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      "source": [
        "# Dfs0 - CMEMS *in-situ* data\n",
        "\n",
        "Copernicus Marine provides access to a wide range of model and\n",
        "[*in-situ*\n",
        "data](https://marine.copernicus.eu/about/producers/insitu-tac). In this\n",
        "example we will look at how to access the *in-situ* data and convert it\n",
        "to a MIKE IO dataset."
      ],
      "id": "aefcb732-54ae-419e-b36b-7eaa0f26a445"
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {},
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import xarray as xr\n",
        "import mikeio"
      ],
      "id": "936f0350"
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {},
      "outputs": [
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              "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 3MB\n",
              "Dimensions:      (TIME: 2879, LATITUDE: 2879, LONGITUDE: 2879, DEPTH: 7,\n",
              "                  POSITION: 2879)\n",
              "Coordinates:\n",
              "  * TIME         (TIME) datetime64[ns] 23kB 2022-09-01 ... 2022-09-30T23:31:5...\n",
              "  * LATITUDE     (LATITUDE) float32 12kB 54.0 54.0 54.0 54.0 ... 54.0 54.0 54.0\n",
              "  * LONGITUDE    (LONGITUDE) float32 12kB 6.583 6.583 6.583 ... 6.583 6.583\n",
              "    DEPH         (TIME, DEPTH) float32 81kB ...\n",
              "Dimensions without coordinates: DEPTH, POSITION\n",
              "Data variables: (12/22)\n",
              "    DEPH_QC      (TIME, DEPTH) float32 81kB ...\n",
              "    TIME_QC      (TIME) float32 12kB ...\n",
              "    POSITION_QC  (POSITION) float32 12kB ...\n",
              "    TEMP         (TIME, DEPTH) float64 161kB ...\n",
              "    TEMP_QC      (TIME, DEPTH) float32 81kB ...\n",
              "    VHM0         (TIME, DEPTH) float64 161kB ...\n",
              "    ...           ...\n",
              "    VTPK_DM      (TIME, DEPTH) object 161kB ...\n",
              "    VTZA         (TIME, DEPTH) float64 161kB ...\n",
              "    VTZA_QC      (TIME, DEPTH) float32 81kB ...\n",
              "    VPED         (TIME, DEPTH) float64 161kB ...\n",
              "    VPED_QC      (TIME, DEPTH) float32 81kB ...\n",
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              "Attributes: (12/46)\n",
              "    platform_code:                  FINO1\n",
              "    platform_name:                  \n",
              "    data_mode:                      M\n",
              "    title:                          NWS - NRT in situ Observations\n",
              "    summary:                        Oceanographic data from North West Shelf\n",
              "    naming_authority:               Copernicus Marine In Situ\n",
              "    ...                             ...\n",
              "    doi:                            \n",
              "    pi_name:                        \n",
              "    qc_manual:                      OceanSITES User&#x27;s Manual v1.2\n",
              "    date_update:                    2022-10-07T05:39:40Z\n",
              "    history:                        2022-10-01T18:04:25Z : Creation; 2022-10-...\n",
              "    wmo_inst_type:                  </pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-4078211b-cad8-4f0c-b3ae-c62e8b60e1f0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4078211b-cad8-4f0c-b3ae-c62e8b60e1f0' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>TIME</span>: 2879</li><li><span class='xr-has-index'>LATITUDE</span>: 2879</li><li><span class='xr-has-index'>LONGITUDE</span>: 2879</li><li><span>DEPTH</span>: 7</li><li><span>POSITION</span>: 2879</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-95776152-6095-4539-a4b3-35a4ae87d2a6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-95776152-6095-4539-a4b3-35a4ae87d2a6' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>TIME</span></div><div class='xr-var-dims'>(TIME)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-09-01 ... 2022-09-30T23:31:...</div><input id='attrs-8a9858b7-e2dc-4ef5-9126-b6797c49cc44' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a9858b7-e2dc-4ef5-9126-b6797c49cc44' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c364ab3-a1f7-4c7e-8898-53c3f58cd5f8' class='xr-var-data-in' type='checkbox'><label for='data-4c364ab3-a1f7-4c7e-8898-53c3f58cd5f8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>valid_min :</span></dt><dd>-90000.0</dd><dt><span>valid_max :</span></dt><dd>90000.0</dd><dt><span>uncertainty :</span></dt><dd> </dd><dt><span>comment :</span></dt><dd> </dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>ancillary_variables :</span></dt><dd>TIME_QC</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-09-01T00:00:00.000000000&#x27;, &#x27;2022-09-01T00:02:00.000000000&#x27;,\n",
              "       &#x27;2022-09-01T00:30:00.000000000&#x27;, ..., &#x27;2022-09-30T23:02:00.000000000&#x27;,\n",
              "       &#x27;2022-09-30T23:30:00.000000000&#x27;, &#x27;2022-09-30T23:31:59.999999744&#x27;],\n",
              "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>LATITUDE</span></div><div class='xr-var-dims'>(LATITUDE)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>54.0 54.0 54.0 ... 54.0 54.0 54.0</div><input id='attrs-34882079-8831-436b-9fad-88bb43a7aa6a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-34882079-8831-436b-9fad-88bb43a7aa6a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d1a8751-daa8-42d0-a28f-b7458a61f6b2' class='xr-var-data-in' type='checkbox'><label for='data-0d1a8751-daa8-42d0-a28f-b7458a61f6b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude of each location</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degree_north</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>uncertainty :</span></dt><dd></dd><dt><span>comment :</span></dt><dd></dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>ancillary_variables :</span></dt><dd>POSITION_QC</dd></dl></div><div class='xr-var-data'><pre>array([54., 54., 54., ..., 54., 54., 54.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>LONGITUDE</span></div><div class='xr-var-dims'>(LONGITUDE)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>6.583 6.583 6.583 ... 6.583 6.583</div><input id='attrs-638054ce-b8ee-4018-9dc6-b549f0b9ac7d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-638054ce-b8ee-4018-9dc6-b549f0b9ac7d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7beb33d1-cc6c-4b74-b0e9-a2fec77d3cf9' class='xr-var-data-in' type='checkbox'><label for='data-7beb33d1-cc6c-4b74-b0e9-a2fec77d3cf9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Longitude of each location</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degree_east</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>uncertainty :</span></dt><dd></dd><dt><span>comment :</span></dt><dd></dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>ancillary_variables :</span></dt><dd>POSITION_QC</dd></dl></div><div class='xr-var-data'><pre>array([6.583333, 6.583333, 6.583333, ..., 6.583333, 6.583333, 6.583333],\n",
              "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DEPH</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9f8ad712-61f5-40f7-a5dd-36258af0a2ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f8ad712-61f5-40f7-a5dd-36258af0a2ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-462f264d-1229-4cd8-8a36-39c47e8673f9' class='xr-var-data-in' type='checkbox'><label for='data-462f264d-1229-4cd8-8a36-39c47e8673f9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Depth</dd><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>valid_min :</span></dt><dd>-12000.0</dd><dt><span>valid_max :</span></dt><dd>12000.0</dd><dt><span>uncertainty :</span></dt><dd></dd><dt><span>comment :</span></dt><dd></dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>reference :</span></dt><dd>sea_level</dd><dt><span>data_mode :</span></dt><dd>R</dd><dt><span>ancillary_variables :</span></dt><dd>DEPH_QC</dd></dl></div><div class='xr-var-data'><pre>[20153 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5bded75d-7f02-4e97-9191-6bfd1d702674' class='xr-section-summary-in' type='checkbox'  ><label for='section-5bded75d-7f02-4e97-9191-6bfd1d702674' class='xr-section-summary' >Data variables: <span>(22)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>DEPH_QC</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-da0f11fd-c9f2-485c-8a82-c0618530db5b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da0f11fd-c9f2-485c-8a82-c0618530db5b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb8d37e4-a64f-43a0-b389-4c7373933cc3' class='xr-var-data-in' type='checkbox'><label for='data-cb8d37e4-a64f-43a0-b389-4c7373933cc3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Depth quality flag</dd><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 2</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed value_below_detection nominal_value interpolated_value missing_value</dd></dl></div><div class='xr-var-data'><pre>[20153 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TIME_QC</span></div><div class='xr-var-dims'>(TIME)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-02854f5d-0471-4af2-b20d-1356102d18b8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-02854f5d-0471-4af2-b20d-1356102d18b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-91f09405-e698-4e64-ba94-cfae367d3ee2' class='xr-var-data-in' type='checkbox'><label for='data-91f09405-e698-4e64-ba94-cfae367d3ee2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Time quality flag</dd><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 2</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed value_below_detection nominal_value interpolated_value missing_value</dd></dl></div><div class='xr-var-data'><pre>[2879 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>POSITION_QC</span></div><div class='xr-var-dims'>(POSITION)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fe8692ea-fcc2-4b7c-91ce-190fcf1d16ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fe8692ea-fcc2-4b7c-91ce-190fcf1d16ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f9199b8-a37e-4bbf-80c4-79e8dbebd471' class='xr-var-data-in' type='checkbox'><label for='data-4f9199b8-a37e-4bbf-80c4-79e8dbebd471' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Position quality flag</dd><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 2</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed value_below_detection nominal_value interpolated_value missing_value</dd></dl></div><div class='xr-var-data'><pre>[2879 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TEMP</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f20d9906-0be3-41af-a80b-84f0cd23f9b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f20d9906-0be3-41af-a80b-84f0cd23f9b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df6ebe24-81a3-40b3-b284-5cd52e6e4013' class='xr-var-data-in' type='checkbox'><label for='data-df6ebe24-81a3-40b3-b284-5cd52e6e4013' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd><dt><span>units :</span></dt><dd>degrees_C</dd><dt><span>long_name :</span></dt><dd>Sea temperature</dd><dt><span>valid_min :</span></dt><dd>-2000</dd><dt><span>valid_max :</span></dt><dd>32000</dd><dt><span>comment :</span></dt><dd> </dd><dt><span>uncertainty :</span></dt><dd> </dd><dt><span>accuracy :</span></dt><dd> </dd><dt><span>precision :</span></dt><dd> </dd><dt><span>resolution :</span></dt><dd> </dd><dt><span>cell_methods :</span></dt><dd> </dd><dt><span>sensor_depth :</span></dt><dd>0.0</dd><dt><span>sensor_mount :</span></dt><dd> </dd><dt><span>sensor_orientation :</span></dt><dd> </dd><dt><span>data_mode :</span></dt><dd>R</dd><dt><span>ancillary_variables :</span></dt><dd>TEMP_QC</dd></dl></div><div class='xr-var-data'><pre>[20153 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TEMP_QC</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e90d3e8b-66a0-45de-aa7b-836ed19e9393' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e90d3e8b-66a0-45de-aa7b-836ed19e9393' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b5cbf10-e5c1-433e-a359-f4c413475d69' class='xr-var-data-in' type='checkbox'><label for='data-9b5cbf10-e5c1-433e-a359-f4c413475d69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea temperature quality flag</dd><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 2</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed value_below_detection nominal_value interpolated_value missing_value</dd></dl></div><div class='xr-var-data'><pre>[20153 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VHM0</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d171151d-461b-42bc-989f-69b810baa04c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d171151d-461b-42bc-989f-69b810baa04c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d47b214d-6f3e-4745-8d1b-e431a7eb076d' class='xr-var-data-in' type='checkbox'><label for='data-d47b214d-6f3e-4745-8d1b-e431a7eb076d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_wave_significant_height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Spectral significant wave height (Hm0)</dd><dt><span>valid_min :</span></dt><dd>1</dd><dt><span>valid_max :</span></dt><dd>25000</dd><dt><span>comment :</span></dt><dd> </dd><dt><span>uncertainty :</span></dt><dd> </dd><dt><span>accuracy :</span></dt><dd> </dd><dt><span>precision :</span></dt><dd> </dd><dt><span>resolution :</span></dt><dd> </dd><dt><span>cell_methods :</span></dt><dd> </dd><dt><span>type_of_analysis :</span></dt><dd>spectral analysis</dd><dt><span>sensor_depth :</span></dt><dd>0.0</dd><dt><span>sensor_mount :</span></dt><dd> </dd><dt><span>sensor_orientation :</span></dt><dd> </dd><dt><span>data_mode :</span></dt><dd>M</dd><dt><span>ancillary_variables :</span></dt><dd>VHM0_QC VHM0_DM</dd></dl></div><div class='xr-var-data'><pre>[20153 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VHM0_QC</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7b44982b-1e87-4c7a-9807-f007c3bee479' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b44982b-1e87-4c7a-9807-f007c3bee479' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06a2d54f-37e5-4488-ab76-f7f7003e0cfa' class='xr-var-data-in' type='checkbox'><label for='data-06a2d54f-37e5-4488-ab76-f7f7003e0cfa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Spectral significant wave height (Hm0) quality flag</dd><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 2</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed value_below_detection nominal_value interpolated_value missing_value</dd></dl></div><div class='xr-var-data'><pre>[20153 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VHM0_DM</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1621dad7-620e-46dd-8b52-3ea355fb6a13' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1621dad7-620e-46dd-8b52-3ea355fb6a13' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24705456-e006-4d29-b335-6f21fc97f3e0' class='xr-var-data-in' type='checkbox'><label for='data-24705456-e006-4d29-b335-6f21fc97f3e0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Spectral significant wave height (Hm0) method of data processing</dd><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 1</dd><dt><span>flag_values :</span></dt><dd>R, A, D</dd><dt><span>flag_meanings :</span></dt><dd>real-time adjusted-in-real-time delayed-mode</dd></dl></div><div class='xr-var-data'><pre>[20153 values with dtype=object]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VZMX</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-423861c3-3204-47d7-a04e-9b62507c981c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-423861c3-3204-47d7-a04e-9b62507c981c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0810ecdc-94a2-4a78-a4d3-df7aabb3b916' class='xr-var-data-in' type='checkbox'><label for='data-0810ecdc-94a2-4a78-a4d3-df7aabb3b916' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_wave_maximum_height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Maximum zero crossing wave height (Hmax)</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>40000</dd><dt><span>comment :</span></dt><dd> </dd><dt><span>uncertainty :</span></dt><dd> </dd><dt><span>accuracy :</span></dt><dd> </dd><dt><span>precision :</span></dt><dd> </dd><dt><span>resolution :</span></dt><dd> </dd><dt><span>cell_methods :</span></dt><dd> </dd><dt><span>type_of_analysis :</span></dt><dd>zero crossing</dd><dt><span>sensor_depth :</span></dt><dd>0.0</dd><dt><span>sensor_mount :</span></dt><dd> </dd><dt><span>sensor_orientation :</span></dt><dd> </dd><dt><span>data_mode :</span></dt><dd>M</dd><dt><span>ancillary_variables :</span></dt><dd>VZMX_QC VZMX_DM</dd></dl></div><div class='xr-var-data'><pre>[20153 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VZMX_QC</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c80034ba-1172-42c4-a28f-c2608f072aec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c80034ba-1172-42c4-a28f-c2608f072aec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-17aac4ff-af9d-485e-a2e1-53d09a93ea97' class='xr-var-data-in' type='checkbox'><label for='data-17aac4ff-af9d-485e-a2e1-53d09a93ea97' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Maximum zero crossing wave height (Hmax) quality flag</dd><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 2</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed value_below_detection nominal_value interpolated_value missing_value</dd></dl></div><div class='xr-var-data'><pre>[20153 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VZMX_DM</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6bf18e3d-1d3f-437f-a2b0-33f0e36fe546' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6bf18e3d-1d3f-437f-a2b0-33f0e36fe546' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64846987-cb8d-48a8-96f6-ae0403a54964' class='xr-var-data-in' type='checkbox'><label for='data-64846987-cb8d-48a8-96f6-ae0403a54964' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Maximum zero crossing wave height (Hmax) method of data processing</dd><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 1</dd><dt><span>flag_values :</span></dt><dd>R, A, D</dd><dt><span>flag_meanings :</span></dt><dd>real-time adjusted-in-real-time delayed-mode</dd></dl></div><div class='xr-var-data'><pre>[20153 values with dtype=object]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VTM02</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-19eea0af-46d8-4b37-82bb-cd4cd1406db7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-19eea0af-46d8-4b37-82bb-cd4cd1406db7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-898638af-796b-4649-91e4-149421989fab' class='xr-var-data-in' type='checkbox'><label for='data-898638af-796b-4649-91e4-149421989fab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_wave_mean_period_from_variance_spectral_density_second_frequency_moment</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>long_name :</span></dt><dd>Spectral moments (0,2) wave period (Tm02)</dd><dt><span>valid_min :</span></dt><dd>1000</dd><dt><span>valid_max :</span></dt><dd>25000</dd><dt><span>comment :</span></dt><dd> </dd><dt><span>uncertainty :</span></dt><dd> </dd><dt><span>accuracy :</span></dt><dd> </dd><dt><span>precision :</span></dt><dd> </dd><dt><span>resolution :</span></dt><dd> </dd><dt><span>cell_methods :</span></dt><dd> </dd><dt><span>type_of_analysis :</span></dt><dd>spectral analysis</dd><dt><span>sensor_depth :</span></dt><dd>0.0</dd><dt><span>sensor_mount :</span></dt><dd> </dd><dt><span>sensor_orientation :</span></dt><dd> </dd><dt><span>data_mode :</span></dt><dd>M</dd><dt><span>ancillary_variables :</span></dt><dd>VTM02_QC VTM02_DM</dd></dl></div><div class='xr-var-data'><pre>[20153 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VTM02_QC</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-84b2e62f-0f63-45ab-9842-d8d31b829478' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-84b2e62f-0f63-45ab-9842-d8d31b829478' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd9e3183-8827-4117-aedb-f8597ba3f36f' class='xr-var-data-in' type='checkbox'><label for='data-fd9e3183-8827-4117-aedb-f8597ba3f36f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Spectral moments (0,2) wave period (Tm02) quality flag</dd><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 2</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed value_below_detection nominal_value interpolated_value missing_value</dd></dl></div><div class='xr-var-data'><pre>[20153 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VTM02_DM</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-57a63ac9-a165-4f87-b03d-22031da50332' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-57a63ac9-a165-4f87-b03d-22031da50332' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f1f86e4-6d42-421f-a00c-70bf054003e3' class='xr-var-data-in' type='checkbox'><label for='data-0f1f86e4-6d42-421f-a00c-70bf054003e3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Spectral moments (0,2) wave period (Tm02) method of data processing</dd><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 1</dd><dt><span>flag_values :</span></dt><dd>R, A, D</dd><dt><span>flag_meanings :</span></dt><dd>real-time adjusted-in-real-time delayed-mode</dd></dl></div><div class='xr-var-data'><pre>[20153 values with dtype=object]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VTPK</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b54b333e-edfb-465b-b7e0-4ee017b43daa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b54b333e-edfb-465b-b7e0-4ee017b43daa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03497419-780b-4d95-9a8d-29b67a6c5c37' class='xr-var-data-in' type='checkbox'><label for='data-03497419-780b-4d95-9a8d-29b67a6c5c37' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_wave_period_at_variance_spectral_density_maximum</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>long_name :</span></dt><dd>Wave period at spectral peak / peak period (Tp)</dd><dt><span>valid_min :</span></dt><dd>1000</dd><dt><span>valid_max :</span></dt><dd>30000</dd><dt><span>comment :</span></dt><dd> </dd><dt><span>uncertainty :</span></dt><dd> </dd><dt><span>accuracy :</span></dt><dd> </dd><dt><span>precision :</span></dt><dd> </dd><dt><span>resolution :</span></dt><dd> </dd><dt><span>cell_methods :</span></dt><dd> </dd><dt><span>type_of_analysis :</span></dt><dd>spectral analysis</dd><dt><span>sensor_depth :</span></dt><dd>0.0</dd><dt><span>sensor_mount :</span></dt><dd> </dd><dt><span>sensor_orientation :</span></dt><dd> </dd><dt><span>data_mode :</span></dt><dd>M</dd><dt><span>ancillary_variables :</span></dt><dd>VTPK_QC VTPK_DM</dd></dl></div><div class='xr-var-data'><pre>[20153 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VTPK_QC</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ea4d8092-e8ef-4915-802d-8ac8b73d4360' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea4d8092-e8ef-4915-802d-8ac8b73d4360' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecdeeaf2-ba2e-406b-9c2e-580fb551bd0d' class='xr-var-data-in' type='checkbox'><label for='data-ecdeeaf2-ba2e-406b-9c2e-580fb551bd0d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Wave period at spectral peak / peak period (Tp) quality flag</dd><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 2</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed value_below_detection nominal_value interpolated_value missing_value</dd></dl></div><div class='xr-var-data'><pre>[20153 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VTPK_DM</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cd657bb0-bd1d-45e2-a2d1-b550f98cb514' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd657bb0-bd1d-45e2-a2d1-b550f98cb514' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7374d954-8982-463a-852e-6cf1b14da62e' class='xr-var-data-in' type='checkbox'><label for='data-7374d954-8982-463a-852e-6cf1b14da62e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Wave period at spectral peak / peak period (Tp) method of data processing</dd><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 1</dd><dt><span>flag_values :</span></dt><dd>R, A, D</dd><dt><span>flag_meanings :</span></dt><dd>real-time adjusted-in-real-time delayed-mode</dd></dl></div><div class='xr-var-data'><pre>[20153 values with dtype=object]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VTZA</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7684925d-9ba4-4777-87f8-35a1ea1e37fd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7684925d-9ba4-4777-87f8-35a1ea1e37fd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23e244e0-4e8b-4c57-8950-cd4113584ebc' class='xr-var-data-in' type='checkbox'><label for='data-23e244e0-4e8b-4c57-8950-cd4113584ebc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_wave_mean_period</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>long_name :</span></dt><dd>Average zero crossing wave period (Tz)</dd><dt><span>valid_min :</span></dt><dd>2000</dd><dt><span>valid_max :</span></dt><dd>25000</dd><dt><span>comment :</span></dt><dd> </dd><dt><span>uncertainty :</span></dt><dd> </dd><dt><span>accuracy :</span></dt><dd> </dd><dt><span>precision :</span></dt><dd> </dd><dt><span>resolution :</span></dt><dd> </dd><dt><span>cell_methods :</span></dt><dd> </dd><dt><span>type_of_analysis :</span></dt><dd>zero crossing</dd><dt><span>sensor_depth :</span></dt><dd>0.0</dd><dt><span>sensor_mount :</span></dt><dd> </dd><dt><span>sensor_orientation :</span></dt><dd> </dd><dt><span>data_mode :</span></dt><dd>R</dd><dt><span>ancillary_variables :</span></dt><dd>VTZA_QC</dd></dl></div><div class='xr-var-data'><pre>[20153 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VTZA_QC</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7794c1d1-2e78-42d0-b460-6522e6105d0d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7794c1d1-2e78-42d0-b460-6522e6105d0d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e48d5a0-9372-4f79-ab5b-1d6caa04c7c9' class='xr-var-data-in' type='checkbox'><label for='data-6e48d5a0-9372-4f79-ab5b-1d6caa04c7c9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Average zero crossing wave period (Tz) quality flag</dd><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 2</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed value_below_detection nominal_value interpolated_value missing_value</dd></dl></div><div class='xr-var-data'><pre>[20153 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VPED</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0d16f6ae-3a45-49f1-9114-6ae14e2cb2a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0d16f6ae-3a45-49f1-9114-6ae14e2cb2a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e72a9698-248d-4cad-87d7-138668b6bc50' class='xr-var-data-in' type='checkbox'><label for='data-e72a9698-248d-4cad-87d7-138668b6bc50' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_wave_from_direction_at_variance_spectral_density_maximum</dd><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Wave principal direction at spectral peak</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>360000</dd><dt><span>comment :</span></dt><dd> </dd><dt><span>uncertainty :</span></dt><dd> </dd><dt><span>accuracy :</span></dt><dd> </dd><dt><span>precision :</span></dt><dd> </dd><dt><span>resolution :</span></dt><dd> </dd><dt><span>cell_methods :</span></dt><dd> </dd><dt><span>type_of_analysis :</span></dt><dd>spectral analysis</dd><dt><span>sensor_depth :</span></dt><dd>0.0</dd><dt><span>sensor_mount :</span></dt><dd> </dd><dt><span>sensor_orientation :</span></dt><dd> </dd><dt><span>data_mode :</span></dt><dd>M</dd><dt><span>ancillary_variables :</span></dt><dd>VPED_QC VPED_DM</dd></dl></div><div class='xr-var-data'><pre>[20153 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VPED_QC</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8aaceddd-9b37-4264-92be-c9592ef2a16b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8aaceddd-9b37-4264-92be-c9592ef2a16b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-464fee47-4c17-4346-8f14-ef50d154a83c' class='xr-var-data-in' type='checkbox'><label for='data-464fee47-4c17-4346-8f14-ef50d154a83c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Wave principal direction at spectral peak quality flag</dd><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 2</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed value_below_detection nominal_value interpolated_value missing_value</dd></dl></div><div class='xr-var-data'><pre>[20153 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VPED_DM</span></div><div class='xr-var-dims'>(TIME, DEPTH)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8b6af51a-d52a-4119-9bf7-00653cb133c0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8b6af51a-d52a-4119-9bf7-00653cb133c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-315ca4c3-4108-46e3-a6b4-d1edc31a9a59' class='xr-var-data-in' type='checkbox'><label for='data-315ca4c3-4108-46e3-a6b4-d1edc31a9a59' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Wave principal direction at spectral peak method of data processing</dd><dt><span>conventions :</span></dt><dd>Copernicus Marine In Situ reference table 1</dd><dt><span>flag_values :</span></dt><dd>R, A, D</dd><dt><span>flag_meanings :</span></dt><dd>real-time adjusted-in-real-time delayed-mode</dd></dl></div><div class='xr-var-data'><pre>[20153 values with dtype=object]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2c9b8f32-76a9-43ba-82d4-c383ab8c7fb6' class='xr-section-summary-in' type='checkbox'  ><label for='section-2c9b8f32-76a9-43ba-82d4-c383ab8c7fb6' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>TIME</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-5fe9c742-6b02-4fa7-8497-d282d09f4ee6' class='xr-index-data-in' type='checkbox'/><label for='index-5fe9c742-6b02-4fa7-8497-d282d09f4ee6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([          &#x27;2022-09-01 00:00:00&#x27;,\n",
              "                         &#x27;2022-09-01 00:02:00&#x27;,\n",
              "                         &#x27;2022-09-01 00:30:00&#x27;,\n",
              "                         &#x27;2022-09-01 00:32:00&#x27;,\n",
              "                         &#x27;2022-09-01 01:00:00&#x27;,\n",
              "               &#x27;2022-09-01 01:01:59.999999744&#x27;,\n",
              "                         &#x27;2022-09-01 01:30:00&#x27;,\n",
              "                         &#x27;2022-09-01 01:32:00&#x27;,\n",
              "                         &#x27;2022-09-01 02:00:00&#x27;,\n",
              "                         &#x27;2022-09-01 02:02:00&#x27;,\n",
              "               ...\n",
              "                         &#x27;2022-09-30 21:30:00&#x27;,\n",
              "                         &#x27;2022-09-30 21:32:00&#x27;,\n",
              "                         &#x27;2022-09-30 22:00:00&#x27;,\n",
              "               &#x27;2022-09-30 22:01:59.999999744&#x27;,\n",
              "                         &#x27;2022-09-30 22:30:00&#x27;,\n",
              "                         &#x27;2022-09-30 22:32:00&#x27;,\n",
              "                         &#x27;2022-09-30 23:00:00&#x27;,\n",
              "                         &#x27;2022-09-30 23:02:00&#x27;,\n",
              "                         &#x27;2022-09-30 23:30:00&#x27;,\n",
              "               &#x27;2022-09-30 23:31:59.999999744&#x27;],\n",
              "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;TIME&#x27;, length=2879, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>LATITUDE</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e6c2abc1-0830-4527-9fda-f684d90a3524' class='xr-index-data-in' type='checkbox'/><label for='index-e6c2abc1-0830-4527-9fda-f684d90a3524' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([54.0, 54.0, 54.0, 54.0, 54.0, 54.0, 54.0, 54.0, 54.0, 54.0,\n",
              "       ...\n",
              "       54.0, 54.0, 54.0, 54.0, 54.0, 54.0, 54.0, 54.0, 54.0, 54.0],\n",
              "      dtype=&#x27;float32&#x27;, name=&#x27;LATITUDE&#x27;, length=2879))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>LONGITUDE</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-72b73aa3-2903-4172-8e64-8321a0d41b32' class='xr-index-data-in' type='checkbox'/><label for='index-72b73aa3-2903-4172-8e64-8321a0d41b32' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([6.5833330154418945, 6.5833330154418945, 6.5833330154418945,\n",
              "       6.5833330154418945, 6.5833330154418945, 6.5833330154418945,\n",
              "       6.5833330154418945, 6.5833330154418945, 6.5833330154418945,\n",
              "       6.5833330154418945,\n",
              "       ...\n",
              "       6.5833330154418945, 6.5833330154418945, 6.5833330154418945,\n",
              "       6.5833330154418945, 6.5833330154418945, 6.5833330154418945,\n",
              "       6.5833330154418945, 6.5833330154418945, 6.5833330154418945,\n",
              "       6.5833330154418945],\n",
              "      dtype=&#x27;float32&#x27;, name=&#x27;LONGITUDE&#x27;, length=2879))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e9679711-dfc9-4254-beb3-920b8b1ba0de' class='xr-section-summary-in' type='checkbox'  ><label for='section-e9679711-dfc9-4254-beb3-920b8b1ba0de' class='xr-section-summary' >Attributes: <span>(46)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>platform_code :</span></dt><dd>FINO1</dd><dt><span>platform_name :</span></dt><dd></dd><dt><span>data_mode :</span></dt><dd>M</dd><dt><span>title :</span></dt><dd>NWS - NRT in situ Observations</dd><dt><span>summary :</span></dt><dd>Oceanographic data from North West Shelf</dd><dt><span>naming_authority :</span></dt><dd>Copernicus Marine In Situ</dd><dt><span>id :</span></dt><dd>NO_TS_MO_FINO1_202209</dd><dt><span>wmo_platform_code :</span></dt><dd>6201065</dd><dt><span>ices_platform_code :</span></dt><dd></dd><dt><span>source :</span></dt><dd>mooring</dd><dt><span>source_platform_category_code :</span></dt><dd>48</dd><dt><span>institution_edmo_code :</span></dt><dd>3356</dd><dt><span>institution :</span></dt><dd>R and D centre Kiel University of Applied Sciences</dd><dt><span>institution_references :</span></dt><dd>www.fh-kiel-gmbh.de/en/</dd><dt><span>site_code :</span></dt><dd></dd><dt><span>comment :</span></dt><dd></dd><dt><span>contact :</span></dt><dd>cmems-service@bsh.de</dd><dt><span>area :</span></dt><dd>North Atlantic Ocean</dd><dt><span>geospatial_lat_min :</span></dt><dd>54.00000</dd><dt><span>geospatial_lat_max :</span></dt><dd>54.00000</dd><dt><span>geospatial_lon_min :</span></dt><dd>6.58333</dd><dt><span>geospatial_lon_max :</span></dt><dd>6.58333</dd><dt><span>last_date_observation :</span></dt><dd>2022-09-30T23:32:00Z</dd><dt><span>last_latitude_observation :</span></dt><dd>54.00000</dd><dt><span>last_longitude_observation :</span></dt><dd>6.58333</dd><dt><span>geospatial_vertical_min :</span></dt><dd>0.00000</dd><dt><span>geospatial_vertical_max :</span></dt><dd>25.00000</dd><dt><span>time_coverage_start :</span></dt><dd>2022-09-01T00:00:00Z</dd><dt><span>time_coverage_end :</span></dt><dd>2022-09-30T23:32:00Z</dd><dt><span>cdm_data_type :</span></dt><dd>timeSeries</dd><dt><span>data_type :</span></dt><dd>OceanSITES time-series data</dd><dt><span>bottom_depth :</span></dt><dd></dd><dt><span>format_version :</span></dt><dd>1.4</dd><dt><span>Conventions :</span></dt><dd>CF-1.6 Copernicus-InSituTAC-FormatManual-1.42 Copernicus-InSituTAC-SRD-1.5 Copernicus-InSituTAC-ParametersList-3.2.1</dd><dt><span>netcdf_version :</span></dt><dd>netCDF-4 classic model</dd><dt><span>references :</span></dt><dd>http://marine.copernicus.eu http://www.marineinsitu.eu</dd><dt><span>data_assembly_center :</span></dt><dd>BSH</dd><dt><span>update_interval :</span></dt><dd>PT1H</dd><dt><span>citation :</span></dt><dd>These data were collected and made freely available by the Copernicus project and the programs that contribute to it</dd><dt><span>distribution_statement :</span></dt><dd>These data follow Copernicus standards; they are public and free of charge. User assumes all risk for use of data. User must display citation in any publication or product using data. User must contact PI prior to any commercial use of data.</dd><dt><span>doi :</span></dt><dd></dd><dt><span>pi_name :</span></dt><dd></dd><dt><span>qc_manual :</span></dt><dd>OceanSITES User&#x27;s Manual v1.2</dd><dt><span>date_update :</span></dt><dd>2022-10-07T05:39:40Z</dd><dt><span>history :</span></dt><dd>2022-10-01T18:04:25Z : Creation; 2022-10-07T05:39:40Z, BSH North West Shelf PU: Monthly subset 202209 extracted from history file NO_TS_MO_FINO1.nc</dd><dt><span>wmo_inst_type :</span></dt><dd></dd></dl></div></li></ul></div></div>"
            ]
          }
        }
      ],
      "source": [
        "fino = xr.open_dataset(\"../../data/NO_TS_MO_FINO1_202209.nc\")\n",
        "fino"
      ],
      "id": "09962186"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "CMEMS *in-situ* data is provided in a [standardised\n",
        "format](https://archimer.ifremer.fr/doc/00488/59938/).\n",
        "\n",
        "Find out which variables we are interested in to extract:"
      ],
      "id": "49328b0d-2eee-46b2-bc87-e1de143832f7"
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "\n",
              "</div>"
            ]
          }
        }
      ],
      "source": [
        "data = [\n",
        "    {\n",
        "        \"name\": fino[var].name,\n",
        "        \"standard_name\": fino[var].standard_name,\n",
        "        \"units\": fino[var].units,\n",
        "    }\n",
        "    for var in fino.data_vars\n",
        "    if hasattr(fino[var], \"units\")\n",
        "]\n",
        "\n",
        "pd.DataFrame(data)"
      ],
      "id": "e886db0d"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "The data have a DEPTH dimension, even though variables are only measured\n",
        "at a single level and doesn’t vary in time although the format allows\n",
        "for it.\n",
        "\n",
        "I.e. temperature (TEMP) is available at level 1 (0.5 m)"
      ],
      "id": "5a676b7c-1941-4a72-a6db-5dad18c65bc1"
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": 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flDFGd911V4P0xwwSAACo1WxOQ/vuu+80a9YsffLJJw3WJzNIAAAgqOXm5urYsWPq3r27\nUlJSlJKSIkm64YYbAjajxAwSAAAIajfddJMGDRpUZV+bNm308ssv68orrwxInwQkAAAQ1KKjoxUd\nHV1tf0pKipKSkgLSJwEJAAA0OsaYgJ6fNUgAAAAWBCQAAAALAhIAAIAFAQkAAMCCgAQAAGBBQAIA\nALAgIAEAAFgQkAAAACwISAAAABYEJAAAAAsCEgAACHozZsxQaGioXC6XbxsxYkTA+uNdbAAAoFHo\n3bu31q5d2yB9EZAAAICevXlIg/f5wBvZDd6nv7jEBgAAGoUtW7aoWbNmSk1N1ciRI7V79+6A9cUM\nEgAACOrZHEm68cYbdfvtt6tt27b617/+pUmTJmnQoEH6/PPP5XK56r0/ZpAAAEDQu/jii5WamiqH\nw6HWrVtr4cKFOnDggNatWxeQ/ghIAACg0XE4HHI4HDLGBOT8BCQAABD03nzzTeXl5UmSDh8+rLFj\nx6pFixbq06dPQPojIAEAgKC3ZMkSde3aVdHR0br00kvl8XiUk5Oj2NjYgPTHIm0AABD0li9f3qD9\nMYMEAABgQUACAACwICABAABYEJAAAAAsCEgAAAAWBCQAAAALWwLSsmXLlJmZqbi4ODkcDnm93irH\nHQ6HnE6nXC6Xb9u2bZsdpQIAgHOQLc9BSkxM1Lhx4+R2u3XHHXfU2Obdd9/VoEGDGrgyAAAAmwJS\nVlaWJGn16tX1cj6Px1NlFsrtdtfLeU/lvT89J29ZWUD7AAAgUEKjnGrR/WcqPHpE4WHB+czoSJdL\nTldgnpLtj+D8qUgaPXq0PB6PUlNTdc899+jOO+88ZdvZs2dr5syZDVbbd599qrKS7xusPwAA6lNU\nfKKSL85QWUmJKkKDczlyaES4pKoBaf369ZoyZYo2btyo0NBQXXjhhVq7dq1CQup/DEEZkHJyctSn\nTx+FhoYqJydHo0aNktfr1T333FNj+ylTpmjy5Mm+z263W8nJyQGrL2vcb1XprQjY+QEACKRKOeRx\nRisuJUURERF2l1Oj0PCqda1fv16DBw/WCy+8oOzsbEVERGjTpk1yOBwB6d9hjDFnanTrrbf6dbLI\nyEgtWLDA785Xr16tK664Qh6PR2GnmeKbMWOGVq1apXXr1vl1XrfbrejoaJWUlMjpdPpdDwAA54Ky\nsjLt2rVL7du3V2RkpN3l+CUzM1O9evXSs88+61f7U43R34zg1wzSsmXLNGrUKL/a1SYg+SskJER+\n5DgAAFBH+x/KbfA+z/99pl/tSkpKtG7dOvXu3Vu9evXSd999p7S0ND3yyCO64YYbAlKbXwEpMjJS\nf/nLX87Y7p133vGr04qKCnk8HpWXl0v6IeV5vV5FRERo69atMsYoPT1dISEh+uCDDzR37lzNmDHD\nr3MDAICm5fjx46qsrNTixYuVnZ2tjIwMLV++XMOHD9dHH32k3r1713uffgWk9evX+3Wy3Fz/0udr\nr72m22+/3ffZ5XJJkj788EMVFRVp0qRJ2rdvn8LCwpSamqonnnhCd999t1/nBgAAtefvbI4dYmN/\nWKw9ZswY9ezZU5J0/fXX64orrtA777xjX0C6+OKL/TqZv+3GjBmjMWPGnPL40KFD/ToPAABo+uLj\n43XBBRcEbEF2Tep0F9uBAwe0efNmFRUVVdk/cuTIeikKAADgx+69917NmTNHw4cPV7du3ZSdna2P\nPvpIjz32WED6q3VA+vOf/6wJEybI6XQqOjrat9/hcBCQAABAQNx3330qKSnR0KFDVVBQoI4dO+qN\nN97QT3/604D059dt/j/WunVrvfDCCwFbNV4fuM0fAIBTa4y3+dfW2d7mX+tHT5aVlen666+vW7UA\nAACNQK0D0k033aTly5cHohYAAICgUOs1SE899ZR+9rOf6aWXXlLLli2rHFu4cGG9FQYAAGCXWs8g\n/eY3v9HBgwfldDrl8XiqbAAAAE1BrWeQ/vM//1Pbtm1TWlpaAMoBAAANpSm/xutsx1brGaTk5GS1\natXqrDoFAAD2CQ8Pl/TDO86aqpNjOznW2qr1DNLkyZP16KOPas6cOQoNDa1TpwAAwD4hISFKSkrS\n4cOHJUnR0dEN+pTqQDLGqKSkRIcPH1ZSUpJCQmo9FySpDs9BatOmjQ4dOqTw8HClpKRUObZ37946\nFVHfeA4SAACnZ4zRkSNHdPz4cbtLCYikpCQ1b968WvDzNyPUegbp8ccfr32VAAAgqDgcDrVo0ULN\nmjVrcjdahYeH13nm6KRazyA1BswgAQCAmtTrk7Tz8/P96rSgoMCvdgAAAMHMr4CUmprq18nat29/\nVsUAAAAEA7/WIJWVlWnatGlnbOf1es+6IAAAALv5FZB69+6t3Nxcv9oBAAA0dn4FpNWrVwe4DAAA\ngOBxdvfAAQAANEEEJAAAAAsCEgAAgAUBCQAAwIKABAAAYFHrd7EVFxfr2Wef1YYNG1RUVFTl2Jo1\na+qtMAAAALvUOiD96le/0tatW3XdddcpJiYmEDUBAADYqtYB6f3339f//M//qEWLFoGoBwAAwHa1\nXoOUkJCgxMTEQNQCAAAQFGodkB5++GE9/PDDqqysDEQ9AAAAtnMYY8yZGrVp00YOh8P3+eDBgwoP\nD1dKSkqVdnv37q3/CuvA7XYrOjpaJSUlcjqddpcDAACChL8Zwa81SI8//ni9FQYAABDs/JpBamyY\nQQIAADXxNyPUeg1SXFxcjfuTkpJqeyoAAICgVOuA1AQnnAAAAKrw+zlI06ZNkyR5PB7f1yft3LlT\nqamp9VsZAACATfwOSLm5uZIkr9fr+1qSQkJCdN555+k//uM/6r86AAAAG/gdkD788ENJ0j333KMX\nX3wxYAUBAADYrc53sR04cED79u1TmzZt1Lp16/qu66xwFxsAAKhJwO5iy8vLU1ZWltq0aaM+ffqo\nbdu2uvLKK3XkyJGzKhgAACBY1Dog3XXXXQoPD9eOHTvkdrv15ZdfKioqSnfffXcg6gMAAGhwtb7E\nlpSUpN27dys+Pt63r6CgQO3atVN+fn69F1gXXGIDAAA1CdgltsTExGr7jDE8KBIAADQZtQ5Is2bN\n0i233KIdO3aopKREO3bs0O23367HH39clZWVvg0AAKCxqvUltpCQHzKVw+Hw7TPGVPksSRUVFfVQ\nXt1wiQ0AANTE34zg93OQTjr5PCQAAICmqtYBqX///oGoAwAAIGjUeg2SJK1bt0533XWXhg4dKkna\nvHmz1q5dW6+FAQAA2KXWAemNN97Q4MGDJUkfffSRJKmysrLaC2wBAAAaq1ov0k5PT9fLL7+sPn36\nKDExUfn5+SorK1ObNm2C5mnaLNIGAAA1CdhzkPbt26c+ffpI+v872SIiIuT1eutYKgAAQHCpdUBK\nS0vTli1bquzbtGmT2rdvX29FAQAA2KnWAel3v/udhg0bpgULFsjr9WrJkiUaNWqUHnjggUDUBwAA\n0OBqfZv/rbfeqsrKSv3hD3+Q1+vVtGnT9Nvf/lYjRowIRH0AAAANrtaLtBsDFmkDAICaBOxJ2rt2\n7dI///lPHTt2TCkpKRowYADrjwAAQJNSq4A0depUzZkzR5KUkpKio0ePKiQkRJMmTdLs2bMDUiAA\nAEBD83uR9n//93/r+eef15///GcVFxfr0KFD+v777/Xyyy9r3rx5WrFiRSDrBAAAaDB+r0G6/vrr\n9fOf/1z33HNPtWMvv/yy/vGPf+jtt9+u9wLrgjVIAACgJvX+oMhNmzbpl7/8ZY3HbrjhBm3atMnv\n4pYtW6bMzEzFxcXJ4XBUe8jkF198ocsuu0wxMTFq1aqVZsyYoSa4lhwAAAQpvwNSYWGhUlJSajyW\nkpKiwsJCvztNTEzUuHHjNHfu3GrHioqKlJWVpb59+yovL08rV67UK6+8UmNbAACAQPB7kXZlZeVZ\nHf+xrKwsSdLq1aurHfvb3/6miooKzZo1S2FhYUpPT9fEiRP1wgsv6P777/e7j0D6/J/7VOH1f7wA\nAKB2zmsfp1YdE23r3++AVFpaqmnTpp3yeHl5eb0UtHXrVmVkZCgs7P9L69mzp3bt2qXCwkLFxcVV\n+x6Px1PlMp3b7a6XWk5lQ/Zulbt59xwAAIHS/arUxhGQevfurdzc3NMerw+FhYVKSEiosi8xMdF3\nrKaANHv2bM2cObNe+vdHtwHnq8LDDBIAAIHSsmOCrf37HZBquhwWCHFxcdq/f3+Vffn5+b5jNZky\nZYomT57s++x2u5WcnBywGn86lAdjAgDQlNX6ZbWBdskll2jLli1VLpl99tlnat++/SkDUnh4uJxO\nZ5UNAACgrmwJSBUVFSotLfWtWyorK1NpaakqKyt1/fXXKzQ0VNOnT5fb7db27dv1zDPPaPz48XaU\nCgAAzkG2BKTXXntNTqfTdzeby+WS0+nUmjVrFBsbq5UrV2rNmjVKTk7WoEGD9Ktf/Spo7mADAABN\nn99P0m5MeJI2AACoSb0/SRsAAOBcQUACAACwICABAABYEJAAAAAsCEgAAAAWBCQAAAALAhIAAIAF\nAQkAAMCCgAQAAGBBQAIAALAgIAEAAFgQkAAAACwISAAAABYEJAAAAAsCEgAAgAUBCQAAwIKABAAA\nYEFAAgAAsCAgAQAAWBCQAAAALAhIAAAAFgQkAAAACwISAACABQEJAADAgoAEAABgQUACAACwICAB\nAABYEJAAAAAsCEgAAAAWBCQAAAALAhIAAIAFAQkAAMCCgAQAAGBBQAIAALAgIAEAAFgQkAAAACwI\nSAAAABYEJAAAAAsCEgAAgAUBCQAAwIKABAAAYEFAAgAAsCAgAQAAWBCQAAAALAhIAAAAFgQkAAAA\nizC7C2iM9v/2flW6S+wuAwCAJivuqsFKGHadbf0TkOrg+48/VmVRkd1lAADQZEV16Wpr/wSkOmj9\n3HMyFV67ywAAoMmKaJtqa/8EpDpwZfazuwQAABBALNIGAACwICABAABYEJAAAAAsCEgAAAAWBCQA\nAAALAhIAAIAFAQkAAMAiaAPSjBkzFBoaKpfL5dtGjBhhd1kAAOAcENQPiuzdu7fWrl1rdxkAAOAc\nE7QzSAAAAHYJ6oC0ZcsWNWvWTKmpqRo5cqR2795dYzuPxyO3211lAwAAqKugDUg33nijduzYoSNH\njmjdunVyOBwaNGiQiouLq7WdPXu2oqOjfVtycrINFQMAgKbCYYwxdhfhj7KyMsXHx2v58uW68sor\nqxzzeDzyer2+z263W8nJySopKZHT6WzoUgEAQJByu92Kjo4+Y0YI6kXaP+ZwOORwOFRTngsPD1d4\neLgNVQEAgKYoaC+xvfnmm8rLy5MkHT58WGPHjlWLFi3Up08fmysDAABNXdAGpCVLlqhr166Kjo7W\npZdeKo/Ho5ycHMXGxtpdGgAAaOIazRqk2vD3+iIAADi3+JsRgnYGCQAAwC4EJAAAAAsCEgAAgAUB\nCQAAwIKABAAAYEFAAgAAsCAgAQAAWBCQAAAALAhIAAAAFgQkAAAACwISAACABQEJAADAgoAEAABg\nQUACAACwICABAABYEJAAAAAsCEgAAAAWBCQAAAALAhIAAIBFmN0FNEbvfveuPJUeu8sAAKDJ6pzY\nWRelXGRb/wSkOpjz6RwVeYrsLgMAgCbrzvQ7CUiNzTXtr1FZRZndZQAA0GRdmHyhrf07jDHG1goC\nwO12Kzo6WiUlJXI6nXaXAwAAgoS/GYFF2gAAABYEJAAAAAsCEgAAgAUBCQAAwIKABAAAYEFAAgAA\nsCAgAQAAWBCQAAAALAhIAAAAFgQkAAAACwISAACABQEJAADAgoAEAABgQUACAACwICABAABYEJAA\nAAAsCEgAAAAWBCQAAAALAhIAAIAFAQkAAMCCgAQAAGBBQAIAALAgIAEAAFgQkAAAACwISAAAABYE\nJAAAAAsCEgAAgAUBCQAAwIKABAAAYEFAAgAAsAizu4BGafFQqfx7u6sAAKDpumSk1HOsbd0TkOri\nX59LZSfsrgIAgKar/eW2dk9Aqotb35FMpd1VAADQdMWeZ2v3BKS6aH2p3RUAAIAACtpF2sYYTZ8+\nXa1atVJMTIwuu+wybd++3e6yAADAOSBoA9IzzzyjhQsXauXKlcrLy1Pfvn2VlZWl4uJiu0sDAABN\nnMMYY+wuoibt2rXTb3/7W913332SJK/Xq5YtW+q5557TLbfcctrvdbvdio6OVklJiZxOZ73XdsLt\nkYLypwYAQNMQGR6iqPDQej+vvxkhKNcgnThxQnv27FGvXr18+8LCwpSRkaEtW7ZUC0gej0der9f3\n2e12B7S+fk9+oKJS75kbAgCAOhl/xQWamNXFtv6DMiAVFhZKkhISEqrsT0xM9B37sdmzZ2vmzJkN\nUZokKS4qXI4G6w0AgHNPZFj9zx7VRlAGpLi4OElSQUFBlf35+flq3bp1tfZTpkzR5MmTfZ/dbreS\nk5MDVt/HDw0I2LkBAID9gnKRdnx8vNLS0rRx40bfPq/Xq61btyojI6Na+/DwcDmdziobAABAXQVl\nQJKkcePG6ZlnntH27dvldrs1ffp0hYeHa9iwYXaXBgAAmrigvMQmSQ8++KCKioo0aNAgFRYWqkeP\nHvrHP/4hl8tld2kAAKCJC9rb/M9GoG/zBwAAjZO/GSFoL7EBAADYhYAEAABgQUACAACwICABAABY\nEJAAAAAsCEgAAAAWBCQAAAALAhIAAIAFAQkAAMCCgAQAAGARtO9iOxsn357idrttrgQAAASTk9ng\nTG9aa5IBqbS0VJKUnJxscyUAACAYlZaWKjo6+pTHm+TLaisrK1VQUKCoqCg5HI56P7/b7VZycrKO\nHTt2zr0Ml7Gfm2OXzu3xM3bGztibTv/GGJWWliohIUEhIadeadQkZ5BCQkKUlJQU8H6cTuc59x/N\nSYz93By7dG6Pn7Ez9nON3WMPVP+nmzk6iUXaAAAAFgQkAAAACwJSHYSFhWn69OkKC2uSVyhPi7Gf\nm2OXzu3xM3bGfq6xe+x29y810UXaAAAAZ4MZJAAAAAsCEgAAgAUBCQAAwIKABAAAYEFA+pHdu3dr\nxIgRatWqlVwul1q1aqWrr75aBw8etLs0WxhjNH36dLVq1UoxMTG67LLLtH37dt9xh8Mhp9Mpl8vl\n27Zt22ZjxfXnTGPPzs5W9+7dFRcXp7Zt22rOnDk2Vlu/li1bpszMTMXFxcnhcMjr9fqO7dq1S337\n9lVKSori4uJ0wQUXaNasWaqsrLSx4vpzurEvXbq0yu+6y+VSWFiYfvKTn9hYcf146KGHlJ6erri4\nOLVs2VIjRozQvn37qrQZO3asLrroIoWFhWn06NE2VRoY/ow/LS1NUVFRVf79Z2dn21Rx/fFn7OvX\nr1dmZqYSEhLUokULPfDAA/J4PGfV76ZNm3TttdcqKSlJ0dHR6tq1q5544gm/z5uWlqZXXnnlrGo4\nEwLSj1x99dWKjY3V9u3bVVxcrC1btujmm28OyOtKGoNnnnlGCxcu1MqVK5WXl6e+ffsqKytLxcXF\nvjbvvvuuiouLfVt6erqNFdef041948aNuvHGGzVt2jQVFBTo73//u55//nm98MILdpddLxITEzVu\n3DjNnTu32rFmzZpp4cKFOnz4sAoLC/X+++/rr3/9q/70pz81fKEBcLqxjxo1qsrven5+vlJSUnTL\nLbc0fKH1zOFwaNGiRcrLy9NXX30lh8OhoUOHVmnTrVs3Pffcc7r22mttqjJw/Bm/JM2bN6/K78CQ\nIUNsqLZ+nWnse/fuVVZWlkaNGqW8vDytW7dO7733niZPnlznPj/44AP169dPF154oXbs2KGCggK9\n/PLLWrRoka677rrg+QuXgTHGmLy8PCPJbNq06ZRtPvnkE9O/f3+TlJRk2rZtax599FHj8Xh8xyWZ\nZ5991vTo0cPExMSYnj17mo0bNzZE+QGRlpZm5s6d6/vs8XhMSkqKefXVV40xP4z3/ffft6u8gDrd\n2CdNmmSysrKqtJ8yZYrp0KFDQ5cZUB9++KGRVOV33GrXrl3mwgsvNOPHj2/AygLPn7G//vrrxul0\nmmPHjjVgZQ1jy5YtRpI5fvx4tWO33XabGTVqlA1VNZyaxp+ammoWLFhgY1UNwzr2+fPnm86dO1dp\ns2DBAhMTE2NKS0vr1EenTp1q/B3asWOHCQsLM6+//roxxph169aZK664wiQnJ5vExERz+eWXm5KS\nEnPVVVcZh8NhIiMjTUxMjLnwwgvrVMeZMIP0b8nJyUpPT9evf/1r/eUvf9EXX3xRJcV+/fXXGjhw\noO6++24dPnxYa9as0fLly/Xkk09WOc/8+fO1ePFiHTt2TFdffbUGDx6sEydONPRwztqJEye0Z88e\n9erVy7cvLCxMGRkZ2rJli2/f6NGjlZycrEsvvVQLFiywo9R6d6axG2NkLI8Pq6ys1LfffquioqKG\nLtcWmZmZcjqdat++vQoLCzV+/Hi7S2pw8+fP180339wg731saKtWrVJqaqoSExPtLsUWpxr/I488\noqSkJF188cV66qmnzvoyUzCyjv1Uf959//332rlzZ63Pv3PnTu3cuVNjxoypdqxr167q1auXsrOz\n9eWXX2rAgAG64YYbtHfvXh06dEjTp09XSEiI3nvvPbVt29Y3o/fll1/WaaxnFJDY1Ujl5eWZqVOn\nmp49e5rIyEiTmJhoHnjgAVNaWmruvfdeM3z48CrtlyxZYi644ALfZ0nmhRde8H2uqKgw5513nm/G\npTHZu3evkWR27NhRZf9NN91k7rjjDmOMMTk5OaakpMSUlZWZFStWmISEBDN//nw7yq1XZxp7bm6u\nCQ8PN2+99ZbxeDxm48aNpkWLFkaS2b9/v01V178zzaJ4vV7z8ccfm4cfftjk5eU1cHWBdaaxb9u2\nzUgyGzZsaODKAu/999830dHR5r333qvxeFOfQTrV+FevXm0KCwuNx+Mxubm5JjU11UyaNMmmKgOj\nprF/++23Jioqyvzxj380ZWVl5uuvvzZdu3Y1kszatWtr3cfatWtr/PP1pJtuusn8/Oc/N+PHjzfX\nXHPNKc/TEDN6zCD9SHJysh577DFt2LBBJ06c0MKFC7VgwQLNmTNH33zzjd5++20lJCT4tnvuuUeH\nDh2qco527dr5vg4JCVFqamq1BW+NQVxcnCSpoKCgyv78/HzfsYEDB8rpdCoiIkJXX3217rvvPr32\n2msNXWq9O9PY+/XrpyVLlujxxx9X8+bNNX78eN1zzz0KCQk5p/7GHRoaqj59+ighIUF33XWX3eU0\nqPnz56tHjx7q2bOn3aXUq+zsbN14441asmSJrrrqKrvLaXCnG3///v0VGxursLAw9evXTzNmzGgS\nf96ddKqxX3DBBcrOztbrr7+uli1b6vrrr9fYsWMlSSkpKbXup1mzZpKkAwcO1Hh8//79at68uXbv\n3q3OnTvXYST1h4B0CpGRkbruuus0aNAgbd68Weedd55GjhypgoIC31ZYWFhlwbIk7dmzx/d1ZWWl\n9u7dq/PPP7+Bqz978fHxSktL08aNG337vF6vtm7dqoyMjBq/JyQkpNpUbGPkz9hvuukmbd68WceP\nH9enn36qgoIC9e7dW9HR0XaVbRuPx6Ovv/7a7jIaTFFRkZYsWaJx48bZXUq9Wrp0qUaNGqU33nhD\nw4YNs7ucBlfb8TeVP++kM4994MCB+vjjj3Xs2DFt375doaGhatOmjTp16lTrvjp16qQOHTro1Vdf\nrXbs66+/1oYNG3TNNdcoLS3ttJfwQkIaIL4EdH6qETl+/LiZPHmy+fzzz01paanxer0mJyfHJCYm\nmqefftps2LDBxMbGmjfffNOUlZUZr9drvvnmmypTkZJMhw4dzI4dO0xZWZl57LHHTHJyssnPz7dv\nYGfhqaeeMm3atDHbtm0zJSUl5pFHHjGtWrUyRUVFZtOmTeazzz4zZWVlxuPxmJUrV5rExETz/PPP\n2112vTjd2CsqKsynn35qPB6P+f77783ixYtNXFxcnaabg5HX6zVut9usXLnSSDLFxcXG7XabiooK\ns2rVKvPxxx+b0tJS4/F4zAcffGCaNWtmJk6caHfZ9eJ0Yz/pT3/6k0lKSjIlJSU2Vlq//vjHP5qE\nhASzZs2aU7YpKyszbrfbjB492owYMcK43e46L9INNmca/86dO82aNWt8vwvr16837dq1M/fff38D\nV1r//Pl3/+mnn5rS0lJTVlZmli9fblJSUsyyZcvq3OeqVatMZGSkefjhh82hQ4dMeXm5yc3NNZ07\ndzZZWVnG6/Wabdu2mcjISPPiiy+akpISU15eblavXu37nevdu7d58MEH61yDPwhI/1ZcXGzuuOMO\n06lTJ+NyuUx8fLy56KKLzO9//3tTWVlpjPnhLraf//znJiUlxcTHx5uf/OQn5qWXXvKdQ/++i617\n9+4mJibG9OjRw3z66ad2DemsVVZWmqlTp5oWLVoYp9NpMjMzzRdffGGMMWb58uWmS5cuJiYmxsTH\nx5tu3bqZF1980eaK68/pxl5eXm569uxpYmNjTUxMjOnfv7/Jzc21ueL685e//MVIqrZ9+OGH5q23\n3jLp6ekmJibGxMXFma5du5pZs2ad9m6vxuR0Yz/p4osvNr/73e/sKzIAJJmwsDATExNTZfvx/zT7\n9+9f7eeSmppqX9H16Ezj//TTT023bt2My+UysbGxpkuXLmb27NmmvLzc5srPnj//7ocOHWri4+NN\ndHS06dGjh3nnnXfOut8NGzaYIUOGmISEBBMVFWU6depkZs2aZcrKynxtcnNzzWWXXWYSEhJMYmKi\nGTBggO8vJu+9957p2LGjiY+PN+np6WddT00cxjSROcIg4HA49P7772vQoEF2lwIAAM4Ca5AAAAAs\nCEgAAAAWYXYX0JRwtRIAgKaBGSQAAAALAhIAAIAFAQkAAMCCgAQAAGBBQALQJFx00UVavHix3WUA\njcpDDz2k9PR0xcXFqWXLlhoxYkS194fu3btXQ4YMUWxsrFJSUjRhwgSVl5f7jj/33HPq3r274uPj\n1bx5cw0ZMkRffvml7/iRI0d02223qV27dnK5XEpLS9PDDz+ssrKyM9bn8Xg0e/Zsde3aVdHR0UpK\nStIvfvELbdmyxe8xLlq0qE6v/CIgAQh6LpfLt0VERCg0NLTKvtzcXH355Ze67bbb7C4VaFQcDocW\nLVqkvLw8ffXVV3I4HBo6dKjveGVlpYYMGaKkpCQdOHBAmzZt0po1azRx4kRfm9LSUs2dO1eHDh3S\n//7v/6pLly4aNGiQ3G63JKm4uFidO3dWTk6OCgsLlZOToxUrVmjy5Mmnra2iokJDhw7V4sWL9dJL\nL6mgoEA7duxQ165d1adPH3300UeB+aGcFJDncwNAgEyZMsX079/f7jKAJmnLli1Gkjl+/LgxxpjV\nq1ebsLAwc/ToUV+bd955x0RHRxu3213jOfLz840ks3nz5lP284c//MF069bttLUsXbrUhIWFma++\n+qrasZEjR5rOnTv7PpeUlJgpU6aYjh07GpfLZdq1a2cWLVpk1qxZYyIjI43D4fC9RmXJkiWn7fck\nZpAANAlpaWl65ZVXJEl79uyRw+HQwoUL1a1bN8XExKhfv37av3+/5s2bp9TUVCUkJOjXv/61Kioq\nfOc4cOCARo4cqdatW6t58+YaMWKEjh49ateQgAa3atUqpaamKjExUZK0detWtW/fXikpKb42PXv2\nVElJiXbu3HnKc8TExKhTp06n7ScjI+O0tWRnZ+unP/2punTpUu3YmDFj9PXXX+vbb7+VJN15551a\ntWqV/v73v6uwsFBr165Venq6MjMz9dJLL6lVq1YqLi5WcXGxRo0adcafg8QlNgBN2LJly5STk6PD\nhw9LkgYOHKh9+/Zp586d+uyzz/TGG2/ozTfflCSVlZVp4MCBatWqlXbu3Kldu3YpLCxMI0eOtHMI\nQIPJycnRzJkz9dJLL/n2FRYWKiEhoUq7k+GpsLCw2jm++OIL3X333Zo7d65iYmJq7GfWrFnasmWL\nHn/88dPWc/ToUbVu3brGYyfXFB05ckR5eXlaunSp5s+fr65du8rhcKhVq1a69NJLT3v+MyEgAWiy\npk6dqubNm8vlcumXv/yl9u/fryeeeEKRkZHq0KGDMjMztWHDBknSihUrVFRUpKeffloxMTFyuVz6\n/e9/r5ycHO3fv9/mkQCBlZ2drRtvvFFLlizRVVdd5dsfFxengoKCKm3z8/N9x35sw4YNGjhwoB57\n7DGNHTu2xn6mTp2qP//5z1q9enWVhdM/XlP4xBNPSJKaNWumAwcO1Hiek/9NNm/eXLt375Ykde7c\nuRYjPjNeNQKgyWrZsqXv65iYGDVr1kyhoaFV9hUVFUmSvvnmGx0+fNj3t+OTIiMjtXfv3jrdBQM0\nBkuXLtW4ceP05ptvKisrq8qxSy65RLt379axY8eUnJwsSfrss88UHR1d5RLaP//5T91www2aO3eu\nxowZU60PY4wmTJiglStXKjc3V2lpaVWOFxcXV/uea665Rrfffrt27txZ7XLdq6++qk6dOqlDhw6+\ny+A7d+5U9+7dq50nJKRuc0HMIAGApPPOO0+pqakqKCiospWWlqpPnz52lwcExLx58zRhwgRlZ2dX\nC0eSlJmZqS5duuiBBx5QUVGR9u7dq2nTpumOO+5QVFSUJOntt9/WsGHD9Morr9QYjrxer0aPHq3V\nq1fXGI5OZfjw4erfv7+uvfZa5ebmyuPx6MiRI5oyZYr+67/+Sy+++KKkH2aaRowYofHjx+vrr7+W\nJB08eFCbN2+W9MN/23l5eTp27FitfjYEJACQdP3118vj8Wjq1Kk6ceKEpB/WN7zxxhs2VwYEzr33\n3qvi4mINHjy42qMzpB9mX959910dPXpULVu2VEZGhvr166enn37ad47f/e53+v777zVmzJgq51i6\ndKkk6eOPP9Zf//pXfffdd+rYsWOVNqcTGhqq7OxsjRo1SmPHjlVcXJw6d+6sL774Qrm5uRowYICv\n7YIFC9S/f3/fOPr27et7FtOAAQP0i1/8Qp06dVJCQoL++te/+vWz4RIbAEiKjY3V+vXr9cgjjyg9\nPV0FBQVq3ry5srKydPPNN9tdHhAQxpgztklNTdWKFStOefzkGqBT6d+/v1/91CQyMlJTp07V1KlT\nT9suJiZGTz75pJ588slqx8LCwur0Fx2HqWvVAAAATRSX2AAAACwISAAAABYEJAAAAAsCEgAAgAUB\nCQAAwIKABAAAYEFAAgAAsCAgAQAAWBCQAAAALAhIAAAAFgQkAAAAi/8Dsm021zA05cwAAAAASUVO\nRK5CYII=\n"
          }
        }
      ],
      "source": [
        "fino.DEPH.plot.line(x=\"TIME\")"
      ],
      "id": "718f629e"
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": 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4gdzcXKjVanh4PMjv4uLiMH36dFy8eBHBwcEYO3YsJk823YE6OTkZkZGR8PX1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\nAAAASUVORK5CYII=\n"
          }
        }
      ],
      "source": [
        "fino['TEMP'].plot.line(\"-^\",x='TIME')"
      ],
      "id": "18ce2ab2"
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": 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2e/fuxYQJE1BWVgaGYTBjxgyEhYWJ2ocYFDwRQgghxK099thjKC0tRXFxMTZt2oRWrVrZ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BF0HGO8vLwwe/ZszJ492+x2vr6++Oyzz/DZZ581eszDw8OiiyCGtbTVhBBCCCHNEA3bEUIIIYSI\nQMETIYQQQogIFDwRQgghhIhAwRMhhBBCiAgUPBFCCCGEiEDBEyGEEEKICBQ8EUIIIYSIQMETIYQQ\nQogIFDwRQgghhIhAwRMhhBBCiAgUPBFCCCGEiPD/D6s5QhslwXcAAAAASUVORK5CYII=\n"
          }
        }
      ],
      "source": [
        "fino['VHM0'].plot.line(\"-^\",x='TIME')"
      ],
      "id": "a6b2f71d"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Wave data are only available at the surface."
      ],
      "id": "6c6ee29f-7edb-4080-98ba-763343f88447"
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
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              "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 104kB\n",
              "Dimensions:  (TIME: 2879)\n",
              "Coordinates:\n",
              "  * TIME     (TIME) datetime64[ns] 23kB 2022-09-01 ... 2022-09-30T23:31:59.99...\n",
              "    DEPH     (TIME) float32 12kB ...\n",
              "Data variables:\n",
              "    VHM0     (TIME) float64 23kB ...\n",
              "    VTZA     (TIME) float64 23kB ...\n",
              "    VPED     (TIME) float64 23kB ...\n",
              "Attributes: (12/46)\n",
              "    platform_code:                  FINO1\n",
              "    platform_name:                  \n",
              "    data_mode:                      M\n",
              "    title:                          NWS - NRT in situ Observations\n",
              "    summary:                        Oceanographic data from North West Shelf\n",
              "    naming_authority:               Copernicus Marine In Situ\n",
              "    ...                             ...\n",
              "    doi:                            \n",
              "    pi_name:                        \n",
              "    qc_manual:                      OceanSITES User&#x27;s Manual v1.2\n",
              "    date_update:                    2022-10-07T05:39:40Z\n",
              "    history:                        2022-10-01T18:04:25Z : Creation; 2022-10-...\n",
              "    wmo_inst_type:                  </pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-148de8a2-9554-4009-9565-f60cfac880d1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-148de8a2-9554-4009-9565-f60cfac880d1' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>TIME</span>: 2879</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-808217e9-e9d5-4240-965f-afa7d6f96ecb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-808217e9-e9d5-4240-965f-afa7d6f96ecb' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>TIME</span></div><div class='xr-var-dims'>(TIME)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-09-01 ... 2022-09-30T23:31:...</div><input id='attrs-6d00a63d-3d42-4eaa-bb9a-0d36e2e5b59b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d00a63d-3d42-4eaa-bb9a-0d36e2e5b59b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-032d0f84-548d-46f8-b265-e6a3ccae9c50' class='xr-var-data-in' type='checkbox'><label for='data-032d0f84-548d-46f8-b265-e6a3ccae9c50' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>valid_min :</span></dt><dd>-90000.0</dd><dt><span>valid_max :</span></dt><dd>90000.0</dd><dt><span>uncertainty :</span></dt><dd> </dd><dt><span>comment :</span></dt><dd> </dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>ancillary_variables :</span></dt><dd>TIME_QC</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2022-09-01T00:00:00.000000000&#x27;, &#x27;2022-09-01T00:02:00.000000000&#x27;,\n",
              "       &#x27;2022-09-01T00:30:00.000000000&#x27;, ..., &#x27;2022-09-30T23:02:00.000000000&#x27;,\n",
              "       &#x27;2022-09-30T23:30:00.000000000&#x27;, &#x27;2022-09-30T23:31:59.999999744&#x27;],\n",
              "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DEPH</span></div><div class='xr-var-dims'>(TIME)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8c604faf-81a7-4410-a925-e9abb203fa89' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c604faf-81a7-4410-a925-e9abb203fa89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-935ad424-39d2-4a93-ad67-c63c422b90f5' class='xr-var-data-in' type='checkbox'><label for='data-935ad424-39d2-4a93-ad67-c63c422b90f5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Depth</dd><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>valid_min :</span></dt><dd>-12000.0</dd><dt><span>valid_max :</span></dt><dd>12000.0</dd><dt><span>uncertainty :</span></dt><dd></dd><dt><span>comment :</span></dt><dd></dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>reference :</span></dt><dd>sea_level</dd><dt><span>data_mode :</span></dt><dd>R</dd><dt><span>ancillary_variables :</span></dt><dd>DEPH_QC</dd></dl></div><div class='xr-var-data'><pre>[2879 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c654912c-92c3-4965-866c-a2e914e3fcb3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c654912c-92c3-4965-866c-a2e914e3fcb3' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>VHM0</span></div><div class='xr-var-dims'>(TIME)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-44786883-f898-4beb-8528-cc6eaa024aff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-44786883-f898-4beb-8528-cc6eaa024aff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88bc6325-8459-4e71-bf58-bedc87e66395' class='xr-var-data-in' type='checkbox'><label for='data-88bc6325-8459-4e71-bf58-bedc87e66395' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_wave_significant_height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Spectral significant wave height (Hm0)</dd><dt><span>valid_min :</span></dt><dd>1</dd><dt><span>valid_max :</span></dt><dd>25000</dd><dt><span>comment :</span></dt><dd> </dd><dt><span>uncertainty :</span></dt><dd> </dd><dt><span>accuracy :</span></dt><dd> </dd><dt><span>precision :</span></dt><dd> </dd><dt><span>resolution :</span></dt><dd> </dd><dt><span>cell_methods :</span></dt><dd> </dd><dt><span>type_of_analysis :</span></dt><dd>spectral analysis</dd><dt><span>sensor_depth :</span></dt><dd>0.0</dd><dt><span>sensor_mount :</span></dt><dd> </dd><dt><span>sensor_orientation :</span></dt><dd> </dd><dt><span>data_mode :</span></dt><dd>M</dd><dt><span>ancillary_variables :</span></dt><dd>VHM0_QC VHM0_DM</dd></dl></div><div class='xr-var-data'><pre>[2879 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VTZA</span></div><div class='xr-var-dims'>(TIME)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3c7beb1d-a518-4374-951d-7d5ef65d12ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c7beb1d-a518-4374-951d-7d5ef65d12ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b083320-8bc3-4adf-ac20-2e532c0ca41e' class='xr-var-data-in' type='checkbox'><label for='data-1b083320-8bc3-4adf-ac20-2e532c0ca41e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_wave_mean_period</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>long_name :</span></dt><dd>Average zero crossing wave period (Tz)</dd><dt><span>valid_min :</span></dt><dd>2000</dd><dt><span>valid_max :</span></dt><dd>25000</dd><dt><span>comment :</span></dt><dd> </dd><dt><span>uncertainty :</span></dt><dd> </dd><dt><span>accuracy :</span></dt><dd> </dd><dt><span>precision :</span></dt><dd> </dd><dt><span>resolution :</span></dt><dd> </dd><dt><span>cell_methods :</span></dt><dd> </dd><dt><span>type_of_analysis :</span></dt><dd>zero crossing</dd><dt><span>sensor_depth :</span></dt><dd>0.0</dd><dt><span>sensor_mount :</span></dt><dd> </dd><dt><span>sensor_orientation :</span></dt><dd> </dd><dt><span>data_mode :</span></dt><dd>R</dd><dt><span>ancillary_variables :</span></dt><dd>VTZA_QC</dd></dl></div><div class='xr-var-data'><pre>[2879 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>VPED</span></div><div class='xr-var-dims'>(TIME)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-16bdfa61-1802-43f1-b1ec-60d49a645fb9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-16bdfa61-1802-43f1-b1ec-60d49a645fb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93b63573-5eb9-4d17-945a-cd737931667b' class='xr-var-data-in' type='checkbox'><label for='data-93b63573-5eb9-4d17-945a-cd737931667b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>sea_surface_wave_from_direction_at_variance_spectral_density_maximum</dd><dt><span>units :</span></dt><dd>degree</dd><dt><span>long_name :</span></dt><dd>Wave principal direction at spectral peak</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>360000</dd><dt><span>comment :</span></dt><dd> </dd><dt><span>uncertainty :</span></dt><dd> </dd><dt><span>accuracy :</span></dt><dd> </dd><dt><span>precision :</span></dt><dd> </dd><dt><span>resolution :</span></dt><dd> </dd><dt><span>cell_methods :</span></dt><dd> </dd><dt><span>type_of_analysis :</span></dt><dd>spectral analysis</dd><dt><span>sensor_depth :</span></dt><dd>0.0</dd><dt><span>sensor_mount :</span></dt><dd> </dd><dt><span>sensor_orientation :</span></dt><dd> </dd><dt><span>data_mode :</span></dt><dd>M</dd><dt><span>ancillary_variables :</span></dt><dd>VPED_QC VPED_DM</dd></dl></div><div class='xr-var-data'><pre>[2879 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0dd0fd52-cb04-40b0-ac4a-27ef8e1db82d' class='xr-section-summary-in' type='checkbox'  ><label for='section-0dd0fd52-cb04-40b0-ac4a-27ef8e1db82d' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>TIME</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-34bd5b00-be2b-4966-8c36-935f2b40f848' class='xr-index-data-in' type='checkbox'/><label for='index-34bd5b00-be2b-4966-8c36-935f2b40f848' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([          &#x27;2022-09-01 00:00:00&#x27;,\n",
              "                         &#x27;2022-09-01 00:02:00&#x27;,\n",
              "                         &#x27;2022-09-01 00:30:00&#x27;,\n",
              "                         &#x27;2022-09-01 00:32:00&#x27;,\n",
              "                         &#x27;2022-09-01 01:00:00&#x27;,\n",
              "               &#x27;2022-09-01 01:01:59.999999744&#x27;,\n",
              "                         &#x27;2022-09-01 01:30:00&#x27;,\n",
              "                         &#x27;2022-09-01 01:32:00&#x27;,\n",
              "                         &#x27;2022-09-01 02:00:00&#x27;,\n",
              "                         &#x27;2022-09-01 02:02:00&#x27;,\n",
              "               ...\n",
              "                         &#x27;2022-09-30 21:30:00&#x27;,\n",
              "                         &#x27;2022-09-30 21:32:00&#x27;,\n",
              "                         &#x27;2022-09-30 22:00:00&#x27;,\n",
              "               &#x27;2022-09-30 22:01:59.999999744&#x27;,\n",
              "                         &#x27;2022-09-30 22:30:00&#x27;,\n",
              "                         &#x27;2022-09-30 22:32:00&#x27;,\n",
              "                         &#x27;2022-09-30 23:00:00&#x27;,\n",
              "                         &#x27;2022-09-30 23:02:00&#x27;,\n",
              "                         &#x27;2022-09-30 23:30:00&#x27;,\n",
              "               &#x27;2022-09-30 23:31:59.999999744&#x27;],\n",
              "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;TIME&#x27;, length=2879, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cb4f57c4-1ba8-4475-a42c-66adb5fd26e0' class='xr-section-summary-in' type='checkbox'  ><label for='section-cb4f57c4-1ba8-4475-a42c-66adb5fd26e0' class='xr-section-summary' >Attributes: <span>(46)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>platform_code :</span></dt><dd>FINO1</dd><dt><span>platform_name :</span></dt><dd></dd><dt><span>data_mode :</span></dt><dd>M</dd><dt><span>title :</span></dt><dd>NWS - NRT in situ Observations</dd><dt><span>summary :</span></dt><dd>Oceanographic data from North West Shelf</dd><dt><span>naming_authority :</span></dt><dd>Copernicus Marine In Situ</dd><dt><span>id :</span></dt><dd>NO_TS_MO_FINO1_202209</dd><dt><span>wmo_platform_code :</span></dt><dd>6201065</dd><dt><span>ices_platform_code :</span></dt><dd></dd><dt><span>source :</span></dt><dd>mooring</dd><dt><span>source_platform_category_code :</span></dt><dd>48</dd><dt><span>institution_edmo_code :</span></dt><dd>3356</dd><dt><span>institution :</span></dt><dd>R and D centre Kiel University of Applied Sciences</dd><dt><span>institution_references :</span></dt><dd>www.fh-kiel-gmbh.de/en/</dd><dt><span>site_code :</span></dt><dd></dd><dt><span>comment :</span></dt><dd></dd><dt><span>contact :</span></dt><dd>cmems-service@bsh.de</dd><dt><span>area :</span></dt><dd>North Atlantic Ocean</dd><dt><span>geospatial_lat_min :</span></dt><dd>54.00000</dd><dt><span>geospatial_lat_max :</span></dt><dd>54.00000</dd><dt><span>geospatial_lon_min :</span></dt><dd>6.58333</dd><dt><span>geospatial_lon_max :</span></dt><dd>6.58333</dd><dt><span>last_date_observation :</span></dt><dd>2022-09-30T23:32:00Z</dd><dt><span>last_latitude_observation :</span></dt><dd>54.00000</dd><dt><span>last_longitude_observation :</span></dt><dd>6.58333</dd><dt><span>geospatial_vertical_min :</span></dt><dd>0.00000</dd><dt><span>geospatial_vertical_max :</span></dt><dd>25.00000</dd><dt><span>time_coverage_start :</span></dt><dd>2022-09-01T00:00:00Z</dd><dt><span>time_coverage_end :</span></dt><dd>2022-09-30T23:32:00Z</dd><dt><span>cdm_data_type :</span></dt><dd>timeSeries</dd><dt><span>data_type :</span></dt><dd>OceanSITES time-series data</dd><dt><span>bottom_depth :</span></dt><dd></dd><dt><span>format_version :</span></dt><dd>1.4</dd><dt><span>Conventions :</span></dt><dd>CF-1.6 Copernicus-InSituTAC-FormatManual-1.42 Copernicus-InSituTAC-SRD-1.5 Copernicus-InSituTAC-ParametersList-3.2.1</dd><dt><span>netcdf_version :</span></dt><dd>netCDF-4 classic model</dd><dt><span>references :</span></dt><dd>http://marine.copernicus.eu http://www.marineinsitu.eu</dd><dt><span>data_assembly_center :</span></dt><dd>BSH</dd><dt><span>update_interval :</span></dt><dd>PT1H</dd><dt><span>citation :</span></dt><dd>These data were collected and made freely available by the Copernicus project and the programs that contribute to it</dd><dt><span>distribution_statement :</span></dt><dd>These data follow Copernicus standards; they are public and free of charge. User assumes all risk for use of data. User must display citation in any publication or product using data. User must contact PI prior to any commercial use of data.</dd><dt><span>doi :</span></dt><dd></dd><dt><span>pi_name :</span></dt><dd></dd><dt><span>qc_manual :</span></dt><dd>OceanSITES User&#x27;s Manual v1.2</dd><dt><span>date_update :</span></dt><dd>2022-10-07T05:39:40Z</dd><dt><span>history :</span></dt><dd>2022-10-01T18:04:25Z : Creation; 2022-10-07T05:39:40Z, BSH North West Shelf PU: Monthly subset 202209 extracted from history file NO_TS_MO_FINO1.nc</dd><dt><span>wmo_inst_type :</span></dt><dd></dd></dl></div></li></ul></div></div>"
            ]
          }
        }
      ],
      "source": [
        "fino[['VHM0','VTZA','VPED']].isel(DEPTH=0)"
      ],
      "id": "d8145152"
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {},
      "outputs": [],
      "source": [
        "df = fino[['VHM0','VTZA','VPED']].isel(DEPTH=0).to_dataframe()"
      ],
      "id": "e09c1eff"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "The data are stored on the concurrent timesteps."
      ],
      "id": "4195fec4-ce82-4576-8cbc-ec76fb4d8695"
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "\n",
              "</div>"
            ]
          }
        }
      ],
      "source": [
        "df[['VHM0','VTZA','VPED']].head()"
      ],
      "id": "eac76c86"
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": 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Tbm5umD17ttmv/etf/4rNmzfj0KFDiv373n33XQwZMgQ7d+7UWf/ZZ59h2bJl+Nvf/oag\nIDFTEfQwagqpnYoc2c9Kz/O3Ss93rqCljUP4gh4Mi3yc224YSh7zJOXbMbkBQacQhpO1YS7QLro4\nFy9ejN/85jd47rnnLCr1X7ZsGXr16qXTuobn8uXL+Oqrr/DRRx8ZeJsee+wx/OUvf8GHH35oss2N\nQOCUqKsomba5Dqgu1N322VzZlwAAzmwBerkBseOAmkvS+rQ5lPuUvYxCf2IAE1gTXqOJaTMBQNAg\nQHWOQsaeAfY7v26G0HHSILSGbIf4bgVOh6l+X51BeJoE1saS61Vcf4p0y151AoFA0CWwpHDmcdql\nCbUNnQv83Aac/lJ3/7B0arcSMx6ouQgEJQGXf5C2h6QCFaeBu1YDqTO76lMIegosTHd5H7BDEy6O\nv4Ouu5y3SbeJSRAIT2enEYaTQCAQ6MMXfFTmS4bTlRyg9rLh/uXHaVmWC9xsBG5c1d1ecZqW9SUd\nTwjvgnZOAieEhekA4OdWaf3IR2iZ8zZds6IYwWoIw0kgEAjkYANSDZfjJGc0AYB3KKC+RkaTEgOn\nkhJ5R2Ed7YUWlIBHqZ8in4uX+yEZUuZeN8JIN4pQDhcIBAI5jqyjnl/GksEZ6mum92lrIuPHBt0E\nBAJFQlJ1/1ZXUU6UsWuQGenMkyXQQXic9OhBufJdhvhOBU6JnLBt1hLKcfrpPcuPV/i91HzV3ARd\nPgzDt3NiiPCLYOxSIP1Ben5hN4WVs5cBYWm0Tl0FbF0qXTc1hcJz2UmE4aShd+/eAEhNu2/fvnY+\nm+5FYyOFL1xdXe18JgKBBbBB5cg6ShQH5EMi5jLmSSB6NNDXj5LHzcEO7ZwETgafj8fCyqoC49eN\nHMJINxshR6Chvb0dJSUlaGtrQ3h4OHr1ElHMztLe3o7GxkZUVFQgICAAISEh9j4lgcAyKvPJSzR4\nJnBmMzBlNeDWj3JGynKBIXOAU58DIx8z3wuVsQC4/XnzBiH9wUyunZMYzASMogPAx1OBORuBwHha\nx66bSStpXU0hCbIm3wOMelTSFDPV764HGOlCjsBCXFxcEBYWhsuXL6OoqMjep9OtCAgIQP/+/e19\nGgKBaZSSYs9sJoNn8Exa7+FLuU8JtwMBcUBsNlByWKquM0buh4BXsHmDkJ3aOQmclKAkMnCiRhpe\nN6wylJH/DT0Aeo0deq46K8Jw4nB1dUViYiLa2tpEXo6VcHV1Fd47gdNQq7oK/72vot4vGb4RA3VD\nFQMmyCfLDr6XZvHMaOoXTnIEwx4ETnyqu+89a4CIdDEICWyDtxGD/IGNQEC8ZBQxBkwEUmYII90C\nhOGkh4uLi2zDW4FA0P2pb2qDPwDfb35luJFV12UsAAbfB8SMBUqPSo18GUzDSd9oAgBXTf4kM8As\nCbN1cTsnQTeh3YWuVXd/+ruPXveGi7uB1FmAV6AI+5qJcAUIBIKejbqKZuGV+XCrKQAANESOV94/\n90OgaC8w+5+kAv7ARsof4ZmyGhg4zfC1m35NOVPvjqaQoEBgTeSkBpqqgeIDwIn1yvIaWx4H/vMk\nUHGO/mZGeruLaemCHojwOAkEgh5N44H34JnzGgAgXLPOq3Sf/M4s3GEqmXbHs+SZylgABA0EvtW0\nwehMzogQwBSYQu4aaa6jZdw4miAo5eGd3w5cLwce/FIK+VXmi2tOBuFxEggEPZpPbk7CpJbVmNSy\nGr9tfRIAsLLtQSxsfRrv3ZTxGrFKtsyFwOJDwMPbDT1O2cuAiAzKi+JDI+x5Z6rhfvpAeAAExmms\n0XpRUa2RKGioBsb/AYg14k0tP05K5AKjCDkCgUDQo1GpW1DTQD2+rl44htt3/9L4CzIWUPsKZvxY\n0pme0VEBTJbUy3u+hCegZyN3jSTeBVz4tmPHCx4E3Pm/QGBcj5PAMNdGEIaTQCAQaCjKz0Xs5xNQ\ndteHiFAdpHwmJZjxU3EO2PcXkiyYvJI0cqa/SYNLfanUrV5fN8ecwceUUdYDtHUEJuiI4d4vArhR\n1rH368bXnNBxEggEAgv5uW8g3rg5E3eHjABSsync9s3jNFjsfVU+R8mlXdJ5Ch9O66JH0X68nMGo\nR4HL+yxrnJq5kFTLm+so5MK0eOLvANLuB/xiyOPQTT0AAjOQ019ihjsAlOdJhtWAiVRFp2Q0MaFX\nJpsh9JxkEYaTQCAQaPANDkd79vPwDQ4HvN1J6BIgLxFgXNdm5CPSc9b6gjecrhyiAcwvBqgrNs+A\n8g6WT0Iv/J4eQLf2AAjMgOkvqauAoh9pHTPcAaC5Xto3IoMMJ4BaAB18S9rmH0eFDIAkm8Fy8oSe\nkw5OZTgNHjwYxcXF2r9v3bqFpqYmbN68GTNmzLDjmQkEgu5AkLc7fjdJ00dOXQXkb6Xnbv10d1Tq\n6+UdAoSly5d8f/cnWp7+Cri0G2ioAjIXAWe/Nm5EMY9CTaHucfk8J4GgUaUbWmbXKLuGAV0DnBlN\nHoEkWVB7Gdj7Cq0z1deuh+NUVXVnzpyBWq3WPl599VUEBgZiypQp9j41gUDQXWC6TqU/ASc30rqf\nWykU11gjtWVhekxskNn0a+oTVn6c9l18iEImAFXdjVlCzxuraZn7IXD1GA1mcorkDO9gMo76+gEJ\nE6X1N1s0x1OJKjuBRMYCSS7j3dHA+W3y+0WOpOXoxUDsOHo+hqpKcd8/qN9d/1QgZRZw/FP5a0xO\nN6oH4FQeJ33WrFmDBQsWoG/fvvY+FYFA0B1QVwFf/ooEA3m2LqVl7ofm9/XyDgYOaGb1fJ8wXkeH\nGWaNNcbPSy5cx3sFRLiuZyLn+Yy9jdbFjaeHZwDw7fNSaJdR+hMtv38Z6BdGz29U0LKhCmgHUHka\nGPEQFTikP2joFe2h2mJOazh99913KCgowGOPPaa4T1tbG27evKn9u6mpqStOTSAQWIpSc92uRlVA\nRlPCRCAyQzJWJq+ksFhfP2qkaq2+XkX7abnvr7SUq7hTV9EAGJYGXNwjhWOyl9E6dk6Cnocpgzpj\nAbVTCYg3NJy8QwH1NXp+o5yWpz6n5Y5ngaBBtjnnboDTGk7vvvsu7rrrLsTFxSnus2rVKrz00ktd\neFYCgaBDOMrM9fRXtLy0mx6MnRqPUfYyIHas+ccbo/FUeYcCB15X3s9YsreSQjlbZ+k5CboPxjyf\nP31ARraSpAYzmmLHSQZ88i8BdSUZ4uoqQHUOOKcJ9R1ZB8RP0C2Y4PP7GN1Y54nhlIbT1atX8c03\n32DLli1G91u+fDmee+457d9NTU0IDAy08dkJBAKngg93hKZJ6/Wrjh7YKOWF8BhrvhsyCPCLNq2z\nM3klSRkwjxNPygxav+NZoP9goPIMrb/tafKK+SeY/oyC7okxz+ftGuPbmBZZ7DiqpGOG07VTlCRe\nckja5/JeWh5Zp9xfsYeFjZ3ScFq7di2ioqJMJoW7urrC1dW1i85KIBBYhFJlGqOrZq5KHh1mNPnH\n0WASEC9/Pqyvlz7qKgr9+ccAWUuAnLcN9xn7O+DA30hfRynMd/Zr6fyY0QQAP2o8WBkLaJDs5rN8\ngQlYnhxbegfTdTHyEfKYXtxt+Jqi/ZLRBNB1zki6Cyjg1MeHPQgMnK7rcbqwm/L3Jq0EEjWFCz2g\nytPpDKebN2/igw8+wJNPPolevZyqKFAgEPA4SsJz5kJKhlWambPBxFKjzlgTYMa1U8rbmGEZNx4o\nOWyYo8LI/RDwUjDeBAIAiB4jbziNfJTEVfM+pwTx254C4KLxbqboGk7BydSGBZCuf6ZXFhjfo3Se\nnK7lyldffYUHH3wQpaWlCAqyzLIVLVcEAgdCrsdWR9qSWPNc9LWSlDDHqGMeJ33VbwBIvR84/QVw\nz3tAXZF8UrypVhrxd1DT1q7+rgSOSWU+yQ8sPkRGjLoK+OEV46G6jsL6NV7cTd6sySvJawo49bXY\nbVuuzJo1C7NmzbL3aQgEgs4il5+R/w0ZJF09e5U7lztfAK5fpbynrUstbzvBKzrr46LxljdpPErM\ngOTPwZQnrPB7IGqU8DT1ZIyFu1lyuLUJSzdMOt+5QreAoptfk05nOAkEgm6IKR2jrsIzCBg4FTi/\nnf7O/ZCSwoGOt52QC9md+oyWOzkvlP6Aw+eo8J6w+DvIaFJKVhf0HMyRIxj5iOTRBYCRjwGq83QN\n3fcP4GYzsOVx4K7VQPx4ErvMeRsYNhe49TOF8QBgymrANxJw9we8/Ok3e/h9muz0sF52wnASCAT2\ng82Ya6VWSnZJENevrDu/XWpVUV/auWOzRr0/raN8qfLjUnWcfjUd07NKmSG1YtE31sb/AQhJBYpz\nhOHU0zFXiJUnfjyQ8TCF9fhrq+QQEJpKavYAcGKj7ut2PEtLZuBX5pPRBPS4XnbCcBIIBPbDURLE\n5c6DKXzveJbCE6zdSkcMOc8AYORCSeiSVccFxEuCmnxOSliapGsFUNglJBWoOE1/tzXSfnJqzoKe\ngykhVtY+iCVxs3WMxhq6/sLSgTOb6SGHXyxw77vychk9EGE4CQQC+8ArYvPJ0/oq3V1Bygw6j9yP\n5KuPyo9TH7qOGHLGqus+mysdU79JK4Nfn7GAluxvRwlxCuwDr7ivL0cAyF97rH0QAJzfQeKpv1hF\n1/cDG4HyPOk1d/6RmlP/4s+0H/PMNqokz3DyPfSelflOnRhuCcJwEggE9kHJoOioSndn4LWS5Bg8\nkwanjhhyLFRXcVoKdwCUq5R2P/UE+/pxIGyotO2yRlvn4m7qXs8YMIGq9Bhlx8gLAPSYQUuggfdQ\nMs+kPnKhPFa5yqjMB1QX6Hl1IXkztWiK7s9tBaJGyv9m87+RQnY9IDEccEI5gs4g5AgEAgdCSQJg\nympNc9IuzG8q+Ylm1lXnlPfryKDAPqOtKpx4esigJdDA5AcA4OHtZEDzcgTG9l98CDizxbTOGM/D\n22nioC8hYiqnyonotnIEAoGgmyCXnwFQLk9XJpqaEqocOBWY8MeO5XaYOnbQIOoH1lkGz6Rwo6D7\nw4zxwn3SuvM7gH4h9PzKYWm9MUOG90ZdOawbwpPj9FfA9Net09zayRGGk0Ag6HqYOGRdMVBxVnfb\n6c1UZecfIyVO25LMhZTf9NlcYMwS4KBea5S47M4dWz9UwuQEAKl9RWc5s5m+qxDhcerWKIla8u18\neAMoe5km/0lFeUjJ91BYrTJf10sUPYqeJ0wEorOA71+mv4fMIYPs4FuAf7yU1+QZJJ9T1UMQoTqB\nQND1mFLFZtgy/CSnXG7Lc2Ghkgc2mqdOLseU1YBbP+Cbx6VzYoaZk4dJBGZgzu9m0iogcQI99wwy\n7fVk1xAL45lD9jIKp388lUJ4XZWLaGNEqE4gEDguLGGaeZz4GfOwB4GY2ySPk60wp5ccoFvl11E5\nAkCamdeVADFjgeIDlh9jx7PkFWD4xfS4MEmPJjYbKMuVr/xk1BYC/Z+Q/jZH6wkAhs4FTmq0m8LS\nJTmOMU+Sx2n6m5JnyjNImnSw4oQehDCcBAJB16NtR5IE9PXVNZyuXyWjydY3ZLkBRQ5j6t6WcH4H\nLb99rmOvZ1zSVNo1VVsv1CdwDn5YadrgTtVrSWZM64n3uiZOkgyn5OmS4RQ9mgynoERSFR84hdbr\nt3gBeozXUxhOAoHAfsh5fQq/l3KAbBmqYzf4RhXQx11an7GA2lCc+JT+tpau1NilknBlRwgaSInq\nPmFAYy2w9xVg5wtUMR4Y32MGrR7N1NeB2kv0/Mw3wKnPpW23/R5orrfsGlXyun73svS8PI+W+18n\noz1HLwfQHoK1dkbkOAkEAvvBksSPbwBulEsG0wMbyVixtTFgbq4VYJ1Bgc3w965WVmnuKOz8eFFE\nYUh1T9RVwNF/SkncgHn5bvrXhlKyuTFY70aWp8d0oZiquBNfc+baCMJwEggE9kVOz6mrtGG0Ssg1\nwPerKAyStYQqiViIztpGnLoK2PVHKSxiCfesASLSdUOLd7wAJE+Tzo8loSvp+QicG3UV8OWvjIfs\nLDHy2W/g8j5JoHXSSsAF9BvIXkZGEdt23z/IQ8sXOHSTa00khwsEAufAEfrVeQZQ7kbxATKaAuJp\n/dC51EjXmoZbo4qMppjxQPE+0/vzHP0IuH4X0NYgrasuAGqSyfD0T6ABT9B9aVTRdTr2aeDM10Dd\nZVqffA/QqzflKoUNN/94LAfq6nFpXeJEqZjB2G+TsXc1MP45IGSQZZ/FSRGGk0AgsC8sSbuxBjj8\nPunMyFX9mIOlYSo5o41PBnf1sK7RpK6SGq6GD7XccCo9Qg+evM/pAVA11Ngn6XkPTNrtURx4Xfdv\n1vbkzGbymv5ipelj8MnhtcXS+ppC4NQm88/lzGbKC2RCsd38WhOhOoFA4Dh0Nsxk6evZwFF2XNJG\nmv4mVRCd/grIXGSdWbS1Wq9kLAB6aea7578F6ouBqCygJMf463pI0m63hTdwzFH5NtdwMpXjF5ZO\nDYCvHpMmFFGjgZJDyq9x4mtNhOoEAoFzYKrDuy2RC1MEJZKgnzVF/czVjFLitqeBH18H2poMc6N4\noyljARB7m7JWj8A5seT6ib+Dws6V+aa9PykzSDUfoMbSh9cAox4H4sZRhZ67H4WxefeKMaNp8EzS\nZ+uM3pkTIAwngUBgXxpVNCgMvhdoqqN1bGlO6E1fAZxfAsYrjNjr+LYvFaetXyHEhyMv76PPGz0W\nuMIl+CbdBRR8K//6H7mwzOJDdJzjG8iICkgAai6RbEL4cKC5jvbrgT3Eui1MMLa5juQBmBHF/vc8\nlsh5nP3a0CA7vIYeHeHMZstChU6KMJwEAoH9UFdR+IrhorfkjSolI6ajyeUH3jTUpAGk6iFr3vyZ\nZ4sPjVzRq4pSMpoS7wKGPwRc2kOhw/6D6DjM88QGTj43S9C98A6Wv171jSbAMk8jLwJ7cTddQ5NX\nAgO45HDPACk8OGklhe1MSWm0NZr8SM6MMJwEAkHXU3EOOLIWiMiQcn4u7AYaKuh5zt9JcJJ5T4xh\nbksJfUyFA6+XWT/kwDcUzlhgXr6TbwTJDSRPkz8OT8JEEikcOleE53oqlngaeVVx9nuoOAukPSB/\njMB4YJcZBrqrp3nv76QIw0kgEHQ9R9aS0cAbDvwNufgANRBlGAu9GWspYRQTdTFnNpMKszUTXb2D\nSd6ANUnN/ZDUwM9vpwa+clo5+i00WIixrx/ls7CwDEBGEwCkz+vWOSY9krFLgfQHycDZ/SJQ+hPl\nFAF0nTJPJqvatDTUzFocndxIlZn8a7VGFfc7zF5G4rUA/VYiRwITX5TC3N0YYTgJBIKuRV0FRGo8\nTcPmAifMEIK0ha5T+jwaJKasBspPWr/FihLewXT+zBhMn0eGk2+ktE//ZBp8spcZnoNSiJFn94vA\n2KdEK5buBD9BGHIfGU5yITPmhbT0d+IZJO8FVVdRPh2gq1SuHx4v/YmMph6QVycMJ4FA0DXIleSb\nMpqGPUgGTeJdNAs2NZtlxobSPnxCuFoTFvQKBvzjpX0GTOyamz87V/8EackPXMzA6gilPwGfd3AA\nFTgm/LXLPEAZC4ABE6SE8elvAtGjaJu5Xh/+uLG30fXHe3iPf2pc5Z55THsQQsdJIBB0DZb0hZPD\nGm0dzDkHe7aPkOslpl9VyPr71RUD+/8PqL6ofLzYccCU13qMonO3xpxr94GNwKBpxvex9LgZCygX\n8fRXUiiYMfIxIHQYcGGHvHCtk3k6Ra86GYThJBDYkY6IQPIemDkbdROkO3MOgJRIPmkl5VcNnAr0\nCwduX+Y4N3wlQU9LjNCMBcDtzzvOZxJ0DLlrlxkqrM9cRwwnY8cFOi7a6oSeTiGAKRAIHAuWo3H7\n8xRe+GwuMOZJ4OBbtH3wTMOcDf6GnfN3ytkBjM9mjWk/ySWSewXSMusJ64pe2hJWSXjyC8PWG/rk\nfkjCmWOWkm6Pue1oBI6F3LXbx52WvTVLdZUUZjPX42OsuEJdRdeOuXQkVOiEOKXhlJOTg+XLl+PI\nkSPo3bs3UlJS8OOPP6JXr172PjWBQGCKhmrguz/Tc3dfaX1cNiW91pdK1WU8Vw6Q9wUwPptV0n5S\nV1FiNQAMmwfUaqqPKjXil2XHpMoie4YZTAl6trsALppAgX+Mecc8uZH67uV+aFwTS+Bc6MtR8K1Y\nOuvxUVcBP7xiPL+p/2CacFRfIJFW72CRHO6I5OTkYMqUKXjrrbewdetWuLm54ejRo3BxES3BBQKn\noPYSUHmanvNVOvxN3zscUF+lqrvGGhKHTL4HGDqHtvsnmP9+zAMVN16qRmtrlLxZBzXrdq2QJBHs\nGWYwJegZM5bkGswhYyEQMYIMrKZ6+sxd1c5GYDs8g0igdeAUXYHKznp8+OKKI+tMh+gqz0g9HnsQ\nTmc4Pfvss1iwYAEeeugh7bpRo0bZ8YwEAkGHYP3XmBZR8j1Sh3f1VVryVXf530jb9VW9mZemsQY4\n/D6tY16amkIyRFhPLoCSXZtqgQGTgGt5uj26AMsMM2tjStCT9zh9/4r0nciRuw5AOxCRTorPAC0d\nwbMm6DjewbrXP9Nu6qzHh6/kZNehqRynwTMlHamOhAqdEKcynBobG3Hw4EFkZWVh5MiRuHTpEmJj\nY/H//t//w6xZswz2b2trw82bN7V/NzVZEKsVCATWo+IceZoAaiYKAPVltAxPJ8Np1KN0026sATY/\nClwvMf/4prw0AHCFa4b701qg/LhuThXfoyt7GRBiJ4+TuYKe6ipg4F1kOCmVhMeONxQa3blCas/i\nhAm8PR5z+jdaA3bs1FlA8EDd8PnQuVIIj/8NWTNU6MA4leFUU1ODW7du4Z///Ce2bt2K9PR0/Pvf\n/8YDDzyAvXv3IisrS2f/VatW4aWXXrLT2QoEAi3bnzYML536nJasgW1znST2yIymKavJkNr7Kt2I\nmSdGPwzBZsc1hboCgKoC6cZ+kBONLD8uPY8cSbpHY56k0KDc8R0RXghTSUdn6P8Aox+j55f3S4bh\nnX+kZsax2bY/T4FlmDKMWA5f3HhOk6xKWlrT4yM3IQEko2nwTCD7WSlUaK7empPjVIZTv379AAAP\nP/wwMjMzAQAzZ87EHXfcgS1bthgYTsuXL8dzzz2n/bupqQmBgYFdd8ICgYCY+jp5nI58ZKgFw/hs\nrq5xBADu/YArh+h5WJp8GIJPpr7ZIq03Vq7v7gO0XAciM4FbGq+0T6TjJbaaEvQ0xd6/AHVFhuu/\n+xMtPfyBuDEdPj2BDeANI1bMMHapoRF0+ivDEJq1PT5sQsJC4HxYePBMYPxz1HSahQovfAtMetHx\nfkdWxqkMJ19fXyQkJJidCO7q6gpXV1cbn5VAIDBJyCB61JVIhhPz9Nz3D8A7hAQd2wGc2SK97vBa\nyTukpDinNCtmJN5FN3T2fgAZTQBQekTar2AHED+enjtKfoYx9XDWu2zvauVu9XJGE09QkvUbGQus\nQ3Od5FEcOMWw0jI0jXSbAPofbl1qXnNrS+DDxp4BZDgx2ZDsZ8lo6oE4leEEAEuWLMErr7yCBx54\nAGlpadi6dSv27t2LP/3pT/Y+NYFAYAp+0sOMGO8QEvCTM374kNqVHHkBzMyFNDuvLQZOfSE1vc1Y\nCAy4k7xc/PspUfi9eXIHjgIb1DIXSoYTa1Ez6nEpLDdwGnB+m/wxvn2OwpkjH3EcY7EnIlfc8NMH\n0vbjGwxlAXjvUsYCWprV3LqD58e8ShHD6Xq7chi4ehxouQHUlUr7ntlC+7Jej93wmnI6w2np0qVo\nbGzE3Xffjbq6OiQmJuLzzz8XlXUCgaPCJ4aXHjXcvv91YPIqMn6a64CLewxDENnLaHtlvuEA7x0s\n3/g2d52mqsxMxjwJBCdT6b4tmvtaE7meewDgFULLPn2ldapLgFco0HBN/lgsedwZjMXuipzXlE0A\nAPLGTlkNuPUDfm419C411nRM3bsj58cKC3jDjYf/HN30mhItVwQCgW1ZN8m0t+feNYCfRsxx94vG\n95e7Gf93haHhxOPhT/ID5qAvdeCIdLbvnz4sX0X0tLMPzBA2FnZlsDZEfBseW1faybVlmf4m0MeN\nPE6sgIMxZTUQkup0HifRckUgEDgGoUNMG05bzBTRy1hAgwOD3dAHTqGQ364VpGZceUZqTurhK3WP\nNwdLWkzYCyWtp97uwOlNQHAq8IMF6QtnNtMgZy8Jhp4MH6ZT8nTy3lDA0LtkLBfOGvC5TkxANSiR\nzrdRJYXxGL6RklZYN0QYTgKBwLbcrrmhmxNKSJhABtDJjYB3GKAup/VjfwdEZZIwJT+DlQtxVJ6R\n3q8j4QtXJ/BGy2k9eYfQYJW5kHLGLEHfIBV0HaaKGwDq55i9DEifS4ZWZyotO0tznbRUOncmCdJN\nG0yLUJ1AILA96iryasj1oLME/TAdP1vf91fKC2GhDIAEIIssMCKc8UZfmU9J7fznNpd71pCquEgM\ntx/8NVx2TGr7w/PARqoKdYT/UdEB4OOpwMPbyeP0wyvGrzsnynMSoTqBQGB/+NyIn1tN758yEwgZ\nTD3sku6iHnUAEDUa8Aw0FGxknpfKfCmZNigJSJhIsgfxt5MAJN8MlW3jGfkokHKP0+VkAJC0nlJm\nUHXcgbeMN2bliUjv9po7Do9+yT9vOMWOp5BYcQ4ZTvZCrhiBLSMzKCRedVYSmc1aAlwvA1LvA6Ls\neN42QhhOAoHAdshVu8nxwEYgIB44/qnU+JcZTQBQohHB7OMOBCdKAw27ofM5FuUngb6+9LwsF2jW\nSwqXE+D86X2gtxsQO9a8z+VI8Pkt6iogfR7QLwz48f909/ONApKmAWVHgKtHKSG8G6s7OxUV54Dy\nY8DVE7rr3fvRtfzj65o8PjsZ9ea0NOJhv3kPf3kJESdHGE4CgcAx8AwiUce2RmXXP0tivuN5MhLk\nwgS8t0WpFUl3xVi+TH0JcOQ96W9b9zoTmI9cSyKA9LeYBtfxDfYz7JWKEbxDKNeprx+guiBJFLAG\n3qmGPWS7A73sfQICgaAbM3YplU3fs8b4fp/NpUHfO5hyjB7eDox92nC/jIUkW1B0gLxZHUn+juJa\nM8WMpfdafIjO1dnJXCh93yGphttHPkoVWgCFWirz6cF6nQmsi7qKpCNMfb+3rwD6RRjfp7GGrvut\nT5OHqivxDpbENVlot38yGXKRIynE2MdN91wB4OoxOududo0Jj5NAILANfF5EU7W0/ran6Ua7cwWQ\nfA8w6lHdpqDewWREHXjd8Ji8qGXWko4lRJfkSM+zfuuc4TklWL5M/2SSYfhsLuWHsVDnT+9L+/Kh\nFidK4HUqWN+5wfcqe/fUVUBLLXCjzPixLnxLD8Z0md+HPZDzch77mJY7uXytbnSNCcNJIBDYBqWw\n0Y/cDf+O5+WTkzMXUi+uXL2mwGOWANFZFBrwCCSDLDIDyN+q21aEr6ZLnQ2c/lLaxtqSAEBzvbwa\nubPCG6vlebRkfwM0eLl704A2aSVQe5nCKXL6QbYWVRTQd7zrj+Yl809eSdf8N4/bNwSm33iahfGq\nC4EjH1CRBmv5M3klED5cd2LUDRCGk0AgsA0pM4CwNOpjdeBvwI1yqr7JXEBqw8akCbyDqRrHww/o\n6yOpKbt6URI5QL28lFqq8BIENyp0tzGjCZCEN7vLbFjOWK2+KD3nt105SDlgqbPkDSNzvCUCQ/RV\ntvklIBnpFeeArxYAlafNO+7OFdSwGpDCrPzxugp9sU0dL6cfGU51xbRtwMRuWbUpDCeBQGAbzn5t\nOIiX5dIDoPwiY7NQOSNg76vSushM4+/v6kmJ5sGJQLHGkLrjBSAwXkputWYneUeAT+K9clhK1h3z\nJIkoTn+TBrnP5gLhI8hwYoKGAutgqgKNGelH1ppvNDFYqM5Rw6zsWmJFGT99YF1dNAfxggrDSSAQ\n2AY2iJ/bBnynkRjIXiYN7KZmyuz1jTXAd6uAKweopP6uv5Dx0+4CuGj0ey/sJv0brxCgQeNhamuk\nJZ8DVXYUCOGSW7vbbFjbFkOl+9169adlHzf63jIWALfaaF1NoeS9aKgFTqyn51Gaxuly3hKBMuy6\nrSmU9MOmvwlEa75PZqSnzqJr844XgOIfdZv6mkIuN9AR6OsnPR84lT6fkkezIziIF1QYTgKBwPpU\nnANqL9HzqgJp/YVd1G8rbLj5Nz7PAGDQFDKc6kuAw+8Bty/TFatkOk7BAyXDSY6C7fTozsh5PJio\nolxPwJ0rpCTekFSgQuMFYXk3jurdcFRY6IpVlrF1/ZM5lXCVJCDZXGeZ0QQA+d8o5wd2NeoqQFVA\nn6Oa01Pr05eWxTnKwrIO4kGyFGE4CQSOhpPeTHRQ0qW5ehTYcpTCdL82YcAoJZcX7QM+3qc7iLOZ\n7tD/IaXlhAnA+a3ACS7pliWqAsD5HY41U7cmvKfu8Ps0yE5/E7iWBzTWAmc3K782MEkynFh4b/JK\nylUBuu93Zi34/Karx6T19aXkuTv+qaEgrDkCsQBd7021upWRjoDS75TlJX7/MnDjKqnat7tQCJ/d\n28ytOjQnZ6wLEYaTQOBoOIg7ulPcvoLK/tUVFKq7XiptS38IiBpDN0RTobrQNHpt1XndkNttT5Oe\nU8U5IGQQzWizl5Fh5B+jybVw0T1eb43OTFBS95Ig0Ee/hUf+NxQmyniYvvPbNUn5LLyZvYy+s/qr\nwIX/Ssdhg1VbiwjRmYuSEcEKIYbOJd0wQOpLN2QOcOpzad/sZUDdFcNKO4Nm1g4SQs1cCMSNp99c\nzt/lJ0ys4fbQufS52L2NeeV475w+5uaMdSHCcBIIBNanaK+ygvXxT+hhqqGudzBw4A2g9CfDbUzS\nICQVmL9FqvT5/hXl92WDV9YS4BcrLfk03QdmVKmrJI/ItVPy3xnz1n3/MlCjCbu6egKZj+h6DQQS\nKTMobHVGwat3ciPgF03P2XfOG01s/cCpwJx/kTHyjUx4FbC78aCFz6tjrY5M8cXDwIT/la6rsmNk\n5AOGRqCSarkdCzuE4SQQOAJy7ujvX9FNAHWmQYrNQn98Hbgo0xsOoBmoV7DxG37oEHnDiVFxmhTE\n3bzoPTMXys/Weyr6mjuMRpU0uDffMH0c/vsccCcN7g1V1q2Y6g6c/VrZaAJospC5ULPvFqBKQQH8\n/Hbgejnwi1VUEFFfonzMoXOlY9oLY61+AGqsnTQZuKkpSFCdAz7/H2n7rhVSHp6+Ech7UBl2Luxw\naW9vb7fbu3cxTU1N8PT0RGNjIzw8POx9OgKBhDFPCeBcSbm8EciXxDP0K4yMDbws8bS2GDj0dyn/\nZvJK0nNiuU0fT6VWI3wCLl/VZEk1X0+gMh94d7R5+05aSVWM7Lt8YKP0nH3nAkLpeuWFW1mi9Nnt\nwI5ndBXDmc7ZhV3GDTAeR/Cgst/cgbc6NmkZ9TgQN46e+ydQ+F0Odt3a6Loz10YQHieBoKswlvQt\n544GaJAKiHeupFxTs89reZRvYw5sthk7FmjlRDNrLgNpD9A2PteDfw2PZ4AY4PUNWnM59YWuZtbZ\nb6TnZcdpKYxRgrUL0r/+D75ND0CaBAXFGbZZGfc0MGgaMGASkP2sRuTVSEuhjAWO0WOR/e/T5wHh\nw3TFbYc9CHiHAq1q4NZN+c9zeA09APp+QhQmiUoe1C5GGE4CQVdhLOmbzxPo4y6tv9kiref3c2Tk\njMDEu4BevSSl6o7gEyk9z/0QGDCBjMoLe2gdWwJ0Y/UMolyR89sB934de8/uhCmDVolrefRg5HE5\nOSz/xlS+Wk9BXUUhas8AQ2X8O18gr1O7C+WPqS4Yvv78t7Q9KpMM/dufp+v8s7lA/B2SbMGAiVQg\noVTmbw+Uri9eqV+JfuHAtNckj5yDI0J1AkFXYcrNbCpcl7VEyuVxlJulKfjP7BnUOZkFdRXwnycl\nVWJjZCyg8mcWKrQkPNhdUVcBP7xieVNkc3GmcLItMOf7zVoCFP0IlB83fiz+u5QLqz683fEqQ7Ua\nVTUUsuMbEt/5AuDWDzj4JnDdSDNjU2FHEaoTCHoAlmiQME9N2XFpJs8P+I01lMvjrDIF+j2uLIF9\nj/G3S4bTpJWkhM1m9mOeBIbNlcIb/ADG51n11AHeO5g8GAkTqO0N32zZEgb9Ejj3b3reHdvWdJQj\n64wbTZEjgcZq40ZT1Ggg/WEgaaK0zjNIKuMHgMEzHdMrw4fIm+vIcIoaDZQcAnzCab0xo8mJEIaT\nQGBLLNEgkcvNYYrDgGEujzNgjZyEinPAvr8YJsuyKhzGjQpKCI/MoCqewDiHKV92GLyDKezWUaMJ\nAC7ukp6Xn6LQsn+Ccxrz1oQPUe96UdfjAlB1qLEKUYCMjPjbJckINunqnyLtkzjJsUP36ioS/ASA\nwAT6THlfmFZHHzhVej3/uYQApkDQw0iZQWXbqbNIDFJpEK84R00/EyYCeZ9Jr6/UlCv39ZNaNDiK\n8J05dMbLxFBSIdfn1OeSJo6+MrmVy5dV6haszynG/KwYBHm7m36BI5EyA/DwJxXrijzT++tzs0l6\nfkBjgJmjBN/d0RceNcbAqUBAgq5q+G1PU+4S8yYp5QxtcdC8Mmbg/LBaUqdn+U3mtJSpu0Le5PQH\ndT+TEMAUCHoYLu3kvh/5iHQzLfoRiB2nd3NYaxheAoDv/mR4TEcRvjMHa7SPmfq61Pfu8n6p+kaJ\nwTOB8c917L3MpKahFW/uuYBpaWHOZzi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RcxWVMDe1gCdrCeAXRRPTKavJiGT3W0dNOegs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\n"
          }
        }
      ],
      "source": [
        "df[['VHM0','VTZA']].plot(style='+')"
      ],
      "id": "981783f0"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Convert the wave height data to a mikeio dataset."
      ],
      "id": "49910d82-85e5-477d-9c3e-615035547b01"
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/plain": [
              "<mikeio.Dataset>\n",
              "dims: (time:1439)\n",
              "time: 2022-09-01 00:02:00 - 2022-09-30 23:31:59.999999744 (1439 non-equidistant records)\n",
              "geometry: GeometryUndefined()\n",
              "items:\n",
              "  0:  VHM0 <Significant wave height> (meter)"
            ]
          }
        }
      ],
      "source": [
        "ds = mikeio.from_pandas(\n",
        "    df[[\"VHM0\"]].dropna(), items=mikeio.ItemInfo(mikeio.EUMType.Significant_wave_height)\n",
        ")\n",
        "ds"
      ],
      "id": "68e581c2"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Store the results in Dfs0 format."
      ],
      "id": "9c522b64-a08a-45bb-a1cd-3d6c95e888a1"
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {},
      "outputs": [],
      "source": [
        "ds.to_dfs(\"FINO1_VHM0.dfs0\")"
      ],
      "id": "aff555a5"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Read the file again to check…"
      ],
      "id": "d0781392-8cf7-40a8-99e4-d6f473549bf3"
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/plain": [
              "<mikeio.Dataset>\n",
              "dims: (time:1439)\n",
              "time: 2022-09-01 00:02:00 - 2022-09-30 23:32:00 (1439 non-equidistant records)\n",
              "geometry: GeometryUndefined()\n",
              "items:\n",
              "  0:  VHM0 <Significant wave height> (meter)"
            ]
          }
        }
      ],
      "source": [
        "ds = mikeio.read(\"FINO1_VHM0.dfs0\")\n",
        "ds"
      ],
      "id": "44ec4a92"
    }
  ],
  "nbformat": 4,
  "nbformat_minor": 5,
  "metadata": {
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3 (ipykernel)",
      "language": "python",
      "path": "/opt/hostedtoolcache/Python/3.12.7/x64/share/jupyter/kernels/python3"
    },
    "language_info": {
      "name": "python",
      "codemirror_mode": {
        "name": "ipython",
        "version": "3"
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.12.7"
    }
  }
}