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 LangYa forecasts with xarray
import xarray
import oceanbench

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

challenger_dataset

<xarray.Dataset> Size: 2TB
Dimensions:             (first_day_datetime: 52, lead_day_index: 7, depth: 32,
                         latitude: 2041, longitude: 4320)
Coordinates:
  * depth               (depth) float32 128B 0.494 1.541 2.646 ... 453.9 541.1
  * latitude            (latitude) float64 16kB -80.0 -79.92 ... 89.92 90.0
  * lead_day_index      (lead_day_index) int64 56B 0 1 2 3 4 5 6
  * longitude           (longitude) float64 35kB -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 411GB dask.array<chunksize=(1, 1, 1, 256, 512), meta=np.ndarray>
    thetao              (first_day_datetime, lead_day_index, depth, latitude, longitude) float32 411GB dask.array<chunksize=(1, 1, 1, 256, 512), meta=np.ndarray>
    uo                  (first_day_datetime, lead_day_index, depth, latitude, longitude) float32 411GB dask.array<chunksize=(1, 1, 1, 256, 512), meta=np.ndarray>
    vo                  (first_day_datetime, lead_day_index, depth, latitude, longitude) float32 411GB dask.array<chunksize=(1, 1, 1, 256, 512), meta=np.ndarray>
    zos                 (first_day_datetime, lead_day_index, latitude, longitude) float32 13GB dask.array<chunksize=(1, 1, 256, 512), meta=np.ndarray>
Attributes:
    Conventions:              CF-1.8
    challenger:               langya
    forecast_reference_time:  2024-01-02
    oceanbench_source_kind:   challenger
    oceanbench_source_name:   langya

xarray.Dataset

• Dimensions:
  • first_day_datetime: 52
  • lead_day_index: 7
  • depth: 32
  • latitude: 2041
  • longitude: 4320
• Coordinates: (5)
  • depth
    (depth)
    float32
    0.494 1.541 2.646 ... 453.9 541.1

    axis :

    Z

    long_name :

    Depth

    positive :

    down

    standard_name :

    depth

    units :

    m

    array([4.940250e-01, 1.541375e+00, 2.645669e+00, 3.819495e+00, 5.078224e+00,
           6.440614e+00, 7.929560e+00, 9.572997e+00, 1.140500e+01, 1.346714e+01,
           1.581007e+01, 1.849556e+01, 2.159882e+01, 2.521141e+01, 2.944473e+01,
           3.443415e+01, 4.034405e+01, 4.737369e+01, 5.576429e+01, 6.580727e+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], dtype=float32)

  • latitude
    (latitude)
    float64
    -80.0 -79.92 -79.83 ... 89.92 90.0

    axis :

    Y

    long_name :

    Latitude

    standard_name :

    latitude

    units :

    degrees_north

    array([-80.      , -79.916667, -79.833333, ...,  89.833333,  89.916667,
            90.      ], shape=(2041,))

  • lead_day_index
    (lead_day_index)
    int64
    0 1 2 3 4 5 6

    array([0, 1, 2, 3, 4, 5, 6])

  • longitude
    (longitude)
    float64
    -180.0 -179.9 ... 179.8 179.9

    axis :

    X

    long_name :

    Longitude

    standard_name :

    longitude

    units :

    degrees_east

    array([-180.      , -179.916667, -179.833333, ...,  179.75    ,  179.833333,
            179.916667], shape=(4320,))

  • 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]')

• Data variables: (5)
  • 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 382.59 GiB 512.00 kiB Shape (52, 7, 32, 2041, 4320) (1, 1, 1, 256, 512) Dask graph 838656 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, 256, 512), meta=np.ndarray>

    long_name :

    Temperature

    standard_name :

    sea_water_potential_temperature

    units :

    degrees_C

    Array Chunk Bytes 382.59 GiB 512.00 kiB Shape (52, 7, 32, 2041, 4320) (1, 1, 1, 256, 512) Dask graph 838656 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, 256, 512), meta=np.ndarray>

    long_name :

    Eastward velocity

    standard_name :

    eastward_sea_water_velocity

    units :

    m s-1

    Array Chunk Bytes 382.59 GiB 512.00 kiB Shape (52, 7, 32, 2041, 4320) (1, 1, 1, 256, 512) Dask graph 838656 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, 256, 512), meta=np.ndarray>

    long_name :

    Northward velocity

    standard_name :

    northward_sea_water_velocity

    units :

    m s-1

    Array Chunk Bytes 382.59 GiB 512.00 kiB Shape (52, 7, 32, 2041, 4320) (1, 1, 1, 256, 512) Dask graph 838656 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, 256, 512), meta=np.ndarray>

    long_name :

    Sea surface height

    standard_name :

    sea_surface_height_above_geoid

    units :

    m

    Array Chunk Bytes 11.96 GiB 512.00 kiB Shape (52, 7, 2041, 4320) (1, 1, 256, 512) Dask graph 26208 chunks in 157 graph layers Data type float32 numpy.ndarray

• Indexes: (5)
  • depth
    PandasIndex

    PandasIndex(Index([0.49402499198913574,  1.5413750410079956,  2.6456689834594727,
            3.8194949626922607,   5.078224182128906,   6.440614223480225,
              7.92956018447876,   9.572997093200684,  11.404999732971191,
            13.467140197753906,  15.810070037841797,  18.495559692382812,
            21.598819732666016,  25.211410522460938,  29.444730758666992,
             34.43415069580078,  40.344051361083984,   47.37369155883789,
             55.76428985595703,   65.80726623535156,   77.85385131835938,
              92.3260726928711,  109.72930145263672,  130.66600036621094,
            155.85069274902344,  186.12559509277344,  222.47520446777344,
             266.0403137207031,   318.1274108886719,   380.2130126953125,
             453.9377136230469,   541.0889282226562],
          dtype='float32', name='depth'))

  • latitude
    PandasIndex

    PandasIndex(Index([             -80.0, -79.91666666666667, -79.83333333333333,
                       -79.75, -79.66666666666667, -79.58333333333333,
                        -79.5, -79.41666666666667, -79.33333333333333,
                       -79.25,
           ...
                        89.25,  89.33333333333334,  89.41666666666666,
                         89.5,  89.58333333333334,  89.66666666666666,
                        89.75,  89.83333333333334,  89.91666666666666,
                         90.0],
          dtype='float64', name='latitude', length=2041))

  • lead_day_index
    PandasIndex

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

  • longitude
    PandasIndex

    PandasIndex(Index([             -180.0, -179.91666666666666, -179.83333333333334,
                       -179.75, -179.66666666666666, -179.58333333333334,
                        -179.5, -179.41666666666666, -179.33333333333334,
                       -179.25,
           ...
            179.16666666666669,              179.25,  179.33333333333331,
            179.41666666666669,               179.5,  179.58333333333331,
            179.66666666666669,              179.75,  179.83333333333331,
            179.91666666666669],
          dtype='float64', 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))

• Attributes: (5)

  Conventions :

  CF-1.8

  challenger :

  langya

  forecast_reference_time :

  2024-01-02

  oceanbench_source_kind :

  challenger

  oceanbench_source_name :

  langya

Evaluation configuration

region = 'ibi'

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	Missing fraction
Sea surface height (m) [sea_surface_height_above_geoid]{surface}	0.060361	0.062578	0.065082	0.068331	0.069573	0.071352	0.066516	0.0
Temperature (°C) [sea_water_potential_temperature]{surface}	0.619591	0.568462	0.505240	0.528274	0.549111	0.612853	0.632734	0.0
Salinity (PSU) [sea_water_salinity]{surface}	0.258264	0.261542	0.265463	0.267390	0.270939	0.274698	0.276671	0.0
Meridional current (m/s) [northward_sea_water_velocity]{surface}	0.105598	0.105737	0.102859	0.103951	0.102178	0.104436	0.109229	0.0
Zonal current (m/s) [eastward_sea_water_velocity]{surface}	0.113686	0.111701	0.110121	0.109988	0.109937	0.112354	0.113514	0.0
Temperature (°C) [sea_water_potential_temperature]{50m}	0.693266	0.699209	0.710640	0.713620	0.718136	0.747845	0.744935	0.0
Salinity (PSU) [sea_water_salinity]{50m}	0.191046	0.191350	0.191892	0.192168	0.192565	0.193710	0.194280	0.0
Meridional current (m/s) [northward_sea_water_velocity]{50m}	0.089183	0.089773	0.092430	0.092289	0.091322	0.092166	0.092957	0.0
Zonal current (m/s) [eastward_sea_water_velocity]{50m}	0.093540	0.094244	0.096792	0.096684	0.095976	0.097110	0.097916	0.0
Temperature (°C) [sea_water_potential_temperature]{100m}	0.735946	0.732490	0.741752	0.742779	0.744096	0.749086	0.750119	0.0
Salinity (PSU) [sea_water_salinity]{100m}	0.197044	0.197021	0.197392	0.197953	0.198622	0.199508	0.200189	0.0
Meridional current (m/s) [northward_sea_water_velocity]{100m}	0.086291	0.086592	0.089129	0.089019	0.088257	0.088798	0.089508	0.0
Zonal current (m/s) [eastward_sea_water_velocity]{100m}	0.089196	0.089467	0.091843	0.091647	0.090944	0.091864	0.092593	0.0
Temperature (°C) [sea_water_potential_temperature]{200m}	0.651387	0.652174	0.664423	0.664613	0.664834	0.663207	0.663016	0.0
Salinity (PSU) [sea_water_salinity]{200m}	0.136729	0.136728	0.137104	0.137246	0.137462	0.137519	0.137627	0.0
Meridional current (m/s) [northward_sea_water_velocity]{200m}	0.081161	0.081074	0.083007	0.082794	0.082310	0.082437	0.083105	0.0
Zonal current (m/s) [eastward_sea_water_velocity]{200m}	0.082564	0.082385	0.084336	0.084006	0.083443	0.083845	0.084531	0.0
Temperature (°C) [sea_water_potential_temperature]{300m}	0.535452	0.535896	0.544263	0.544470	0.545047	0.542135	0.541994	0.0
Salinity (PSU) [sea_water_salinity]{300m}	0.104837	0.104819	0.105079	0.105125	0.105259	0.105151	0.105182	0.0
Meridional current (m/s) [northward_sea_water_velocity]{300m}	0.080341	0.080196	0.082214	0.081860	0.081293	0.081590	0.082362	0.0
Zonal current (m/s) [eastward_sea_water_velocity]{300m}	0.081833	0.081639	0.083668	0.083238	0.082589	0.083023	0.083738	0.0
Temperature (°C) [sea_water_potential_temperature]{500m}	0.397534	0.397231	0.401003	0.401662	0.402973	0.401047	0.401161	0.0
Salinity (PSU) [sea_water_salinity]{500m}	0.091117	0.091135	0.090943	0.091076	0.091236	0.091314	0.091462	0.0
Meridional current (m/s) [northward_sea_water_velocity]{500m}	0.083489	0.083185	0.085235	0.084612	0.083823	0.084656	0.085556	0.0
Zonal current (m/s) [eastward_sea_water_velocity]{500m}	0.085435	0.085063	0.087108	0.086460	0.085616	0.086447	0.087204	0.0

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	Missing fraction
Mixed layer depth (m) [ocean_mixed_layer_thickness]{surface}	46.275248	37.511662	30.935132	32.834266	34.092312	38.74794	39.862172	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	Missing fraction
Meridional geostrophic current (m/s) [geostrophic_northward_sea_water_velocity]{surface}	0.089485	0.091299	0.092995	0.093784	0.093857	0.094922	0.096218	0.000431
Zonal geostrophic current (m/s) [geostrophic_eastward_sea_water_velocity]{surface}	0.091048	0.092437	0.094141	0.094622	0.094675	0.096071	0.097104	0.000628

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	Observations	Missing
Temperature (°C) [sea_water_potential_temperature]{surface}	0.650009	0.591540	0.549957	0.537278	0.560059	0.600052	0.665789	1807	33
Temperature (°C) [sea_water_potential_temperature]{0-5m}	0.639775	0.605587	0.439613	0.532822	0.600434	0.614761	0.679914	1496	9
Temperature (°C) [sea_water_potential_temperature]{5-100m}	0.737509	0.723009	0.700277	0.697670	0.810807	0.754858	0.752674	36018	236
Temperature (°C) [sea_water_potential_temperature]{100-300m}	0.309742	0.338091	0.339540	0.318991	0.342714	0.333061	0.336143	50931	497
Temperature (°C) [sea_water_potential_temperature]{300-600m}	0.270864	0.269176	0.263324	0.249133	0.270494	0.274889	0.252062	45078	554
Salinity (PSU) [sea_water_salinity]{0-5m}	0.668715	0.881734	0.856255	0.666592	0.633342	0.738632	0.647318	1303	10
Salinity (PSU) [sea_water_salinity]{5-100m}	0.273933	0.338200	0.341017	0.273579	0.307731	0.309617	0.300736	32900	236
Salinity (PSU) [sea_water_salinity]{100-300m}	0.102783	0.095493	0.113442	0.078963	0.131953	0.108194	0.122462	46897	497
Salinity (PSU) [sea_water_salinity]{300-600m}	0.045602	0.046491	0.050477	0.044160	0.050272	0.052329	0.054179	40027	554
Sea level anomaly (m) [sea_surface_height_above_geoid]{surface}	0.047582	0.047741	0.048533	0.046671	0.047154	0.050549	0.052761	179488	2562
Zonal current (m/s) [eastward_sea_water_velocity]{15m}	0.112079	0.111786	0.113843	0.116246	0.109807	0.109515	0.113425	18905	363
Meridional current (m/s) [northward_sea_water_velocity]{15m}	0.106568	0.109692	0.110870	0.107173	0.106608	0.103952	0.103492	18905	363

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
Lagrangian trajectory deviation (km) []{surface}	10.325734	19.372845	27.442385	35.009396	42.015175	48.678066

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	Missing fraction
Sea surface height (m) [sea_surface_height_above_geoid]{surface}	0.029432	0.035548	0.037690	0.044180	0.045998	0.048296	0.045289	0.0
Temperature (°C) [sea_water_potential_temperature]{surface}	0.513924	0.431846	0.349182	0.403144	0.443882	0.513787	0.559750	0.0
Salinity (PSU) [sea_water_salinity]{surface}	0.059625	0.088356	0.107840	0.122619	0.134953	0.144234	0.152166	0.0
Meridional current (m/s) [northward_sea_water_velocity]{surface}	0.070947	0.072757	0.063752	0.070001	0.072912	0.083437	0.094977	0.0
Zonal current (m/s) [eastward_sea_water_velocity]{surface}	0.073848	0.073745	0.068712	0.073388	0.078423	0.089197	0.096121	0.0
Temperature (°C) [sea_water_potential_temperature]{50m}	0.265211	0.308902	0.329312	0.379631	0.422848	0.481632	0.518157	0.0
Salinity (PSU) [sea_water_salinity]{50m}	0.039823	0.057989	0.072603	0.084471	0.094026	0.102853	0.110202	0.0
Meridional current (m/s) [northward_sea_water_velocity]{50m}	0.042606	0.045889	0.046228	0.052830	0.057951	0.068222	0.076104	0.0
Zonal current (m/s) [eastward_sea_water_velocity]{50m}	0.042432	0.046820	0.047701	0.054628	0.059972	0.070701	0.078664	0.0
Temperature (°C) [sea_water_potential_temperature]{100m}	0.193323	0.236043	0.270483	0.314833	0.352906	0.398303	0.434098	0.0
Salinity (PSU) [sea_water_salinity]{100m}	0.039249	0.057841	0.073379	0.086407	0.096931	0.105816	0.113270	0.0
Meridional current (m/s) [northward_sea_water_velocity]{100m}	0.038084	0.041282	0.042366	0.048914	0.054146	0.064709	0.072564	0.0
Zonal current (m/s) [eastward_sea_water_velocity]{100m}	0.036710	0.041483	0.043380	0.049954	0.055317	0.066056	0.073644	0.0
Temperature (°C) [sea_water_potential_temperature]{200m}	0.148955	0.181373	0.208665	0.241646	0.270245	0.303929	0.333526	0.0
Salinity (PSU) [sea_water_salinity]{200m}	0.026540	0.037439	0.046565	0.054262	0.060628	0.066080	0.070961	0.0
Meridional current (m/s) [northward_sea_water_velocity]{200m}	0.032766	0.035726	0.036138	0.042114	0.047492	0.057406	0.064902	0.0
Zonal current (m/s) [eastward_sea_water_velocity]{200m}	0.031497	0.035590	0.036725	0.042587	0.047916	0.057573	0.064887	0.0
Temperature (°C) [sea_water_potential_temperature]{300m}	0.121616	0.155394	0.182075	0.211577	0.237013	0.265150	0.289963	0.0
Salinity (PSU) [sea_water_salinity]{300m}	0.021178	0.030514	0.037889	0.044184	0.049368	0.053730	0.057658	0.0
Meridional current (m/s) [northward_sea_water_velocity]{300m}	0.030338	0.033891	0.035102	0.040987	0.046293	0.055641	0.062921	0.0
Zonal current (m/s) [eastward_sea_water_velocity]{300m}	0.029572	0.034127	0.035595	0.041403	0.046681	0.055704	0.062812	0.0
Temperature (°C) [sea_water_potential_temperature]{500m}	0.091498	0.128918	0.156000	0.183091	0.206376	0.228633	0.247577	0.0
Salinity (PSU) [sea_water_salinity]{500m}	0.018351	0.027467	0.034626	0.040607	0.045538	0.049614	0.053194	0.0
Meridional current (m/s) [northward_sea_water_velocity]{500m}	0.026235	0.032325	0.036942	0.043041	0.048324	0.056845	0.063593	0.0
Zonal current (m/s) [eastward_sea_water_velocity]{500m}	0.025359	0.032376	0.037554	0.043768	0.049109	0.057371	0.063934	0.0

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	Missing fraction
Mixed layer depth (m) [ocean_mixed_layer_thickness]{surface}	43.551025	33.943386	26.734418	29.485549	31.316682	36.968545	38.643863	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	Missing fraction
Meridional geostrophic current (m/s) [geostrophic_northward_sea_water_velocity]{surface}	0.040530	0.047781	0.049246	0.056713	0.062341	0.072234	0.079969	0.0
Zonal geostrophic current (m/s) [geostrophic_eastward_sea_water_velocity]{surface}	0.037688	0.044811	0.046818	0.053935	0.059834	0.070092	0.077648	0.0

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
Lagrangian trajectory deviation (km) []{surface}	6.939085	12.581881	17.534214	22.869261	28.461174	34.517525