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 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,
                         latitude: 672, longitude: 1440)
Coordinates:
  * depth               (depth) float32 84B 0.494 47.37 ... 4.833e+03 5.275e+03
  * latitude            (latitude) 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
  * longitude           (longitude) float64 12kB -180.0 -179.8 ... 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, latitude, longitude) float64 85GB dask.array<chunksize=(1, 2, 3, 168, 360), meta=np.ndarray>
    thetao              (first_day_datetime, lead_day_index, depth, latitude, longitude) float64 85GB dask.array<chunksize=(1, 2, 3, 168, 360), meta=np.ndarray>
    uo                  (first_day_datetime, lead_day_index, depth, latitude, longitude) float64 85GB dask.array<chunksize=(1, 2, 3, 168, 360), meta=np.ndarray>
    vo                  (first_day_datetime, lead_day_index, depth, latitude, longitude) float64 85GB dask.array<chunksize=(1, 2, 3, 168, 360), meta=np.ndarray>
    zos                 (first_day_datetime, lead_day_index, latitude, longitude) float64 4GB dask.array<chunksize=(1, 2, 168, 360), meta=np.ndarray>
Attributes:
    Conventions:              CF-1.8
    area:                     Global
    challenger:               glonet
    contact:                  glonet@mercator-ocean.eu
    forecast_reference_time:  2024-01-02
    institution:              Mercator Ocean International
    references:               www.edito.eu
    source:                   MOI GLONET
    title:                    Daily mean fields from GLONET 1/4 degree resolu...
    oceanbench_source_kind:   challenger
    oceanbench_source_name:   glonet

xarray.Dataset

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

    axis :

    Z

    long_name :

    Depth

    positive :

    down

    standard_name :

    depth

    units :

    m

    valid_max :

    5727.917

    valid_min :

    0.494025

    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)

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

    axis :

    Y

    long_name :

    Latitude

    standard_name :

    latitude

    units :

    degrees_north

    valid_max :

    89.75

    valid_min :

    -78.0

    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])

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

    axis :

    X

    long_name :

    Longitude

    standard_name :

    longitude

    units :

    degrees_east

    valid_max :

    179.75

    valid_min :

    -180.0

    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, latitude, longitude)
    float64
    dask.array<chunksize=(1, 2, 3, 168, 360), meta=np.ndarray>

    cell_methods :

    area: mean

    long_name :

    Salinity

    standard_name :

    sea_water_salinity

    units :

    1e-3

    valid_max :

    50.0

    valid_min :

    0.0

    Array Chunk Bytes 78.73 GiB 2.77 MiB Shape (52, 10, 21, 672, 1440) (1, 2, 3, 168, 360) Dask graph 29120 chunks in 157 graph layers Data type float64 numpy.ndarray

  • thetao
    (first_day_datetime, lead_day_index, depth, latitude, longitude)
    float64
    dask.array<chunksize=(1, 2, 3, 168, 360), meta=np.ndarray>

    cell_methods :

    area: mean

    long_name :

    Temperature

    standard_name :

    sea_water_potential_temperature

    units :

    degrees_C

    valid_max :

    40.0

    valid_min :

    -10.0

    Array Chunk Bytes 78.73 GiB 2.77 MiB Shape (52, 10, 21, 672, 1440) (1, 2, 3, 168, 360) Dask graph 29120 chunks in 157 graph layers Data type float64 numpy.ndarray

  • uo
    (first_day_datetime, lead_day_index, depth, latitude, longitude)
    float64
    dask.array<chunksize=(1, 2, 3, 168, 360), meta=np.ndarray>

    cell_methods :

    area: mean

    long_name :

    Eastward velocity

    standard_name :

    eastward_sea_water_velocity

    units :

    m s-1

    valid_max :

    5.0

    valid_min :

    -5.0

    Array Chunk Bytes 78.73 GiB 2.77 MiB Shape (52, 10, 21, 672, 1440) (1, 2, 3, 168, 360) Dask graph 29120 chunks in 157 graph layers Data type float64 numpy.ndarray

  • vo
    (first_day_datetime, lead_day_index, depth, latitude, longitude)
    float64
    dask.array<chunksize=(1, 2, 3, 168, 360), meta=np.ndarray>

    cell_methods :

    area: mean

    long_name :

    Northward velocity

    standard_name :

    northward_sea_water_velocity

    units :

    m s-1

    valid_max :

    5.0

    valid_min :

    -5.0

    Array Chunk Bytes 78.73 GiB 2.77 MiB Shape (52, 10, 21, 672, 1440) (1, 2, 3, 168, 360) Dask graph 29120 chunks in 157 graph layers Data type float64 numpy.ndarray

  • zos
    (first_day_datetime, lead_day_index, latitude, longitude)
    float64
    dask.array<chunksize=(1, 2, 168, 360), meta=np.ndarray>

    cell_methods :

    area: mean

    long_name :

    Sea surface height

    standard_name :

    sea_surface_height_above_geoid

    units :

    m

    valid_max :

    5.0

    valid_min :

    -5.0

    Array Chunk Bytes 3.75 GiB 0.92 MiB Shape (52, 10, 672, 1440) (1, 2, 168, 360) Dask graph 4160 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'))

  • latitude
    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='latitude', length=672))

  • 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, -179.75,  -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='longitude', 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: (11)

  Conventions :

  CF-1.8

  area :

  Global

  challenger :

  glonet

  contact :

  glonet@mercator-ocean.eu

  forecast_reference_time :

  2024-01-02

  institution :

  Mercator Ocean International

  references :

  www.edito.eu

  source :

  MOI GLONET

  title :

  Daily mean fields from GLONET 1/4 degree resolution forecast

  oceanbench_source_kind :

  challenger

  oceanbench_source_name :

  glonet

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	Lead day 8	Lead day 9	Lead day 10
Sea surface height (m) [sea_surface_height_above_geoid]{surface}	0.060808	0.063137	0.067338	0.069758	0.073030	0.072788	0.071879	0.073320	0.076123	0.077413
Temperature (°C) [sea_water_potential_temperature]{surface}	0.592775	0.589118	0.695289	0.683195	0.793817	0.779265	0.889844	0.869271	0.982367	0.950306
Salinity (PSU) [sea_water_salinity]{surface}	0.259294	0.258783	0.264182	0.262762	0.273430	0.272915	0.284940	0.283145	0.295259	0.293693
Meridional current (m/s) [northward_sea_water_velocity]{surface}	0.094750	0.097489	0.099932	0.102772	0.103094	0.102658	0.103629	0.103884	0.104896	0.104267
Zonal current (m/s) [eastward_sea_water_velocity]{surface}	0.098224	0.102067	0.104769	0.107070	0.109503	0.109776	0.112542	0.112635	0.114299	0.114730
Temperature (°C) [sea_water_potential_temperature]{50m}	0.854456	0.852906	0.951926	0.951772	1.065961	1.065687	1.174906	1.174736	1.278222	1.278034
Salinity (PSU) [sea_water_salinity]{50m}	0.208439	0.207579	0.225481	0.224106	0.245745	0.244087	0.268031	0.265787	0.290913	0.287719
Meridional current (m/s) [northward_sea_water_velocity]{50m}	0.088766	0.088903	0.088661	0.089320	0.090220	0.090184	0.091745	0.092326	0.093884	0.094264
Zonal current (m/s) [eastward_sea_water_velocity]{50m}	0.091295	0.091312	0.090986	0.091336	0.092213	0.092164	0.093560	0.094040	0.095509	0.095962
Temperature (°C) [sea_water_potential_temperature]{100m}	0.779576	0.776669	0.842148	0.839730	0.908094	0.908899	0.974412	0.980088	1.043179	1.053783
Salinity (PSU) [sea_water_salinity]{100m}	0.196727	0.196540	0.196256	0.196541	0.200722	0.201480	0.208545	0.209395	0.218183	0.218768
Meridional current (m/s) [northward_sea_water_velocity]{100m}	0.084993	0.085162	0.084675	0.085387	0.086021	0.086332	0.087441	0.088126	0.089145	0.089748
Zonal current (m/s) [eastward_sea_water_velocity]{100m}	0.087106	0.087134	0.086311	0.086709	0.087139	0.087578	0.088573	0.089330	0.090266	0.090818
Temperature (°C) [sea_water_potential_temperature]{200m}	0.774573	0.774946	0.837050	0.837918	0.871452	0.873718	0.902159	0.905229	0.934971	0.937390
Salinity (PSU) [sea_water_salinity]{200m}	0.147628	0.146890	0.156291	0.155514	0.165372	0.164875	0.174984	0.174673	0.184812	0.184424
Meridional current (m/s) [northward_sea_water_velocity]{200m}	0.079670	0.079811	0.078810	0.079326	0.079445	0.080143	0.080693	0.081489	0.081916	0.082481
Zonal current (m/s) [eastward_sea_water_velocity]{200m}	0.080579	0.080559	0.079749	0.080013	0.080379	0.080897	0.081727	0.082382	0.083075	0.083413
Temperature (°C) [sea_water_potential_temperature]{300m}	0.703195	0.702291	0.750980	0.752719	0.760244	0.765531	0.769148	0.776827	0.786576	0.793752
Salinity (PSU) [sea_water_salinity]{300m}	0.120528	0.120426	0.126143	0.125923	0.132873	0.132852	0.140774	0.140744	0.149574	0.149315
Meridional current (m/s) [northward_sea_water_velocity]{300m}	0.079316	0.079438	0.078377	0.078765	0.078834	0.079385	0.079860	0.080455	0.080838	0.081217
Zonal current (m/s) [eastward_sea_water_velocity]{300m}	0.080205	0.080224	0.079266	0.079508	0.079736	0.080193	0.080909	0.081461	0.082131	0.082379
Temperature (°C) [sea_water_potential_temperature]{500m}	0.446855	0.449053	0.441028	0.443778	0.460831	0.463640	0.489842	0.492156	0.524005	0.524871
Salinity (PSU) [sea_water_salinity]{500m}	0.105162	0.105170	0.115833	0.115930	0.124935	0.125036	0.133273	0.133277	0.141167	0.140936
Meridional current (m/s) [northward_sea_water_velocity]{500m}	0.082252	0.082393	0.081396	0.081726	0.081858	0.082281	0.082695	0.083151	0.083451	0.083717
Zonal current (m/s) [eastward_sea_water_velocity]{500m}	0.083341	0.083386	0.082128	0.082299	0.082251	0.082551	0.082903	0.083216	0.083483	0.083570

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}	42.826419	43.148652	45.656525	45.925669	48.682357	49.146437	51.218224	51.242755	52.952274	52.823102

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}	0.081148	0.081353	0.089569	0.089816	0.096873	0.09641	0.102110	0.102265	0.106671	0.107129
Zonal geostrophic current (m/s) [geostrophic_eastward_sea_water_velocity]{surface}	0.070103	0.070479	0.076722	0.077108	0.082668	0.08286	0.087593	0.088473	0.092098	0.093124

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}	0.586672	0.596031	0.697303	0.677697	0.755620	0.725741	1.032391	0.814358	0.907177	0.871010
Temperature (°C) [sea_water_potential_temperature]{0-5m}	0.789828	0.733837	0.952779	0.914444	1.016245	0.935859	1.128196	1.003265	1.185476	1.208344
Temperature (°C) [sea_water_potential_temperature]{5-100m}	1.045088	1.041089	1.147332	1.048087	1.234094	1.169967	1.291416	1.266419	1.372554	1.438536
Temperature (°C) [sea_water_potential_temperature]{100-300m}	0.449898	0.473675	0.544319	0.520966	0.598340	0.584838	0.714990	0.670977	0.753294	0.774588
Temperature (°C) [sea_water_potential_temperature]{300-600m}	0.412232	0.438214	0.399305	0.425153	0.446921	0.448998	0.504823	0.484916	0.545003	0.530690
Salinity (PSU) [sea_water_salinity]{0-5m}	0.394977	0.348498	0.316568	0.294657	0.325947	0.493939	0.307341	0.440722	0.418871	0.381298
Salinity (PSU) [sea_water_salinity]{5-100m}	0.232713	0.241860	0.260364	0.226786	0.299367	0.304481	0.312446	0.299970	0.334235	0.355567
Salinity (PSU) [sea_water_salinity]{100-300m}	0.110366	0.110895	0.123137	0.104473	0.154680	0.142934	0.173442	0.136884	0.173965	0.175883
Salinity (PSU) [sea_water_salinity]{300-600m}	0.079518	0.078259	0.084289	0.095100	0.107678	0.108940	0.114984	0.126423	0.149098	0.135883
Sea level anomaly (m) [sea_surface_height_above_geoid]{surface}	0.045548	0.046853	0.048154	0.046700	0.049035	0.050231	0.051552	0.052827	0.055530	0.058817
Zonal current (m/s) [eastward_sea_water_velocity]{15m}	0.201773	0.205514	0.205710	0.206548	0.194364	0.206807	0.196057	0.208905	0.211395	0.211832
Meridional current (m/s) [northward_sea_water_velocity]{15m}	0.174135	0.175563	0.176049	0.173476	0.177488	0.175104	0.177943	0.179721	0.180747	0.182318

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}	8.350428	16.100475	23.443907	30.392088	36.878788	43.015072	49.007515	54.83445

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}	0.027111	0.034163	0.040985	0.047771	0.051741	0.051421	0.051173	0.053276	0.057978	0.060551
Temperature (°C) [sea_water_potential_temperature]{surface}	0.408416	0.408322	0.570535	0.564788	0.700794	0.693306	0.815837	0.802655	0.916711	0.893554
Salinity (PSU) [sea_water_salinity]{surface}	0.113654	0.115320	0.149651	0.151067	0.178939	0.178695	0.202511	0.202825	0.223447	0.225200
Meridional current (m/s) [northward_sea_water_velocity]{surface}	0.036865	0.051002	0.061293	0.071321	0.077194	0.082121	0.088011	0.092400	0.096683	0.098486
Zonal current (m/s) [eastward_sea_water_velocity]{surface}	0.038333	0.054737	0.064703	0.074019	0.081865	0.087288	0.094666	0.098642	0.103570	0.106318
Temperature (°C) [sea_water_potential_temperature]{50m}	0.704061	0.696270	0.832898	0.833204	0.971963	0.975095	1.100987	1.107354	1.218654	1.222877
Salinity (PSU) [sea_water_salinity]{50m}	0.115667	0.114513	0.162131	0.160998	0.199735	0.198222	0.233096	0.231078	0.263196	0.259703
Meridional current (m/s) [northward_sea_water_velocity]{50m}	0.031153	0.037853	0.046072	0.052359	0.059076	0.063154	0.069645	0.074519	0.079708	0.082960
Zonal current (m/s) [eastward_sea_water_velocity]{50m}	0.032239	0.038370	0.047275	0.053730	0.060465	0.065077	0.071508	0.076338	0.081198	0.084593
Temperature (°C) [sea_water_potential_temperature]{100m}	0.490886	0.494962	0.606461	0.615971	0.715044	0.729065	0.817349	0.835132	0.912917	0.932340
Salinity (PSU) [sea_water_salinity]{100m}	0.091680	0.091327	0.123261	0.123929	0.147814	0.149074	0.170124	0.171340	0.190092	0.190523
Meridional current (m/s) [northward_sea_water_velocity]{100m}	0.026803	0.032240	0.039789	0.045906	0.052287	0.057234	0.063628	0.068649	0.073308	0.076990
Zonal current (m/s) [eastward_sea_water_velocity]{100m}	0.026899	0.032440	0.040010	0.046150	0.052378	0.057763	0.063981	0.069269	0.073877	0.077589
Temperature (°C) [sea_water_potential_temperature]{200m}	0.372431	0.374121	0.477619	0.484075	0.547539	0.558392	0.613030	0.625879	0.675068	0.685493
Salinity (PSU) [sea_water_salinity]{200m}	0.067076	0.066560	0.090771	0.090717	0.110361	0.110721	0.127788	0.128353	0.143197	0.143338
Meridional current (m/s) [northward_sea_water_velocity]{200m}	0.021928	0.025847	0.031887	0.037176	0.043012	0.048615	0.054475	0.059841	0.064002	0.067683
Zonal current (m/s) [eastward_sea_water_velocity]{200m}	0.022122	0.025993	0.032720	0.037666	0.043772	0.049217	0.055233	0.060425	0.064814	0.068382
Temperature (°C) [sea_water_potential_temperature]{300m}	0.398024	0.399091	0.478154	0.484742	0.512979	0.524883	0.550619	0.564734	0.595601	0.606310
Salinity (PSU) [sea_water_salinity]{300m}	0.069892	0.070047	0.085827	0.086221	0.099767	0.100470	0.113310	0.113950	0.126396	0.126467
Meridional current (m/s) [northward_sea_water_velocity]{300m}	0.020371	0.024041	0.029906	0.035123	0.040794	0.046447	0.052121	0.057436	0.061498	0.065181
Zonal current (m/s) [eastward_sea_water_velocity]{300m}	0.020823	0.024619	0.031290	0.036211	0.042256	0.047683	0.053625	0.058738	0.063144	0.066657
Temperature (°C) [sea_water_potential_temperature]{500m}	0.227874	0.229592	0.286700	0.290102	0.351989	0.355704	0.413777	0.416201	0.470345	0.469719
Salinity (PSU) [sea_water_salinity]{500m}	0.068376	0.068098	0.087412	0.087406	0.101756	0.102029	0.113895	0.114090	0.124327	0.124239
Meridional current (m/s) [northward_sea_water_velocity]{500m}	0.019723	0.023467	0.029462	0.034726	0.040492	0.046084	0.051731	0.056895	0.061051	0.064758
Zonal current (m/s) [eastward_sea_water_velocity]{500m}	0.020294	0.024179	0.030462	0.035675	0.041349	0.046888	0.052499	0.057540	0.061607	0.065111

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}	41.271889	41.747284	44.60371	45.118945	47.944402	48.539611	50.608162	50.674786	52.445666	52.382732

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}	0.041993	0.045001	0.061390	0.065649	0.077152	0.080338	0.089236	0.092464	0.098486	0.101166
Zonal geostrophic current (m/s) [geostrophic_eastward_sea_water_velocity]{surface}	0.033907	0.036562	0.049931	0.053385	0.063098	0.066391	0.073968	0.077710	0.082907	0.085867

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}	3.676244	7.896177	12.434446	17.292439	22.39011	27.741343	33.388687	39.177395