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 = '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
Sea surface height (m) [sea_surface_height_above_geoid]{surface}	0.061403	0.063327	0.065901	0.068986	0.070190	0.071981	0.067203
Temperature (°C) [sea_water_potential_temperature]{surface}	0.603204	0.564613	0.510377	0.532521	0.553422	0.623181	0.637008
Salinity (PSU) [sea_water_salinity]{surface}	0.249468	0.253163	0.256327	0.257050	0.259445	0.262642	0.264345
Meridional current (m/s) [northward_sea_water_velocity]{surface}	0.106537	0.106598	0.104055	0.105115	0.103240	0.105411	0.110026
Zonal current (m/s) [eastward_sea_water_velocity]{surface}	0.116165	0.113720	0.112303	0.111855	0.111708	0.114146	0.115293
Temperature (°C) [sea_water_potential_temperature]{50m}	0.695380	0.704750	0.718744	0.721718	0.726131	0.758454	0.752230
Salinity (PSU) [sea_water_salinity]{50m}	0.192349	0.192575	0.192962	0.193133	0.193427	0.194472	0.194877
Meridional current (m/s) [northward_sea_water_velocity]{50m}	0.090203	0.090716	0.093400	0.093202	0.092200	0.093045	0.093826
Zonal current (m/s) [eastward_sea_water_velocity]{50m}	0.095964	0.096362	0.099184	0.098901	0.098095	0.099199	0.099974
Temperature (°C) [sea_water_potential_temperature]{100m}	0.743420	0.740042	0.749597	0.750400	0.751628	0.757175	0.757487
Salinity (PSU) [sea_water_salinity]{100m}	0.200490	0.200397	0.200596	0.201032	0.201662	0.202509	0.203086
Meridional current (m/s) [northward_sea_water_velocity]{100m}	0.087220	0.087448	0.090065	0.089889	0.089090	0.089630	0.090308
Zonal current (m/s) [eastward_sea_water_velocity]{100m}	0.091127	0.091157	0.093788	0.093445	0.092704	0.093592	0.094285
Temperature (°C) [sea_water_potential_temperature]{200m}	0.658064	0.658912	0.671906	0.671935	0.671894	0.670319	0.670057
Salinity (PSU) [sea_water_salinity]{200m}	0.137846	0.137836	0.138226	0.138345	0.138522	0.138590	0.138664
Meridional current (m/s) [northward_sea_water_velocity]{200m}	0.081960	0.081832	0.083857	0.083620	0.083128	0.083233	0.083867
Zonal current (m/s) [eastward_sea_water_velocity]{200m}	0.083962	0.083610	0.085928	0.085576	0.084971	0.085356	0.085944
Temperature (°C) [sea_water_potential_temperature]{300m}	0.540204	0.540651	0.549816	0.549857	0.550278	0.547486	0.547415
Salinity (PSU) [sea_water_salinity]{300m}	0.105290	0.105278	0.105587	0.105626	0.105761	0.105687	0.105701
Meridional current (m/s) [northward_sea_water_velocity]{300m}	0.081045	0.080853	0.082983	0.082622	0.082051	0.082339	0.083070
Zonal current (m/s) [eastward_sea_water_velocity]{300m}	0.082876	0.082527	0.084944	0.084509	0.083818	0.084260	0.084894
Temperature (°C) [sea_water_potential_temperature]{500m}	0.401182	0.401051	0.405274	0.405907	0.407251	0.405688	0.405939
Salinity (PSU) [sea_water_salinity]{500m}	0.091542	0.091578	0.091376	0.091501	0.091641	0.091726	0.091854
Meridional current (m/s) [northward_sea_water_velocity]{500m}	0.084144	0.083795	0.085950	0.085311	0.084525	0.085366	0.086231
Zonal current (m/s) [eastward_sea_water_velocity]{500m}	0.086530	0.086063	0.088371	0.087738	0.086867	0.087696	0.088384

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}	46.676925	38.071514	31.57378	33.373463	34.680205	39.337104	40.491243

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}	0.090612	0.092298	0.094006	0.094703	0.094733	0.095855	0.097142
Zonal geostrophic current (m/s) [geostrophic_eastward_sea_water_velocity]{surface}	0.093619	0.094559	0.096446	0.096592	0.096486	0.098000	0.099031

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}	0.770993	0.661069	0.718360	0.715718	0.693699	0.769072	0.944062
Temperature (°C) [sea_water_potential_temperature]{0-5m}	0.631508	0.566354	0.508483	0.598180	0.612680	0.674602	0.702842
Temperature (°C) [sea_water_potential_temperature]{5-100m}	0.707035	0.710896	0.695521	0.711983	0.805308	0.761474	0.756023
Temperature (°C) [sea_water_potential_temperature]{100-300m}	0.300613	0.315809	0.332118	0.335119	0.324359	0.343311	0.339647
Temperature (°C) [sea_water_potential_temperature]{300-600m}	0.256294	0.249651	0.242777	0.245255	0.239802	0.264513	0.247248
Salinity (PSU) [sea_water_salinity]{0-5m}	0.654134	0.853800	0.837935	0.652831	0.625067	0.736924	0.631822
Salinity (PSU) [sea_water_salinity]{5-100m}	0.265386	0.321050	0.327803	0.274161	0.293020	0.306346	0.291096
Salinity (PSU) [sea_water_salinity]{100-300m}	0.109454	0.100698	0.117241	0.094039	0.122124	0.124723	0.126719
Salinity (PSU) [sea_water_salinity]{300-600m}	0.043430	0.045118	0.044631	0.044311	0.045890	0.048614	0.050479
Sea level anomaly (m) [sea_surface_height_above_geoid]{surface}	0.048010	0.047992	0.049194	0.046770	0.047531	0.050940	0.053283
Zonal current (m/s) [eastward_sea_water_velocity]{15m}	0.219563	0.222801	0.222899	0.220794	0.207182	0.220185	0.214736
Meridional current (m/s) [northward_sea_water_velocity]{15m}	0.185119	0.184961	0.184538	0.181305	0.183252	0.181841	0.185170

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}	10.334837	19.332563	27.335705	34.855476	41.843407

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}	0.030254	0.035706	0.038076	0.044352	0.045986	0.048258	0.045231
Temperature (°C) [sea_water_potential_temperature]{surface}	0.509151	0.439852	0.365877	0.414473	0.452830	0.527163	0.564812
Salinity (PSU) [sea_water_salinity]{surface}	0.109957	0.124124	0.136073	0.146301	0.154606	0.161187	0.167782
Meridional current (m/s) [northward_sea_water_velocity]{surface}	0.074899	0.076026	0.067842	0.073333	0.075754	0.085629	0.096525
Zonal current (m/s) [eastward_sea_water_velocity]{surface}	0.085460	0.083647	0.079743	0.082324	0.085707	0.094775	0.100476
Temperature (°C) [sea_water_potential_temperature]{50m}	0.318485	0.349134	0.364251	0.404748	0.442314	0.501094	0.530135
Salinity (PSU) [sea_water_salinity]{50m}	0.061811	0.071661	0.081745	0.090995	0.099059	0.106624	0.113194
Meridional current (m/s) [northward_sea_water_velocity]{50m}	0.048217	0.050495	0.051105	0.056613	0.061028	0.070460	0.077798
Zonal current (m/s) [eastward_sea_water_velocity]{50m}	0.058881	0.060324	0.062153	0.065976	0.069130	0.077406	0.083796
Temperature (°C) [sea_water_potential_temperature]{100m}	0.258336	0.282211	0.306995	0.341259	0.373083	0.415129	0.446938
Salinity (PSU) [sea_water_salinity]{100m}	0.065428	0.075633	0.086266	0.096271	0.104844	0.112378	0.118877
Meridional current (m/s) [northward_sea_water_velocity]{100m}	0.044504	0.046319	0.047414	0.052804	0.057327	0.066985	0.074323
Zonal current (m/s) [eastward_sea_water_velocity]{100m}	0.054248	0.055333	0.057452	0.060947	0.064150	0.072340	0.078516
Temperature (°C) [sea_water_potential_temperature]{200m}	0.191705	0.211598	0.232629	0.259833	0.284716	0.314889	0.342090
Salinity (PSU) [sea_water_salinity]{200m}	0.038695	0.045057	0.051782	0.058161	0.063701	0.068545	0.073055
Meridional current (m/s) [northward_sea_water_velocity]{200m}	0.039322	0.040887	0.041397	0.046280	0.050898	0.059845	0.066810
Zonal current (m/s) [eastward_sea_water_velocity]{200m}	0.048734	0.049337	0.050907	0.054059	0.057443	0.064568	0.070310
Temperature (°C) [sea_water_potential_temperature]{300m}	0.162773	0.183615	0.203976	0.228293	0.250499	0.275659	0.298358
Salinity (PSU) [sea_water_salinity]{300m}	0.030981	0.036513	0.041974	0.047218	0.051761	0.055697	0.059281
Meridional current (m/s) [northward_sea_water_velocity]{300m}	0.037117	0.039149	0.040445	0.045275	0.049811	0.058231	0.064939
Zonal current (m/s) [eastward_sea_water_velocity]{300m}	0.047708	0.048609	0.050346	0.053525	0.056890	0.063435	0.068939
Temperature (°C) [sea_water_potential_temperature]{500m}	0.136438	0.159328	0.179331	0.201236	0.221339	0.242091	0.259687
Salinity (PSU) [sea_water_salinity]{500m}	0.031423	0.036127	0.040998	0.045592	0.049686	0.053344	0.056593
Meridional current (m/s) [northward_sea_water_velocity]{500m}	0.034397	0.038200	0.042080	0.047093	0.051660	0.059408	0.065597
Zonal current (m/s) [eastward_sea_water_velocity]{500m}	0.047102	0.048812	0.052279	0.055737	0.059182	0.065248	0.070372

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}	44.097298	34.903148	27.892671	30.356421	32.201392	37.771837	39.559798

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}	0.046447	0.05205	0.053517	0.059906	0.064821	0.074217	0.081630
Zonal geostrophic current (m/s) [geostrophic_eastward_sea_water_velocity]{surface}	0.052788	0.05645	0.058860	0.063133	0.067114	0.075765	0.082092

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}	7.41926	13.231584	18.248125	23.49873	28.979614