Open challenger datasets

import oceanbench

oceanbench.__version__

'0.4.0'

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: 2040, 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 ... 89.83 89.92
  * 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[us] 416B 2024-01-03 ....
Data variables:
    so                  (first_day_datetime, lead_day_index, depth, latitude, longitude) float32 411GB dask.array<chunksize=(1, 1, 1, 2040, 4320), meta=np.ndarray>
    thetao              (first_day_datetime, lead_day_index, depth, latitude, longitude) float32 411GB dask.array<chunksize=(1, 1, 1, 2040, 4320), meta=np.ndarray>
    uo                  (first_day_datetime, lead_day_index, depth, latitude, longitude) float32 411GB dask.array<chunksize=(1, 1, 1, 2040, 4320), meta=np.ndarray>
    vo                  (first_day_datetime, lead_day_index, depth, latitude, longitude) float32 411GB dask.array<chunksize=(1, 1, 1, 2040, 4320), meta=np.ndarray>
    zos                 (first_day_datetime, lead_day_index, latitude, longitude) float32 13GB dask.array<chunksize=(1, 1, 2040, 4320), 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: 2040
  • 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 ... 89.83 89.92

    axis :

    Y

    long_name :

    Latitude

    standard_name :

    latitude

    units :

    degrees_north

    array([-80.      , -79.916667, -79.833333, ...,  89.75    ,  89.833333,
            89.916667], shape=(2040,))

  • 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[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, 2040, 4320), meta=np.ndarray>

    long_name :

    Salinity

    standard_name :

    sea_water_salinity

    units :

    1e-3

    Array Chunk Bytes 382.41 GiB 33.62 MiB Shape (52, 7, 32, 2040, 4320) (1, 1, 1, 2040, 4320) Dask graph 11648 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, 2040, 4320), meta=np.ndarray>

    long_name :

    Temperature

    standard_name :

    sea_water_potential_temperature

    units :

    degrees_C

    Array Chunk Bytes 382.41 GiB 33.62 MiB Shape (52, 7, 32, 2040, 4320) (1, 1, 1, 2040, 4320) Dask graph 11648 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, 2040, 4320), meta=np.ndarray>

    long_name :

    Eastward velocity

    standard_name :

    eastward_sea_water_velocity

    units :

    m s-1

    Array Chunk Bytes 382.41 GiB 33.62 MiB Shape (52, 7, 32, 2040, 4320) (1, 1, 1, 2040, 4320) Dask graph 11648 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, 2040, 4320), meta=np.ndarray>

    long_name :

    Northward velocity

    standard_name :

    northward_sea_water_velocity

    units :

    m s-1

    Array Chunk Bytes 382.41 GiB 33.62 MiB Shape (52, 7, 32, 2040, 4320) (1, 1, 1, 2040, 4320) Dask graph 11648 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, 2040, 4320), meta=np.ndarray>

    long_name :

    Sea surface height

    standard_name :

    sea_surface_height_above_geoid

    units :

    m

    Array Chunk Bytes 11.95 GiB 33.62 MiB Shape (52, 7, 2040, 4320) (1, 1, 2040, 4320) Dask graph 364 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,
           ...
            89.16666666666666,              89.25,  89.33333333333334,
            89.41666666666666,               89.5,  89.58333333333334,
            89.66666666666666,              89.75,  89.83333333333334,
            89.91666666666666],
          dtype='float64', name='latitude', length=2040))

  • 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[us]', 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 = '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
Sea surface height (m) [sea_surface_height_above_geoid]{surface}	0.072453	0.074295	0.073324	0.074269	0.075283	0.078947	0.081520
Temperature (°C) [sea_water_potential_temperature]{surface}	0.682194	0.668692	0.579549	0.592355	0.605324	0.655539	0.711380
Salinity (PSU) [sea_water_salinity]{surface}	0.616679	0.620864	0.623386	0.628032	0.631518	0.637006	0.642241
Meridional current (m/s) [northward_sea_water_velocity]{surface}	0.134442	0.133738	0.133453	0.133547	0.133388	0.143643	0.148840
Zonal current (m/s) [eastward_sea_water_velocity]{surface}	0.138877	0.139186	0.139691	0.140010	0.140208	0.149271	0.153763
Temperature (°C) [sea_water_potential_temperature]{50m}	0.955821	0.956601	0.925243	0.928298	0.930763	0.975742	1.008430
Salinity (PSU) [sea_water_salinity]{50m}	0.255182	0.256212	0.255879	0.256739	0.257780	0.260933	0.263369
Meridional current (m/s) [northward_sea_water_velocity]{50m}	0.121474	0.120967	0.122490	0.122306	0.121947	0.130451	0.134775
Zonal current (m/s) [eastward_sea_water_velocity]{50m}	0.124348	0.124563	0.126394	0.126329	0.126032	0.133243	0.137213
Temperature (°C) [sea_water_potential_temperature]{100m}	1.115415	1.116022	1.113147	1.118567	1.122602	1.158759	1.184112
Salinity (PSU) [sea_water_salinity]{100m}	0.200884	0.201060	0.201156	0.201628	0.202265	0.204135	0.205383
Meridional current (m/s) [northward_sea_water_velocity]{100m}	0.117952	0.117555	0.119166	0.118869	0.118353	0.125269	0.128859
Zonal current (m/s) [eastward_sea_water_velocity]{100m}	0.124374	0.124358	0.125737	0.125442	0.125071	0.131169	0.134185
Temperature (°C) [sea_water_potential_temperature]{200m}	0.918591	0.918775	0.920941	0.922623	0.924835	0.940347	0.949960
Salinity (PSU) [sea_water_salinity]{200m}	0.163564	0.163605	0.163789	0.164044	0.164429	0.165722	0.166568
Meridional current (m/s) [northward_sea_water_velocity]{200m}	0.114604	0.114498	0.116384	0.115857	0.115066	0.118762	0.120090
Zonal current (m/s) [eastward_sea_water_velocity]{200m}	0.121759	0.121749	0.123544	0.122787	0.121911	0.125602	0.126642
Temperature (°C) [sea_water_potential_temperature]{300m}	0.775976	0.775899	0.778276	0.779503	0.781282	0.794251	0.801826
Salinity (PSU) [sea_water_salinity]{300m}	0.136538	0.136537	0.136756	0.136966	0.137287	0.138426	0.139189
Meridional current (m/s) [northward_sea_water_velocity]{300m}	0.111908	0.111833	0.113738	0.113121	0.112294	0.115536	0.116472
Zonal current (m/s) [eastward_sea_water_velocity]{300m}	0.117141	0.117138	0.118963	0.118258	0.117398	0.120456	0.121161
Temperature (°C) [sea_water_potential_temperature]{500m}	0.594986	0.595638	0.598702	0.600406	0.602644	0.612005	0.618573
Salinity (PSU) [sea_water_salinity]{500m}	0.103444	0.103528	0.103778	0.104021	0.104341	0.105046	0.105677
Meridional current (m/s) [northward_sea_water_velocity]{500m}	0.102669	0.102712	0.104278	0.103611	0.102833	0.105718	0.106416
Zonal current (m/s) [eastward_sea_water_velocity]{500m}	0.107629	0.107658	0.109264	0.108703	0.108063	0.110335	0.110749

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
Mixed layer depth (m) [ocean_mixed_layer_thickness]{surface}	41.38633	40.16363	37.282013	38.219248	38.997901	40.505128	41.783716

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
Meridional geostrophic current (m/s) [geostrophic_northward_sea_water_velocity]{surface}	0.172858	0.175257	0.163070	0.166246	0.168675	0.174845	0.185482
Zonal geostrophic current (m/s) [geostrophic_eastward_sea_water_velocity]{surface}	0.197407	0.200152	0.182174	0.185833	0.188162	0.195766	0.208595

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
Temperature (°C) [sea_water_potential_temperature]{surface}	0.912465	0.911941	0.818189	0.849885	0.880025	0.951731	0.977392
Temperature (°C) [sea_water_potential_temperature]{0-5m}	0.870754	0.876176	0.812984	0.846279	0.855536	0.907237	0.966076
Temperature (°C) [sea_water_potential_temperature]{5-100m}	0.950844	0.952187	0.906571	0.936326	0.930166	0.972249	1.007846
Temperature (°C) [sea_water_potential_temperature]{100-300m}	0.827663	0.848126	0.829347	0.833413	0.845878	0.857058	0.884400
Temperature (°C) [sea_water_potential_temperature]{300-600m}	0.572644	0.583934	0.577803	0.572927	0.580002	0.610685	0.618646
Salinity (PSU) [sea_water_salinity]{0-5m}	0.275824	0.299090	0.285466	0.330874	0.290480	0.300734	0.299216
Salinity (PSU) [sea_water_salinity]{5-100m}	0.265583	0.262144	0.267598	0.256039	0.273197	0.279033	0.270121
Salinity (PSU) [sea_water_salinity]{100-300m}	0.137102	0.138676	0.139487	0.138535	0.141151	0.140128	0.146165
Salinity (PSU) [sea_water_salinity]{300-600m}	0.092662	0.092538	0.091199	0.091821	0.092086	0.094326	0.095307
Sea level anomaly (m) [sea_surface_height_above_geoid]{surface}	0.050917	0.052370	0.050938	0.052732	0.053955	0.059026	0.061779
Zonal current (m/s) [eastward_sea_water_velocity]{15m}	0.217615	0.217039	0.219337	0.219474	0.217363	0.220084	0.224409
Meridional current (m/s) [northward_sea_water_velocity]{15m}	0.199125	0.198230	0.198910	0.201291	0.200587	0.204581	0.206440

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
Lagrangian trajectory deviation (km) []{surface}	12.331295	23.472412	33.808994	43.817959	53.371319

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
Sea surface height (m) [sea_surface_height_above_geoid]{surface}	0.029998	0.034676	0.034023	0.037733	0.041418	0.050014	0.054382
Temperature (°C) [sea_water_potential_temperature]{surface}	0.455949	0.461170	0.361880	0.406637	0.445623	0.533625	0.605565
Salinity (PSU) [sea_water_salinity]{surface}	0.153159	0.194985	0.222000	0.244799	0.262592	0.281928	0.298422
Meridional current (m/s) [northward_sea_water_velocity]{surface}	0.104787	0.102258	0.090840	0.097542	0.104015	0.127649	0.139555
Zonal current (m/s) [eastward_sea_water_velocity]{surface}	0.104982	0.105572	0.095973	0.102560	0.109354	0.130820	0.142900
Temperature (°C) [sea_water_potential_temperature]{50m}	0.435986	0.491426	0.488929	0.534800	0.578074	0.673771	0.741074
Salinity (PSU) [sea_water_salinity]{50m}	0.075120	0.096340	0.111004	0.124115	0.135273	0.148653	0.158386
Meridional current (m/s) [northward_sea_water_velocity]{50m}	0.082323	0.080355	0.072719	0.079090	0.085339	0.108933	0.120481
Zonal current (m/s) [eastward_sea_water_velocity]{50m}	0.079579	0.080819	0.076598	0.082717	0.088929	0.109603	0.120623
Temperature (°C) [sea_water_potential_temperature]{100m}	0.423789	0.490137	0.513558	0.569906	0.622744	0.730116	0.805842
Salinity (PSU) [sea_water_salinity]{100m}	0.060453	0.077799	0.091375	0.103256	0.113220	0.124355	0.132145
Meridional current (m/s) [northward_sea_water_velocity]{100m}	0.072919	0.072288	0.066548	0.072807	0.079103	0.100782	0.111725
Zonal current (m/s) [eastward_sea_water_velocity]{100m}	0.070576	0.073584	0.072044	0.078264	0.084336	0.102687	0.112370
Temperature (°C) [sea_water_potential_temperature]{200m}	0.293783	0.346081	0.382539	0.432802	0.478326	0.556036	0.606101
Salinity (PSU) [sea_water_salinity]{200m}	0.044697	0.059879	0.072125	0.082607	0.091368	0.100882	0.107821
Meridional current (m/s) [northward_sea_water_velocity]{200m}	0.058695	0.058774	0.054875	0.060838	0.066702	0.084920	0.094362
Zonal current (m/s) [eastward_sea_water_velocity]{200m}	0.055303	0.057162	0.056752	0.062453	0.068082	0.083794	0.091841
Temperature (°C) [sea_water_potential_temperature]{300m}	0.242912	0.290632	0.328370	0.373686	0.414159	0.480629	0.522239
Salinity (PSU) [sea_water_salinity]{300m}	0.037175	0.050184	0.060822	0.069789	0.077273	0.085350	0.091313
Meridional current (m/s) [northward_sea_water_velocity]{300m}	0.054100	0.054495	0.051356	0.057255	0.062995	0.079935	0.088893
Zonal current (m/s) [eastward_sea_water_velocity]{300m}	0.050994	0.052652	0.052155	0.057648	0.063024	0.077726	0.085483
Temperature (°C) [sea_water_potential_temperature]{500m}	0.179264	0.222946	0.259640	0.297282	0.330571	0.379968	0.413639
Salinity (PSU) [sea_water_salinity]{500m}	0.027151	0.037368	0.045841	0.052761	0.058494	0.064115	0.068673
Meridional current (m/s) [northward_sea_water_velocity]{500m}	0.045566	0.047796	0.047344	0.053151	0.058544	0.071856	0.079515
Zonal current (m/s) [eastward_sea_water_velocity]{500m}	0.042775	0.046074	0.047775	0.053289	0.058436	0.069772	0.076297

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
Mixed layer depth (m) [ocean_mixed_layer_thickness]{surface}	32.404414	31.901359	27.507015	29.64698	31.342262	33.79178	36.58206

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
Meridional geostrophic current (m/s) [geostrophic_northward_sea_water_velocity]{surface}	0.140157	0.147533	0.128114	0.136482	0.143801	0.159651	0.176116
Zonal geostrophic current (m/s) [geostrophic_eastward_sea_water_velocity]{surface}	0.168493	0.179531	0.154632	0.162146	0.169372	0.183534	0.202413

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
Lagrangian trajectory deviation (km) []{surface}	8.697826	15.511682	21.487734	27.985483	35.05283