 GiB 1.24 MiB Shape (52, 10, 23, 2041, 4320) (1, 1, 1, 75, 4320) Dask graph 334880 chunks in 157 graph layers Data type float32 numpy.ndarray

  • zos
    (first_day_datetime, lead_day_index, latitude, longitude)
    float32
    dask.array<chunksize=(1, 1, 75, 4320), meta=np.ndarray>

    standard_name :

    sea_surface_height_above_geoid

    Array Chunk Bytes 17.08 GiB 1.24 MiB Shape (52, 10, 2041, 4320) (1, 1, 75, 4320) Dask graph 14560 chunks in 157 graph layers Data type float32 numpy.ndarray

• Indexes: (5)
  • depth
    PandasIndex

    PandasIndex(Index([0.49402499198913574,  2.6456689834594727,   5.078224182128906,
              7.92956018447876,  11.404999732971191,  15.810070037841797,
            21.598819732666016,  29.444730758666992,  40.344051361083984,
             55.76428985595703,   77.85385131835938,    92.3260726928711,
            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[us]', name='first_day_datetime', freq=None))

• Attributes: (2)

  oceanbench_source_kind :

  challenger

  oceanbench_source_name :

  wenhai

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}	0.117936	0.119326	0.120405	0.121890	0.123527	0.124938	0.126198	0.128150	0.129734	0.131197
Temperature (°C) [sea_water_potential_temperature]{surface}	0.636610	0.676715	0.724786	0.777295	0.833948	0.894556	0.956482	1.019887	1.081684	1.143576
Salinity (PSU) [sea_water_salinity]{surface}	1.165410	1.159223	1.154345	1.150104	1.146210	1.142716	1.139488	1.136587	1.133925	1.131841
Meridional current (m/s) [northward_sea_water_velocity]{surface}	0.169033	0.171479	0.172797	0.173662	0.173647	0.174265	0.174428	0.175774	0.176791	0.177929
Zonal current (m/s) [eastward_sea_water_velocity]{surface}	0.175052	0.178725	0.181329	0.183258	0.185767	0.188347	0.191473	0.195155	0.198207	0.200856
Temperature (°C) [sea_water_potential_temperature]{50m}	0.908994	0.913487	0.920660	0.929841	0.943584	0.959693	0.975712	0.993755	1.012006	1.031556
Salinity (PSU) [sea_water_salinity]{50m}	1.118684	1.118045	1.117535	1.117115	1.116808	1.116618	1.116468	1.116366	1.116281	1.116234
Meridional current (m/s) [northward_sea_water_velocity]{50m}	0.152908	0.153765	0.154233	0.154652	0.155090	0.156234	0.157344	0.158785	0.159863	0.160897
Zonal current (m/s) [eastward_sea_water_velocity]{50m}	0.160478	0.161111	0.162077	0.162970	0.164255	0.166103	0.168386	0.170798	0.173035	0.175370
Temperature (°C) [sea_water_potential_temperature]{100m}	1.043987	1.041574	1.042213	1.045517	1.049893	1.055099	1.061954	1.069025	1.074913	1.082386
Salinity (PSU) [sea_water_salinity]{100m}	1.058178	1.057918	1.057716	1.057553	1.057452	1.057398	1.057386	1.057391	1.057365	1.057352
Meridional current (m/s) [northward_sea_water_velocity]{100m}	0.136102	0.136015	0.136185	0.136648	0.137546	0.138529	0.139631	0.140828	0.141658	0.142459
Zonal current (m/s) [eastward_sea_water_velocity]{100m}	0.140943	0.140957	0.141284	0.142017	0.143056	0.144393	0.146023	0.147744	0.148988	0.150145
Temperature (°C) [sea_water_potential_temperature]{200m}	0.884340	0.884433	0.885293	0.886902	0.889292	0.892907	0.897694	0.903039	0.906942	0.911333
Salinity (PSU) [sea_water_salinity]{200m}	0.998186	0.998076	0.997996	0.997945	0.997927	0.997940	0.997967	0.997998	0.998004	0.998022
Meridional current (m/s) [northward_sea_water_velocity]{200m}	0.122751	0.122261	0.122046	0.122082	0.122263	0.122611	0.123239	0.124017	0.124487	0.124951
Zonal current (m/s) [eastward_sea_water_velocity]{200m}	0.130453	0.130082	0.129851	0.129820	0.130087	0.130668	0.131494	0.132347	0.132887	0.133434
Temperature (°C) [sea_water_potential_temperature]{300m}	0.745871	0.743991	0.742910	0.742717	0.743423	0.745199	0.747995	0.751226	0.752776	0.754548
Salinity (PSU) [sea_water_salinity]{300m}	0.924675	0.924586	0.924526	0.924485	0.924458	0.924456	0.924467	0.924486	0.924485	0.924491
Meridional current (m/s) [northward_sea_water_velocity]{300m}	0.114820	0.114286	0.113984	0.113914	0.114030	0.114383	0.114980	0.115646	0.116015	0.116379
Zonal current (m/s) [eastward_sea_water_velocity]{300m}	0.120393	0.120039	0.119861	0.119881	0.120076	0.120489	0.121137	0.121874	0.122411	0.122959
Temperature (°C) [sea_water_potential_temperature]{500m}	0.558853	0.557991	0.557703	0.558112	0.559218	0.561123	0.563738	0.566703	0.568641	0.570782
Salinity (PSU) [sea_water_salinity]{500m}	0.807835	0.807768	0.807712	0.807669	0.807636	0.807613	0.807599	0.807589	0.807568	0.807549
Meridional current (m/s) [northward_sea_water_velocity]{500m}	0.102864	0.102299	0.101909	0.101693	0.101654	0.101816	0.102129	0.102516	0.102742	0.103000
Zonal current (m/s) [eastward_sea_water_velocity]{500m}	0.104457	0.103984	0.103689	0.103586	0.103659	0.103909	0.104365	0.104916	0.105296	0.105677

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}	40.989891	44.66428	48.199032	51.175068	53.73135	56.075073	58.270535	60.281654	62.023113	63.750553

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}	2.003364	2.001574	2.001816	2.002808	2.004714	2.007325	2.010693	2.014608	2.019036	2.024157
Zonal geostrophic current (m/s) [geostrophic_eastward_sea_water_velocity]{surface}	1.374501	1.374736	1.375313	1.376242	1.377484	1.378612	1.379764	1.381036	1.382474	1.383831

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}	0.826222	0.897982	0.923981	0.996089	1.083161	1.170855	1.236276	1.312160	1.392777	1.439388
Temperature (°C) [sea_water_potential_temperature]{0-5m}	0.789748	0.850788	0.930444	1.036360	1.105004	1.163745	1.262358	1.322898	1.425029	1.518971
Temperature (°C) [sea_water_potential_temperature]{5-100m}	0.905630	0.926770	0.932844	0.998875	1.020880	1.041443	1.075968	1.123357	1.156757	1.212691
Temperature (°C) [sea_water_potential_temperature]{100-300m}	0.830376	0.847431	0.839268	0.845265	0.874818	0.889800	0.905932	0.924203	0.946887	0.968450
Temperature (°C) [sea_water_potential_temperature]{300-600m}	0.561423	0.574833	0.582151	0.567878	0.583829	0.602180	0.610776	0.622046	0.633044	0.654323
Salinity (PSU) [sea_water_salinity]{0-5m}	0.275184	0.294415	0.290083	0.313835	0.290914	0.311716	0.292831	0.301578	0.317907	0.321107
Salinity (PSU) [sea_water_salinity]{5-100m}	0.272919	0.271807	0.272837	0.277795	0.283371	0.310991	0.301107	0.290185	0.286525	0.297370
Salinity (PSU) [sea_water_salinity]{100-300m}	0.356136	0.238899	0.254708	0.169031	0.166563	0.355329	0.242042	0.359265	0.243763	0.263459
Salinity (PSU) [sea_water_salinity]{300-600m}	0.289916	0.255591	0.334693	0.205744	0.147240	0.231281	0.236028	0.291814	0.257533	0.337816
Sea level anomaly (m) [sea_surface_height_above_geoid]{surface}	0.115417	0.117026	0.118630	0.120887	0.122861	0.125226	0.127472	0.129828	0.132340	0.134090
Zonal current (m/s) [eastward_sea_water_velocity]{15m}	0.221214	0.220049	0.223465	0.224547	0.223146	0.224418	0.228671	0.231042	0.230587	0.233563
Meridional current (m/s) [northward_sea_water_velocity]{15m}	0.199425	0.200555	0.202299	0.204824	0.205496	0.207515	0.208458	0.210780	0.211124	0.212584

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}	11.972132	23.633472	34.887955	45.829075	56.541447	67.022987	77.361565	87.643463

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}	0.025482	0.034515	0.040628	0.047213	0.053173	0.058105	0.062539	0.067846	0.071383	0.074650
Temperature (°C) [sea_water_potential_temperature]{surface}	0.218313	0.341897	0.451660	0.553087	0.651549	0.747403	0.840669	0.931545	1.014947	1.096082
Salinity (PSU) [sea_water_salinity]{surface}	0.156964	0.207174	0.248075	0.282948	0.312167	0.337679	0.362143	0.385489	0.405630	0.423130
Meridional current (m/s) [northward_sea_water_velocity]{surface}	0.075082	0.091375	0.100300	0.107087	0.112368	0.118462	0.123398	0.129844	0.134377	0.138488
Zonal current (m/s) [eastward_sea_water_velocity]{surface}	0.083591	0.101107	0.112058	0.120610	0.129828	0.138711	0.147807	0.157166	0.164176	0.169991
Temperature (°C) [sea_water_potential_temperature]{50m}	0.218471	0.297482	0.366370	0.430855	0.493030	0.552038	0.606945	0.658092	0.700077	0.741276
Salinity (PSU) [sea_water_salinity]{50m}	0.055039	0.074147	0.089309	0.102527	0.114730	0.126204	0.136973	0.146808	0.154710	0.162187
Meridional current (m/s) [northward_sea_water_velocity]{50m}	0.048003	0.059788	0.067698	0.074733	0.081964	0.090331	0.098032	0.105518	0.110710	0.115318
Zonal current (m/s) [eastward_sea_water_velocity]{50m}	0.043776	0.056274	0.066717	0.075461	0.084609	0.094418	0.104197	0.113087	0.120051	0.126546
Temperature (°C) [sea_water_potential_temperature]{100m}	0.229313	0.299454	0.363019	0.426032	0.485356	0.540632	0.597149	0.649329	0.687345	0.724520
Salinity (PSU) [sea_water_salinity]{100m}	0.041431	0.055156	0.065838	0.075231	0.084037	0.092487	0.100687	0.108268	0.113934	0.119189
Meridional current (m/s) [northward_sea_water_velocity]{100m}	0.033738	0.043421	0.051458	0.059575	0.068152	0.076427	0.084410	0.091669	0.096683	0.101070
Zonal current (m/s) [eastward_sea_water_velocity]{100m}	0.033030	0.043482	0.052434	0.061441	0.070471	0.079404	0.088178	0.096058	0.101763	0.106725
Temperature (°C) [sea_water_potential_temperature]{200m}	0.169728	0.226238	0.272728	0.316577	0.359625	0.402867	0.446585	0.487121	0.515684	0.541981
Salinity (PSU) [sea_water_salinity]{200m}	0.032491	0.043509	0.052259	0.059827	0.066821	0.073536	0.080059	0.086037	0.090535	0.094697
Meridional current (m/s) [northward_sea_water_velocity]{200m}	0.026985	0.035438	0.042539	0.049468	0.056394	0.063341	0.070411	0.076965	0.081507	0.085518
Zonal current (m/s) [eastward_sea_water_velocity]{200m}	0.025722	0.034473	0.041679	0.048747	0.055867	0.062982	0.070016	0.076451	0.081176	0.085418
Temperature (°C) [sea_water_potential_temperature]{300m}	0.143616	0.194493	0.235773	0.273981	0.311528	0.349290	0.387324	0.422343	0.446570	0.468767
Salinity (PSU) [sea_water_salinity]{300m}	0.028007	0.037612	0.045297	0.051901	0.057977	0.063777	0.069390	0.074519	0.078383	0.081939
Meridional current (m/s) [northward_sea_water_velocity]{300m}	0.025087	0.033265	0.040083	0.046652	0.053253	0.059923	0.066619	0.072785	0.077113	0.080960
Zonal current (m/s) [eastward_sea_water_velocity]{300m}	0.023691	0.032090	0.038993	0.045576	0.052166	0.058836	0.065468	0.071606	0.076155	0.080220
Temperature (°C) [sea_water_potential_temperature]{500m}	0.113169	0.158337	0.193957	0.225382	0.255180	0.284710	0.314195	0.341423	0.360400	0.377775
Salinity (PSU) [sea_water_salinity]{500m}	0.022792	0.030583	0.036837	0.042081	0.046759	0.051132	0.055305	0.059111	0.062013	0.064668
Meridional current (m/s) [northward_sea_water_velocity]{500m}	0.022555	0.030682	0.037202	0.043155	0.048942	0.054696	0.060360	0.065558	0.069382	0.072826
Zonal current (m/s) [eastward_sea_water_velocity]{500m}	0.021153	0.029520	0.036125	0.042113	0.047921	0.053690	0.059430	0.064766	0.068740	0.072272

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}	22.69087	29.883696	35.384216	39.592567	43.037315	45.854511	48.376492	50.521053	52.386028	54.182945

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}	0.148903	0.230443	0.313687	0.402502	0.493434	0.588748	0.67989	0.772022	0.865438	0.962317
Zonal geostrophic current (m/s) [geostrophic_eastward_sea_water_velocity]{surface}	0.108310	0.141786	0.167987	0.191738	0.212865	0.231705	0.25020	0.268083	0.284863	0.301078

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}	7.604764	15.685378	24.137423	33.069489	42.492592	52.282753	62.414532	72.851532