interpolate_over_distance_8_13_2020.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/home/jovyan/ohw20-proj-ooi-profiles-section/ohw20-proj-ooi-profiles-section'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Import required packages\n",
    "import ctd\n",
    "import gsw\n",
    "from ctd.read import _basename\n",
    "import gsw\n",
    "import requests\n",
    "import os\n",
    "import re\n",
    "import xarray as xr\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# Make the Plots pretty\n",
    "import seaborn as sns\n",
    "sns.set()\n",
    "\n",
    "# Supress open_mfdataset warnings\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "#Set wd\n",
    "os.chdir('/home/jovyan/ohw20-proj-ooi-profiles-section/ohw20-proj-ooi-profiles-section/')\n",
    "os.getcwd()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read in data from 10/2019 using Stace's generated urls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Provide URL to load a single file that has already been downloaded to OOI's OPENDAP server\n",
    "# remember to use #fillmismatch\n",
    "# Create directory that includes all urls\n",
    "data_url = {}\n",
    "data_url['inshore'] = 'https://opendap.oceanobservatories.org/thredds/dodsC/ooi/sbeaulieu@whoi.edu/20200806T132326640Z-CP03ISPM-WFP01-03-CTDPFK000-recovered_wfp-ctdpf_ckl_wfp_instrument_recovered/deployment0003_CP03ISPM-WFP01-03-CTDPFK000-recovered_wfp-ctdpf_ckl_wfp_instrument_recovered_20191006T150003-20191031T212239.977728.nc#fillmismatch'\n",
    "data_url['central_inshore'] = 'https://opendap.oceanobservatories.org/thredds/dodsC/ooi/sbeaulieu@whoi.edu/20200806T132900316Z-CP02PMCI-WFP01-03-CTDPFK000-recovered_wfp-ctdpf_ckl_wfp_instrument_recovered/deployment0013_CP02PMCI-WFP01-03-CTDPFK000-recovered_wfp-ctdpf_ckl_wfp_instrument_recovered_20191007T210003-20191031T212442.986087.nc#fillmismatch'\n",
    "data_url['central_offshore'] = 'https://opendap.oceanobservatories.org/thredds/dodsC/ooi/sbeaulieu@whoi.edu/20200806T133142674Z-CP02PMCO-WFP01-03-CTDPFK000-recovered_wfp-ctdpf_ckl_wfp_instrument_recovered/deployment0013_CP02PMCO-WFP01-03-CTDPFK000-recovered_wfp-ctdpf_ckl_wfp_instrument_recovered_20191008T140003-20191031T212529.983845.nc#fillmismatch'\n",
    "data_url['offshore'] = 'https://opendap.oceanobservatories.org/thredds/dodsC/ooi/sbeaulieu@whoi.edu/20200806T133343088Z-CP04OSPM-WFP01-03-CTDPFK000-recovered_wfp-ctdpf_ckl_wfp_instrument_recovered/deployment0012_CP04OSPM-WFP01-03-CTDPFK000-recovered_wfp-ctdpf_ckl_wfp_instrument_recovered_20191013T160003-20191031T211622.990750.nc#fillmismatch'\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load in the bathymetric data from the shelf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Load in bathymetric data\n",
    "bathymetry=xr.open_dataset('data/GMRT_39-41N_70-71W.nc')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f4d443f57f0>]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plot\n",
    "\n",
    "#take the mean z across longitude (the moorings are essentially N-S oriented)\n",
    "z=bathymetry.z.values.reshape([1023,535]).mean(axis=1)\n",
    "#plt.imshow(z)\n",
    "#plt.colorbar()\n",
    "\n",
    "# #Get lat/lon range\n",
    "# x=np.linspace(bathymetry.x_range[0],bathymetry.x_range[1],535)\n",
    "y=np.linspace(bathymetry.y_range[1],bathymetry.y_range[0],1023)\n",
    "\n",
    "\n",
    "#Initial plot of depth values\n",
    "plt.plot(y,z)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Taken from Kelly's code to plot a single day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Extract a single time for a single day and plot all side by side\n",
    "I_URL = 'https://opendap.oceanobservatories.org/thredds/dodsC/ooi/sbeaulieu@whoi.edu/20200806T132326640Z-CP03ISPM-WFP01-03-CTDPFK000-recovered_wfp-ctdpf_ckl_wfp_instrument_recovered/deployment0003_CP03ISPM-WFP01-03-CTDPFK000-recovered_wfp-ctdpf_ckl_wfp_instrument_recovered_20191006T150003-20191031T212239.977728.nc#fillmismatch'\n",
    "CI_URL = 'https://opendap.oceanobservatories.org/thredds/dodsC/ooi/sbeaulieu@whoi.edu/20200806T132900316Z-CP02PMCI-WFP01-03-CTDPFK000-recovered_wfp-ctdpf_ckl_wfp_instrument_recovered/deployment0013_CP02PMCI-WFP01-03-CTDPFK000-recovered_wfp-ctdpf_ckl_wfp_instrument_recovered_20191007T210003-20191031T212442.986087.nc#fillmismatch'\n",
    "CO_URL = 'https://opendap.oceanobservatories.org/thredds/dodsC/ooi/sbeaulieu@whoi.edu/20200806T133142674Z-CP02PMCO-WFP01-03-CTDPFK000-recovered_wfp-ctdpf_ckl_wfp_instrument_recovered/deployment0013_CP02PMCO-WFP01-03-CTDPFK000-recovered_wfp-ctdpf_ckl_wfp_instrument_recovered_20191008T140003-20191031T212529.983845.nc#fillmismatch'\n",
    "O_URL = 'https://opendap.oceanobservatories.org/thredds/dodsC/ooi/sbeaulieu@whoi.edu/20200806T133343088Z-CP04OSPM-WFP01-03-CTDPFK000-recovered_wfp-ctdpf_ckl_wfp_instrument_recovered/deployment0012_CP04OSPM-WFP01-03-CTDPFK000-recovered_wfp-ctdpf_ckl_wfp_instrument_recovered_20191013T160003-20191031T211622.990750.nc#fillmismatch'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "ids = xr.open_dataset(I_URL)\n",
    "cids = xr.open_dataset(CI_URL)\n",
    "cods = xr.open_dataset(CO_URL)\n",
    "ods = xr.open_dataset(O_URL)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "ids = ids.swap_dims({'obs': 'time'}) #Swap dimensions\n",
    "cids = cids.swap_dims({'obs': 'time'}) #Swap dimensions\n",
    "cods = cods.swap_dims({'obs': 'time'}) #Swap dimensions\n",
    "ods = ods.swap_dims({'obs': 'time'}) #Swap dimensions\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Select a single time slice "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# select same day for each profiler\n",
    "ids15=ids[['ctdpf_ckl_seawater_pressure','ctdpf_ckl_seawater_temperature','practical_salinity']].sel(time=\"2019-10-15T03\", method=\"nearest\")\n",
    "cids15=cids[['ctdpf_ckl_seawater_pressure','ctdpf_ckl_seawater_temperature','practical_salinity']].sel(time=\"2019-10-15T03\", method=\"nearest\")\n",
    "cods15=cods[['ctdpf_ckl_seawater_pressure','ctdpf_ckl_seawater_temperature','practical_salinity']].sel(time=\"2019-10-15T03\", method=\"nearest\")\n",
    "ods15=ods[['ctdpf_ckl_seawater_pressure','ctdpf_ckl_seawater_temperature','practical_salinity']].sel(time=\"2019-10-15T03\", method=\"nearest\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
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       "\n",
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       "\n",
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       "\n",
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       "\n",
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       "\n",
       ".xr-attrs dt {\n",
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       "\n",
       ".xr-attrs dt:hover span {\n",
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       ".xr-attrs dd {\n",
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       "\n",
       ".xr-icon-database,\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:                         (time: 801)\n",
       "Coordinates:\n",
       "  * time                            (time) datetime64[ns] 2019-10-15T03:00:02...\n",
       "    lat                             (time) float64 40.36 40.36 ... 40.36 40.36\n",
       "    pressure                        (time) float64 6.415e+03 ... 7.789e+03\n",
       "    lon                             (time) float64 -70.89 -70.89 ... -70.89\n",
       "    obs                             (time) int32 51980 51981 ... 52779 52780\n",
       "Data variables:\n",
       "    ctdpf_ckl_seawater_pressure     (time) float64 54.15 54.13 ... 67.88 67.89\n",
       "    ctdpf_ckl_seawater_temperature  (time) float64 20.46 20.46 ... 20.32 20.31\n",
       "    practical_salinity              (time) float64 35.31 35.32 ... 35.26 35.26\n",
       "Attributes:\n",
       "    _NCProperties:                   version=1|netcdflibversion=4.6.1|hdf5lib...\n",
       "    node:                            WFP01\n",
       "    comment:                         \n",
       "    publisher_email:                 \n",
       "    sourceUrl:                       http://oceanobservatories.org/\n",
       "    collection_method:               recovered_wfp\n",
       "    stream:                          ctdpf_ckl_wfp_instrument_recovered\n",
       "    featureType:                     point\n",
       "    creator_email:                   \n",
       "    publisher_name:                  Ocean Observatories Initiative\n",
       "    date_modified:                   2020-08-06T13:23:41.238357\n",
       "    keywords:                        \n",
       "    cdm_data_type:                   Point\n",
       "    references:                      More information can be found at http://...\n",
       "    Metadata_Conventions:            Unidata Dataset Discovery v1.0\n",
       "    date_created:                    2020-08-06T13:23:41.238351\n",
       "    id:                              CP03ISPM-WFP01-03-CTDPFK000-recovered_wf...\n",
       "    requestUUID:                     607b59bd-cfc8-4659-868c-a894a197fb41\n",
       "    contributor_role:                \n",
       "    summary:                         Dataset Generated by Stream Engine from ...\n",
       "    keywords_vocabulary:             \n",
       "    institution:                     Ocean Observatories Initiative\n",
       "    naming_authority:                org.oceanobservatories\n",
       "    feature_Type:                    point\n",
       "    infoUrl:                         http://oceanobservatories.org/\n",
       "    license:                         \n",
       "    contributor_name:                \n",
       "    uuid:                            607b59bd-cfc8-4659-868c-a894a197fb41\n",
       "    creator_name:                    Ocean Observatories Initiative\n",
       "    title:                           Data produced by Stream Engine version 1...\n",
       "    sensor:                          03-CTDPFK000\n",
       "    standard_name_vocabulary:        NetCDF Climate and Forecast (CF) Metadat...\n",
       "    acknowledgement:                 \n",
       "    Conventions:                     CF-1.6\n",
       "    project:                         Ocean Observatories Initiative\n",
       "    source:                          CP03ISPM-WFP01-03-CTDPFK000-recovered_wf...\n",
       "    publisher_url:                   http://oceanobservatories.org/\n",
       "    creator_url:                     http://oceanobservatories.org/\n",
       "    nodc_template_version:           NODC_NetCDF_TimeSeries_Orthogonal_Templa...\n",
       "    subsite:                         CP03ISPM\n",
       "    processing_level:                L2\n",
       "    history:                         2020-08-06T13:23:41.238281 generated fro...\n",
       "    time_coverage_start:             2019-10-06T15:00:03\n",
       "    time_coverage_end:               2019-10-31T21:22:39.977728\n",
       "    time_coverage_resolution:        P13.80S\n",
       "    geospatial_lat_min:              40.364817\n",
       "    geospatial_lat_max:              40.364817\n",
       "    geospatial_lat_units:            degrees_north\n",
       "    geospatial_lat_resolution:       0.1\n",
       "    geospatial_lon_min:              -70.888668\n",
       "    geospatial_lon_max:              -70.888668\n",
       "    geospatial_lon_units:            degrees_east\n",
       "    geospatial_lon_resolution:       0.1\n",
       "    geospatial_vertical_units:       meters\n",
       "    geospatial_vertical_resolution:  0.1\n",
       "    geospatial_vertical_positive:    down\n",
       "    DODS.strlen:                     18\n",
       "    DODS.dimName:                    string18\n",
       "    DODS_EXTRA.Unlimited_Dimension:  obs</pre><div class='xr-wrap' hidden><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-40910959-13c8-40ed-ace8-2c5e85bd125f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-40910959-13c8-40ed-ace8-2c5e85bd125f' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 801</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a2128ebd-0933-4b32-b3d7-f3723ae10d5c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a2128ebd-0933-4b32-b3d7-f3723ae10d5c' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-10-15T03:00:02 ... 2019-10-...</div><input id='attrs-ec53f5c2-9c9b-4d91-ac01-c891b6c515ab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ec53f5c2-9c9b-4d91-ac01-c891b6c515ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06928d9a-6b56-454c-aeaf-0fcf55b73526' class='xr-var-data-in' type='checkbox'><label for='data-06928d9a-6b56-454c-aeaf-0fcf55b73526' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>_ChunkSizes :</span></dt><dd>511</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-10-15T03:00:02.000000000&#x27;, &#x27;2019-10-15T03:00:03.025210368&#x27;,\n",
       "       &#x27;2019-10-15T03:00:04.050420224&#x27;, ..., &#x27;2019-10-15T03:22:32.932432384&#x27;,\n",
       "       &#x27;2019-10-15T03:22:33.954955264&#x27;, &#x27;2019-10-15T03:22:34.977477632&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9b8451b8-47bd-41c4-9926-a40a8eefc72b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9b8451b8-47bd-41c4-9926-a40a8eefc72b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b5beb10-a4b4-403a-8e84-29c9b02dbbe2' class='xr-var-data-in' type='checkbox'><label for='data-9b5beb10-a4b4-403a-8e84-29c9b02dbbe2' 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>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>_ChunkSizes :</span></dt><dd>511</dd></dl></div><div class='xr-var-data'><pre>array([40.364817, 40.364817, 40.364817, ..., 40.364817, 40.364817, 40.364817])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9232214d-2da2-4c51-8c48-f6fc98910d89' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9232214d-2da2-4c51-8c48-f6fc98910d89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b33d14f1-dea0-43a6-be7b-30afa6160594' class='xr-var-data-in' type='checkbox'><label for='data-b33d14f1-dea0-43a6-be7b-30afa6160594' 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>comment :</span></dt><dd>Seawater Pressure refers to the pressure exerted on a sensor in situ by the weight of the column of seawater above it. It is calculated by subtracting one standard atmosphere from the absolute pressure at the sensor to remove the weight of the atmosphere on top of the water column. The pressure at a sensor in situ provides a metric of the depth of that sensor. This is the unprocessed data that are output directly from the sensor which are then converted to pressure in dbar.</dd><dt><span>long_name :</span></dt><dd>Seawater Pressure Measurement</dd><dt><span>precision :</span></dt><dd>0</dd><dt><span>data_product_identifier :</span></dt><dd>PRESWAT_L0</dd><dt><span>units :</span></dt><dd>counts</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>_ChunkSizes :</span></dt><dd>1021</dd></dl></div><div class='xr-var-data'><pre>array([6415., 6413., 6411., ..., 7788., 7788., 7789.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f312411e-458b-4aab-a47c-0ff82f78741d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f312411e-458b-4aab-a47c-0ff82f78741d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26655a59-4650-4623-aa66-779cbd4e6428' class='xr-var-data-in' type='checkbox'><label for='data-26655a59-4650-4623-aa66-779cbd4e6428' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>_ChunkSizes :</span></dt><dd>511</dd></dl></div><div class='xr-var-data'><pre>array([-70.888668, -70.888668, -70.888668, ..., -70.888668, -70.888668,\n",
       "       -70.888668])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>obs</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>51980 51981 51982 ... 52779 52780</div><input id='attrs-114659ca-49ef-4a6b-9ee5-8da45f4f71b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-114659ca-49ef-4a6b-9ee5-8da45f4f71b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a69dab7a-db1c-41a2-bf4b-b6ca1d2f8775' class='xr-var-data-in' type='checkbox'><label for='data-a69dab7a-db1c-41a2-bf4b-b6ca1d2f8775' 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>_ChunkSizes :</span></dt><dd>1024</dd></dl></div><div class='xr-var-data'><pre>array([51980, 51981, 51982, ..., 52778, 52779, 52780], dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1b39c078-2f46-4a43-a9de-6e9b5fa2b07f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1b39c078-2f46-4a43-a9de-6e9b5fa2b07f' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ctdpf_ckl_seawater_pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c1dc889d-f705-4def-ac88-360d9183d0d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1dc889d-f705-4def-ac88-360d9183d0d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4ff6af8f-65ea-4670-9e98-6110ca388f8e' class='xr-var-data-in' type='checkbox'><label for='data-4ff6af8f-65ea-4670-9e98-6110ca388f8e' 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>comment :</span></dt><dd>Seawater Pressure refers to the pressure exerted on a sensor in situ by the weight of the column of seawater above it. It is calculated by subtracting one standard atmosphere from the absolute pressure at the sensor to remove the weight of the atmosphere on top of the water column. The pressure at a sensor in situ provides a metric of the depth of that sensor.</dd><dt><span>long_name :</span></dt><dd>Seawater Pressure</dd><dt><span>data_product_identifier :</span></dt><dd>PRESWAT_L1</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd><dt><span>units :</span></dt><dd>dbar</dd><dt><span>ancillary_variables :</span></dt><dd>pressure</dd><dt><span>_ChunkSizes :</span></dt><dd>10000</dd></dl></div><div class='xr-var-data'><pre>array([54.15, 54.13, 54.11, ..., 67.88, 67.88, 67.89])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ctdpf_ckl_seawater_temperature</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cd13b234-c85b-461d-aa5a-e4e7ba96f451' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd13b234-c85b-461d-aa5a-e4e7ba96f451' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cace19a4-b78f-4a08-af87-29540b961849' class='xr-var-data-in' type='checkbox'><label for='data-cace19a4-b78f-4a08-af87-29540b961849' 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>comment :</span></dt><dd>Seawater temperature near the sensor.</dd><dt><span>long_name :</span></dt><dd>Seawater Temperature</dd><dt><span>precision :</span></dt><dd>4</dd><dt><span>data_product_identifier :</span></dt><dd>TEMPWAT_L1</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd><dt><span>units :</span></dt><dd>ºC</dd><dt><span>ancillary_variables :</span></dt><dd>ctdpf_ckl_seawater_temperature_qartod_results ctdpf_ckl_seawater_temperature_qartod_executed temperature</dd><dt><span>_ChunkSizes :</span></dt><dd>10000</dd></dl></div><div class='xr-var-data'><pre>array([20.4614, 20.4639, 20.4689, ..., 20.318 , 20.3163, 20.314 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>practical_salinity</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2c2780e5-cf00-420f-b9f5-d88135f114d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2c2780e5-cf00-420f-b9f5-d88135f114d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3c106d7-90f5-4502-885c-dd6ef22c69dd' class='xr-var-data-in' type='checkbox'><label for='data-f3c106d7-90f5-4502-885c-dd6ef22c69dd' 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>comment :</span></dt><dd>Salinity is generally defined as the concentration of dissolved salt in a parcel of seawater. Practical Salinity is a more specific unitless quantity calculated from the conductivity of seawater and adjusted for temperature and pressure. It is approximately equivalent to Absolute Salinity (the mass fraction of dissolved salt in seawater) but they are not interchangeable.</dd><dt><span>long_name :</span></dt><dd>Practical Salinity</dd><dt><span>precision :</span></dt><dd>4</dd><dt><span>data_product_identifier :</span></dt><dd>PRACSAL_L2</dd><dt><span>standard_name :</span></dt><dd>sea_water_practical_salinity</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>ancillary_variables :</span></dt><dd>pressure conductivity temperature</dd><dt><span>_ChunkSizes :</span></dt><dd>10000</dd></dl></div><div class='xr-var-data'><pre>array([35.314641, 35.315   , 35.314737, ..., 35.262025, 35.260755, 35.258353])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6a880e9d-9f9b-43b3-9677-37ad3b56075d' class='xr-section-summary-in' type='checkbox'  ><label for='section-6a880e9d-9f9b-43b3-9677-37ad3b56075d' class='xr-section-summary' >Attributes: <span>(59)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>_NCProperties :</span></dt><dd>version=1|netcdflibversion=4.6.1|hdf5libversion=1.10.4</dd><dt><span>node :</span></dt><dd>WFP01</dd><dt><span>comment :</span></dt><dd></dd><dt><span>publisher_email :</span></dt><dd></dd><dt><span>sourceUrl :</span></dt><dd>http://oceanobservatories.org/</dd><dt><span>collection_method :</span></dt><dd>recovered_wfp</dd><dt><span>stream :</span></dt><dd>ctdpf_ckl_wfp_instrument_recovered</dd><dt><span>featureType :</span></dt><dd>point</dd><dt><span>creator_email :</span></dt><dd></dd><dt><span>publisher_name :</span></dt><dd>Ocean Observatories Initiative</dd><dt><span>date_modified :</span></dt><dd>2020-08-06T13:23:41.238357</dd><dt><span>keywords :</span></dt><dd></dd><dt><span>cdm_data_type :</span></dt><dd>Point</dd><dt><span>references :</span></dt><dd>More information can be found at http://oceanobservatories.org/</dd><dt><span>Metadata_Conventions :</span></dt><dd>Unidata Dataset Discovery v1.0</dd><dt><span>date_created :</span></dt><dd>2020-08-06T13:23:41.238351</dd><dt><span>id :</span></dt><dd>CP03ISPM-WFP01-03-CTDPFK000-recovered_wfp-ctdpf_ckl_wfp_instrument_recovered</dd><dt><span>requestUUID :</span></dt><dd>607b59bd-cfc8-4659-868c-a894a197fb41</dd><dt><span>contributor_role :</span></dt><dd></dd><dt><span>summary :</span></dt><dd>Dataset Generated by Stream Engine from Ocean Observatories Initiative</dd><dt><span>keywords_vocabulary :</span></dt><dd></dd><dt><span>institution :</span></dt><dd>Ocean Observatories Initiative</dd><dt><span>naming_authority :</span></dt><dd>org.oceanobservatories</dd><dt><span>feature_Type :</span></dt><dd>point</dd><dt><span>infoUrl :</span></dt><dd>http://oceanobservatories.org/</dd><dt><span>license :</span></dt><dd></dd><dt><span>contributor_name :</span></dt><dd></dd><dt><span>uuid :</span></dt><dd>607b59bd-cfc8-4659-868c-a894a197fb41</dd><dt><span>creator_name :</span></dt><dd>Ocean Observatories Initiative</dd><dt><span>title :</span></dt><dd>Data produced by Stream Engine version 1.15.0 for CP03ISPM-WFP01-03-CTDPFK000-recovered_wfp-ctdpf_ckl_wfp_instrument_recovered</dd><dt><span>sensor :</span></dt><dd>03-CTDPFK000</dd><dt><span>standard_name_vocabulary :</span></dt><dd>NetCDF Climate and Forecast (CF) Metadata Convention Standard Name Table 29</dd><dt><span>acknowledgement :</span></dt><dd></dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>project :</span></dt><dd>Ocean Observatories Initiative</dd><dt><span>source :</span></dt><dd>CP03ISPM-WFP01-03-CTDPFK000-recovered_wfp-ctdpf_ckl_wfp_instrument_recovered</dd><dt><span>publisher_url :</span></dt><dd>http://oceanobservatories.org/</dd><dt><span>creator_url :</span></dt><dd>http://oceanobservatories.org/</dd><dt><span>nodc_template_version :</span></dt><dd>NODC_NetCDF_TimeSeries_Orthogonal_Template_v1.1</dd><dt><span>subsite :</span></dt><dd>CP03ISPM</dd><dt><span>processing_level :</span></dt><dd>L2</dd><dt><span>history :</span></dt><dd>2020-08-06T13:23:41.238281 generated from Stream Engine</dd><dt><span>time_coverage_start :</span></dt><dd>2019-10-06T15:00:03</dd><dt><span>time_coverage_end :</span></dt><dd>2019-10-31T21:22:39.977728</dd><dt><span>time_coverage_resolution :</span></dt><dd>P13.80S</dd><dt><span>geospatial_lat_min :</span></dt><dd>40.364817</dd><dt><span>geospatial_lat_max :</span></dt><dd>40.364817</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.1</dd><dt><span>geospatial_lon_min :</span></dt><dd>-70.888668</dd><dt><span>geospatial_lon_max :</span></dt><dd>-70.888668</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.1</dd><dt><span>geospatial_vertical_units :</span></dt><dd>meters</dd><dt><span>geospatial_vertical_resolution :</span></dt><dd>0.1</dd><dt><span>geospatial_vertical_positive :</span></dt><dd>down</dd><dt><span>DODS.strlen :</span></dt><dd>18</dd><dt><span>DODS.dimName :</span></dt><dd>string18</dd><dt><span>DODS_EXTRA.Unlimited_Dimension :</span></dt><dd>obs</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                         (time: 801)\n",
       "Coordinates:\n",
       "  * time                            (time) datetime64[ns] 2019-10-15T03:00:02...\n",
       "    lat                             (time) float64 ...\n",
       "    pressure                        (time) float64 ...\n",
       "    lon                             (time) float64 ...\n",
       "    obs                             (time) int32 51980 51981 ... 52779 52780\n",
       "Data variables:\n",
       "    ctdpf_ckl_seawater_pressure     (time) float64 ...\n",
       "    ctdpf_ckl_seawater_temperature  (time) float64 ...\n",
       "    practical_salinity              (time) float64 ...\n",
       "Attributes:\n",
       "    _NCProperties:                   version=1|netcdflibversion=4.6.1|hdf5lib...\n",
       "    node:                            WFP01\n",
       "    comment:                         \n",
       "    publisher_email:                 \n",
       "    sourceUrl:                       http://oceanobservatories.org/\n",
       "    collection_method:               recovered_wfp\n",
       "    stream:                          ctdpf_ckl_wfp_instrument_recovered\n",
       "    featureType:                     point\n",
       "    creator_email:                   \n",
       "    publisher_name:                  Ocean Observatories Initiative\n",
       "    date_modified:                   2020-08-06T13:23:41.238357\n",
       "    keywords:                        \n",
       "    cdm_data_type:                   Point\n",
       "    references:                      More information can be found at http://...\n",
       "    Metadata_Conventions:            Unidata Dataset Discovery v1.0\n",
       "    date_created:                    2020-08-06T13:23:41.238351\n",
       "    id:                              CP03ISPM-WFP01-03-CTDPFK000-recovered_wf...\n",
       "    requestUUID:                     607b59bd-cfc8-4659-868c-a894a197fb41\n",
       "    contributor_role:                \n",
       "    summary:                         Dataset Generated by Stream Engine from ...\n",
       "    keywords_vocabulary:             \n",
       "    institution:                     Ocean Observatories Initiative\n",
       "    naming_authority:                org.oceanobservatories\n",
       "    feature_Type:                    point\n",
       "    infoUrl:                         http://oceanobservatories.org/\n",
       "    license:                         \n",
       "    contributor_name:                \n",
       "    uuid:                            607b59bd-cfc8-4659-868c-a894a197fb41\n",
       "    creator_name:                    Ocean Observatories Initiative\n",
       "    title:                           Data produced by Stream Engine version 1...\n",
       "    sensor:                          03-CTDPFK000\n",
       "    standard_name_vocabulary:        NetCDF Climate and Forecast (CF) Metadat...\n",
       "    acknowledgement:                 \n",
       "    Conventions:                     CF-1.6\n",
       "    project:                         Ocean Observatories Initiative\n",
       "    source:                          CP03ISPM-WFP01-03-CTDPFK000-recovered_wf...\n",
       "    publisher_url:                   http://oceanobservatories.org/\n",
       "    creator_url:                     http://oceanobservatories.org/\n",
       "    nodc_template_version:           NODC_NetCDF_TimeSeries_Orthogonal_Templa...\n",
       "    subsite:                         CP03ISPM\n",
       "    processing_level:                L2\n",
       "    history:                         2020-08-06T13:23:41.238281 generated fro...\n",
       "    time_coverage_start:             2019-10-06T15:00:03\n",
       "    time_coverage_end:               2019-10-31T21:22:39.977728\n",
       "    time_coverage_resolution:        P13.80S\n",
       "    geospatial_lat_min:              40.364817\n",
       "    geospatial_lat_max:              40.364817\n",
       "    geospatial_lat_units:            degrees_north\n",
       "    geospatial_lat_resolution:       0.1\n",
       "    geospatial_lon_min:              -70.888668\n",
       "    geospatial_lon_max:              -70.888668\n",
       "    geospatial_lon_units:            degrees_east\n",
       "    geospatial_lon_resolution:       0.1\n",
       "    geospatial_vertical_units:       meters\n",
       "    geospatial_vertical_resolution:  0.1\n",
       "    geospatial_vertical_positive:    down\n",
       "    DODS.strlen:                     18\n",
       "    DODS.dimName:                    string18\n",
       "    DODS_EXTRA.Unlimited_Dimension:  obs"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ids15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:                         (space: 4, time: 4949)\n",
       "Coordinates:\n",
       "  * time                            (time) datetime64[ns] 2019-10-15T03:00:02...\n",
       "    lat                             (space, time) object 40.36 &#x27;nan&#x27; ... 39.94\n",
       "    pressure                        (space, time) object 6.415e+03 ... 4.206e+04\n",
       "    lon                             (space, time) object -70.89 &#x27;nan&#x27; ... -70.88\n",
       "    obs                             (space, time) object 51980 &#x27;nan&#x27; ... 17896\n",
       "Dimensions without coordinates: space\n",
       "Data variables:\n",
       "    ctdpf_ckl_seawater_pressure     (space, time) object 54.15 &#x27;nan&#x27; ... 410.6\n",
       "    ctdpf_ckl_seawater_temperature  (space, time) object 20.46 &#x27;nan&#x27; ... 9.674\n",
       "    practical_salinity              (space, time) object 35.31 &#x27;nan&#x27; ... 35.28\n",
       "Attributes:\n",
       "    _NCProperties:                   version=1|netcdflibversion=4.6.1|hdf5lib...\n",
       "    node:                            WFP01\n",
       "    comment:                         \n",
       "    publisher_email:                 \n",
       "    sourceUrl:                       http://oceanobservatories.org/\n",
       "    collection_method:               recovered_wfp\n",
       "    stream:                          ctdpf_ckl_wfp_instrument_recovered\n",
       "    featureType:                     point\n",
       "    creator_email:                   \n",
       "    publisher_name:                  Ocean Observatories Initiative\n",
       "    date_modified:                   2020-08-06T13:23:41.238357\n",
       "    keywords:                        \n",
       "    cdm_data_type:                   Point\n",
       "    references:                      More information can be found at http://...\n",
       "    Metadata_Conventions:            Unidata Dataset Discovery v1.0\n",
       "    date_created:                    2020-08-06T13:23:41.238351\n",
       "    id:                              CP03ISPM-WFP01-03-CTDPFK000-recovered_wf...\n",
       "    requestUUID:                     607b59bd-cfc8-4659-868c-a894a197fb41\n",
       "    contributor_role:                \n",
       "    summary:                         Dataset Generated by Stream Engine from ...\n",
       "    keywords_vocabulary:             \n",
       "    institution:                     Ocean Observatories Initiative\n",
       "    naming_authority:                org.oceanobservatories\n",
       "    feature_Type:                    point\n",
       "    infoUrl:                         http://oceanobservatories.org/\n",
       "    license:                         \n",
       "    contributor_name:                \n",
       "    uuid:                            607b59bd-cfc8-4659-868c-a894a197fb41\n",
       "    creator_name:                    Ocean Observatories Initiative\n",
       "    title:                           Data produced by Stream Engine version 1...\n",
       "    sensor:                          03-CTDPFK000\n",
       "    standard_name_vocabulary:        NetCDF Climate and Forecast (CF) Metadat...\n",
       "    acknowledgement:                 \n",
       "    Conventions:                     CF-1.6\n",
       "    project:                         Ocean Observatories Initiative\n",
       "    source:                          CP03ISPM-WFP01-03-CTDPFK000-recovered_wf...\n",
       "    publisher_url:                   http://oceanobservatories.org/\n",
       "    creator_url:                     http://oceanobservatories.org/\n",
       "    nodc_template_version:           NODC_NetCDF_TimeSeries_Orthogonal_Templa...\n",
       "    subsite:                         CP03ISPM\n",
       "    processing_level:                L2\n",
       "    history:                         2020-08-06T13:23:41.238281 generated fro...\n",
       "    time_coverage_start:             2019-10-06T15:00:03\n",
       "    time_coverage_end:               2019-10-31T21:22:39.977728\n",
       "    time_coverage_resolution:        P13.80S\n",
       "    geospatial_lat_min:              40.364817\n",
       "    geospatial_lat_max:              40.364817\n",
       "    geospatial_lat_units:            degrees_north\n",
       "    geospatial_lat_resolution:       0.1\n",
       "    geospatial_lon_min:              -70.888668\n",
       "    geospatial_lon_max:              -70.888668\n",
       "    geospatial_lon_units:            degrees_east\n",
       "    geospatial_lon_resolution:       0.1\n",
       "    geospatial_vertical_units:       meters\n",
       "    geospatial_vertical_resolution:  0.1\n",
       "    geospatial_vertical_positive:    down\n",
       "    DODS.strlen:                     18\n",
       "    DODS.dimName:                    string18\n",
       "    DODS_EXTRA.Unlimited_Dimension:  obs</pre><div class='xr-wrap' hidden><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-fea31205-5e3d-46c3-a1f7-4f773bd36ae8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-fea31205-5e3d-46c3-a1f7-4f773bd36ae8' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>space</span>: 4</li><li><span class='xr-has-index'>time</span>: 4949</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-d90e43cf-12af-4d13-851e-211dda47938a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d90e43cf-12af-4d13-851e-211dda47938a' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-10-15T03:00:02 ... 2019-10-...</div><input id='attrs-84df4c2c-a767-48d5-8cf3-cb1e999508f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-84df4c2c-a767-48d5-8cf3-cb1e999508f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-daf84d48-8d08-4262-9558-b918a1ab032e' class='xr-var-data-in' type='checkbox'><label for='data-daf84d48-8d08-4262-9558-b918a1ab032e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>_ChunkSizes :</span></dt><dd>511</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-10-15T03:00:02.000000000&#x27;, &#x27;2019-10-15T03:00:03.004489216&#x27;,\n",
       "       &#x27;2019-10-15T03:00:03.012558848&#x27;, ..., &#x27;2019-10-15T03:29:48.986532352&#x27;,\n",
       "       &#x27;2019-10-15T03:29:49.991021056&#x27;, &#x27;2019-10-15T03:29:50.995510784&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(space, time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>40.36 &#x27;nan&#x27; &#x27;nan&#x27; ... 39.94 39.94</div><input id='attrs-df3d1c4f-5890-4085-acd5-4530bc9425e6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-df3d1c4f-5890-4085-acd5-4530bc9425e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e6e2d49-a91b-4baf-b3a2-cc8d28eb365b' class='xr-var-data-in' type='checkbox'><label for='data-9e6e2d49-a91b-4baf-b3a2-cc8d28eb365b' 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>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>_ChunkSizes :</span></dt><dd>511</dd></dl></div><div class='xr-var-data'><pre>array([[40.364817, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;],\n",
       "       [40.226972, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;],\n",
       "       [40.096798, &#x27;nan&#x27;, 40.096798, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;],\n",
       "       [39.935558, 39.935558, &#x27;nan&#x27;, ..., 39.935558, 39.935558,\n",
       "        39.935558]], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(space, time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>6.415e+03 &#x27;nan&#x27; ... 4.206e+04</div><input id='attrs-a77655a4-8ff6-44b3-bb55-7c09f29ef6bd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a77655a4-8ff6-44b3-bb55-7c09f29ef6bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cad6805f-9ee5-4132-bfec-e76fe6ac2b19' class='xr-var-data-in' type='checkbox'><label for='data-cad6805f-9ee5-4132-bfec-e76fe6ac2b19' 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>comment :</span></dt><dd>Seawater Pressure refers to the pressure exerted on a sensor in situ by the weight of the column of seawater above it. It is calculated by subtracting one standard atmosphere from the absolute pressure at the sensor to remove the weight of the atmosphere on top of the water column. The pressure at a sensor in situ provides a metric of the depth of that sensor. This is the unprocessed data that are output directly from the sensor which are then converted to pressure in dbar.</dd><dt><span>long_name :</span></dt><dd>Seawater Pressure Measurement</dd><dt><span>precision :</span></dt><dd>0</dd><dt><span>data_product_identifier :</span></dt><dd>PRESWAT_L0</dd><dt><span>units :</span></dt><dd>counts</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>_ChunkSizes :</span></dt><dd>1021</dd></dl></div><div class='xr-var-data'><pre>array([[6415.0, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;],\n",
       "       [11060.0, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;],\n",
       "       [13234.0, &#x27;nan&#x27;, 13234.0, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;],\n",
       "       [2965.0, 2963.0, &#x27;nan&#x27;, ..., 42062.0, 42062.0, 42062.0]],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(space, time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>-70.89 &#x27;nan&#x27; ... -70.88 -70.88</div><input id='attrs-563b7d28-2bd1-4acd-8bd1-22a58f555f02' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-563b7d28-2bd1-4acd-8bd1-22a58f555f02' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97a509f2-22de-4d4c-bae1-b72960699a9e' class='xr-var-data-in' type='checkbox'><label for='data-97a509f2-22de-4d4c-bae1-b72960699a9e' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>_ChunkSizes :</span></dt><dd>511</dd></dl></div><div class='xr-var-data'><pre>array([[-70.888668, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;],\n",
       "       [-70.877882, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;],\n",
       "       [-70.879063, &#x27;nan&#x27;, -70.879063, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;],\n",
       "       [-70.880328, -70.880328, &#x27;nan&#x27;, ..., -70.880328, -70.880328,\n",
       "        -70.880328]], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>obs</span></div><div class='xr-var-dims'>(space, time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>51980 &#x27;nan&#x27; &#x27;nan&#x27; ... 17895 17896</div><input id='attrs-dc1c234b-cc5b-4438-af8f-5e1b754e7e33' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dc1c234b-cc5b-4438-af8f-5e1b754e7e33' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f9b4a744-f84d-4485-8085-e071990d5d47' class='xr-var-data-in' type='checkbox'><label for='data-f9b4a744-f84d-4485-8085-e071990d5d47' 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>_ChunkSizes :</span></dt><dd>1024</dd></dl></div><div class='xr-var-data'><pre>array([[51980, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;],\n",
       "       [61684, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;],\n",
       "       [67602, &#x27;nan&#x27;, 67603, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;],\n",
       "       [16115, 16116, &#x27;nan&#x27;, ..., 17894, 17895, 17896]], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-94f0bcc0-6102-4c43-a78f-4e196cfeaa9b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-94f0bcc0-6102-4c43-a78f-4e196cfeaa9b' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>ctdpf_ckl_seawater_pressure</span></div><div class='xr-var-dims'>(space, time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>54.15 &#x27;nan&#x27; &#x27;nan&#x27; ... 410.6 410.6</div><input id='attrs-a140d608-1b31-49b7-9435-ac340b8d6225' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a140d608-1b31-49b7-9435-ac340b8d6225' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ee11702-90b6-44cb-9cda-0eec5c6fc81f' class='xr-var-data-in' type='checkbox'><label for='data-6ee11702-90b6-44cb-9cda-0eec5c6fc81f' 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>comment :</span></dt><dd>Seawater Pressure refers to the pressure exerted on a sensor in situ by the weight of the column of seawater above it. It is calculated by subtracting one standard atmosphere from the absolute pressure at the sensor to remove the weight of the atmosphere on top of the water column. The pressure at a sensor in situ provides a metric of the depth of that sensor.</dd><dt><span>long_name :</span></dt><dd>Seawater Pressure</dd><dt><span>data_product_identifier :</span></dt><dd>PRESWAT_L1</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd><dt><span>units :</span></dt><dd>dbar</dd><dt><span>ancillary_variables :</span></dt><dd>pressure</dd><dt><span>_ChunkSizes :</span></dt><dd>10000</dd></dl></div><div class='xr-var-data'><pre>array([[54.150000000000006, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;],\n",
       "       [100.6, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;],\n",
       "       [122.34, &#x27;nan&#x27;, 122.34, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;],\n",
       "       [19.65, 19.63, &#x27;nan&#x27;, ..., 410.62, 410.62, 410.62]], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ctdpf_ckl_seawater_temperature</span></div><div class='xr-var-dims'>(space, time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>20.46 &#x27;nan&#x27; &#x27;nan&#x27; ... 9.675 9.674</div><input id='attrs-3765a6eb-9188-417c-bb4f-05f8ebe03c50' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3765a6eb-9188-417c-bb4f-05f8ebe03c50' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-548ef3c6-d4a2-421f-897b-7c0746401ad5' class='xr-var-data-in' type='checkbox'><label for='data-548ef3c6-d4a2-421f-897b-7c0746401ad5' 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>comment :</span></dt><dd>Seawater temperature near the sensor.</dd><dt><span>long_name :</span></dt><dd>Seawater Temperature</dd><dt><span>precision :</span></dt><dd>4</dd><dt><span>data_product_identifier :</span></dt><dd>TEMPWAT_L1</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd><dt><span>units :</span></dt><dd>ºC</dd><dt><span>ancillary_variables :</span></dt><dd>ctdpf_ckl_seawater_temperature_qartod_results ctdpf_ckl_seawater_temperature_qartod_executed temperature</dd><dt><span>_ChunkSizes :</span></dt><dd>10000</dd></dl></div><div class='xr-var-data'><pre>array([[20.4614, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;],\n",
       "       [14.9423, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;],\n",
       "       [15.6482, &#x27;nan&#x27;, 15.6482, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;],\n",
       "       [23.3567, 23.3548, &#x27;nan&#x27;, ..., 9.6786, 9.6749, 9.6739]],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>practical_salinity</span></div><div class='xr-var-dims'>(space, time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>35.31 &#x27;nan&#x27; &#x27;nan&#x27; ... 35.28 35.28</div><input id='attrs-bea99cc4-7aa3-4ba0-8ff0-c4a389a63062' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bea99cc4-7aa3-4ba0-8ff0-c4a389a63062' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93efa399-405f-4eb8-a7c4-66956e02d9f1' class='xr-var-data-in' type='checkbox'><label for='data-93efa399-405f-4eb8-a7c4-66956e02d9f1' 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>comment :</span></dt><dd>Salinity is generally defined as the concentration of dissolved salt in a parcel of seawater. Practical Salinity is a more specific unitless quantity calculated from the conductivity of seawater and adjusted for temperature and pressure. It is approximately equivalent to Absolute Salinity (the mass fraction of dissolved salt in seawater) but they are not interchangeable.</dd><dt><span>long_name :</span></dt><dd>Practical Salinity</dd><dt><span>precision :</span></dt><dd>4</dd><dt><span>data_product_identifier :</span></dt><dd>PRACSAL_L2</dd><dt><span>standard_name :</span></dt><dd>sea_water_practical_salinity</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>ancillary_variables :</span></dt><dd>pressure conductivity temperature</dd><dt><span>_ChunkSizes :</span></dt><dd>10000</dd></dl></div><div class='xr-var-data'><pre>array([[35.31464116031057, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;],\n",
       "       [35.47381083487019, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;],\n",
       "       [36.005347029670425, &#x27;nan&#x27;, 36.004986033055076, ..., &#x27;nan&#x27;, &#x27;nan&#x27;,\n",
       "        &#x27;nan&#x27;],\n",
       "       [35.97571004180622, 35.973881760935875, &#x27;nan&#x27;, ...,\n",
       "        35.281689180945946, 35.28139718949233, 35.282581802907956]],\n",
       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7a0ecebb-a1b4-44bc-8873-6a2d9e369b79' class='xr-section-summary-in' type='checkbox'  ><label for='section-7a0ecebb-a1b4-44bc-8873-6a2d9e369b79' class='xr-section-summary' >Attributes: <span>(59)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>_NCProperties :</span></dt><dd>version=1|netcdflibversion=4.6.1|hdf5libversion=1.10.4</dd><dt><span>node :</span></dt><dd>WFP01</dd><dt><span>comment :</span></dt><dd></dd><dt><span>publisher_email :</span></dt><dd></dd><dt><span>sourceUrl :</span></dt><dd>http://oceanobservatories.org/</dd><dt><span>collection_method :</span></dt><dd>recovered_wfp</dd><dt><span>stream :</span></dt><dd>ctdpf_ckl_wfp_instrument_recovered</dd><dt><span>featureType :</span></dt><dd>point</dd><dt><span>creator_email :</span></dt><dd></dd><dt><span>publisher_name :</span></dt><dd>Ocean Observatories Initiative</dd><dt><span>date_modified :</span></dt><dd>2020-08-06T13:23:41.238357</dd><dt><span>keywords :</span></dt><dd></dd><dt><span>cdm_data_type :</span></dt><dd>Point</dd><dt><span>references :</span></dt><dd>More information can be found at http://oceanobservatories.org/</dd><dt><span>Metadata_Conventions :</span></dt><dd>Unidata Dataset Discovery v1.0</dd><dt><span>date_created :</span></dt><dd>2020-08-06T13:23:41.238351</dd><dt><span>id :</span></dt><dd>CP03ISPM-WFP01-03-CTDPFK000-recovered_wfp-ctdpf_ckl_wfp_instrument_recovered</dd><dt><span>requestUUID :</span></dt><dd>607b59bd-cfc8-4659-868c-a894a197fb41</dd><dt><span>contributor_role :</span></dt><dd></dd><dt><span>summary :</span></dt><dd>Dataset Generated by Stream Engine from Ocean Observatories Initiative</dd><dt><span>keywords_vocabulary :</span></dt><dd></dd><dt><span>institution :</span></dt><dd>Ocean Observatories Initiative</dd><dt><span>naming_authority :</span></dt><dd>org.oceanobservatories</dd><dt><span>feature_Type :</span></dt><dd>point</dd><dt><span>infoUrl :</span></dt><dd>http://oceanobservatories.org/</dd><dt><span>license :</span></dt><dd></dd><dt><span>contributor_name :</span></dt><dd></dd><dt><span>uuid :</span></dt><dd>607b59bd-cfc8-4659-868c-a894a197fb41</dd><dt><span>creator_name :</span></dt><dd>Ocean Observatories Initiative</dd><dt><span>title :</span></dt><dd>Data produced by Stream Engine version 1.15.0 for CP03ISPM-WFP01-03-CTDPFK000-recovered_wfp-ctdpf_ckl_wfp_instrument_recovered</dd><dt><span>sensor :</span></dt><dd>03-CTDPFK000</dd><dt><span>standard_name_vocabulary :</span></dt><dd>NetCDF Climate and Forecast (CF) Metadata Convention Standard Name Table 29</dd><dt><span>acknowledgement :</span></dt><dd></dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>project :</span></dt><dd>Ocean Observatories Initiative</dd><dt><span>source :</span></dt><dd>CP03ISPM-WFP01-03-CTDPFK000-recovered_wfp-ctdpf_ckl_wfp_instrument_recovered</dd><dt><span>publisher_url :</span></dt><dd>http://oceanobservatories.org/</dd><dt><span>creator_url :</span></dt><dd>http://oceanobservatories.org/</dd><dt><span>nodc_template_version :</span></dt><dd>NODC_NetCDF_TimeSeries_Orthogonal_Template_v1.1</dd><dt><span>subsite :</span></dt><dd>CP03ISPM</dd><dt><span>processing_level :</span></dt><dd>L2</dd><dt><span>history :</span></dt><dd>2020-08-06T13:23:41.238281 generated from Stream Engine</dd><dt><span>time_coverage_start :</span></dt><dd>2019-10-06T15:00:03</dd><dt><span>time_coverage_end :</span></dt><dd>2019-10-31T21:22:39.977728</dd><dt><span>time_coverage_resolution :</span></dt><dd>P13.80S</dd><dt><span>geospatial_lat_min :</span></dt><dd>40.364817</dd><dt><span>geospatial_lat_max :</span></dt><dd>40.364817</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.1</dd><dt><span>geospatial_lon_min :</span></dt><dd>-70.888668</dd><dt><span>geospatial_lon_max :</span></dt><dd>-70.888668</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.1</dd><dt><span>geospatial_vertical_units :</span></dt><dd>meters</dd><dt><span>geospatial_vertical_resolution :</span></dt><dd>0.1</dd><dt><span>geospatial_vertical_positive :</span></dt><dd>down</dd><dt><span>DODS.strlen :</span></dt><dd>18</dd><dt><span>DODS.dimName :</span></dt><dd>string18</dd><dt><span>DODS_EXTRA.Unlimited_Dimension :</span></dt><dd>obs</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                         (space: 4, time: 4949)\n",
       "Coordinates:\n",
       "  * time                            (time) datetime64[ns] 2019-10-15T03:00:02...\n",
       "    lat                             (space, time) object 40.36 'nan' ... 39.94\n",
       "    pressure                        (space, time) object 6.415e+03 ... 4.206e+04\n",
       "    lon                             (space, time) object -70.89 'nan' ... -70.88\n",
       "    obs                             (space, time) object 51980 'nan' ... 17896\n",
       "Dimensions without coordinates: space\n",
       "Data variables:\n",
       "    ctdpf_ckl_seawater_pressure     (space, time) object 54.15 'nan' ... 410.6\n",
       "    ctdpf_ckl_seawater_temperature  (space, time) object 20.46 'nan' ... 9.674\n",
       "    practical_salinity              (space, time) object 35.31 'nan' ... 35.28\n",
       "Attributes:\n",
       "    _NCProperties:                   version=1|netcdflibversion=4.6.1|hdf5lib...\n",
       "    node:                            WFP01\n",
       "    comment:                         \n",
       "    publisher_email:                 \n",
       "    sourceUrl:                       http://oceanobservatories.org/\n",
       "    collection_method:               recovered_wfp\n",
       "    stream:                          ctdpf_ckl_wfp_instrument_recovered\n",
       "    featureType:                     point\n",
       "    creator_email:                   \n",
       "    publisher_name:                  Ocean Observatories Initiative\n",
       "    date_modified:                   2020-08-06T13:23:41.238357\n",
       "    keywords:                        \n",
       "    cdm_data_type:                   Point\n",
       "    references:                      More information can be found at http://...\n",
       "    Metadata_Conventions:            Unidata Dataset Discovery v1.0\n",
       "    date_created:                    2020-08-06T13:23:41.238351\n",
       "    id:                              CP03ISPM-WFP01-03-CTDPFK000-recovered_wf...\n",
       "    requestUUID:                     607b59bd-cfc8-4659-868c-a894a197fb41\n",
       "    contributor_role:                \n",
       "    summary:                         Dataset Generated by Stream Engine from ...\n",
       "    keywords_vocabulary:             \n",
       "    institution:                     Ocean Observatories Initiative\n",
       "    naming_authority:                org.oceanobservatories\n",
       "    feature_Type:                    point\n",
       "    infoUrl:                         http://oceanobservatories.org/\n",
       "    license:                         \n",
       "    contributor_name:                \n",
       "    uuid:                            607b59bd-cfc8-4659-868c-a894a197fb41\n",
       "    creator_name:                    Ocean Observatories Initiative\n",
       "    title:                           Data produced by Stream Engine version 1...\n",
       "    sensor:                          03-CTDPFK000\n",
       "    standard_name_vocabulary:        NetCDF Climate and Forecast (CF) Metadat...\n",
       "    acknowledgement:                 \n",
       "    Conventions:                     CF-1.6\n",
       "    project:                         Ocean Observatories Initiative\n",
       "    source:                          CP03ISPM-WFP01-03-CTDPFK000-recovered_wf...\n",
       "    publisher_url:                   http://oceanobservatories.org/\n",
       "    creator_url:                     http://oceanobservatories.org/\n",
       "    nodc_template_version:           NODC_NetCDF_TimeSeries_Orthogonal_Templa...\n",
       "    subsite:                         CP03ISPM\n",
       "    processing_level:                L2\n",
       "    history:                         2020-08-06T13:23:41.238281 generated fro...\n",
       "    time_coverage_start:             2019-10-06T15:00:03\n",
       "    time_coverage_end:               2019-10-31T21:22:39.977728\n",
       "    time_coverage_resolution:        P13.80S\n",
       "    geospatial_lat_min:              40.364817\n",
       "    geospatial_lat_max:              40.364817\n",
       "    geospatial_lat_units:            degrees_north\n",
       "    geospatial_lat_resolution:       0.1\n",
       "    geospatial_lon_min:              -70.888668\n",
       "    geospatial_lon_max:              -70.888668\n",
       "    geospatial_lon_units:            degrees_east\n",
       "    geospatial_lon_resolution:       0.1\n",
       "    geospatial_vertical_units:       meters\n",
       "    geospatial_vertical_resolution:  0.1\n",
       "    geospatial_vertical_positive:    down\n",
       "    DODS.strlen:                     18\n",
       "    DODS.dimName:                    string18\n",
       "    DODS_EXTRA.Unlimited_Dimension:  obs"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Merge into a single dataframe\n",
    "xr.concat([ids15,cids15,cods15,ods15],dim=\"space\",fill_value='nan')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualize Profile Slice with bathymetry"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(500.0, 0.0)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Visualize\n",
    "figsize=(12, 6)\n",
    "fig, ax= plt.subplots(figsize=figsize)\n",
    "\n",
    "cci=ids15.plot.scatter(x=\"lat\", y=\"ctdpf_ckl_seawater_pressure\", c=ids15.practical_salinity.data, vmin=34.0,vmax=36.0)\n",
    "\n",
    "\n",
    "ccci=cids15.plot.scatter(x=\"lat\", y=\"ctdpf_ckl_seawater_pressure\", c=cids15.practical_salinity.data, vmin=34.0,vmax=36.0)\n",
    "\n",
    "\n",
    "ccco=cods15.plot.scatter(x=\"lat\", y=\"ctdpf_ckl_seawater_pressure\", c=cods15.practical_salinity.data, vmin=34.0,vmax=36.0)\n",
    "\n",
    "cco=ods15.plot.scatter(x=\"lat\", y=\"ctdpf_ckl_seawater_pressure\", c=ods15.practical_salinity.data, vmin=34.0,vmax=36.0)\n",
    "\n",
    "cco.set_clim(34.0,36.0)\n",
    "\n",
    "#Add colorbar\n",
    "plt.colorbar(cco,label='Salinity',cmap='hot')\n",
    "\n",
    "\n",
    "######### =======  Bathymetry\n",
    "z=bathymetry.z.values.reshape([1023,535]).mean(axis=1)\n",
    "\n",
    "# #Get lattitude range\n",
    "y=np.linspace(bathymetry.y_range[1],bathymetry.y_range[0],1023)\n",
    "\n",
    "\n",
    "#Convert to z to p\n",
    "p=gsw.p_from_z(z,y)\n",
    "\n",
    "# #PLot bathymetry line\n",
    "plt.plot(y,p,color=\"black\", linewidth=1.5, zorder=3)\n",
    "plt.fill_between(y,p, y2=p.max(), color=\"0.9\", zorder=3)\n",
    "\n",
    "#Remove grid\n",
    "plt.grid(False)\n",
    "\n",
    "#Flip x and y axes\n",
    "plt.gca().invert_yaxis()\n",
    "plt.gca().invert_xaxis()\n",
    "plt.xlim(40.5,39.75)\n",
    "plt.ylim(500,0)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ultimate Goal\n",
    "Write a function that takes in a dataframe with nx4xt observations, where \n",
    "n=maximum number of depth points\n",
    "4=number of mooring profilers\n",
    "t=number of time steps observed\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Merge data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "x and y must have same first dimension, but have shapes (1023,) and (535,)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-114-7d6e768b038a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     32\u001b[0m \u001b[0;31m#PLot\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     33\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 34\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mz\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     35\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mxlim\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m39.8\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m40.5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     36\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mylim\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m500\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/my-conda-envs/OHW20/lib/python3.8/site-packages/matplotlib/pyplot.py\u001b[0m in \u001b[0;36mplot\u001b[0;34m(scalex, scaley, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m   2821\u001b[0m \u001b[0;34m@\u001b[0m\u001b[0m_copy_docstring_and_deprecators\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mAxes\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2822\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscalex\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscaley\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2823\u001b[0;31m     return gca().plot(\n\u001b[0m\u001b[1;32m   2824\u001b[0m         \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscalex\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mscalex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mscaley\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mscaley\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2825\u001b[0m         **({\"data\": data} if data is not None else {}), **kwargs)\n",
      "\u001b[0;32m~/my-conda-envs/OHW20/lib/python3.8/site-packages/matplotlib/axes/_axes.py\u001b[0m in \u001b[0;36mplot\u001b[0;34m(self, scalex, scaley, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1741\u001b[0m         \"\"\"\n\u001b[1;32m   1742\u001b[0m         \u001b[0mkwargs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcbook\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnormalize_kwargs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmlines\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mLine2D\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1743\u001b[0;31m         \u001b[0mlines\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_lines\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1744\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mline\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mlines\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1745\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd_line\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mline\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/my-conda-envs/OHW20/lib/python3.8/site-packages/matplotlib/axes/_base.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m    271\u001b[0m                 \u001b[0mthis\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    272\u001b[0m                 \u001b[0margs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 273\u001b[0;31m             \u001b[0;32myield\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_plot_args\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mthis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    274\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    275\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mget_next_color\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/my-conda-envs/OHW20/lib/python3.8/site-packages/matplotlib/axes/_base.py\u001b[0m in \u001b[0;36m_plot_args\u001b[0;34m(self, tup, kwargs)\u001b[0m\n\u001b[1;32m    397\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    398\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 399\u001b[0;31m             raise ValueError(f\"x and y must have same first dimension, but \"\n\u001b[0m\u001b[1;32m    400\u001b[0m                              f\"have shapes {x.shape} and {y.shape}\")\n\u001b[1;32m    401\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m2\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: x and y must have same first dimension, but have shapes (1023,) and (535,)"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:OHW20]",
   "language": "python",
   "name": "conda-env-OHW20-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}