{
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    {
      "cell_type": "markdown",
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      "source": [
        "\n# CMEMS current components\n\nThe global CMEMS/copernicus ocean model contains several different surface current fields.\nOpenDrift will by default use the variables with \"standard_name\" attribute equal to what is requested from a module, typically \"x_sea_water_velocity\"/\"y_sea_water_velocity\" for currents.\nNote that \"east/north\" counterparts will also be detected, and eventual rotation will be performed automatically.\n\nThis example illustrates how a \"standard_name_mapping\" can be added to the generic netCDF reader to chose alternative variables.\nThe example also illustrates the alternative (experimental) mechanism of summing two readers.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "from datetime import datetime, timedelta\nimport cf_xarray\nimport copernicusmarine\nfrom opendrift.models.oceandrift import OceanDrift\nfrom opendrift.readers.reader_netCDF_CF_generic import Reader"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Get an Xarray dataset from copernicusmarine client\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "ds = copernicusmarine.open_dataset(dataset_id='cmems_mod_glo_phy_anfc_merged-uv_PT1H-i')\nprint(ds)     # Default Xarray output\nprint(ds.cf)  # Output from cf-xarray"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Create an OpenDrift reader from this dataset\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "reader_default = Reader(ds, name='CMEMS default')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Mapping other variables to required standard_name's\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "reader_tides = Reader(ds, standard_name_mapping={\n                        'utide': 'x_sea_water_velocity',\n                        'vtide': 'y_sea_water_velocity',\n                        }, name='Tides only')\nreader_stokes = Reader(ds, standard_name_mapping={\n                        'vsdx': 'x_sea_water_velocity',\n                        'vsdy': 'y_sea_water_velocity',\n                        }, name='Stokes only')\nreader_total = Reader(ds, standard_name_mapping={\n                        'utotal': 'x_sea_water_velocity',\n                        'vtotal': 'y_sea_water_velocity',\n                        }, name='Total current')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Run and compare simulations using the different current components\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "cases = {'Eulerian current': reader_default,\n         'Tides only': reader_tides,\n         'Stokes drift only': reader_stokes,\n         'Total current': reader_total,\n         'SUM: Eulerian + Tides': reader_default + reader_tides,  # Experimental feature\n         'SUM: Eulerian + Stokes': reader_default + reader_stokes,     # Experimental feature\n         'SUM: Eulerian + Tides + Stokes': reader_default + reader_tides + reader_stokes  # Experimental feature\n         }\n\nsimulations = []\nfor cname, reader in cases.items():\n    o = OceanDrift()\n    o.add_reader(reader, variables=['x_sea_water_velocity', 'y_sea_water_velocity'])\n    o.seed_elements(lon=4.8, lat=60, time=datetime(2024, 10, 31, 6))\n    o.run(duration=timedelta(hours=12))\n    simulations.append(o)\n\nsimulations[0].plot(filename='cmems_comparison.png', buffer=.05,\n                    compare=simulations[1:], legend=list(cases))"
      ]
    }
  ],
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