simulation/stitch_together_output_files.ipynb

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    "This notebook deals with the matter of stitching the output files of unfinished simulations due to TIMEOUTS. It is structured in 2 parts:\n",
    "\n",
    "1. **Make fake `part1_file`**\n",
    "We make a fake outputfile with the last two timesteps to use as a restart file for `backtrack_from_existing_file.py`.\n",
    "\n",
    "2. **Stitch `part1` and `part2`**:\n",
    "We stitch together part1 and part2 files of the simulations in question.\n",
    "\n",
    "> This notebook is not generalized for all incomplete output. You need to modify it manually to get the outputs for the files you want to address."
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   "id": "429ec2cf-31a9-43b1-8071-08e5327037b9",
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   "source": [
    "import numpy as np\n",
    "import xarray as xr\n",
    "import matplotlib.pyplot as plt\n",
    "import cartopy"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac2c0ccd",
   "metadata": {},
   "source": [
    "# 1. MAKE fake `part1_file`"
   ]
  },
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   "cell_type": "code",
   "execution_count": 2,
   "id": "42527b71-e37d-45f6-90fe-a516f49fa517",
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     "text": [
      "/nethome/6525954/.conda/envs/abyssal-nps/lib/python3.8/site-packages/xarray/coding/times.py:250: RuntimeWarning: invalid value encountered in cast\n",
      "  flat_num_dates_ns_int = (flat_num_dates * _NS_PER_TIME_DELTA[delta]).astype(\n"
     ]
    }
   ],
   "source": [
    "sim = xr.open_zarr('/storage/shared/oceanparcels/output_data/data_Claudio/abyssal_nps_outputs/hc13_25000_BM_True.zarr')\n",
    "sim = sim.compute()\n",
    "sim = sim.dropna(dim='obs')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ab83d4ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "# select the last obs and create a new dataset with the last two obs\n",
    "sim_last = sim.isel(obs=[-2,-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "524b7b6f",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;time&#x27; (obs: 2)&gt;\n",
       "array([&#x27;2012-10-22T12:00:00.000000000&#x27;, &#x27;2012-10-21T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)\n",
       "Coordinates:\n",
       "  * obs         (obs) int32 2281 2282\n",
       "    trajectory  int64 0\n",
       "Attributes:\n",
       "    axis:           T\n",
       "    long_name:      \n",
       "    standard_name:  time</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'time'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>obs</span>: 2</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-088233dc-a9d5-4252-b2ff-f4037f47e508' class='xr-array-in' type='checkbox' checked><label for='section-088233dc-a9d5-4252-b2ff-f4037f47e508' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>2012-10-22T12:00:00 2012-10-21T12:00:00</span></div><div class='xr-array-data'><pre>array([&#x27;2012-10-22T12:00:00.000000000&#x27;, &#x27;2012-10-21T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></div></li><li class='xr-section-item'><input id='section-5e8b4639-30b1-4609-bf6f-a177f51f9b60' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5e8b4639-30b1-4609-bf6f-a177f51f9b60' 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'>obs</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>2281 2282</div><input id='attrs-82ac5be3-cb4c-4f19-9b7b-87c0f785f267' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-82ac5be3-cb4c-4f19-9b7b-87c0f785f267' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c0ad860f-0c2e-4fbe-898a-df64f017e1cb' class='xr-var-data-in' type='checkbox'><label for='data-c0ad860f-0c2e-4fbe-898a-df64f017e1cb' 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'></dl></div><div class='xr-var-data'><pre>array([2281, 2282], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>trajectory</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-c0aaeb10-fe3d-4f65-bc86-f56d0e6385b0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c0aaeb10-fe3d-4f65-bc86-f56d0e6385b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d98f23bd-9c8a-40d2-a04b-026e3dd5f087' class='xr-var-data-in' type='checkbox'><label for='data-d98f23bd-9c8a-40d2-a04b-026e3dd5f087' 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'></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-63694f44-192a-44d2-8021-dbde5e442912' class='xr-section-summary-in' type='checkbox'  ><label for='section-63694f44-192a-44d2-8021-dbde5e442912' 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>obs</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c9f7262d-a21a-4afd-866a-a93d6e9b58f1' class='xr-index-data-in' type='checkbox'/><label for='index-c9f7262d-a21a-4afd-866a-a93d6e9b58f1' 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([2281, 2282], dtype=&#x27;int32&#x27;, name=&#x27;obs&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-253653de-8af0-4d1e-a866-d796b6e5b7d3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-253653de-8af0-4d1e-a866-d796b6e5b7d3' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'time' (obs: 2)>\n",
       "array(['2012-10-22T12:00:00.000000000', '2012-10-21T12:00:00.000000000'],\n",
       "      dtype='datetime64[ns]')\n",
       "Coordinates:\n",
       "  * obs         (obs) int32 2281 2282\n",
       "    trajectory  int64 0\n",
       "Attributes:\n",
       "    axis:           T\n",
       "    long_name:      \n",
       "    standard_name:  time"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim_last.time[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d2eb3d81",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f116c323210>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(sim_last.lon[:1000, 1], sim_last.lat[:1000, 1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "60386475",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<xarray.backends.zarr.ZarrStore at 0x7f116c55d230>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim_last.to_zarr('/storage/shared/oceanparcels/output_data/data_Claudio/abyssal_nps_outputs/hc13_25000_BM_False_lasttwo.zarr')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c34ba69a",
   "metadata": {},
   "source": [
    "# 2. Stitch `part1` and `part2`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9f05466a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load part 1 \n",
    "part1 = xr.open_zarr('/storage/shared/oceanparcels/output_data/data_Claudio/abyssal_nps_outputs/merge_23000/hc13_23000_BM_False_part1.zarr')\n",
    "part1 = part1.compute()\n",
    "part1 = part1.dropna(dim='obs') # Drop the nans because of the chunking."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "262c951c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
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       "\n",
       ".xr-attrs dt,\n",
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       "\n",
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       "\n",
       ".xr-attrs dt:hover span {\n",
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       "\n",
       ".xr-attrs dd {\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:           (trajectory: 8192, obs: 2875)\n",
       "Coordinates:\n",
       "  * obs               (obs) int32 0 1 2 3 4 5 ... 2869 2870 2871 2872 2873 2874\n",
       "  * trajectory        (trajectory) int64 0 1 2 3 4 ... 8187 8188 8189 8190 8191\n",
       "Data variables: (12/20)\n",
       "    abs_salinity      (trajectory, obs) float32 34.75 34.75 ... 34.72 34.72\n",
       "    bottom            (trajectory, obs) float32 5.5e+03 5.5e+03 ... 5.052e+03\n",
       "    cons_temperature  (trajectory, obs) float32 0.755 0.7429 ... 0.4315 0.4132\n",
       "    density           (trajectory, obs) float32 1.028e+03 ... 1.028e+03\n",
       "    distance          (trajectory, obs) float32 51.0 51.0 51.0 ... 51.0 51.0\n",
       "    floored           (trajectory, obs) float32 0.0 0.0 0.0 ... 77.0 77.0 77.0\n",
       "    ...                ...\n",
       "    u                 (trajectory, obs) float32 0.0 3.982e-07 ... -2.242e-07\n",
       "    v                 (trajectory, obs) float32 0.0 -4.395e-07 ... 7.65e-07\n",
       "    v_s               (trajectory, obs) float32 8.861e-08 ... 3.976e-08\n",
       "    w                 (trajectory, obs) float32 0.0 -0.0002636 ... -0.0003031\n",
       "    z                 (trajectory, obs) float64 5e+03 5.019e+03 ... 4.575e+03\n",
       "    z_kz              (trajectory, obs) float32 0.0 1.721 ... -0.4716 0.4672\n",
       "Attributes:\n",
       "    Conventions:            CF-1.6/CF-1.7\n",
       "    feature_type:           trajectory\n",
       "    ncei_template_version:  NCEI_NetCDF_Trajectory_Template_v2.0\n",
       "    parcels_mesh:           spherical\n",
       "    parcels_version:        2.4.2</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-986b0a60-2935-41f1-b3ea-84bd349b6087' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-986b0a60-2935-41f1-b3ea-84bd349b6087' 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'>trajectory</span>: 8192</li><li><span class='xr-has-index'>obs</span>: 2875</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b88aa89f-ca5a-4251-a900-f4efb9a1cda1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b88aa89f-ca5a-4251-a900-f4efb9a1cda1' 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'>obs</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 2871 2872 2873 2874</div><input id='attrs-a262285e-3034-41d9-8774-0ac6e58c7392' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a262285e-3034-41d9-8774-0ac6e58c7392' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b56a296-0109-4219-9048-f7a87d11ab5b' class='xr-var-data-in' type='checkbox'><label for='data-1b56a296-0109-4219-9048-f7a87d11ab5b' 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'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 2872, 2873, 2874], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>trajectory</span></div><div class='xr-var-dims'>(trajectory)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 8188 8189 8190 8191</div><input id='attrs-9cdaf99d-fdc5-454a-b63d-f75e2e44b9e9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9cdaf99d-fdc5-454a-b63d-f75e2e44b9e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c439941-e1d8-48c9-bea4-bcd3766af1af' class='xr-var-data-in' type='checkbox'><label for='data-1c439941-e1d8-48c9-bea4-bcd3766af1af' 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'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 8189, 8190, 8191])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a15b4cd8-220a-4786-b825-e535b556e963' class='xr-section-summary-in' type='checkbox'  ><label for='section-a15b4cd8-220a-4786-b825-e535b556e963' class='xr-section-summary' >Data variables: <span>(20)</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>abs_salinity</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>34.75 34.75 34.75 ... 34.72 34.72</div><input id='attrs-5ecd4be4-1d50-4f2a-9370-6deffff3ff4e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ecd4be4-1d50-4f2a-9370-6deffff3ff4e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f80035f4-4984-44f1-b068-e07b632fcf7c' class='xr-var-data-in' type='checkbox'><label for='data-f80035f4-4984-44f1-b068-e07b632fcf7c' 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></dd><dt><span>standard_name :</span></dt><dd>abs_salinity</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[34.74838 , 34.749405, 34.74884 , ..., 34.73666 , 34.736584,\n",
       "        34.736538],\n",
       "       [34.749557, 34.749405, 34.74884 , ..., 34.690704, 34.691956,\n",
       "        34.692513],\n",
       "       [34.74838 , 34.749405, 34.74884 , ..., 34.748905, 34.749504,\n",
       "        34.750748],\n",
       "       ...,\n",
       "       [34.74838 , 34.749012, 34.74884 , ..., 34.800014, 34.801083,\n",
       "        34.808983],\n",
       "       [34.74838 , 34.749405, 34.74884 , ..., 34.716064, 34.717392,\n",
       "        34.714966],\n",
       "       [34.749557, 34.749405, 34.74884 , ..., 34.718742, 34.71666 ,\n",
       "        34.71743 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>bottom</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>5.5e+03 5.5e+03 ... 5.052e+03</div><input id='attrs-1e51d228-5e38-476f-8e16-4ec1ae868839' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1e51d228-5e38-476f-8e16-4ec1ae868839' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0674f545-14ca-4abf-87fc-fd219c50a10b' class='xr-var-data-in' type='checkbox'><label for='data-0674f545-14ca-4abf-87fc-fd219c50a10b' 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></dd><dt><span>standard_name :</span></dt><dd>bottom</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[5500.0015, 5500.0015, 5500.0015, ..., 5052.474 , 5052.474 ,\n",
       "        5052.474 ],\n",
       "       [5500.0015, 5500.0015, 5500.0015, ..., 5500.0015, 5500.0015,\n",
       "        5500.0015],\n",
       "       [5500.0015, 5500.0015, 5500.0015, ..., 5500.0015, 5500.0015,\n",
       "        5500.0015],\n",
       "       ...,\n",
       "       [5500.0015, 5500.0015, 5500.0015, ..., 5052.474 , 5500.0015,\n",
       "        5500.0015],\n",
       "       [5500.0015, 5500.0015, 5500.0015, ..., 5052.474 , 5052.474 ,\n",
       "        5052.474 ],\n",
       "       [5500.0015, 5500.0015, 5500.0015, ..., 5052.474 , 5052.474 ,\n",
       "        5052.474 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cons_temperature</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.755 0.7429 ... 0.4315 0.4132</div><input id='attrs-2a80fcd3-b86e-4ec3-a174-b24328a552f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a80fcd3-b86e-4ec3-a174-b24328a552f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-12cf2751-193b-416b-b41d-9ac360df3cfb' class='xr-var-data-in' type='checkbox'><label for='data-12cf2751-193b-416b-b41d-9ac360df3cfb' 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></dd><dt><span>standard_name :</span></dt><dd>cons_temperature</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[0.75500983, 0.74287575, 0.7480616 , ..., 0.67186797, 0.6724403 ,\n",
       "        0.67330027],\n",
       "       [0.74459046, 0.74287575, 0.7480616 , ..., 0.10586962, 0.12133964,\n",
       "        0.12295641],\n",
       "       [0.75500983, 0.74287575, 0.7480616 , ..., 0.9385787 , 0.94813144,\n",
       "        0.9701152 ],\n",
       "       ...,\n",
       "       [0.75500983, 0.74967885, 0.7480616 , ..., 1.4250987 , 1.4277028 ,\n",
       "        1.5065871 ],\n",
       "       [0.75500983, 0.74287575, 0.7480616 , ..., 0.56627023, 0.5700347 ,\n",
       "        0.55315894],\n",
       "       [0.74459046, 0.74287575, 0.7480616 , ..., 0.45163608, 0.43153575,\n",
       "        0.41321528]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>density</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.028e+03 1.028e+03 ... 1.028e+03</div><input id='attrs-a013ebd3-35e7-4f99-b9c6-2db63f6ac609' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a013ebd3-35e7-4f99-b9c6-2db63f6ac609' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d118b4e4-5fb3-4c89-941c-1802ae06ed1f' class='xr-var-data-in' type='checkbox'><label for='data-d118b4e4-5fb3-4c89-941c-1802ae06ed1f' 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></dd><dt><span>standard_name :</span></dt><dd>density</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[1028.1653, 1028.1698, 1028.1705, ..., 1028.1586, 1028.1583,\n",
       "        1028.158 ],\n",
       "       [1028.1682, 1028.1704, 1028.1709, ..., 1028.163 , 1028.1619,\n",
       "        1028.1626],\n",
       "       [1028.1653, 1028.1696, 1028.1694, ..., 1028.0903, 1028.0902,\n",
       "        1028.088 ],\n",
       "       ...,\n",
       "       [1028.1653, 1028.1677, 1028.1693, ..., 1028.0044, 1028.0067,\n",
       "        1028.0002],\n",
       "       [1028.1653, 1028.1691, 1028.1703, ..., 1028.1449, 1028.1437,\n",
       "        1028.1443],\n",
       "       [1028.1682, 1028.1705, 1028.1702, ..., 1028.1665, 1028.1642,\n",
       "        1028.1719]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>distance</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>51.0 51.0 51.0 ... 51.0 51.0 51.0</div><input id='attrs-f661f5dd-30ea-42e6-ba53-109098673f71' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f661f5dd-30ea-42e6-ba53-109098673f71' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40fd1964-3c43-4027-86b0-c12cc517d913' class='xr-var-data-in' type='checkbox'><label for='data-40fd1964-3c43-4027-86b0-c12cc517d913' 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></dd><dt><span>standard_name :</span></dt><dd>distance</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[51., 51., 51., ..., 51., 51., 51.],\n",
       "       [51., 51., 51., ..., 51., 51., 51.],\n",
       "       [51., 51., 51., ..., 51., 51., 51.],\n",
       "       ...,\n",
       "       [51., 51., 51., ..., 51., 51., 51.],\n",
       "       [51., 51., 51., ..., 51., 51., 51.],\n",
       "       [51., 51., 51., ..., 51., 51., 51.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>floored</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 77.0 77.0 77.0</div><input id='attrs-8aeee9b5-65f3-4d73-ace7-2b2c138cfb9b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8aeee9b5-65f3-4d73-ace7-2b2c138cfb9b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e8a134a-41c7-41c4-a451-406cdb8027dd' class='xr-var-data-in' type='checkbox'><label for='data-7e8a134a-41c7-41c4-a451-406cdb8027dd' 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></dd><dt><span>standard_name :</span></dt><dd>floored</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.,  0.,  0., ..., 96., 96., 96.],\n",
       "       [ 0.,  0.,  0., ..., 21., 21., 21.],\n",
       "       [ 0.,  0.,  0., ..., 11., 11., 11.],\n",
       "       ...,\n",
       "       [ 0.,  0.,  0., ..., 30., 30., 30.],\n",
       "       [ 0.,  0.,  0., ..., 48., 48., 48.],\n",
       "       [ 0.,  0.,  0., ..., 77., 77., 77.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>frag_events</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-58462047-85bf-4d2d-8071-586a6ff91876' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-58462047-85bf-4d2d-8071-586a6ff91876' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c38ddae-1298-4412-aa4b-18f602f90b38' class='xr-var-data-in' type='checkbox'><label for='data-3c38ddae-1298-4412-aa4b-18f602f90b38' 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></dd><dt><span>standard_name :</span></dt><dd>frag_events</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       ...,\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>in_ml</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-4d6fd151-362d-4b30-ab73-03b02c307780' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4d6fd151-362d-4b30-ab73-03b02c307780' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0313f910-9d8c-4b24-9667-4a47ece15ea9' class='xr-var-data-in' type='checkbox'><label for='data-0313f910-9d8c-4b24-9667-4a47ece15ea9' 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></dd><dt><span>standard_name :</span></dt><dd>in_ml</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       ...,\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>kz</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0003607 ... 2.231e-05</div><input id='attrs-683e6eef-f8b3-4d64-aaa0-0711da16684b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-683e6eef-f8b3-4d64-aaa0-0711da16684b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f7dba18-f29d-4b2b-8ef9-d57c9be3a54d' class='xr-var-data-in' type='checkbox'><label for='data-4f7dba18-f29d-4b2b-8ef9-d57c9be3a54d' 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></dd><dt><span>standard_name :</span></dt><dd>kz</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[0.0000000e+00, 3.6070295e-04, 5.3864811e-04, ..., 1.5829930e-05,\n",
       "        1.5876683e-05, 1.6011898e-05],\n",
       "       [0.0000000e+00, 4.4348932e-04, 5.9251772e-04, ..., 3.8312010e-05,\n",
       "        3.9018927e-05, 4.1242638e-05],\n",
       "       [0.0000000e+00, 3.4446249e-04, 4.8800881e-04, ..., 1.6795899e-05,\n",
       "        1.6655576e-05, 1.6450142e-05],\n",
       "       ...,\n",
       "       [0.0000000e+00, 2.9774281e-04, 4.3435767e-04, ..., 1.5738677e-05,\n",
       "        1.5183908e-05, 1.5282554e-05],\n",
       "       [0.0000000e+00, 3.2203304e-04, 6.0979329e-04, ..., 3.8255472e-05,\n",
       "        3.8131129e-05, 4.0795032e-05],\n",
       "       [0.0000000e+00, 4.6840584e-04, 5.8679376e-04, ..., 2.7785314e-05,\n",
       "        1.9628740e-05, 2.2312226e-05]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-32.17 -32.13 ... -40.7 -40.77</div><input id='attrs-8155f5f1-bfbf-4381-93ca-acad3d92eeeb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8155f5f1-bfbf-4381-93ca-acad3d92eeeb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c0fbfd7-a59e-46cb-947c-2c2c9d32c357' class='xr-var-data-in' type='checkbox'><label for='data-4c0fbfd7-a59e-46cb-947c-2c2c9d32c357' 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>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([[-32.17170837, -32.13059055, -32.09489508, ..., -36.49711755,\n",
       "        -36.51212471, -36.52741794],\n",
       "       [-32.17008875, -32.12925211, -32.09376234, ..., -47.15264643,\n",
       "        -47.1712654 , -47.19138463],\n",
       "       [-32.16992301, -32.12912808, -32.0936573 , ..., -34.3960205 ,\n",
       "        -34.39927255, -34.40100272],\n",
       "       ...,\n",
       "       [-32.16742837, -32.12706772, -32.09191188, ..., -35.41440629,\n",
       "        -35.38532342, -35.3395228 ],\n",
       "       [-32.17995947, -32.13742135, -32.10065609, ..., -40.28861562,\n",
       "        -40.28605215, -40.29805437],\n",
       "       [-32.16828966, -32.12776772, -32.0925049 , ..., -40.61486625,\n",
       "        -40.69619679, -40.76512772]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.292 6.259 6.235 ... 16.24 16.29</div><input id='attrs-f7fa7012-96b6-4a48-8cdc-db5239ed0ff2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f7fa7012-96b6-4a48-8cdc-db5239ed0ff2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a82dc762-6c69-4a1e-a16a-2547ba7666c9' class='xr-var-data-in' type='checkbox'><label for='data-a82dc762-6c69-4a1e-a16a-2547ba7666c9' 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>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([[ 6.29196714,  6.25932257,  6.23465676, ..., -0.65197972,\n",
       "        -0.6490821 , -0.64391709],\n",
       "       [ 6.28561736,  6.25237037,  6.22768959, ..., 21.52273218,\n",
       "        21.52542761, 21.53425358],\n",
       "       [ 6.29347689,  6.26098219,  6.23700845, ...,  7.96968512,\n",
       "         8.0280081 ,  8.0857738 ],\n",
       "       ...,\n",
       "       [ 6.29646577,  6.26488686,  6.24132585, ...,  7.14935853,\n",
       "         7.06395533,  6.99323056],\n",
       "       [ 6.29304052,  6.26049847,  6.23369919, ...,  4.33516048,\n",
       "         4.31325805,  4.28041413],\n",
       "       [ 6.28289971,  6.24982853,  6.22503323, ..., 16.17653237,\n",
       "        16.23816589, 16.28650456]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>particle_density</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.38e+03 1.38e+03 ... 1.38e+03</div><input id='attrs-1f844d71-c545-4db0-8a33-e2c9c123f3bf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f844d71-c545-4db0-8a33-e2c9c123f3bf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0ff8252-d358-4a91-b363-1086221eac50' class='xr-var-data-in' type='checkbox'><label for='data-a0ff8252-d358-4a91-b363-1086221eac50' 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></dd><dt><span>standard_name :</span></dt><dd>particle_density</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[1380., 1380., 1380., ..., 1380., 1380., 1380.],\n",
       "       [1380., 1380., 1380., ..., 1380., 1380., 1380.],\n",
       "       [1380., 1380., 1380., ..., 1380., 1380., 1380.],\n",
       "       ...,\n",
       "       [1380., 1380., 1380., ..., 1380., 1380., 1380.],\n",
       "       [1380., 1380., 1380., ..., 1380., 1380., 1380.],\n",
       "       [1380., 1380., 1380., ..., 1380., 1380., 1380.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>radius</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.221e-07 4.221e-07 ... 2.828e-07</div><input id='attrs-0cf27ae3-7421-448e-ac5b-5443cf92c83a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0cf27ae3-7421-448e-ac5b-5443cf92c83a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dae700ce-a719-4937-8e65-0e85f9acf2d5' class='xr-var-data-in' type='checkbox'><label for='data-dae700ce-a719-4937-8e65-0e85f9acf2d5' 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></dd><dt><span>standard_name :</span></dt><dd>radius</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[4.22100463e-07, 4.22100463e-07, 4.22100463e-07, ...,\n",
       "        4.22100463e-07, 4.22100463e-07, 4.22100463e-07],\n",
       "       [4.96517676e-07, 4.96517676e-07, 4.96517676e-07, ...,\n",
       "        4.96517676e-07, 4.96517676e-07, 4.96517676e-07],\n",
       "       [1.86342351e-07, 1.86342351e-07, 1.86342351e-07, ...,\n",
       "        1.86342351e-07, 1.86342351e-07, 1.86342351e-07],\n",
       "       ...,\n",
       "       [4.58297622e-07, 4.58297622e-07, 4.58297622e-07, ...,\n",
       "        4.58297622e-07, 4.58297622e-07, 4.58297622e-07],\n",
       "       [1.77726796e-07, 1.77726796e-07, 1.77726796e-07, ...,\n",
       "        1.77726796e-07, 1.77726796e-07, 1.77726796e-07],\n",
       "       [2.82760863e-07, 2.82760863e-07, 2.82760863e-07, ...,\n",
       "        2.82760863e-07, 2.82760863e-07, 2.82760863e-07]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-01-20T12:00:00 ... 2011-03-...</div><input id='attrs-979629c9-bda5-47b3-a1ef-98e32053ff62' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-979629c9-bda5-47b3-a1ef-98e32053ff62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ad07ecb-f639-4bc6-99ca-76d172e1f5d6' class='xr-var-data-in' type='checkbox'><label for='data-5ad07ecb-f639-4bc6-99ca-76d172e1f5d6' 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>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([[&#x27;2019-01-20T12:00:00.000000000&#x27;, &#x27;2019-01-19T12:00:00.000000000&#x27;,\n",
       "        &#x27;2019-01-18T12:00:00.000000000&#x27;, ...,\n",
       "        &#x27;2011-03-11T12:00:00.000000000&#x27;, &#x27;2011-03-10T12:00:00.000000000&#x27;,\n",
       "        &#x27;2011-03-09T12:00:00.000000000&#x27;],\n",
       "       [&#x27;2019-01-20T12:00:00.000000000&#x27;, &#x27;2019-01-19T12:00:00.000000000&#x27;,\n",
       "        &#x27;2019-01-18T12:00:00.000000000&#x27;, ...,\n",
       "        &#x27;2011-03-11T12:00:00.000000000&#x27;, &#x27;2011-03-10T12:00:00.000000000&#x27;,\n",
       "        &#x27;2011-03-09T12:00:00.000000000&#x27;],\n",
       "       [&#x27;2019-01-20T12:00:00.000000000&#x27;, &#x27;2019-01-19T12:00:00.000000000&#x27;,\n",
       "        &#x27;2019-01-18T12:00:00.000000000&#x27;, ...,\n",
       "        &#x27;2011-03-11T12:00:00.000000000&#x27;, &#x27;2011-03-10T12:00:00.000000000&#x27;,\n",
       "        &#x27;2011-03-09T12:00:00.000000000&#x27;],\n",
       "       ...,\n",
       "       [&#x27;2019-01-20T12:00:00.000000000&#x27;, &#x27;2019-01-19T12:00:00.000000000&#x27;,\n",
       "        &#x27;2019-01-18T12:00:00.000000000&#x27;, ...,\n",
       "        &#x27;2011-03-11T12:00:00.000000000&#x27;, &#x27;2011-03-10T12:00:00.000000000&#x27;,\n",
       "        &#x27;2011-03-09T12:00:00.000000000&#x27;],\n",
       "       [&#x27;2019-01-20T12:00:00.000000000&#x27;, &#x27;2019-01-19T12:00:00.000000000&#x27;,\n",
       "        &#x27;2019-01-18T12:00:00.000000000&#x27;, ...,\n",
       "        &#x27;2011-03-11T12:00:00.000000000&#x27;, &#x27;2011-03-10T12:00:00.000000000&#x27;,\n",
       "        &#x27;2011-03-09T12:00:00.000000000&#x27;],\n",
       "       [&#x27;2019-01-20T12:00:00.000000000&#x27;, &#x27;2019-01-19T12:00:00.000000000&#x27;,\n",
       "        &#x27;2019-01-18T12:00:00.000000000&#x27;, ...,\n",
       "        &#x27;2011-03-11T12:00:00.000000000&#x27;, &#x27;2011-03-10T12:00:00.000000000&#x27;,\n",
       "        &#x27;2011-03-09T12:00:00.000000000&#x27;]], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 3.982e-07 ... -2.242e-07</div><input id='attrs-bac79c9c-094f-4c86-875c-35618b9dc901' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bac79c9c-094f-4c86-875c-35618b9dc901' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d343be22-9d6a-47e9-ae5f-9028ab8345d5' class='xr-var-data-in' type='checkbox'><label for='data-d343be22-9d6a-47e9-ae5f-9028ab8345d5' 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></dd><dt><span>standard_name :</span></dt><dd>u</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.0000000e+00,  3.9817516e-07,  2.9804730e-07, ...,\n",
       "        -1.8891679e-08, -4.7183811e-08, -7.0534227e-08],\n",
       "       [ 0.0000000e+00,  4.0572019e-07,  3.0459475e-07, ...,\n",
       "        -2.4636982e-08, -8.2932452e-08, -1.1985335e-07],\n",
       "       [ 0.0000000e+00,  3.9636620e-07,  2.9583197e-07, ...,\n",
       "        -6.7610659e-07, -6.7391312e-07, -6.7264693e-07],\n",
       "       ...,\n",
       "       [ 0.0000000e+00,  2.5221269e-07,  2.9176675e-07, ...,\n",
       "         9.9375757e-07,  9.7242241e-07,  8.2108568e-07],\n",
       "       [ 0.0000000e+00,  3.9692782e-07,  2.9896663e-07, ...,\n",
       "         1.5213674e-07,  3.3788359e-07,  4.0434139e-07],\n",
       "       [ 0.0000000e+00,  4.0894471e-07,  3.0708827e-07, ...,\n",
       "        -3.7812006e-07, -7.7716896e-07, -2.2424622e-07]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 -4.395e-07 ... 7.65e-07</div><input id='attrs-9b611451-049e-4484-80fe-bebc4e973d85' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9b611451-049e-4484-80fe-bebc4e973d85' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac44385e-8c70-44f7-9591-541569966f97' class='xr-var-data-in' type='checkbox'><label for='data-ac44385e-8c70-44f7-9591-541569966f97' 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></dd><dt><span>standard_name :</span></dt><dd>v</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.0000000e+00, -4.3948191e-07, -3.9371204e-07, ...,\n",
       "         1.7518325e-07,  1.7204972e-07,  1.8122762e-07],\n",
       "       [ 0.0000000e+00, -4.3639074e-07, -3.9153008e-07, ...,\n",
       "         2.0160189e-07,  2.2750953e-07,  2.3681150e-07],\n",
       "       [ 0.0000000e+00, -4.3610430e-07, -3.9132775e-07, ...,\n",
       "         1.2645230e-08,  5.9702096e-08,  1.1751988e-08],\n",
       "       ...,\n",
       "       [ 0.0000000e+00, -4.3140170e-07, -3.8796574e-07, ...,\n",
       "        -2.1302152e-07, -3.9461406e-07, -5.9433091e-07],\n",
       "       [ 0.0000000e+00, -4.5525931e-07, -4.0481007e-07, ...,\n",
       "        -6.4912840e-08, -1.8990263e-09,  3.7948425e-07],\n",
       "       [ 0.0000000e+00, -4.3296356e-07, -3.8910801e-07, ...,\n",
       "         1.1692146e-06,  8.5213208e-07,  7.6496383e-07]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v_s</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>8.861e-08 8.861e-08 ... 3.976e-08</div><input id='attrs-3fedc3a3-c375-4224-9ede-ccd75625e656' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3fedc3a3-c375-4224-9ede-ccd75625e656' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9ab728b-0c47-490a-af5e-1008b0e3aced' class='xr-var-data-in' type='checkbox'><label for='data-e9ab728b-0c47-490a-af5e-1008b0e3aced' 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></dd><dt><span>standard_name :</span></dt><dd>v_s</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[8.86078126e-08, 8.86062850e-08, 8.86060363e-08, ...,\n",
       "        8.86100864e-08, 8.86101645e-08, 8.86102924e-08],\n",
       "       [1.22604007e-07, 1.22602984e-07, 1.22602756e-07, ...,\n",
       "        1.22606465e-07, 1.22606977e-07, 1.22606636e-07],\n",
       "       [1.72688743e-08, 1.72685919e-08, 1.72686008e-08, ...,\n",
       "        1.72738126e-08, 1.72738197e-08, 1.72739654e-08],\n",
       "       ...,\n",
       "       [1.04456497e-07, 1.04455523e-07, 1.04454891e-07, ...,\n",
       "        1.04520616e-07, 1.04519692e-07, 1.04522272e-07],\n",
       "       [1.57089328e-08, 1.57087072e-08, 1.57086344e-08, ...,\n",
       "        1.57101550e-08, 1.57102278e-08, 1.57101923e-08],\n",
       "       [3.97625719e-08, 3.97622202e-08, 3.97622735e-08, ...,\n",
       "        3.97628312e-08, 3.97631830e-08, 3.97620141e-08]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>w</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 -0.0002636 ... -0.0003031</div><input id='attrs-539d054f-3a25-42f5-8b17-2af5073f9442' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-539d054f-3a25-42f5-8b17-2af5073f9442' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0380d86-d078-4e1f-9d5b-1004531582ed' class='xr-var-data-in' type='checkbox'><label for='data-f0380d86-d078-4e1f-9d5b-1004531582ed' 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></dd><dt><span>standard_name :</span></dt><dd>w</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00000000e+00, -2.63608556e-04, -2.24901785e-04, ...,\n",
       "         2.51844849e-05,  2.37838176e-05,  2.32914972e-05],\n",
       "       [ 0.00000000e+00, -2.71594472e-04, -2.29382553e-04, ...,\n",
       "        -6.99503507e-05, -1.07988475e-04, -8.56154365e-05],\n",
       "       [ 0.00000000e+00, -2.58678047e-04, -2.11169652e-04, ...,\n",
       "        -1.95804678e-04, -2.80748878e-04, -8.31549551e-05],\n",
       "       ...,\n",
       "       [ 0.00000000e+00, -1.74362358e-04, -2.10573475e-04, ...,\n",
       "        -2.80195673e-04, -3.58582416e-04, -4.14544425e-04],\n",
       "       [ 0.00000000e+00, -2.52851692e-04, -2.22337214e-04, ...,\n",
       "         1.75207257e-04,  1.74739966e-04,  7.48424209e-05],\n",
       "       [ 0.00000000e+00, -2.73999351e-04, -2.20643953e-04, ...,\n",
       "         1.08297949e-03,  7.24372512e-05, -3.03132081e-04]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5e+03 5.019e+03 ... 4.575e+03</div><input id='attrs-11f62169-d50a-442e-ba6a-61679908e3db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11f62169-d50a-442e-ba6a-61679908e3db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2e6a207-2f0c-4e0a-a34c-c010cc025110' class='xr-var-data-in' type='checkbox'><label for='data-b2e6a207-2f0c-4e0a-a34c-c010cc025110' 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></dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([[5000.        , 5019.43599813, 5046.09723781, ..., 4822.51288144,\n",
       "        4821.85670221, 4819.76470807],\n",
       "       [5000.        , 5024.05517783, 5046.6208768 , ..., 4114.57384968,\n",
       "        4122.0565247 , 4126.78374083],\n",
       "       [5000.        , 5011.1339549 , 5033.79707012, ..., 4488.60754629,\n",
       "        4505.91258573, 4517.8425497 ],\n",
       "       ...,\n",
       "       [5000.        , 5009.14988753, 5031.60740986, ..., 3993.39890154,\n",
       "        4023.56908441, 4054.66965721],\n",
       "       [5000.        , 5009.59075278, 5045.64560089, ..., 4603.06110723,\n",
       "        4587.65865942, 4577.3855731 ],\n",
       "       [5000.        , 5027.42944999, 5037.31577509, ..., 4579.17420468,\n",
       "        4531.76452092, 4574.9622832 ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z_kz</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 1.721 1.104 ... -0.4716 0.4672</div><input id='attrs-64416bd1-fae5-4229-9d66-ca12c1c126dd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-64416bd1-fae5-4229-9d66-ca12c1c126dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a55582b6-5972-49f4-9c85-4811514626d1' class='xr-var-data-in' type='checkbox'><label for='data-a55582b6-5972-49f4-9c85-4811514626d1' 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></dd><dt><span>standard_name :</span></dt><dd>z_kz</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.        ,  1.7209712 ,  1.1036078 , ..., -0.16289331,\n",
       "        -0.17810859,  0.43263406],\n",
       "       [ 0.        , -0.37036186, -3.0334806 , ...,  0.07965707,\n",
       "         0.8062517 , -0.04347214],\n",
       "       [ 0.        , -2.438167  ,  3.0871944 , ..., -0.24203505,\n",
       "         0.49680933, -0.59044635],\n",
       "       ...,\n",
       "       [ 0.        , -1.9523056 ,  1.5179752 , ...,  0.47352153,\n",
       "        -0.25080234,  0.23782139],\n",
       "       [ 0.        ,  0.9145878 ,  3.3193552 , ..., -0.8025396 ,\n",
       "         0.84954613, -0.75973153],\n",
       "       [ 0.        ,  1.2352989 , -3.2490857 , ...,  0.5606426 ,\n",
       "        -0.47158843,  0.46719596]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d70ba485-7fab-44f3-8918-19e4ac2f9403' class='xr-section-summary-in' type='checkbox'  ><label for='section-d70ba485-7fab-44f3-8918-19e4ac2f9403' class='xr-section-summary' >Indexes: <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-index-name'><div>obs</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f2d52aba-a96c-4aec-9ee0-b310d577d6ab' class='xr-index-data-in' type='checkbox'/><label for='index-f2d52aba-a96c-4aec-9ee0-b310d577d6ab' 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(Int64Index([   0,    1,    2,    3,    4,    5,    6,    7,    8,    9,\n",
       "            ...\n",
       "            2865, 2866, 2867, 2868, 2869, 2870, 2871, 2872, 2873, 2874],\n",
       "           dtype=&#x27;int64&#x27;, name=&#x27;obs&#x27;, length=2875))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>trajectory</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-dfcee15e-6519-46e2-879d-9368a5a637ee' class='xr-index-data-in' type='checkbox'/><label for='index-dfcee15e-6519-46e2-879d-9368a5a637ee' 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(Int64Index([   0,    1,    2,    3,    4,    5,    6,    7,    8,    9,\n",
       "            ...\n",
       "            8182, 8183, 8184, 8185, 8186, 8187, 8188, 8189, 8190, 8191],\n",
       "           dtype=&#x27;int64&#x27;, name=&#x27;trajectory&#x27;, length=8192))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-78ed4653-866c-4748-acf5-832fb0f305c1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-78ed4653-866c-4748-acf5-832fb0f305c1' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6/CF-1.7</dd><dt><span>feature_type :</span></dt><dd>trajectory</dd><dt><span>ncei_template_version :</span></dt><dd>NCEI_NetCDF_Trajectory_Template_v2.0</dd><dt><span>parcels_mesh :</span></dt><dd>spherical</dd><dt><span>parcels_version :</span></dt><dd>2.4.2</dd></dl></div></li></ul></div></div>"
      ],
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       "<xarray.Dataset>\n",
       "Dimensions:           (trajectory: 8192, obs: 2875)\n",
       "Coordinates:\n",
       "  * obs               (obs) int32 0 1 2 3 4 5 ... 2869 2870 2871 2872 2873 2874\n",
       "  * trajectory        (trajectory) int64 0 1 2 3 4 ... 8187 8188 8189 8190 8191\n",
       "Data variables: (12/20)\n",
       "    abs_salinity      (trajectory, obs) float32 34.75 34.75 ... 34.72 34.72\n",
       "    bottom            (trajectory, obs) float32 5.5e+03 5.5e+03 ... 5.052e+03\n",
       "    cons_temperature  (trajectory, obs) float32 0.755 0.7429 ... 0.4315 0.4132\n",
       "    density           (trajectory, obs) float32 1.028e+03 ... 1.028e+03\n",
       "    distance          (trajectory, obs) float32 51.0 51.0 51.0 ... 51.0 51.0\n",
       "    floored           (trajectory, obs) float32 0.0 0.0 0.0 ... 77.0 77.0 77.0\n",
       "    ...                ...\n",
       "    u                 (trajectory, obs) float32 0.0 3.982e-07 ... -2.242e-07\n",
       "    v                 (trajectory, obs) float32 0.0 -4.395e-07 ... 7.65e-07\n",
       "    v_s               (trajectory, obs) float32 8.861e-08 ... 3.976e-08\n",
       "    w                 (trajectory, obs) float32 0.0 -0.0002636 ... -0.0003031\n",
       "    z                 (trajectory, obs) float64 5e+03 5.019e+03 ... 4.575e+03\n",
       "    z_kz              (trajectory, obs) float32 0.0 1.721 ... -0.4716 0.4672\n",
       "Attributes:\n",
       "    Conventions:            CF-1.6/CF-1.7\n",
       "    feature_type:           trajectory\n",
       "    ncei_template_version:  NCEI_NetCDF_Trajectory_Template_v2.0\n",
       "    parcels_mesh:           spherical\n",
       "    parcels_version:        2.4.2"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "part1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8510bf6e",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/nethome/6525954/.conda/envs/abyssal-nps/lib/python3.8/site-packages/xarray/backends/plugins.py:139: RuntimeWarning: 'netcdf4' fails while guessing\n",
      "  warnings.warn(f\"{engine!r} fails while guessing\", RuntimeWarning)\n",
      "/nethome/6525954/.conda/envs/abyssal-nps/lib/python3.8/site-packages/xarray/backends/plugins.py:139: RuntimeWarning: 'scipy' fails while guessing\n",
      "  warnings.warn(f\"{engine!r} fails while guessing\", RuntimeWarning)\n"
     ]
    }
   ],
   "source": [
    "part2 = xr.open_dataset('/storage/shared/oceanparcels/output_data/data_Claudio/abyssal_nps_outputs/merge_23000/hc13_23000_BM_False_part2.zarr')\n",
    "part2 = part2.compute()\n",
    "part2 = part2.dropna(dim='obs') # Drop the nans because of the chunking."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1938979e",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:           (trajectory: 8192, obs: 1530)\n",
       "Coordinates:\n",
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       "Data variables: (12/20)\n",
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       "    bottom            (trajectory, obs) float32 5.052e+03 ... 4.617e+03\n",
       "    cons_temperature  (trajectory, obs) float32 0.6724 0.6733 ... 1.535 1.359\n",
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       "    ...                ...\n",
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       "    v                 (trajectory, obs) float32 1.72e-07 ... -2.246e-06\n",
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       "    w                 (trajectory, obs) float32 2.378e-05 ... -0.0004499\n",
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       "    z_kz              (trajectory, obs) float32 -0.1781 0.3619 ... 0.2405\n",
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       "    ncei_template_version:  NCEI_NetCDF_Trajectory_Template_v2.0\n",
       "    parcels_mesh:           spherical\n",
       "    parcels_version:        2.4.2</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-6ba579b7-a82f-493a-8c5c-4dbfd9cfc4df' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6ba579b7-a82f-493a-8c5c-4dbfd9cfc4df' 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'>trajectory</span>: 8192</li><li><span class='xr-has-index'>obs</span>: 1530</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9fef7851-c5a5-4b2e-a6af-5a48a6117dae' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9fef7851-c5a5-4b2e-a6af-5a48a6117dae' 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'>obs</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1526 1527 1528 1529</div><input id='attrs-2ff1eaf2-16fa-43df-893f-2e6d043512aa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2ff1eaf2-16fa-43df-893f-2e6d043512aa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59c18e56-ea92-45dc-a85b-5a35e3a3e400' class='xr-var-data-in' type='checkbox'><label for='data-59c18e56-ea92-45dc-a85b-5a35e3a3e400' 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'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1527, 1528, 1529], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>trajectory</span></div><div class='xr-var-dims'>(trajectory)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 8188 8189 8190 8191</div><input id='attrs-2df9452d-6304-43f8-8fc3-fcbfdf53e6b5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2df9452d-6304-43f8-8fc3-fcbfdf53e6b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-55af2489-be8a-4e28-8411-277e02ca1a64' class='xr-var-data-in' type='checkbox'><label for='data-55af2489-be8a-4e28-8411-277e02ca1a64' 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'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 8189, 8190, 8191])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-68df4182-66de-4178-9473-d82a31bc0850' class='xr-section-summary-in' type='checkbox'  ><label for='section-68df4182-66de-4178-9473-d82a31bc0850' class='xr-section-summary' >Data variables: <span>(20)</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>abs_salinity</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>34.74 34.74 34.74 ... 34.81 34.8</div><input id='attrs-1d3095a7-3632-4383-8512-26ebfab9dfae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1d3095a7-3632-4383-8512-26ebfab9dfae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-372748b7-5893-4f67-b1ce-c39f8bbe4f27' class='xr-var-data-in' type='checkbox'><label for='data-372748b7-5893-4f67-b1ce-c39f8bbe4f27' 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></dd><dt><span>standard_name :</span></dt><dd>abs_salinity</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[34.736584, 34.736538, 34.737457, ..., 34.710144, 34.70965 ,\n",
       "        34.71072 ],\n",
       "       [34.691956, 34.692513, 34.693497, ..., 34.690674, 34.690674,\n",
       "        34.690678],\n",
       "       [34.749504, 34.750748, 34.75024 , ..., 34.729843, 34.72913 ,\n",
       "        34.728027],\n",
       "       ...,\n",
       "       [34.801083, 34.808983, 34.815628, ..., 34.87157 , 34.87173 ,\n",
       "        34.871758],\n",
       "       [34.717392, 34.714966, 34.71349 , ..., 34.733746, 34.73411 ,\n",
       "        34.733894],\n",
       "       [34.71666 , 34.71743 , 34.71863 , ..., 34.772865, 34.813034,\n",
       "        34.798264]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>bottom</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>5.052e+03 5.052e+03 ... 4.617e+03</div><input id='attrs-1a5d3cfe-55be-4be4-87f9-8fd34bdf7f5c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a5d3cfe-55be-4be4-87f9-8fd34bdf7f5c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-188c112a-8ff2-48af-861a-a29c52f9e3f4' class='xr-var-data-in' type='checkbox'><label for='data-188c112a-8ff2-48af-861a-a29c52f9e3f4' 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></dd><dt><span>standard_name :</span></dt><dd>bottom</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[5052.474 , 5052.474 , 5052.474 , ..., 5500.0015, 5500.0015,\n",
       "        5500.0015],\n",
       "       [5500.0015, 5500.0015, 5500.0015, ..., 5500.0015, 5500.0015,\n",
       "        5500.0015],\n",
       "       [5500.0015, 5500.0015, 5500.0015, ..., 4617.4624, 4617.4624,\n",
       "        5052.474 ],\n",
       "       ...,\n",
       "       [5500.0015, 5500.0015, 5500.0015, ..., 4196.816 , 4617.4624,\n",
       "        4196.816 ],\n",
       "       [5052.474 , 5052.474 , 5052.474 , ..., 5052.474 , 5500.0015,\n",
       "        5500.0015],\n",
       "       [5052.474 , 5052.474 , 5052.474 , ..., 5052.474 , 5052.474 ,\n",
       "        4617.4624]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cons_temperature</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6724 0.6733 ... 1.535 1.359</div><input id='attrs-e6ecc1ac-166e-43e2-97ba-c54d12cc33b5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e6ecc1ac-166e-43e2-97ba-c54d12cc33b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2312a294-a869-4ee9-a015-889732238bae' class='xr-var-data-in' type='checkbox'><label for='data-2312a294-a869-4ee9-a015-889732238bae' 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></dd><dt><span>standard_name :</span></dt><dd>cons_temperature</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6724403 ,  0.67330027,  0.67452633, ...,  0.38604578,\n",
       "         0.3782125 ,  0.389283  ],\n",
       "       [ 0.12133964,  0.12295641,  0.13020411, ..., -0.0363351 ,\n",
       "        -0.03494737, -0.0346791 ],\n",
       "       [ 0.94813144,  0.9701152 ,  0.9722129 , ...,  0.76204836,\n",
       "         0.7537743 ,  0.74429846],\n",
       "       ...,\n",
       "       [ 1.4277028 ,  1.5065871 ,  1.5678087 , ...,  2.0370247 ,\n",
       "         2.027865  ,  2.0365455 ],\n",
       "       [ 0.5700347 ,  0.55315894,  0.55920035, ...,  0.7658431 ,\n",
       "         0.77142155,  0.77154964],\n",
       "       [ 0.43153575,  0.41321528,  0.46893713, ...,  1.1361235 ,\n",
       "         1.5353706 ,  1.3586261 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>density</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.028e+03 1.028e+03 ... 1.028e+03</div><input id='attrs-d17adc0e-edd9-4e1d-af98-b044c81ddc17' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d17adc0e-edd9-4e1d-af98-b044c81ddc17' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dbe945cc-3e11-4604-bfeb-a14dcd3134bf' class='xr-var-data-in' type='checkbox'><label for='data-dbe945cc-3e11-4604-bfeb-a14dcd3134bf' 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></dd><dt><span>standard_name :</span></dt><dd>density</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[1028.1583, 1028.1578, 1028.1581, ..., 1028.2262, 1028.2269,\n",
       "        1028.2206],\n",
       "       [1028.1619, 1028.163 , 1028.1637, ..., 1028.2764, 1028.2755,\n",
       "        1028.2753],\n",
       "       [1028.0902, 1028.0879, 1028.0873, ..., 1028.068 , 1028.0686,\n",
       "        1028.0695],\n",
       "       ...,\n",
       "       [1028.0067, 1028.0002, 1027.9962, ..., 1027.9271, 1027.9285,\n",
       "        1027.927 ],\n",
       "       [1028.1437, 1028.1438, 1028.1412, ..., 1028.0929, 1028.0974,\n",
       "        1028.0986],\n",
       "       [1028.1642, 1028.1718, 1028.1636, ..., 1028.0227, 1027.981 ,\n",
       "        1027.9933]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>distance</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>51.0 51.0 51.0 ... 51.0 51.0 51.0</div><input id='attrs-37264d70-90a1-4d8d-9de9-8e068539bca3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-37264d70-90a1-4d8d-9de9-8e068539bca3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecb644b0-b444-4c1e-b23b-e91495e7f7ea' class='xr-var-data-in' type='checkbox'><label for='data-ecb644b0-b444-4c1e-b23b-e91495e7f7ea' 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></dd><dt><span>standard_name :</span></dt><dd>distance</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[51., 51., 51., ..., 51., 51., 51.],\n",
       "       [51., 51., 51., ..., 51., 51., 51.],\n",
       "       [51., 51., 51., ..., 51., 51., 51.],\n",
       "       ...,\n",
       "       [51., 51., 51., ..., 51., 51., 51.],\n",
       "       [51., 51., 51., ..., 51., 51., 51.],\n",
       "       [51., 51., 51., ..., 51., 51., 51.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>floored</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>96.0 96.0 96.0 ... 121.0 121.0</div><input id='attrs-464d9cc1-b16d-410d-a919-0a868702523d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-464d9cc1-b16d-410d-a919-0a868702523d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5fa4e445-41f4-451f-b443-c22dd80bdca8' class='xr-var-data-in' type='checkbox'><label for='data-5fa4e445-41f4-451f-b443-c22dd80bdca8' 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></dd><dt><span>standard_name :</span></dt><dd>floored</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[ 96.,  96.,  96., ..., 134., 134., 134.],\n",
       "       [ 21.,  21.,  21., ...,  46.,  46.,  46.],\n",
       "       [ 11.,  11.,  11., ...,  11.,  11.,  11.],\n",
       "       ...,\n",
       "       [ 30.,  30.,  30., ...,  30.,  30.,  30.],\n",
       "       [ 48.,  48.,  48., ...,  58.,  58.,  58.],\n",
       "       [ 77.,  77.,  77., ..., 121., 121., 121.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>frag_events</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-ca1db545-0bba-4848-a92e-6fc1c793fa6b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca1db545-0bba-4848-a92e-6fc1c793fa6b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd491355-9521-49c3-9f4c-f56b442197b1' class='xr-var-data-in' type='checkbox'><label for='data-cd491355-9521-49c3-9f4c-f56b442197b1' 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></dd><dt><span>standard_name :</span></dt><dd>frag_events</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[0., 0., 0., ..., 1., 1., 1.],\n",
       "       [0., 0., 0., ..., 1., 1., 1.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       ...,\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 1., 1., 1.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>in_ml</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-ad2d253f-b57b-410e-a6b3-94e7ec104609' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad2d253f-b57b-410e-a6b3-94e7ec104609' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85d08773-a6f1-4b71-95fe-0fe20156abbf' class='xr-var-data-in' type='checkbox'><label for='data-85d08773-a6f1-4b71-95fe-0fe20156abbf' 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></dd><dt><span>standard_name :</span></dt><dd>in_ml</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       ...,\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>kz</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.588e-05 1.603e-05 ... 1.238e-05</div><input id='attrs-cc4b0dcf-46b0-4b01-8d37-bef848b4b61e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc4b0dcf-46b0-4b01-8d37-bef848b4b61e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f457c9bc-75ff-4ce3-a224-366df635e2c9' class='xr-var-data-in' type='checkbox'><label for='data-f457c9bc-75ff-4ce3-a224-366df635e2c9' 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></dd><dt><span>standard_name :</span></dt><dd>kz</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[1.58766834e-05, 1.60255768e-05, 1.61421758e-05, ...,\n",
       "        4.86412877e-03, 2.63872966e-02, 2.97758728e-01],\n",
       "       [3.90189271e-05, 4.15598333e-05, 4.23895144e-05, ...,\n",
       "        2.70439687e-05, 2.63230504e-05, 2.59263597e-05],\n",
       "       [1.66555765e-05, 1.64283483e-05, 1.61901062e-05, ...,\n",
       "        1.33524136e-05, 1.34130169e-05, 1.34670863e-05],\n",
       "       ...,\n",
       "       [1.51839076e-05, 1.53112742e-05, 1.50001815e-05, ...,\n",
       "        2.19459580e-05, 2.16322678e-05, 3.05683498e-05],\n",
       "       [3.81311293e-05, 4.04309067e-05, 3.66600434e-05, ...,\n",
       "        4.82747518e-02, 5.89918531e-02, 1.52347703e-02],\n",
       "       [1.96287401e-05, 2.23038278e-05, 2.07402773e-05, ...,\n",
       "        1.37462121e-05, 1.39884187e-05, 1.23836535e-05]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-36.51 -36.53 ... -39.62 -39.41</div><input id='attrs-e075bedd-fa68-4ac7-9e5f-02bbae156452' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e075bedd-fa68-4ac7-9e5f-02bbae156452' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af029393-7535-4223-ba0c-d254f61b793d' class='xr-var-data-in' type='checkbox'><label for='data-af029393-7535-4223-ba0c-d254f61b793d' 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>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([[-36.51212471, -36.52741794, -36.54348024, ..., -38.01032684,\n",
       "        -38.09117123, -38.23322188],\n",
       "       [-47.1712654 , -47.19138463, -47.20782633, ..., -45.28974138,\n",
       "        -45.29442674, -45.29755497],\n",
       "       [-34.39927255, -34.40100272, -34.40013323, ..., -43.08064038,\n",
       "        -43.07830648, -43.07538899],\n",
       "       ...,\n",
       "       [-35.38532342, -35.3395228 , -35.28315371, ..., -32.43200713,\n",
       "        -32.41201872, -32.39146133],\n",
       "       [-40.28605215, -40.29805437, -40.33450197, ..., -37.15688528,\n",
       "        -37.11983817, -37.07900523],\n",
       "       [-40.69619679, -40.76512772, -40.83717239, ..., -39.84860174,\n",
       "        -39.61646534, -39.40964097]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.6491 -0.6439 ... 17.7 17.92</div><input id='attrs-8341dc18-c323-4793-a1f4-987393784813' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8341dc18-c323-4793-a1f4-987393784813' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c7b8afca-895a-4583-888e-4649eec71d18' class='xr-var-data-in' type='checkbox'><label for='data-c7b8afca-895a-4583-888e-4649eec71d18' 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>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([[-0.6490821 , -0.64391709, -0.62901375, ..., 21.37766704,\n",
       "        21.33235831, 21.38230184],\n",
       "       [21.52542761, 21.53425358, 21.54448679, ..., 23.55226535,\n",
       "        23.54952556, 23.54614042],\n",
       "       [ 8.0280081 ,  8.0857738 ,  8.14246865, ..., 14.72759042,\n",
       "        14.70897275, 14.68947125],\n",
       "       ...,\n",
       "       [ 7.06395533,  6.99323056,  6.93209113, ..., -8.81206239,\n",
       "        -8.77243177, -8.75266745],\n",
       "       [ 4.31325805,  4.28041413,  4.26045623, ...,  4.69095085,\n",
       "         4.73228884,  4.78663488],\n",
       "       [16.23816589, 16.28650456, 16.29552657, ..., 17.47907331,\n",
       "        17.69709716, 17.91909373]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>particle_density</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.38e+03 1.38e+03 ... 1.38e+03</div><input id='attrs-92f25711-26f8-4bf4-ad52-b8a47e7ace34' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-92f25711-26f8-4bf4-ad52-b8a47e7ace34' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6962179-f359-4de7-add8-6e9341234eef' class='xr-var-data-in' type='checkbox'><label for='data-a6962179-f359-4de7-add8-6e9341234eef' 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></dd><dt><span>standard_name :</span></dt><dd>particle_density</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[1380., 1380., 1380., ..., 1380., 1380., 1380.],\n",
       "       [1380., 1380., 1380., ..., 1380., 1380., 1380.],\n",
       "       [1380., 1380., 1380., ..., 1380., 1380., 1380.],\n",
       "       ...,\n",
       "       [1380., 1380., 1380., ..., 1380., 1380., 1380.],\n",
       "       [1380., 1380., 1380., ..., 1380., 1380., 1380.],\n",
       "       [1380., 1380., 1380., ..., 1380., 1380., 1380.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>radius</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.221e-07 4.221e-07 ... 2.828e-07</div><input id='attrs-bb27e577-15b3-4561-a285-d78b65c3f1eb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bb27e577-15b3-4561-a285-d78b65c3f1eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dfc50221-9014-461d-9f71-b2062caf3fbf' class='xr-var-data-in' type='checkbox'><label for='data-dfc50221-9014-461d-9f71-b2062caf3fbf' 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></dd><dt><span>standard_name :</span></dt><dd>radius</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[4.22100463e-07, 4.22100463e-07, 4.22100463e-07, ...,\n",
       "        3.37680371e-06, 3.37680371e-06, 3.37680371e-06],\n",
       "       [4.96517676e-07, 4.96517676e-07, 4.96517676e-07, ...,\n",
       "        3.97214141e-06, 3.97214141e-06, 3.97214141e-06],\n",
       "       [1.86342351e-07, 1.86342351e-07, 1.86342351e-07, ...,\n",
       "        1.86342351e-07, 1.86342351e-07, 1.86342351e-07],\n",
       "       ...,\n",
       "       [4.58297622e-07, 4.58297622e-07, 4.58297622e-07, ...,\n",
       "        4.58297622e-07, 4.58297622e-07, 4.58297622e-07],\n",
       "       [1.77726796e-07, 1.77726796e-07, 1.77726796e-07, ...,\n",
       "        1.42181437e-06, 1.42181437e-06, 1.42181437e-06],\n",
       "       [2.82760863e-07, 2.82760863e-07, 2.82760863e-07, ...,\n",
       "        2.82760863e-07, 2.82760863e-07, 2.82760863e-07]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2011-03-10T12:00:00 ... 2007-01-...</div><input id='attrs-d577fff2-42e1-4480-841b-cc8bb4c58628' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d577fff2-42e1-4480-841b-cc8bb4c58628' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8767bf16-89ba-4e6d-884f-62b01c9306d6' class='xr-var-data-in' type='checkbox'><label for='data-8767bf16-89ba-4e6d-884f-62b01c9306d6' 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>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([[&#x27;2011-03-10T12:00:00.000000000&#x27;, &#x27;2011-03-09T12:00:00.000000000&#x27;,\n",
       "        &#x27;2011-03-08T12:00:00.000000000&#x27;, ...,\n",
       "        &#x27;2007-01-03T12:00:00.000000000&#x27;, &#x27;2007-01-02T12:00:00.000000000&#x27;,\n",
       "        &#x27;2007-01-01T12:00:00.000000000&#x27;],\n",
       "       [&#x27;2011-03-10T12:00:00.000000000&#x27;, &#x27;2011-03-09T12:00:00.000000000&#x27;,\n",
       "        &#x27;2011-03-08T12:00:00.000000000&#x27;, ...,\n",
       "        &#x27;2007-01-03T12:00:00.000000000&#x27;, &#x27;2007-01-02T12:00:00.000000000&#x27;,\n",
       "        &#x27;2007-01-01T12:00:00.000000000&#x27;],\n",
       "       [&#x27;2011-03-10T12:00:00.000000000&#x27;, &#x27;2011-03-09T12:00:00.000000000&#x27;,\n",
       "        &#x27;2011-03-08T12:00:00.000000000&#x27;, ...,\n",
       "        &#x27;2007-01-03T12:00:00.000000000&#x27;, &#x27;2007-01-02T12:00:00.000000000&#x27;,\n",
       "        &#x27;2007-01-01T12:00:00.000000000&#x27;],\n",
       "       ...,\n",
       "       [&#x27;2011-03-10T12:00:00.000000000&#x27;, &#x27;2011-03-09T12:00:00.000000000&#x27;,\n",
       "        &#x27;2011-03-08T12:00:00.000000000&#x27;, ...,\n",
       "        &#x27;2007-01-03T12:00:00.000000000&#x27;, &#x27;2007-01-02T12:00:00.000000000&#x27;,\n",
       "        &#x27;2007-01-01T12:00:00.000000000&#x27;],\n",
       "       [&#x27;2011-03-10T12:00:00.000000000&#x27;, &#x27;2011-03-09T12:00:00.000000000&#x27;,\n",
       "        &#x27;2011-03-08T12:00:00.000000000&#x27;, ...,\n",
       "        &#x27;2007-01-03T12:00:00.000000000&#x27;, &#x27;2007-01-02T12:00:00.000000000&#x27;,\n",
       "        &#x27;2007-01-01T12:00:00.000000000&#x27;],\n",
       "       [&#x27;2011-03-10T12:00:00.000000000&#x27;, &#x27;2011-03-09T12:00:00.000000000&#x27;,\n",
       "        &#x27;2011-03-08T12:00:00.000000000&#x27;, ...,\n",
       "        &#x27;2007-01-03T12:00:00.000000000&#x27;, &#x27;2007-01-02T12:00:00.000000000&#x27;,\n",
       "        &#x27;2007-01-01T12:00:00.000000000&#x27;]], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-4.718e-08 ... -3.068e-06</div><input id='attrs-81e2ad78-c739-4f94-8ecd-a27ac017b8cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-81e2ad78-c739-4f94-8ecd-a27ac017b8cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a9cec742-27e4-4611-8c5e-094c0fb7fcb2' class='xr-var-data-in' type='checkbox'><label for='data-a9cec742-27e4-4611-8c5e-094c0fb7fcb2' 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></dd><dt><span>standard_name :</span></dt><dd>u</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[-4.7183811e-08, -7.0534227e-08, -2.1265240e-07, ...,\n",
       "         8.6405936e-07,  3.4143333e-08, -8.3815797e-07],\n",
       "       [-8.2932452e-08, -1.1985335e-07, -1.1633100e-07, ...,\n",
       "         3.0441818e-08,  3.4166835e-08,  4.3629083e-08],\n",
       "       [-6.7391312e-07, -6.7264693e-07, -6.5084652e-07, ...,\n",
       "         2.2560467e-07,  2.0781201e-07,  2.4301607e-07],\n",
       "       ...,\n",
       "       [ 9.7242241e-07,  8.2108568e-07,  6.4026943e-07, ...,\n",
       "        -4.3937987e-07, -4.6922676e-07, -2.1254215e-07],\n",
       "       [ 3.3788359e-07,  4.0434139e-07,  7.9094072e-08, ...,\n",
       "        -4.1739568e-07, -6.2094745e-07, -6.3719517e-07],\n",
       "       [-7.7716896e-07, -2.2424622e-07,  2.7953703e-07, ...,\n",
       "        -2.1549870e-06, -2.5713455e-06, -3.0675251e-06]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.72e-07 1.812e-07 ... -2.246e-06</div><input id='attrs-87011b0f-977c-41e9-a8c7-8dbaeda848c7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-87011b0f-977c-41e9-a8c7-8dbaeda848c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fda3603d-6678-4d9e-b74c-08e25433e09b' class='xr-var-data-in' type='checkbox'><label for='data-fda3603d-6678-4d9e-b74c-08e25433e09b' 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></dd><dt><span>standard_name :</span></dt><dd>v</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.7204972e-07,  1.8122762e-07,  1.9038325e-07, ...,\n",
       "         2.7003975e-07,  1.4102476e-06,  9.5205621e-07],\n",
       "       [ 2.2750953e-07,  2.3681150e-07,  6.8942462e-08, ...,\n",
       "         6.2967473e-08,  4.5463732e-08,  2.8547525e-08],\n",
       "       [ 5.9702096e-08,  1.1751988e-08, -6.4509031e-08, ...,\n",
       "        -2.7167390e-08, -2.6440448e-08, -3.5348823e-08],\n",
       "       ...,\n",
       "       [-3.9461406e-07, -5.9433091e-07, -7.0875603e-07, ...,\n",
       "        -2.2994061e-07, -2.3103264e-07, -2.4006999e-07],\n",
       "       [-1.8990263e-09,  3.7948425e-07,  4.6026409e-07, ...,\n",
       "        -3.9056417e-07, -4.6437984e-07, -4.7831082e-07],\n",
       "       [ 8.5213208e-07,  7.6496383e-07,  8.1610585e-07, ...,\n",
       "        -2.9381249e-06, -2.5157278e-06, -2.2460720e-06]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v_s</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>8.861e-08 8.861e-08 ... 3.979e-08</div><input id='attrs-95dcc32d-d700-47e6-bd30-16838dceb535' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-95dcc32d-d700-47e6-bd30-16838dceb535' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fdbc360e-2e5d-4f30-9738-baa72f7f1569' class='xr-var-data-in' type='checkbox'><label for='data-fdbc360e-2e5d-4f30-9738-baa72f7f1569' 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></dd><dt><span>standard_name :</span></dt><dd>v_s</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[8.86101645e-08, 8.86103280e-08, 8.86102498e-08, ...,\n",
       "        5.66899598e-06, 5.66898007e-06, 5.66911740e-06],\n",
       "       [1.22606977e-07, 1.22606465e-07, 1.22606124e-07, ...,\n",
       "        7.84228632e-06, 7.84231179e-06, 7.84231906e-06],\n",
       "       [1.72738197e-08, 1.72739725e-08, 1.72740133e-08, ...,\n",
       "        1.72752834e-08, 1.72752443e-08, 1.72751875e-08],\n",
       "       ...,\n",
       "       [1.04519692e-07, 1.04522272e-07, 1.04523878e-07, ...,\n",
       "        1.04551418e-07, 1.04550885e-07, 1.04551468e-07],\n",
       "       [1.57102278e-08, 1.57102207e-08, 1.57103752e-08, ...,\n",
       "        1.00563193e-06, 1.00561454e-06, 1.00560987e-06],\n",
       "       [3.97631830e-08, 3.97620354e-08, 3.97632753e-08, ...,\n",
       "        3.97846449e-08, 3.97909794e-08, 3.97891107e-08]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>w</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>2.378e-05 2.331e-05 ... -0.0004499</div><input id='attrs-08413209-efbc-4f64-a44e-751c0a97ae62' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-08413209-efbc-4f64-a44e-751c0a97ae62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7295877-47a0-4e96-a9fd-ee8244bd8a94' class='xr-var-data-in' type='checkbox'><label for='data-d7295877-47a0-4e96-a9fd-ee8244bd8a94' 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></dd><dt><span>standard_name :</span></dt><dd>w</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[ 2.37838176e-05,  2.33113933e-05,  5.81873464e-05, ...,\n",
       "        -7.06969004e-04,  2.94966274e-04,  4.09309578e-04],\n",
       "       [-1.07988475e-04, -8.56043625e-05, -7.79657785e-05, ...,\n",
       "         5.78790750e-05,  2.57019346e-05,  3.04499754e-05],\n",
       "       [-2.80748878e-04, -8.30849749e-05,  1.32569849e-05, ...,\n",
       "         5.86296446e-05,  5.49927681e-05, -3.75255445e-06],\n",
       "       ...,\n",
       "       [-3.58582416e-04, -4.14306181e-04, -3.06497794e-04, ...,\n",
       "         3.96556388e-05,  1.35161230e-04, -2.86427112e-05],\n",
       "       [ 1.74739966e-04,  7.21122924e-05,  3.81471327e-05, ...,\n",
       "        -1.11488283e-04, -3.10471572e-04, -3.20642401e-04],\n",
       "       [ 7.24372512e-05, -3.03128152e-04, -4.78114322e-04, ...,\n",
       "         4.95834800e-04,  4.62717609e-04, -4.49943152e-04]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.822e+03 4.819e+03 ... 3.67e+03</div><input id='attrs-01c8c523-109b-42c8-8519-de982ddcf003' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-01c8c523-109b-42c8-8519-de982ddcf003' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b26cff9-afff-4e50-a1db-e454fe66af75' class='xr-var-data-in' type='checkbox'><label for='data-7b26cff9-afff-4e50-a1db-e454fe66af75' 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></dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([[4821.85670221, 4819.4947554 , 4816.03432076, ..., 5186.55742492,\n",
       "        5162.6930849 , 5176.2526331 ],\n",
       "       [4122.0565247 , 4130.29042091, 4142.46576001, ..., 4994.20497186,\n",
       "        4988.97836453, 4986.97569315],\n",
       "       [4505.91258573, 4515.75884461, 4519.36805625, ..., 3987.34404124,\n",
       "        3983.20646836, 3983.47003453],\n",
       "       ...,\n",
       "       [4023.56908441, 4053.45895471, 4086.5851885 , ..., 3599.08025588,\n",
       "        3590.14254875, 3590.72382537],\n",
       "       [4587.65865942, 4572.7955389 , 4570.51209835, ..., 4241.847452  ,\n",
       "        4349.65075514, 4359.53334429],\n",
       "       [4531.76452092, 4574.70125091, 4590.14706074, ..., 3815.10766611,\n",
       "        3775.3452144 , 3669.75916961]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z_kz</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.1781 0.3619 ... -0.5244 0.2405</div><input id='attrs-4fac685f-f287-465f-b824-b0312c46fdde' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4fac685f-f287-465f-b824-b0312c46fdde' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6658c1b4-dad2-4e99-b90b-f05fc4504a6a' class='xr-var-data-in' type='checkbox'><label for='data-6658c1b4-dad2-4e99-b90b-f05fc4504a6a' 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></dd><dt><span>standard_name :</span></dt><dd>z_kz</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[-1.78108588e-01,  3.61850500e-01,  2.62224488e-02, ...,\n",
       "        -7.22356319e+00, -2.17589588e+01,  4.85986748e+01],\n",
       "       [ 8.06251705e-01, -1.14210695e-01, -9.53459814e-02, ...,\n",
       "         5.45314560e-03,  3.10939550e-01, -3.79161566e-01],\n",
       "       [ 4.96809334e-01, -5.33075333e-01, -3.17433625e-01, ...,\n",
       "         9.55590159e-02,  8.60733539e-02, -1.22570969e-01],\n",
       "       ...,\n",
       "       [-2.50802338e-01,  1.28664091e-01, -3.94546330e-01, ...,\n",
       "        -6.51491284e-01,  5.70554554e-01, -7.24027529e-02],\n",
       "       [ 8.49546134e-01, -8.24079990e-01,  4.40200031e-01, ...,\n",
       "        -2.16756859e+01,  2.08708439e+01,  1.39247179e+01],\n",
       "       [-4.71588433e-01,  5.55114806e-01,  6.11314833e-01, ...,\n",
       "        -2.35051841e-01, -5.24380207e-01,  2.40503713e-01]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7a961751-732a-485b-93bf-0e460a363a7b' class='xr-section-summary-in' type='checkbox'  ><label for='section-7a961751-732a-485b-93bf-0e460a363a7b' class='xr-section-summary' >Indexes: <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-index-name'><div>obs</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bb8c4f3f-2e55-4ec2-a961-1ec9e1f33826' class='xr-index-data-in' type='checkbox'/><label for='index-bb8c4f3f-2e55-4ec2-a961-1ec9e1f33826' 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(Int64Index([   0,    1,    2,    3,    4,    5,    6,    7,    8,    9,\n",
       "            ...\n",
       "            1520, 1521, 1522, 1523, 1524, 1525, 1526, 1527, 1528, 1529],\n",
       "           dtype=&#x27;int64&#x27;, name=&#x27;obs&#x27;, length=1530))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>trajectory</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-369963ad-ee96-47d9-8388-623f51f4cf2d' class='xr-index-data-in' type='checkbox'/><label for='index-369963ad-ee96-47d9-8388-623f51f4cf2d' 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(Int64Index([   0,    1,    2,    3,    4,    5,    6,    7,    8,    9,\n",
       "            ...\n",
       "            8182, 8183, 8184, 8185, 8186, 8187, 8188, 8189, 8190, 8191],\n",
       "           dtype=&#x27;int64&#x27;, name=&#x27;trajectory&#x27;, length=8192))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-901dd3c4-0f6b-4867-bef4-89c00cc463e8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-901dd3c4-0f6b-4867-bef4-89c00cc463e8' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6/CF-1.7</dd><dt><span>feature_type :</span></dt><dd>trajectory</dd><dt><span>ncei_template_version :</span></dt><dd>NCEI_NetCDF_Trajectory_Template_v2.0</dd><dt><span>parcels_mesh :</span></dt><dd>spherical</dd><dt><span>parcels_version :</span></dt><dd>2.4.2</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:           (trajectory: 8192, obs: 1530)\n",
       "Coordinates:\n",
       "  * obs               (obs) int32 0 1 2 3 4 5 ... 1524 1525 1526 1527 1528 1529\n",
       "  * trajectory        (trajectory) int64 0 1 2 3 4 ... 8187 8188 8189 8190 8191\n",
       "Data variables: (12/20)\n",
       "    abs_salinity      (trajectory, obs) float32 34.74 34.74 34.74 ... 34.81 34.8\n",
       "    bottom            (trajectory, obs) float32 5.052e+03 ... 4.617e+03\n",
       "    cons_temperature  (trajectory, obs) float32 0.6724 0.6733 ... 1.535 1.359\n",
       "    density           (trajectory, obs) float32 1.028e+03 ... 1.028e+03\n",
       "    distance          (trajectory, obs) float32 51.0 51.0 51.0 ... 51.0 51.0\n",
       "    floored           (trajectory, obs) float32 96.0 96.0 96.0 ... 121.0 121.0\n",
       "    ...                ...\n",
       "    u                 (trajectory, obs) float32 -4.718e-08 ... -3.068e-06\n",
       "    v                 (trajectory, obs) float32 1.72e-07 ... -2.246e-06\n",
       "    v_s               (trajectory, obs) float32 8.861e-08 ... 3.979e-08\n",
       "    w                 (trajectory, obs) float32 2.378e-05 ... -0.0004499\n",
       "    z                 (trajectory, obs) float64 4.822e+03 4.819e+03 ... 3.67e+03\n",
       "    z_kz              (trajectory, obs) float32 -0.1781 0.3619 ... 0.2405\n",
       "Attributes:\n",
       "    Conventions:            CF-1.6/CF-1.7\n",
       "    feature_type:           trajectory\n",
       "    ncei_template_version:  NCEI_NetCDF_Trajectory_Template_v2.0\n",
       "    parcels_mesh:           spherical\n",
       "    parcels_version:        2.4.2"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "part2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b02220f7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fa6d0585eb0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pp = 40\n",
    "\n",
    "plt.plot(part2.lon[pp, :5], part2.lat[pp, :5], 'bs', label='part2')\n",
    "plt.plot(part1.lon[pp,-7:], part1.lat[pp,-7:], 'r.', label='part1')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "cc80dc29",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fa6e366f280>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pp = 40\n",
    "plt.plot(part2.time[pp, :5], part2.cons_temperature[pp, :5], 'bs', label='part2')\n",
    "plt.plot(part1.time[pp, -7:], part1.cons_temperature[pp,-7:], 'r.', label='part1')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a35a030",
   "metadata": {},
   "source": [
    "> The two first timesteps of `part2` are the last ones of `part1`. We need to drop them and concatenate both Datasets into one."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "729f527f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# The two first timesteps of `part2` are the last ones of `part1`. We need to drop them and concatenate both Datasets into one\n",
    "part1_a = part1.isel(obs=slice(0,-2))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "183bfadf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fa6e35bf430>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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MR2ABAADGI7AAAADj/X95C4Mq4mUkOAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pp = 40\n",
    "plt.plot(part2.time[pp, :5], part2.cons_temperature[pp, :5], 'bs', label='part2')\n",
    "plt.plot(part1_a.time[pp, -7:], part1_a.cons_temperature[pp,-7:], 'r.', label='part1_a')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5b9326b3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# concatenate both datasets in the obs dimension\n",
    "full = xr.concat([part1_a, part2], dim='obs')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "da6f3464",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:           (trajectory: 8192, obs: 4403)\n",
       "Coordinates:\n",
       "  * obs               (obs) int32 0 1 2 3 4 5 ... 1524 1525 1526 1527 1528 1529\n",
       "  * trajectory        (trajectory) int64 0 1 2 3 4 ... 8187 8188 8189 8190 8191\n",
       "Data variables: (12/20)\n",
       "    abs_salinity      (trajectory, obs) float32 34.75 34.75 34.75 ... 34.81 34.8\n",
       "    bottom            (trajectory, obs) float32 5.5e+03 5.5e+03 ... 4.617e+03\n",
       "    cons_temperature  (trajectory, obs) float32 0.755 0.7429 ... 1.535 1.359\n",
       "    density           (trajectory, obs) float32 1.028e+03 ... 1.028e+03\n",
       "    distance          (trajectory, obs) float32 51.0 51.0 51.0 ... 51.0 51.0\n",
       "    floored           (trajectory, obs) float32 0.0 0.0 0.0 ... 121.0 121.0\n",
       "    ...                ...\n",
       "    u                 (trajectory, obs) float32 0.0 3.982e-07 ... -3.068e-06\n",
       "    v                 (trajectory, obs) float32 0.0 -4.395e-07 ... -2.246e-06\n",
       "    v_s               (trajectory, obs) float32 8.861e-08 ... 3.979e-08\n",
       "    w                 (trajectory, obs) float32 0.0 -0.0002636 ... -0.0004499\n",
       "    z                 (trajectory, obs) float64 5e+03 5.019e+03 ... 3.67e+03\n",
       "    z_kz              (trajectory, obs) float32 0.0 1.721 ... -0.5244 0.2405\n",
       "Attributes:\n",
       "    Conventions:            CF-1.6/CF-1.7\n",
       "    feature_type:           trajectory\n",
       "    ncei_template_version:  NCEI_NetCDF_Trajectory_Template_v2.0\n",
       "    parcels_mesh:           spherical\n",
       "    parcels_version:        2.4.2</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-3fa02c5c-fdcb-4a1c-bbf7-68d2559acf85' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3fa02c5c-fdcb-4a1c-bbf7-68d2559acf85' 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'>trajectory</span>: 8192</li><li><span class='xr-has-index'>obs</span>: 4403</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-075f5208-8d15-4a04-95c0-b67fc9f255dc' class='xr-section-summary-in' type='checkbox'  checked><label for='section-075f5208-8d15-4a04-95c0-b67fc9f255dc' 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'>obs</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1526 1527 1528 1529</div><input id='attrs-6bf53f4d-6198-40b2-8a30-2fcf9c45902c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6bf53f4d-6198-40b2-8a30-2fcf9c45902c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c547ba05-ae03-4168-b213-9712ece3570d' class='xr-var-data-in' type='checkbox'><label for='data-c547ba05-ae03-4168-b213-9712ece3570d' 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'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1527, 1528, 1529], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>trajectory</span></div><div class='xr-var-dims'>(trajectory)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 8188 8189 8190 8191</div><input id='attrs-8de9892c-b949-4e56-a666-d6bd08b54d31' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8de9892c-b949-4e56-a666-d6bd08b54d31' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97fe6c96-b7df-4ceb-898a-40b421ffb0c3' class='xr-var-data-in' type='checkbox'><label for='data-97fe6c96-b7df-4ceb-898a-40b421ffb0c3' 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'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 8189, 8190, 8191])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a616a179-6918-4cc4-be50-cec7e8677693' class='xr-section-summary-in' type='checkbox'  ><label for='section-a616a179-6918-4cc4-be50-cec7e8677693' class='xr-section-summary' >Data variables: <span>(20)</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>abs_salinity</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>34.75 34.75 34.75 ... 34.81 34.8</div><input id='attrs-f4b8ad15-b0a3-4f20-be28-0f4c0c11c9c4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f4b8ad15-b0a3-4f20-be28-0f4c0c11c9c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65e1bad7-4a7c-48ae-bfd2-6fcd627a1cd5' class='xr-var-data-in' type='checkbox'><label for='data-65e1bad7-4a7c-48ae-bfd2-6fcd627a1cd5' 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></dd><dt><span>standard_name :</span></dt><dd>abs_salinity</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[34.74838 , 34.749405, 34.74884 , ..., 34.710144, 34.70965 ,\n",
       "        34.71072 ],\n",
       "       [34.749557, 34.749405, 34.74884 , ..., 34.690674, 34.690674,\n",
       "        34.690678],\n",
       "       [34.74838 , 34.749405, 34.74884 , ..., 34.729843, 34.72913 ,\n",
       "        34.728027],\n",
       "       ...,\n",
       "       [34.74838 , 34.749012, 34.74884 , ..., 34.87157 , 34.87173 ,\n",
       "        34.871758],\n",
       "       [34.74838 , 34.749405, 34.74884 , ..., 34.733746, 34.73411 ,\n",
       "        34.733894],\n",
       "       [34.749557, 34.749405, 34.74884 , ..., 34.772865, 34.813034,\n",
       "        34.798264]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>bottom</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>5.5e+03 5.5e+03 ... 4.617e+03</div><input id='attrs-0f9e840f-f151-495b-baf9-b79bdac25583' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0f9e840f-f151-495b-baf9-b79bdac25583' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-194d0134-e6a3-426f-a996-7f6f419a6679' class='xr-var-data-in' type='checkbox'><label for='data-194d0134-e6a3-426f-a996-7f6f419a6679' 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></dd><dt><span>standard_name :</span></dt><dd>bottom</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[5500.0015, 5500.0015, 5500.0015, ..., 5500.0015, 5500.0015,\n",
       "        5500.0015],\n",
       "       [5500.0015, 5500.0015, 5500.0015, ..., 5500.0015, 5500.0015,\n",
       "        5500.0015],\n",
       "       [5500.0015, 5500.0015, 5500.0015, ..., 4617.4624, 4617.4624,\n",
       "        5052.474 ],\n",
       "       ...,\n",
       "       [5500.0015, 5500.0015, 5500.0015, ..., 4196.816 , 4617.4624,\n",
       "        4196.816 ],\n",
       "       [5500.0015, 5500.0015, 5500.0015, ..., 5052.474 , 5500.0015,\n",
       "        5500.0015],\n",
       "       [5500.0015, 5500.0015, 5500.0015, ..., 5052.474 , 5052.474 ,\n",
       "        4617.4624]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cons_temperature</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.755 0.7429 0.7481 ... 1.535 1.359</div><input id='attrs-05206992-ffda-4180-8f54-9bb01fc100f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-05206992-ffda-4180-8f54-9bb01fc100f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13a51f62-e0e3-4286-afec-c54985f6386c' class='xr-var-data-in' type='checkbox'><label for='data-13a51f62-e0e3-4286-afec-c54985f6386c' 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></dd><dt><span>standard_name :</span></dt><dd>cons_temperature</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.75500983,  0.74287575,  0.7480616 , ...,  0.38604578,\n",
       "         0.3782125 ,  0.389283  ],\n",
       "       [ 0.74459046,  0.74287575,  0.7480616 , ..., -0.0363351 ,\n",
       "        -0.03494737, -0.0346791 ],\n",
       "       [ 0.75500983,  0.74287575,  0.7480616 , ...,  0.76204836,\n",
       "         0.7537743 ,  0.74429846],\n",
       "       ...,\n",
       "       [ 0.75500983,  0.74967885,  0.7480616 , ...,  2.0370247 ,\n",
       "         2.027865  ,  2.0365455 ],\n",
       "       [ 0.75500983,  0.74287575,  0.7480616 , ...,  0.7658431 ,\n",
       "         0.77142155,  0.77154964],\n",
       "       [ 0.74459046,  0.74287575,  0.7480616 , ...,  1.1361235 ,\n",
       "         1.5353706 ,  1.3586261 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>density</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.028e+03 1.028e+03 ... 1.028e+03</div><input id='attrs-86c7cb40-5fa6-4548-b703-c9a13f41b5e6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-86c7cb40-5fa6-4548-b703-c9a13f41b5e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-948cc140-9b8a-4d8f-ab16-0d19ae9ba231' class='xr-var-data-in' type='checkbox'><label for='data-948cc140-9b8a-4d8f-ab16-0d19ae9ba231' 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></dd><dt><span>standard_name :</span></dt><dd>density</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[1028.1653, 1028.1698, 1028.1705, ..., 1028.2262, 1028.2269,\n",
       "        1028.2206],\n",
       "       [1028.1682, 1028.1704, 1028.1709, ..., 1028.2764, 1028.2755,\n",
       "        1028.2753],\n",
       "       [1028.1653, 1028.1696, 1028.1694, ..., 1028.068 , 1028.0686,\n",
       "        1028.0695],\n",
       "       ...,\n",
       "       [1028.1653, 1028.1677, 1028.1693, ..., 1027.9271, 1027.9285,\n",
       "        1027.927 ],\n",
       "       [1028.1653, 1028.1691, 1028.1703, ..., 1028.0929, 1028.0974,\n",
       "        1028.0986],\n",
       "       [1028.1682, 1028.1705, 1028.1702, ..., 1028.0227, 1027.981 ,\n",
       "        1027.9933]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>distance</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>51.0 51.0 51.0 ... 51.0 51.0 51.0</div><input id='attrs-ea63f80a-70b6-4e7a-9d46-ff0a5371df02' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea63f80a-70b6-4e7a-9d46-ff0a5371df02' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c363ec89-3e4d-48ff-94cd-f75bc03f585b' class='xr-var-data-in' type='checkbox'><label for='data-c363ec89-3e4d-48ff-94cd-f75bc03f585b' 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></dd><dt><span>standard_name :</span></dt><dd>distance</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[51., 51., 51., ..., 51., 51., 51.],\n",
       "       [51., 51., 51., ..., 51., 51., 51.],\n",
       "       [51., 51., 51., ..., 51., 51., 51.],\n",
       "       ...,\n",
       "       [51., 51., 51., ..., 51., 51., 51.],\n",
       "       [51., 51., 51., ..., 51., 51., 51.],\n",
       "       [51., 51., 51., ..., 51., 51., 51.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>floored</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... 121.0 121.0 121.0</div><input id='attrs-d3c75909-2c11-47ce-910f-f68b0c9ccbcf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3c75909-2c11-47ce-910f-f68b0c9ccbcf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c7c1af65-f700-4f4d-a09c-2ea6d3d98a85' class='xr-var-data-in' type='checkbox'><label for='data-c7c1af65-f700-4f4d-a09c-2ea6d3d98a85' 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></dd><dt><span>standard_name :</span></dt><dd>floored</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[  0.,   0.,   0., ..., 134., 134., 134.],\n",
       "       [  0.,   0.,   0., ...,  46.,  46.,  46.],\n",
       "       [  0.,   0.,   0., ...,  11.,  11.,  11.],\n",
       "       ...,\n",
       "       [  0.,   0.,   0., ...,  30.,  30.,  30.],\n",
       "       [  0.,   0.,   0., ...,  58.,  58.,  58.],\n",
       "       [  0.,   0.,   0., ..., 121., 121., 121.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>frag_events</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-3c6864af-a59f-40f7-b19f-b921d0c431e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c6864af-a59f-40f7-b19f-b921d0c431e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df60a91e-e07f-4c14-a891-250eb0b06ec4' class='xr-var-data-in' type='checkbox'><label for='data-df60a91e-e07f-4c14-a891-250eb0b06ec4' 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></dd><dt><span>standard_name :</span></dt><dd>frag_events</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[0., 0., 0., ..., 1., 1., 1.],\n",
       "       [0., 0., 0., ..., 1., 1., 1.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       ...,\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 1., 1., 1.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>in_ml</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-29ed8303-d8d7-4f8d-aa78-337e917f2de0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29ed8303-d8d7-4f8d-aa78-337e917f2de0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4ecf5828-96e0-44c3-a192-0371b68a309f' class='xr-var-data-in' type='checkbox'><label for='data-4ecf5828-96e0-44c3-a192-0371b68a309f' 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></dd><dt><span>standard_name :</span></dt><dd>in_ml</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       ...,\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>kz</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0003607 ... 1.238e-05</div><input id='attrs-8d848432-4e26-4de8-81f2-9909ed81891a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d848432-4e26-4de8-81f2-9909ed81891a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a944398-b5ee-48cc-853c-44a27ebc9550' class='xr-var-data-in' type='checkbox'><label for='data-7a944398-b5ee-48cc-853c-44a27ebc9550' 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></dd><dt><span>standard_name :</span></dt><dd>kz</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[0.00000000e+00, 3.60702950e-04, 5.38648106e-04, ...,\n",
       "        4.86412877e-03, 2.63872966e-02, 2.97758728e-01],\n",
       "       [0.00000000e+00, 4.43489320e-04, 5.92517725e-04, ...,\n",
       "        2.70439687e-05, 2.63230504e-05, 2.59263597e-05],\n",
       "       [0.00000000e+00, 3.44462489e-04, 4.88008809e-04, ...,\n",
       "        1.33524136e-05, 1.34130169e-05, 1.34670863e-05],\n",
       "       ...,\n",
       "       [0.00000000e+00, 2.97742808e-04, 4.34357673e-04, ...,\n",
       "        2.19459580e-05, 2.16322678e-05, 3.05683498e-05],\n",
       "       [0.00000000e+00, 3.22033040e-04, 6.09793293e-04, ...,\n",
       "        4.82747518e-02, 5.89918531e-02, 1.52347703e-02],\n",
       "       [0.00000000e+00, 4.68405837e-04, 5.86793758e-04, ...,\n",
       "        1.37462121e-05, 1.39884187e-05, 1.23836535e-05]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-32.17 -32.13 ... -39.62 -39.41</div><input id='attrs-4364372b-565a-4c36-95d8-861881efcad1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4364372b-565a-4c36-95d8-861881efcad1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-80aa2d0e-39c1-4736-b022-aace8b37f648' class='xr-var-data-in' type='checkbox'><label for='data-80aa2d0e-39c1-4736-b022-aace8b37f648' 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>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([[-32.17170837, -32.13059055, -32.09489508, ..., -38.01032684,\n",
       "        -38.09117123, -38.23322188],\n",
       "       [-32.17008875, -32.12925211, -32.09376234, ..., -45.28974138,\n",
       "        -45.29442674, -45.29755497],\n",
       "       [-32.16992301, -32.12912808, -32.0936573 , ..., -43.08064038,\n",
       "        -43.07830648, -43.07538899],\n",
       "       ...,\n",
       "       [-32.16742837, -32.12706772, -32.09191188, ..., -32.43200713,\n",
       "        -32.41201872, -32.39146133],\n",
       "       [-32.17995947, -32.13742135, -32.10065609, ..., -37.15688528,\n",
       "        -37.11983817, -37.07900523],\n",
       "       [-32.16828966, -32.12776772, -32.0925049 , ..., -39.84860174,\n",
       "        -39.61646534, -39.40964097]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.292 6.259 6.235 ... 17.7 17.92</div><input id='attrs-685ed949-0d8b-423d-bfd5-0658c2c675d4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-685ed949-0d8b-423d-bfd5-0658c2c675d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-288fe54b-afbb-4999-8e7c-9881f49c866b' class='xr-var-data-in' type='checkbox'><label for='data-288fe54b-afbb-4999-8e7c-9881f49c866b' 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>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([[ 6.29196714,  6.25932257,  6.23465676, ..., 21.37766704,\n",
       "        21.33235831, 21.38230184],\n",
       "       [ 6.28561736,  6.25237037,  6.22768959, ..., 23.55226535,\n",
       "        23.54952556, 23.54614042],\n",
       "       [ 6.29347689,  6.26098219,  6.23700845, ..., 14.72759042,\n",
       "        14.70897275, 14.68947125],\n",
       "       ...,\n",
       "       [ 6.29646577,  6.26488686,  6.24132585, ..., -8.81206239,\n",
       "        -8.77243177, -8.75266745],\n",
       "       [ 6.29304052,  6.26049847,  6.23369919, ...,  4.69095085,\n",
       "         4.73228884,  4.78663488],\n",
       "       [ 6.28289971,  6.24982853,  6.22503323, ..., 17.47907331,\n",
       "        17.69709716, 17.91909373]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>particle_density</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.38e+03 1.38e+03 ... 1.38e+03</div><input id='attrs-f94a54dc-b1a6-45b4-8c03-1af3d0a2e625' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f94a54dc-b1a6-45b4-8c03-1af3d0a2e625' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ed142d12-428e-4ad0-b4b8-b3d636aa5da8' class='xr-var-data-in' type='checkbox'><label for='data-ed142d12-428e-4ad0-b4b8-b3d636aa5da8' 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></dd><dt><span>standard_name :</span></dt><dd>particle_density</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[1380., 1380., 1380., ..., 1380., 1380., 1380.],\n",
       "       [1380., 1380., 1380., ..., 1380., 1380., 1380.],\n",
       "       [1380., 1380., 1380., ..., 1380., 1380., 1380.],\n",
       "       ...,\n",
       "       [1380., 1380., 1380., ..., 1380., 1380., 1380.],\n",
       "       [1380., 1380., 1380., ..., 1380., 1380., 1380.],\n",
       "       [1380., 1380., 1380., ..., 1380., 1380., 1380.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>radius</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.221e-07 4.221e-07 ... 2.828e-07</div><input id='attrs-93d49813-8b29-49b7-83cc-07c2ea33726d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-93d49813-8b29-49b7-83cc-07c2ea33726d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a17774b-6cd0-4f84-9879-875a9c0016de' class='xr-var-data-in' type='checkbox'><label for='data-3a17774b-6cd0-4f84-9879-875a9c0016de' 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></dd><dt><span>standard_name :</span></dt><dd>radius</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[4.22100463e-07, 4.22100463e-07, 4.22100463e-07, ...,\n",
       "        3.37680371e-06, 3.37680371e-06, 3.37680371e-06],\n",
       "       [4.96517676e-07, 4.96517676e-07, 4.96517676e-07, ...,\n",
       "        3.97214141e-06, 3.97214141e-06, 3.97214141e-06],\n",
       "       [1.86342351e-07, 1.86342351e-07, 1.86342351e-07, ...,\n",
       "        1.86342351e-07, 1.86342351e-07, 1.86342351e-07],\n",
       "       ...,\n",
       "       [4.58297622e-07, 4.58297622e-07, 4.58297622e-07, ...,\n",
       "        4.58297622e-07, 4.58297622e-07, 4.58297622e-07],\n",
       "       [1.77726796e-07, 1.77726796e-07, 1.77726796e-07, ...,\n",
       "        1.42181437e-06, 1.42181437e-06, 1.42181437e-06],\n",
       "       [2.82760863e-07, 2.82760863e-07, 2.82760863e-07, ...,\n",
       "        2.82760863e-07, 2.82760863e-07, 2.82760863e-07]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-01-20T12:00:00 ... 2007-01-...</div><input id='attrs-8db6d4c6-cdf1-418d-bf06-c233ea77f0e5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8db6d4c6-cdf1-418d-bf06-c233ea77f0e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3ebdfbe-1052-4e41-b15c-842f5d3ec754' class='xr-var-data-in' type='checkbox'><label for='data-e3ebdfbe-1052-4e41-b15c-842f5d3ec754' 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>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd></dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([[&#x27;2019-01-20T12:00:00.000000000&#x27;, &#x27;2019-01-19T12:00:00.000000000&#x27;,\n",
       "        &#x27;2019-01-18T12:00:00.000000000&#x27;, ...,\n",
       "        &#x27;2007-01-03T12:00:00.000000000&#x27;, &#x27;2007-01-02T12:00:00.000000000&#x27;,\n",
       "        &#x27;2007-01-01T12:00:00.000000000&#x27;],\n",
       "       [&#x27;2019-01-20T12:00:00.000000000&#x27;, &#x27;2019-01-19T12:00:00.000000000&#x27;,\n",
       "        &#x27;2019-01-18T12:00:00.000000000&#x27;, ...,\n",
       "        &#x27;2007-01-03T12:00:00.000000000&#x27;, &#x27;2007-01-02T12:00:00.000000000&#x27;,\n",
       "        &#x27;2007-01-01T12:00:00.000000000&#x27;],\n",
       "       [&#x27;2019-01-20T12:00:00.000000000&#x27;, &#x27;2019-01-19T12:00:00.000000000&#x27;,\n",
       "        &#x27;2019-01-18T12:00:00.000000000&#x27;, ...,\n",
       "        &#x27;2007-01-03T12:00:00.000000000&#x27;, &#x27;2007-01-02T12:00:00.000000000&#x27;,\n",
       "        &#x27;2007-01-01T12:00:00.000000000&#x27;],\n",
       "       ...,\n",
       "       [&#x27;2019-01-20T12:00:00.000000000&#x27;, &#x27;2019-01-19T12:00:00.000000000&#x27;,\n",
       "        &#x27;2019-01-18T12:00:00.000000000&#x27;, ...,\n",
       "        &#x27;2007-01-03T12:00:00.000000000&#x27;, &#x27;2007-01-02T12:00:00.000000000&#x27;,\n",
       "        &#x27;2007-01-01T12:00:00.000000000&#x27;],\n",
       "       [&#x27;2019-01-20T12:00:00.000000000&#x27;, &#x27;2019-01-19T12:00:00.000000000&#x27;,\n",
       "        &#x27;2019-01-18T12:00:00.000000000&#x27;, ...,\n",
       "        &#x27;2007-01-03T12:00:00.000000000&#x27;, &#x27;2007-01-02T12:00:00.000000000&#x27;,\n",
       "        &#x27;2007-01-01T12:00:00.000000000&#x27;],\n",
       "       [&#x27;2019-01-20T12:00:00.000000000&#x27;, &#x27;2019-01-19T12:00:00.000000000&#x27;,\n",
       "        &#x27;2019-01-18T12:00:00.000000000&#x27;, ...,\n",
       "        &#x27;2007-01-03T12:00:00.000000000&#x27;, &#x27;2007-01-02T12:00:00.000000000&#x27;,\n",
       "        &#x27;2007-01-01T12:00:00.000000000&#x27;]], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 3.982e-07 ... -3.068e-06</div><input id='attrs-e5727625-571e-497f-8de2-8b42ad71ab4b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5727625-571e-497f-8de2-8b42ad71ab4b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b767a3c-8b74-400b-8063-7f5e8a9aa60c' class='xr-var-data-in' type='checkbox'><label for='data-8b767a3c-8b74-400b-8063-7f5e8a9aa60c' 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></dd><dt><span>standard_name :</span></dt><dd>u</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.0000000e+00,  3.9817516e-07,  2.9804730e-07, ...,\n",
       "         8.6405936e-07,  3.4143333e-08, -8.3815797e-07],\n",
       "       [ 0.0000000e+00,  4.0572019e-07,  3.0459475e-07, ...,\n",
       "         3.0441818e-08,  3.4166835e-08,  4.3629083e-08],\n",
       "       [ 0.0000000e+00,  3.9636620e-07,  2.9583197e-07, ...,\n",
       "         2.2560467e-07,  2.0781201e-07,  2.4301607e-07],\n",
       "       ...,\n",
       "       [ 0.0000000e+00,  2.5221269e-07,  2.9176675e-07, ...,\n",
       "        -4.3937987e-07, -4.6922676e-07, -2.1254215e-07],\n",
       "       [ 0.0000000e+00,  3.9692782e-07,  2.9896663e-07, ...,\n",
       "        -4.1739568e-07, -6.2094745e-07, -6.3719517e-07],\n",
       "       [ 0.0000000e+00,  4.0894471e-07,  3.0708827e-07, ...,\n",
       "        -2.1549870e-06, -2.5713455e-06, -3.0675251e-06]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 -4.395e-07 ... -2.246e-06</div><input id='attrs-518f38db-0ffe-43b1-ab1c-db28ae87a6fd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-518f38db-0ffe-43b1-ab1c-db28ae87a6fd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-57d1452b-f5bd-4ab3-b738-0af8287bfa92' class='xr-var-data-in' type='checkbox'><label for='data-57d1452b-f5bd-4ab3-b738-0af8287bfa92' 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></dd><dt><span>standard_name :</span></dt><dd>v</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.0000000e+00, -4.3948191e-07, -3.9371204e-07, ...,\n",
       "         2.7003975e-07,  1.4102476e-06,  9.5205621e-07],\n",
       "       [ 0.0000000e+00, -4.3639074e-07, -3.9153008e-07, ...,\n",
       "         6.2967473e-08,  4.5463732e-08,  2.8547525e-08],\n",
       "       [ 0.0000000e+00, -4.3610430e-07, -3.9132775e-07, ...,\n",
       "        -2.7167390e-08, -2.6440448e-08, -3.5348823e-08],\n",
       "       ...,\n",
       "       [ 0.0000000e+00, -4.3140170e-07, -3.8796574e-07, ...,\n",
       "        -2.2994061e-07, -2.3103264e-07, -2.4006999e-07],\n",
       "       [ 0.0000000e+00, -4.5525931e-07, -4.0481007e-07, ...,\n",
       "        -3.9056417e-07, -4.6437984e-07, -4.7831082e-07],\n",
       "       [ 0.0000000e+00, -4.3296356e-07, -3.8910801e-07, ...,\n",
       "        -2.9381249e-06, -2.5157278e-06, -2.2460720e-06]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v_s</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>8.861e-08 8.861e-08 ... 3.979e-08</div><input id='attrs-4c1553f3-5960-406a-9584-d5956573efc5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4c1553f3-5960-406a-9584-d5956573efc5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-575da282-dfde-4944-8573-238b541c4f37' class='xr-var-data-in' type='checkbox'><label for='data-575da282-dfde-4944-8573-238b541c4f37' 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></dd><dt><span>standard_name :</span></dt><dd>v_s</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[8.86078126e-08, 8.86062850e-08, 8.86060363e-08, ...,\n",
       "        5.66899598e-06, 5.66898007e-06, 5.66911740e-06],\n",
       "       [1.22604007e-07, 1.22602984e-07, 1.22602756e-07, ...,\n",
       "        7.84228632e-06, 7.84231179e-06, 7.84231906e-06],\n",
       "       [1.72688743e-08, 1.72685919e-08, 1.72686008e-08, ...,\n",
       "        1.72752834e-08, 1.72752443e-08, 1.72751875e-08],\n",
       "       ...,\n",
       "       [1.04456497e-07, 1.04455523e-07, 1.04454891e-07, ...,\n",
       "        1.04551418e-07, 1.04550885e-07, 1.04551468e-07],\n",
       "       [1.57089328e-08, 1.57087072e-08, 1.57086344e-08, ...,\n",
       "        1.00563193e-06, 1.00561454e-06, 1.00560987e-06],\n",
       "       [3.97625719e-08, 3.97622202e-08, 3.97622735e-08, ...,\n",
       "        3.97846449e-08, 3.97909794e-08, 3.97891107e-08]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>w</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 -0.0002636 ... -0.0004499</div><input id='attrs-6ad84ac6-0662-4ef6-abc7-3dfb505545dc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6ad84ac6-0662-4ef6-abc7-3dfb505545dc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1063701-32a8-458c-b47e-9c074d0baab8' class='xr-var-data-in' type='checkbox'><label for='data-f1063701-32a8-458c-b47e-9c074d0baab8' 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></dd><dt><span>standard_name :</span></dt><dd>w</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.0000000e+00, -2.6360856e-04, -2.2490179e-04, ...,\n",
       "        -7.0696900e-04,  2.9496627e-04,  4.0930958e-04],\n",
       "       [ 0.0000000e+00, -2.7159447e-04, -2.2938255e-04, ...,\n",
       "         5.7879075e-05,  2.5701935e-05,  3.0449975e-05],\n",
       "       [ 0.0000000e+00, -2.5867805e-04, -2.1116965e-04, ...,\n",
       "         5.8629645e-05,  5.4992768e-05, -3.7525544e-06],\n",
       "       ...,\n",
       "       [ 0.0000000e+00, -1.7436236e-04, -2.1057347e-04, ...,\n",
       "         3.9655639e-05,  1.3516123e-04, -2.8642711e-05],\n",
       "       [ 0.0000000e+00, -2.5285169e-04, -2.2233721e-04, ...,\n",
       "        -1.1148828e-04, -3.1047157e-04, -3.2064240e-04],\n",
       "       [ 0.0000000e+00, -2.7399935e-04, -2.2064395e-04, ...,\n",
       "         4.9583480e-04,  4.6271761e-04, -4.4994315e-04]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5e+03 5.019e+03 ... 3.67e+03</div><input id='attrs-ecbf853a-f8f0-4fbb-b00b-a9ba4c4b72c4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ecbf853a-f8f0-4fbb-b00b-a9ba4c4b72c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9953fb20-3383-4bc7-abcd-c9f93aca39b7' class='xr-var-data-in' type='checkbox'><label for='data-9953fb20-3383-4bc7-abcd-c9f93aca39b7' 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></dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([[5000.        , 5019.43599813, 5046.09723781, ..., 5186.55742492,\n",
       "        5162.6930849 , 5176.2526331 ],\n",
       "       [5000.        , 5024.05517783, 5046.6208768 , ..., 4994.20497186,\n",
       "        4988.97836453, 4986.97569315],\n",
       "       [5000.        , 5011.1339549 , 5033.79707012, ..., 3987.34404124,\n",
       "        3983.20646836, 3983.47003453],\n",
       "       ...,\n",
       "       [5000.        , 5009.14988753, 5031.60740986, ..., 3599.08025588,\n",
       "        3590.14254875, 3590.72382537],\n",
       "       [5000.        , 5009.59075278, 5045.64560089, ..., 4241.847452  ,\n",
       "        4349.65075514, 4359.53334429],\n",
       "       [5000.        , 5027.42944999, 5037.31577509, ..., 3815.10766611,\n",
       "        3775.3452144 , 3669.75916961]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z_kz</span></div><div class='xr-var-dims'>(trajectory, obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 1.721 1.104 ... -0.5244 0.2405</div><input id='attrs-2f269f2a-0e72-4750-94e5-3f248dd4d855' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2f269f2a-0e72-4750-94e5-3f248dd4d855' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-663cf4f9-efe9-4a7a-a174-aea68f7b85d3' class='xr-var-data-in' type='checkbox'><label for='data-663cf4f9-efe9-4a7a-a174-aea68f7b85d3' 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></dd><dt><span>standard_name :</span></dt><dd>z_kz</dd><dt><span>units :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.0000000e+00,  1.7209712e+00,  1.1036078e+00, ...,\n",
       "        -7.2235632e+00, -2.1758959e+01,  4.8598675e+01],\n",
       "       [ 0.0000000e+00, -3.7036186e-01, -3.0334806e+00, ...,\n",
       "         5.4531456e-03,  3.1093955e-01, -3.7916157e-01],\n",
       "       [ 0.0000000e+00, -2.4381671e+00,  3.0871944e+00, ...,\n",
       "         9.5559016e-02,  8.6073354e-02, -1.2257097e-01],\n",
       "       ...,\n",
       "       [ 0.0000000e+00, -1.9523056e+00,  1.5179752e+00, ...,\n",
       "        -6.5149128e-01,  5.7055455e-01, -7.2402753e-02],\n",
       "       [ 0.0000000e+00,  9.1458780e-01,  3.3193552e+00, ...,\n",
       "        -2.1675686e+01,  2.0870844e+01,  1.3924718e+01],\n",
       "       [ 0.0000000e+00,  1.2352989e+00, -3.2490857e+00, ...,\n",
       "        -2.3505184e-01, -5.2438021e-01,  2.4050371e-01]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-adf6f32b-dbdf-46a1-a4cf-0ff7d566b73d' class='xr-section-summary-in' type='checkbox'  ><label for='section-adf6f32b-dbdf-46a1-a4cf-0ff7d566b73d' class='xr-section-summary' >Indexes: <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-index-name'><div>obs</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-5a04ec19-9bb7-4f31-893e-b0e1f51f300e' class='xr-index-data-in' type='checkbox'/><label for='index-5a04ec19-9bb7-4f31-893e-b0e1f51f300e' 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(Int64Index([   0,    1,    2,    3,    4,    5,    6,    7,    8,    9,\n",
       "            ...\n",
       "            1520, 1521, 1522, 1523, 1524, 1525, 1526, 1527, 1528, 1529],\n",
       "           dtype=&#x27;int64&#x27;, name=&#x27;obs&#x27;, length=4403))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>trajectory</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-753e72e5-a5ea-4255-869a-57ab519a7261' class='xr-index-data-in' type='checkbox'/><label for='index-753e72e5-a5ea-4255-869a-57ab519a7261' 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(Int64Index([   0,    1,    2,    3,    4,    5,    6,    7,    8,    9,\n",
       "            ...\n",
       "            8182, 8183, 8184, 8185, 8186, 8187, 8188, 8189, 8190, 8191],\n",
       "           dtype=&#x27;int64&#x27;, name=&#x27;trajectory&#x27;, length=8192))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-628ec17f-2edf-4575-8a99-1331ac07f23b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-628ec17f-2edf-4575-8a99-1331ac07f23b' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6/CF-1.7</dd><dt><span>feature_type :</span></dt><dd>trajectory</dd><dt><span>ncei_template_version :</span></dt><dd>NCEI_NetCDF_Trajectory_Template_v2.0</dd><dt><span>parcels_mesh :</span></dt><dd>spherical</dd><dt><span>parcels_version :</span></dt><dd>2.4.2</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:           (trajectory: 8192, obs: 4403)\n",
       "Coordinates:\n",
       "  * obs               (obs) int32 0 1 2 3 4 5 ... 1524 1525 1526 1527 1528 1529\n",
       "  * trajectory        (trajectory) int64 0 1 2 3 4 ... 8187 8188 8189 8190 8191\n",
       "Data variables: (12/20)\n",
       "    abs_salinity      (trajectory, obs) float32 34.75 34.75 34.75 ... 34.81 34.8\n",
       "    bottom            (trajectory, obs) float32 5.5e+03 5.5e+03 ... 4.617e+03\n",
       "    cons_temperature  (trajectory, obs) float32 0.755 0.7429 ... 1.535 1.359\n",
       "    density           (trajectory, obs) float32 1.028e+03 ... 1.028e+03\n",
       "    distance          (trajectory, obs) float32 51.0 51.0 51.0 ... 51.0 51.0\n",
       "    floored           (trajectory, obs) float32 0.0 0.0 0.0 ... 121.0 121.0\n",
       "    ...                ...\n",
       "    u                 (trajectory, obs) float32 0.0 3.982e-07 ... -3.068e-06\n",
       "    v                 (trajectory, obs) float32 0.0 -4.395e-07 ... -2.246e-06\n",
       "    v_s               (trajectory, obs) float32 8.861e-08 ... 3.979e-08\n",
       "    w                 (trajectory, obs) float32 0.0 -0.0002636 ... -0.0004499\n",
       "    z                 (trajectory, obs) float64 5e+03 5.019e+03 ... 3.67e+03\n",
       "    z_kz              (trajectory, obs) float32 0.0 1.721 ... -0.5244 0.2405\n",
       "Attributes:\n",
       "    Conventions:            CF-1.6/CF-1.7\n",
       "    feature_type:           trajectory\n",
       "    ncei_template_version:  NCEI_NetCDF_Trajectory_Template_v2.0\n",
       "    parcels_mesh:           spherical\n",
       "    parcels_version:        2.4.2"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c74b2e41",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fa6e34dcdf0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pp = 40\n",
    "plt.plot(full.time[pp, :10], full.cons_temperature[pp, :10], 'bs', label='full')\n",
    "plt.plot(part1_a.time[pp, :10], part1_a.cons_temperature[pp, :10], 'r.', label='part1_a')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "07a07ef3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for pp in range(0, 100):\n",
    "    plt.plot(full.time[pp, :], -full.z[pp, :])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "feceec11",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['2019-01-20T12:00:00.000000000', '2019-01-19T12:00:00.000000000',\n",
       "       '2019-01-18T12:00:00.000000000', ...,\n",
       "       '2007-01-03T12:00:00.000000000', '2007-01-02T12:00:00.000000000',\n",
       "       '2007-01-01T12:00:00.000000000'], dtype='datetime64[ns]')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full['time'][0,:].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "aeb1af26",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-86400000000000]\n"
     ]
    }
   ],
   "source": [
    "#write a test to check if the time is continuous\n",
    "time_diff = full['time'][0,:].diff('obs').values\n",
    "print(np.unique(time_diff))\n",
    "\n",
    "#If one dt, then the time is continuous\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "8674293b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<xarray.backends.zarr.ZarrStore at 0x7fa6c808a9e0>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# save full dataset to zarr\n",
    "full.to_zarr('/storage/shared/oceanparcels/output_data/data_Claudio/abyssal_nps_outputs/merge_23000/hc13_23000.zarr')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6ccc9019",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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