physics/reports/Molly_James.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Molly_datareport.ipynb","version":"0.3.2","views":{},"default_view":{},"provenance":[],"collapsed_sections":[]}},"cells":[{"metadata":{"id":"7FhTQgqrnnOI","colab_type":"text"},"cell_type":"markdown","source":["# Connecticut River plume signature in the Coastal Pioneer Array from annual peak discharge, 2017\n","Looking at the Inshore Surface Mooring (**CP03ISSM**), the Central Surface Mooring (**CP01CNSM**), and the Offshore Surface Mooring (**CP04OSSM**). Using the Bulk Meteorology Package (METBK) to try to corroborate each other and track the surface salinity. Cruise data is available as well. \n","\n","Possibly corroborate other Connecticut River Plume data from NASA MODIS satellite data, OOI Cruise data, and/or from Mike Whitney, UConn (?). \n","\n","\n","---\n","\n","\n","Molly James, University of Connecticut (molly.james@uconn.edu)\n","\n","OOI Data Workshop - Physics\n","\n","May 21-25, 2018"]},{"metadata":{"id":"d7jEh2xJscm6","colab_type":"text"},"cell_type":"markdown","source":["# Starting to look at the data \n","| Site | Instrument | Deployment | Reference Designator | Method | Stream \n","| -- | -- | -- | -- | -- | --\n","| Inshore  | METBK | 5 | [CP03ISSM-SBD11-06-METBKA000](https://ooinet.oceanobservatories.org/data_access/?search=CP03ISSM-SBD11-06-METBKA000) | recovered_host | metbk_a_dcl_instrument\n","| Central | METBK | 6 & 7  |[CP01CNSM-SBD12-06-METBKA000](https://ooinet.oceanobservatories.org/data_access/?search=CP01CNSM-SBD12-06-METBKA000) | recovered_host | metbk_a_dcl_instrument |\n","| Offshore | METBK | 5 & 6 | [CP04OSSM-SBD11-06-METBKA000](https://ooinet.oceanobservatories.org/data_access/?search=CP04OSSM-SBD11-06-METBKA000) | recovered_host | metbk_a_dcl_instrument"]},{"metadata":{"id":"sqobFT5BrCis","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":["## Using the API to navigate the data available from CP03ISPM\n","\n","# First, let's import the Python libraries we will need\n","import requests\n","import datetime\n","import matplotlib.pyplot as plt\n","import pandas as pd\n","import numpy as np\n","import re\n","import os"],"execution_count":0,"outputs":[]},{"metadata":{"id":"JRGr4wXhm-4J","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":["# API Information\n","USERNAME ='OOIAPI-B3GJ9N7J18VVKI'\n","TOKEN= '9KXZ1WIFTM'\n","VOCAB_API = 'https://ooinet.oceanobservatories.org/api/m2m/12586/vocab/inv' # used to get metadata\n","ANNO_API = 'https://ooinet.oceanobservatories.org/api/m2m/12580/anno/find'  # annotations API url\n"],"execution_count":0,"outputs":[]},{"metadata":{"id":"xnJxUOF0tea1","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":["# Instrument Information\n","site1 = 'CP03ISSM' # inshore surface mooring\n","site2 = 'CP01CNSM' # central surface mooring\n","site3 = 'CP04OSSM' # offshore surface mooring\n","node  = 'SBD11'\n","node2 = 'SBD12'\n","instrument = '06-METBKA000'\n","method = 'recovered_host'              # need to have the underscore not a dash!\n","stream = 'metbk_a_dcl_instrument_recovered'"],"execution_count":0,"outputs":[]},{"metadata":{"id":"b3YDIyx4acud","colab_type":"text"},"cell_type":"markdown","source":["## Time of interest\n","Time period of interest is the peak discharge of the Connecticut River in the spring. This is usually in April when the snow melts in the watershed, therefore, to get a window of data is good, so March to May. \n","\n","Only going to consider the data from Spring 2017.\n","* Inshore Surface\n","* Central Surface\n","  * two options for METBK instruments \n","* Offshore Surface\n","* MODIS Satellite Ocean Color \n","* Cruise Data?\n","  * Need to see timing of cruises for deployments"]},{"metadata":{"id":"x_AvkQ0qcG5m","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":221},"outputId":"5c497d61-a8a6-44c5-f33d-7df00668638d","executionInfo":{"status":"ok","timestamp":1527256025238,"user_tz":240,"elapsed":6378,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["# importing new libraries\n","!pip install netCDF4\n","import netCDF4 as nc\n","\n","!pip install xarray\n","import xarray as xr\n","\n","!pip install cmocean\n","import cmocean\n"],"execution_count":0,"outputs":[{"output_type":"stream","text":["Requirement already satisfied: netCDF4 in /usr/local/lib/python2.7/dist-packages (1.4.0)\r\n","Requirement already satisfied: numpy>=1.7 in /usr/local/lib/python2.7/dist-packages (from netCDF4) (1.14.3)\r\n","Requirement already satisfied: cftime in /usr/local/lib/python2.7/dist-packages (from netCDF4) (1.0.0)\r\n","Requirement already satisfied: setuptools>=18.0 in /usr/local/lib/python2.7/dist-packages (from cftime->netCDF4) (39.2.0)\r\n","Requirement already satisfied: cython in /usr/local/lib/python2.7/dist-packages (from cftime->netCDF4) (0.28.2)\n","Requirement already satisfied: xarray in /usr/local/lib/python2.7/dist-packages (0.10.4)\n","Requirement already satisfied: pandas>=0.18.0 in /usr/local/lib/python2.7/dist-packages (from xarray) (0.22.0)\n","Requirement already satisfied: numpy>=1.11 in /usr/local/lib/python2.7/dist-packages (from xarray) (1.14.3)\n","Requirement already satisfied: pytz>=2011k in /usr/local/lib/python2.7/dist-packages (from pandas>=0.18.0->xarray) (2018.4)\n","Requirement already satisfied: python-dateutil in /usr/local/lib/python2.7/dist-packages (from pandas>=0.18.0->xarray) (2.5.3)\n","Requirement already satisfied: six>=1.5 in /usr/local/lib/python2.7/dist-packages (from python-dateutil->pandas>=0.18.0->xarray) (1.11.0)\n","Requirement already satisfied: cmocean in /usr/local/lib/python2.7/dist-packages (1.1)\n"],"name":"stdout"}]},{"metadata":{"id":"zwYKJuUBjpoH","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":["# request to see the timing of the deployments, when time periods we want to look at\n","# Specify some functions to convert timestamps\n","ntp_epoch = datetime.datetime(1900, 1, 1)\n","unix_epoch = datetime.datetime(1970, 1, 1)\n","ntp_delta = (unix_epoch - ntp_epoch).total_seconds()\n","\n","def ntp_seconds_to_datetime(ntp_seconds):\n","    return datetime.datetime.utcfromtimestamp(ntp_seconds - ntp_delta).replace(microsecond=0)\n","  \n","def convert_time(ms):\n","  if ms != None:\n","    return datetime.datetime.utcfromtimestamp(ms/1000)\n","  else:\n","    return None"],"execution_count":0,"outputs":[]},{"metadata":{"id":"wwqJCr7vZpvu","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":80},"outputId":"b59d808d-39e4-4c26-dab2-669228816283","executionInfo":{"status":"ok","timestamp":1527256029458,"user_tz":240,"elapsed":1021,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["# Setup the API request url\n","# to check the time period of the deployment\n","\n","ASSET_API = 'https://ooinet.oceanobservatories.org/api/m2m/12587'           # calibration/deployment Info\n","data_request_url = ASSET_API + '/events/deployment/query'\n","params = {                                  # checking if available for spring 2018\n","  'beginDT':'2017-03-01T00:00:00.000Z', \n","  'endDT':'2017-06-01T00:00:00.000Z',\n","  'refdes':site1+'-'+node+'-'+instrument,   # change site between site1, site2, site3\n","}\n","\n","# Grab the information from the server\n","r = requests.get(data_request_url, params=params, auth=(USERNAME, TOKEN))\n","data = r.json()\n","\n","df = pd.DataFrame() # Setup empty array\n","for d in data:\n","  df = df.append({\n","      'deployment': d['deploymentNumber'],\n","      'start': convert_time(d['eventStartTime']),\n","      'stop': convert_time(d['eventStopTime']),\n","      'latitude': d['location']['latitude'],\n","      'longitude': d['location']['longitude'],\n","      'sensor': d['sensor']['uid'],\n","      'asset_id': d['sensor']['assetId'],\n","    }, ignore_index=True)\n","df"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>asset_id</th>\n","      <th>deployment</th>\n","      <th>latitude</th>\n","      <th>longitude</th>\n","      <th>sensor</th>\n","      <th>start</th>\n","      <th>stop</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>284.0</td>\n","      <td>5.0</td>\n","      <td>40.36192</td>\n","      <td>-70.87827</td>\n","      <td>CGINS-METLGR-00012</td>\n","      <td>2016-10-11 13:39:00</td>\n","      <td>2017-06-15 15:56:00</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   asset_id  deployment  latitude  longitude              sensor  \\\n","0     284.0         5.0  40.36192  -70.87827  CGINS-METLGR-00012   \n","\n","                start                stop  \n","0 2016-10-11 13:39:00 2017-06-15 15:56:00  "]},"metadata":{"tags":[]},"execution_count":64}]},{"metadata":{"id":"aPpW4PpdfKAa","colab_type":"text"},"cell_type":"markdown","source":["## Inshore Surface Mooring CP03ISSM\n","\n","Asynchronous requesting the NetCDF files to get the whole data set telemetered because not recovered yet"]},{"metadata":{"id":"FA9LkuP2ZcKK","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":["beginDT = '2017-03-01T00:00:00.000Z'\n","endDT = '2017-06-01T00:00:00.000Z'\n","\n","DATA_API = 'https://ooinet.oceanobservatories.org/api/m2m/12576/sensor/inv' # used to get data\n"],"execution_count":0,"outputs":[]},{"metadata":{"id":"8sMYfJZRgFPK","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":["# Inshore Surface Mooring \n","# DO NOT RERUN B/C ALREADY REQUESTED\n","#data_request_url ='/'.join((DATA_API,site1,node,instrument,method,stream))\n","#params = {\n","#    'beginDT':beginDT,\n","#    'endDT':endDT,   \n","#}\n","#r = requests.get(data_request_url, params=params, auth=(USERNAME, TOKEN))\n","#data = r.json()\n"],"execution_count":0,"outputs":[]},{"metadata":{"id":"_4psARyzcfB4","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":["#data\n"],"execution_count":0,"outputs":[]},{"metadata":{"id":"yKSzlBOHXt-6","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":["#whos # lets you see your variable space"],"execution_count":0,"outputs":[]},{"metadata":{"id":"67ixtUEqYI6P","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":["#%%time\n","#check_complete = data['allURLs'][1] + '/status.txt'\n","#for i in range(1800): \n","#    r = requests.get(check_complete)\n","#    if r.status_code == requests.codes.ok:\n","#        print('request completed')\n","#        break\n","#    else:\n","#        time.sleep(1)"],"execution_count":0,"outputs":[]},{"metadata":{"id":"aUAjwb3YmsWQ","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":["#data['allURLs'][0]"],"execution_count":0,"outputs":[]},{"metadata":{"id":"_d_01YJSgIUX","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":71},"outputId":"42ff4d52-5402-4d02-b803-2e68edd7ec1f","executionInfo":{"status":"ok","timestamp":1527256038509,"user_tz":240,"elapsed":549,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["#Parse the thredds server to get a list of all NetCDF files. Each deployment is seperated into a seperate netcdf file.\n","\n","url = 'https://opendap.oceanobservatories.org/thredds/catalog/ooi/molly.james@uconn.edu/20180524T140008-CP03ISSM-SBD11-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered/catalog.html'\n","tds_url = 'https://opendap.oceanobservatories.org/thredds/dodsC'\n","datasets = requests.get(url).text\n","urls = re.findall(r'href=[\\'\"]?([^\\'\" >]+)', datasets)\n","x = re.findall(r'(ooi/.*?.nc)', datasets)\n","for i in x:\n","    if i.endswith('.nc') == False:\n","        x.remove(i)\n","for i in x:\n","    try:\n","        float(i[-4])\n","    except:\n","        x.remove(i)\n","datasets1 = [os.path.join(tds_url, i) for i in x]\n","datasets1"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["[u'https://opendap.oceanobservatories.org/thredds/dodsC/ooi/molly.james@uconn.edu/20180524T140008-CP03ISSM-SBD11-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered/deployment0005_CP03ISSM-SBD11-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered_20170301T000032.626000-20170531T235954.139000.nc',\n"," u'https://opendap.oceanobservatories.org/thredds/dodsC/ooi/molly.james@uconn.edu/20180524T140008-CP03ISSM-SBD11-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered/deployment0005_CP03ISSM-RID26-04-VELPTA000-recovered_host-velpt_ab_dcl_instrument_recovered_20170301T000008-20170531T234516.nc']"]},"metadata":{"tags":[]},"execution_count":69}]},{"metadata":{"id":"L5jwG6DqnVb9","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":["# remove the VELPT (point velocity instrument) data from datasets that was added???\n"],"execution_count":0,"outputs":[]},{"metadata":{"id":"MCdvYfERp4R5","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":34},"outputId":"bfd51b77-a3a6-4dbb-9cea-be0713e3893e","executionInfo":{"status":"ok","timestamp":1527256043087,"user_tz":240,"elapsed":2198,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["!pip install dask"],"execution_count":0,"outputs":[{"output_type":"stream","text":["Requirement already satisfied: dask in /usr/local/lib/python2.7/dist-packages (0.17.5)\r\n"],"name":"stdout"}]},{"metadata":{"id":"d3uE9t6QgLX5","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":54},"outputId":"c61d2f67-f4c7-4830-e4c4-f5ed5c8032f0","executionInfo":{"status":"ok","timestamp":1527256047208,"user_tz":240,"elapsed":344,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["# Load all files into a single xarray dataset.\n","# xarray is for the geosciences community. uses pandas, numpy, and math libraries under the hood. and understands the netCDF file formats.\n","data_url1 = datasets1[0]\n","data_url1"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["u'https://opendap.oceanobservatories.org/thredds/dodsC/ooi/molly.james@uconn.edu/20180524T140008-CP03ISSM-SBD11-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered/deployment0005_CP03ISSM-SBD11-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered_20170301T000032.626000-20170531T235954.139000.nc'"]},"metadata":{"tags":[]},"execution_count":71}]},{"metadata":{"id":"2HYuNyiYi9Nc","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":2618},"outputId":"c738eb09-a155-4df7-9244-243294dc3932","executionInfo":{"status":"ok","timestamp":1527256054281,"user_tz":240,"elapsed":5956,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["# Open the dataset\n","ds_issm = xr.open_dataset(data_url1)\n","\n","# Swap the dimensions\n","ds_issm = ds_issm.swap_dims({'obs': 'time'})\n","ds_issm"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<xarray.Dataset>\n","Dimensions:                               (time: 132121)\n","Coordinates:\n","    obs                                   (time) int32 0 1 2 3 4 5 6 7 8 9 ...\n","  * time                                  (time) datetime64[ns] 2017-03-01T00:00:32.625999872 ...\n","    lat                                   (time) float64 ...\n","    lon                                   (time) float64 ...\n","Data variables:\n","    deployment                            (time) int32 ...\n","    id                                    (time) |S64 ...\n","    air_temperature                       (time) float32 ...\n","    barometric_pressure                   (time) float32 ...\n","    dcl_controller_timestamp              (time) object ...\n","    driver_timestamp                      (time) datetime64[ns] ...\n","    eastward_wind_velocity                (time) float32 ...\n","    ingestion_timestamp                   (time) datetime64[ns] ...\n","    internal_timestamp                    (time) datetime64[ns] ...\n","    longwave_irradiance                   (time) float32 ...\n","    northward_wind_velocity               (time) float32 ...\n","    port_timestamp                        (time) datetime64[ns] ...\n","    precipitation                         (time) float32 ...\n","    preferred_timestamp                   (time) object ...\n","    provenance                            (time) |S64 ...\n","    relative_humidity                     (time) float32 ...\n","    sea_surface_conductivity              (time) float32 ...\n","    sea_surface_temperature               (time) float32 ...\n","    shortwave_irradiance                  (time) float32 ...\n","    met_barpres                           (time) float32 ...\n","    met_windavg_mag_corr_east             (time) float64 ...\n","    met_windavg_mag_corr_north            (time) float64 ...\n","    met_netsirr                           (time) float32 ...\n","    met_salsurf                           (time) float64 ...\n","    met_spechum                           (time) float32 ...\n","    ct_depth                              (time) float64 ...\n","    eastward_velocity                     (time) float64 ...\n","    northward_velocity                    (time) float64 ...\n","    met_current_direction                 (time) float64 ...\n","    met_current_speed                     (time) float64 ...\n","    met_relwind_direction                 (time) float64 ...\n","    met_relwind_speed                     (time) float64 ...\n","    met_heatflx_minute                    (time) float64 ...\n","    met_latnflx_minute                    (time) float64 ...\n","    met_netlirr_minute                    (time) float64 ...\n","    met_sensflx_minute                    (time) float64 ...\n","    barometric_pressure_qc_executed       (time) float32 ...\n","    barometric_pressure_qc_results        (time) float32 ...\n","    relative_humidity_qc_executed         (time) float32 ...\n","    relative_humidity_qc_results          (time) float32 ...\n","    air_temperature_qc_executed           (time) float32 ...\n","    air_temperature_qc_results            (time) float32 ...\n","    longwave_irradiance_qc_executed       (time) float32 ...\n","    longwave_irradiance_qc_results        (time) float32 ...\n","    precipitation_qc_executed             (time) float32 ...\n","    precipitation_qc_results              (time) float32 ...\n","    sea_surface_temperature_qc_executed   (time) float32 ...\n","    sea_surface_temperature_qc_results    (time) float32 ...\n","    sea_surface_conductivity_qc_executed  (time) float32 ...\n","    sea_surface_conductivity_qc_results   (time) float32 ...\n","    shortwave_irradiance_qc_executed      (time) float32 ...\n","    shortwave_irradiance_qc_results       (time) float32 ...\n","    eastward_wind_velocity_qc_executed    (time) float32 ...\n","    eastward_wind_velocity_qc_results     (time) float32 ...\n","    northward_wind_velocity_qc_executed   (time) float32 ...\n","    northward_wind_velocity_qc_results    (time) float32 ...\n","    met_barpres_qc_executed               (time) float32 ...\n","    met_barpres_qc_results                (time) float32 ...\n","    met_current_direction_qc_executed     (time) float32 ...\n","    met_current_direction_qc_results      (time) float32 ...\n","    met_current_speed_qc_executed         (time) float32 ...\n","    met_current_speed_qc_results          (time) float32 ...\n","    met_relwind_direction_qc_executed     (time) float32 ...\n","    met_relwind_direction_qc_results      (time) float32 ...\n","    met_relwind_speed_qc_executed         (time) float32 ...\n","    met_relwind_speed_qc_results          (time) float32 ...\n","    met_netsirr_qc_executed               (time) float32 ...\n","    met_netsirr_qc_results                (time) float32 ...\n","    met_salsurf_qc_executed               (time) float32 ...\n","    met_salsurf_qc_results                (time) float32 ...\n","    met_spechum_qc_executed               (time) float32 ...\n","    met_spechum_qc_results                (time) float32 ...\n","Attributes:\n","    _NCProperties:                      version=1|netcdflibversion=4.4.1.1|hd...\n","    node:                               SBD11\n","    comment:                            \n","    publisher_email:                    \n","    sourceUrl:                          http://oceanobservatories.org/\n","    collection_method:                  recovered_host\n","    stream:                             metbk_a_dcl_instrument_recovered\n","    featureType:                        point\n","    creator_email:                      \n","    publisher_name:                     Ocean Observatories Initiative\n","    date_modified:                      2018-05-24T14:00:27.503008\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:                       2018-05-24T14:00:27.503002\n","    id:                                 CP03ISSM-SBD11-06-METBKA000-recovered...\n","    requestUUID:                        13e7ef22-aee5-4efc-b367-754990dc63ae\n","    contributor_role:                   \n","    summary:                            Dataset Generated by Stream Engine fr...\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:                               13e7ef22-aee5-4efc-b367-754990dc63ae\n","    creator_name:                       Ocean Observatories Initiative\n","    title:                              Data produced by Stream Engine versio...\n","    sensor:                             06-METBKA000\n","    standard_name_vocabulary:           NetCDF Climate and Forecast (CF) Meta...\n","    acknowledgement:                    \n","    Conventions:                        CF-1.6\n","    project:                            Ocean Observatories Initiative\n","    source:                             CP03ISSM-SBD11-06-METBKA000-recovered...\n","    publisher_url:                      http://oceanobservatories.org/\n","    creator_url:                        http://oceanobservatories.org/\n","    nodc_template_version:              NODC_NetCDF_TimeSeries_Orthogonal_Tem...\n","    subsite:                            CP03ISSM\n","    processing_level:                   L2\n","    history:                            2018-05-24T14:00:27.502931 generated ...\n","    Manufacturer:                       Star Engineering\n","    ModelNumber:                        ASIMET\n","    SerialNumber:                       LGR012\n","    Description:                        Bulk Meteorology Instrument Package: ...\n","    FirmwareVersion:                    Not specified.\n","    SoftwareVersion:                    Not specified.\n","    AssetUniqueID:                      CGINS-METLGR-00012\n","    Notes:                              Not specified.\n","    Owner:                              Not specified.\n","    RemoteResources:                    []\n","    ShelfLifeExpirationDate:            Not specified.\n","    Mobile:                             False\n","    AssetManagementRecordLastModified:  2018-05-21T12:22:39.937000\n","    time_coverage_start:                2017-03-01T00:00:32.626000\n","    time_coverage_end:                  2017-05-31T23:59:54.139000\n","    time_coverage_resolution:           P60.16S\n","    geospatial_lat_min:                 40.36192\n","    geospatial_lat_max:                 40.36192\n","    geospatial_lat_units:               degrees_north\n","    geospatial_lat_resolution:          0.1\n","    geospatial_lon_min:                 -70.87827\n","    geospatial_lon_max:                 -70.87827\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:                        36\n","    DODS.dimName:                       string36\n","    DODS_EXTRA.Unlimited_Dimension:     obs"]},"metadata":{"tags":[]},"execution_count":72}]},{"metadata":{"id":"UwTohKA-RAJ6","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":51},"outputId":"246ec4e1-8170-4f90-cac3-4b2d4c590974","executionInfo":{"status":"ok","timestamp":1527256056697,"user_tz":240,"elapsed":300,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["print(ds_issm.geospatial_lat_max)\n","print(ds_issm.geospatial_lon_max)"],"execution_count":0,"outputs":[{"output_type":"stream","text":["40.36192\n","-70.87827\n"],"name":"stdout"}]},{"metadata":{"id":"v9MAIDmPjAFE","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":376},"outputId":"a7ea1613-d430-41b4-ebf6-009c0785dd2e","executionInfo":{"status":"ok","timestamp":1527256066785,"user_tz":240,"elapsed":2239,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["# plotting?\n","## my attempt at plotting\n","\n","plt.plot(ds_issm['time'],ds_issm['met_salsurf'],'r.')\n","plt.title('CP03ISSM, Sea Surface Salinity')\n","plt.ylabel('Salinity')\n","plt.xlabel('Time')\n","plt.show()"],"execution_count":0,"outputs":[{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAfUAAAFnCAYAAAC/5tBZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nvwtx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9lAHHFXXxt49MHa50d7s8/B9AT1UBlP03NmBn1T6/zepehdCgnppBS2cS9iFEfaP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\nkS0qHvqH/7X+XRVdMVvsWHQFaIPv1G1JPS8vD5GRkYiN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hLh69aqYN2+eT8U9ZswYUVVV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\n","text/plain":["<matplotlib.figure.Figure at 0x7fe12886bc10>"]},"metadata":{"tags":[]}}]},{"metadata":{"id":"HrgARM_SnDLu","colab_type":"text"},"cell_type":"markdown","source":["![alt text](https://nadww01.er.usgs.gov/nwisweb/data/img/USGS.01184000.66838.00060..20170301.20170601.log.0.p50.pres.gif)\n","\n","This is the peak discharge time period for the Connecticut River. There will be a delay in the response of the ocean. It makes sense that the salinity would decrease after around April 15th (which it does in the above salinity plot)"]},{"metadata":{"id":"1638fixmkigf","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":376},"outputId":"0b4a6eed-373b-4dc7-87e0-534ee7532a25","executionInfo":{"status":"ok","timestamp":1527256079988,"user_tz":240,"elapsed":1277,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["\n","plt.plot(ds_issm['time'],ds_issm['met_salsurf_qc_executed'],'b.')\n","\n","plt.title('CP03ISSM, OOI QC Executed SSS')\n","plt.ylabel('Salinity')\n","plt.xlabel('Time')\n","\n","plt.show()"],"execution_count":0,"outputs":[{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAfUAAAFnCAYAAAC/5tBZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nsWM1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cJlBgwblesfr169XfHx8prHBwcEKDw9XRESEnnrqKTVv3lySNHjwYE2ePFl169ZV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\nglAHAMAiCHUAACyCUAcAwCL+P3BJmwJR/4eJAAAAAElFTkSuQmCC\n","text/plain":["<matplotlib.figure.Figure at 0x7fe124a15e90>"]},"metadata":{"tags":[]}}]},{"metadata":{"id":"P5l0WKTnuyJy","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":376},"outputId":"20ffcb32-0f43-4f69-d9d8-3d8dff920f51","executionInfo":{"status":"ok","timestamp":1527256084234,"user_tz":240,"elapsed":1702,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["plt.plot(ds_issm['time'],ds_issm['met_salsurf_qc_results'],'.')\n","\n","plt.title('CP03ISSM, OOI QC Results SSS')\n","plt.ylabel('Salinity')\n","plt.xlabel('Time')\n","plt.xlim(['2017-03-01T00:00:00.000Z','2017-06-01T00:00:00.000Z'])\n","\n","plt.show()"],"execution_count":0,"outputs":[{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAgYAAAFnCAYAAADdf4HCAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nLIIBAACwCAYAAMD6f7FQ/qcPEmEAAAAAAElFTkSuQmCC\n","text/plain":["<matplotlib.figure.Figure at 0x7fe125625410>"]},"metadata":{"tags":[]}}]},{"metadata":{"id":"4BDQu5dzohO7","colab_type":"text"},"cell_type":"markdown","source":["## Central Surface Mooring CP01CNSM\n","going to get a larger time window to show the movement of the plume to the shelf.\n"]},{"metadata":{"id":"owcTvQ3_o_V5","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":["beginDT = '2017-02-01T00:00:00.000Z'\n","endDT = '2017-09-01T00:00:00.000Z'\n","#Larger time period \n"],"execution_count":0,"outputs":[]},{"metadata":{"id":"mJTNmGI1nEJv","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":111},"outputId":"eed7cbfa-de24-432d-dc1c-af58f5ec0468","executionInfo":{"status":"ok","timestamp":1527256088733,"user_tz":240,"elapsed":1251,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["data_request_url = ASSET_API + '/events/deployment/query'\n","params = {                                   # checking if available for spring 2018\n","  'beginDT':beginDT, \n","  'endDT':endDT,\n","  'refdes':site2+'-'+node2+'-'+instrument,   # change site between site1, site2, site3\n","}\n","\n","# Grab the information from the server\n","r = requests.get(data_request_url, params=params, auth=(USERNAME, TOKEN))\n","data = r.json()\n","\n","df = pd.DataFrame() # Setup empty array\n","for d in data:\n","  df = df.append({\n","      'deployment': d['deploymentNumber'],\n","      'start': convert_time(d['eventStartTime']),\n","      'stop': convert_time(d['eventStopTime']),\n","      'latitude': d['location']['latitude'],\n","      'longitude': d['location']['longitude'],\n","      'sensor': d['sensor']['uid'],\n","      'asset_id': d['sensor']['assetId'],\n","    }, ignore_index=True)\n","df"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>asset_id</th>\n","      <th>deployment</th>\n","      <th>latitude</th>\n","      <th>longitude</th>\n","      <th>sensor</th>\n","      <th>start</th>\n","      <th>stop</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>313.0</td>\n","      <td>6.0</td>\n","      <td>40.133420</td>\n","      <td>-70.77847</td>\n","      <td>CGINS-METLGR-00031</td>\n","      <td>2016-10-13 18:36:00</td>\n","      <td>2017-06-09 16:05:00</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>146.0</td>\n","      <td>7.0</td>\n","      <td>40.139817</td>\n","      <td>-70.77115</td>\n","      <td>CGINS-METLGR-00007</td>\n","      <td>2017-06-09 14:24:00</td>\n","      <td>2017-11-01 20:33:00</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   asset_id  deployment   latitude  longitude              sensor  \\\n","0     313.0         6.0  40.133420  -70.77847  CGINS-METLGR-00031   \n","1     146.0         7.0  40.139817  -70.77115  CGINS-METLGR-00007   \n","\n","                start                stop  \n","0 2016-10-13 18:36:00 2017-06-09 16:05:00  \n","1 2017-06-09 14:24:00 2017-11-01 20:33:00  "]},"metadata":{"tags":[]},"execution_count":80}]},{"metadata":{"id":"RSlb8pDApCnw","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":["# Central Surface Mooring, site2 and node2 (more data at node2)\n","# DO NOT RERUN B/C ALREADY REQUESTED\n","\n","#data_request_url ='/'.join((DATA_API,site2,node2,instrument,method,stream))\n","#params = {\n","#    'beginDT':beginDT,\n","#    'endDT':endDT,   \n","#}\n","#r = requests.get(data_request_url, params=params, auth=(USERNAME, TOKEN))\n","#data = r.json()\n"],"execution_count":0,"outputs":[]},{"metadata":{"id":"_2l9aDhsnHah","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":["#data"],"execution_count":0,"outputs":[]},{"metadata":{"id":"1Wvci6clnD_0","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":["#data['allURLs'][0]"],"execution_count":0,"outputs":[]},{"metadata":{"id":"3ECw2tRjnDj2","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":105},"outputId":"24e86c1f-2502-4250-e06a-d0500a115328","executionInfo":{"status":"ok","timestamp":1527256094449,"user_tz":240,"elapsed":489,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["#Parse the thredds server to get a list of all NetCDF files. Each deployment is seperated into a seperate netcdf file.\n","\n","url = 'https://opendap.oceanobservatories.org/thredds/catalog/ooi/molly.james@uconn.edu/20180524T150109-CP01CNSM-SBD12-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered/catalog.html'\n","tds_url = 'https://opendap.oceanobservatories.org/thredds/dodsC'\n","datasets = requests.get(url).text\n","urls = re.findall(r'href=[\\'\"]?([^\\'\" >]+)', datasets)\n","x = re.findall(r'(ooi/.*?.nc)', datasets)\n","for i in x:\n","    if i.endswith('.nc') == False:\n","        x.remove(i)\n","for i in x:\n","    try:\n","        float(i[-4])\n","    except:\n","        x.remove(i)\n","datasets2 = [os.path.join(tds_url, i) for i in x]\n","datasets2"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["[u'https://opendap.oceanobservatories.org/thredds/dodsC/ooi/molly.james@uconn.edu/20180524T150109-CP01CNSM-SBD12-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered/deployment0007_CP01CNSM-SBD12-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered_20170609T142445.583000-20170831T235925.584000.nc',\n"," u'https://opendap.oceanobservatories.org/thredds/dodsC/ooi/molly.james@uconn.edu/20180524T150109-CP01CNSM-SBD12-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered/deployment0007_CP01CNSM-RID26-04-VELPTA000-recovered_host-velpt_ab_dcl_instrument_recovered_20170609T143000-20170901T000000.nc',\n"," u'https://opendap.oceanobservatories.org/thredds/dodsC/ooi/molly.james@uconn.edu/20180524T150109-CP01CNSM-SBD12-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered/deployment0006_CP01CNSM-SBD12-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered_20170201T000059.314000-20170609T095244.332000.nc',\n"," u'https://opendap.oceanobservatories.org/thredds/dodsC/ooi/molly.james@uconn.edu/20180524T150109-CP01CNSM-SBD12-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered/deployment0006_CP01CNSM-RID26-04-VELPTA000-recovered_host-velpt_ab_dcl_instrument_recovered_20170201T000023-20170609T094542.nc']"]},"metadata":{"tags":[]},"execution_count":83}]},{"metadata":{"id":"SNZoC9sztMCi","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":71},"outputId":"6f05ade0-cee0-4749-c8c7-bbdd630e3c15","executionInfo":{"status":"ok","timestamp":1527256096131,"user_tz":240,"elapsed":338,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["# only looking at the METBK package not the VELPT\n","data_url2 = datasets2[0],datasets2[2]\n","data_url2"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(u'https://opendap.oceanobservatories.org/thredds/dodsC/ooi/molly.james@uconn.edu/20180524T150109-CP01CNSM-SBD12-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered/deployment0007_CP01CNSM-SBD12-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered_20170609T142445.583000-20170831T235925.584000.nc',\n"," u'https://opendap.oceanobservatories.org/thredds/dodsC/ooi/molly.james@uconn.edu/20180524T150109-CP01CNSM-SBD12-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered/deployment0006_CP01CNSM-SBD12-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered_20170201T000059.314000-20170609T095244.332000.nc')"]},"metadata":{"tags":[]},"execution_count":84}]},{"metadata":{"id":"8vcyOYvItL4e","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":["#Load all files into a single xarray dataset.\n","\n","ds_cnsm = xr.open_mfdataset(data_url2)\n","ds_cnsm = ds_cnsm.swap_dims({'obs': 'time'})\n","ds_cnsm = ds_cnsm.chunk({'time': 100})\n","ds_cnsm = ds_cnsm.sortby('time') # data from different deployments can overlap so we want to sort all data by time stamp.\n","ds_cnsm"],"execution_count":0,"outputs":[]},{"metadata":{"id":"JSTwiDTTtLoy","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":376},"outputId":"80de02d7-7bce-4d4a-8ef7-89328ed7b8ef","executionInfo":{"status":"ok","timestamp":1527255872008,"user_tz":240,"elapsed":1026,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["\n","plt.plot(ds_cnsm['time'],ds_cnsm['met_salsurf'],'r.')\n","plt.title('CP01CNSM, Sea Surface Salinity')\n","plt.ylabel('Salinity')\n","plt.xlabel('Time')\n","#plt.xlim(['2017-05-14T00:00:00.000Z','2017-06-15T00:00:00.000Z'])\n","plt.show()\n"],"execution_count":0,"outputs":[{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAfUAAAFnCAYAAAC/5tBZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nx47FDz/8g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b5VyJnPyZz199e8nHK/A+7sRFt6gag5cRxC4ybQp3+HqIa3ui1XAcb3zh4m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\nrkJggg==\n","text/plain":["<matplotlib.figure.Figure at 0x7fe1307e8ed0>"]},"metadata":{"tags":[]}}]},{"metadata":{"id":"a9pk01bCu67O","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":376},"outputId":"2a53f383-fd18-4d25-b75f-db206291ffb7","executionInfo":{"status":"ok","timestamp":1527176419156,"user_tz":240,"elapsed":839,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["\n","plt.plot(ds_cnsm['time'],ds_cnsm['met_salsurf_qc_executed'],'b.')\n","\n","plt.title('CP01CNSM, OOI QC Executed SSS')\n","plt.ylabel('Salinity')\n","plt.xlabel('Time')\n","plt.show()"],"execution_count":0,"outputs":[{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAfUAAAFnCAYAAAC/5tBZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n3KOVK1eqQ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hds2bJFCQkJWr58uTIzMxUdHa21a9eqXbt2Ra7PF+dy2yUpLS3rsvuUXlWd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\noj7LcPgAAAAASUVORK5CYII=\n","text/plain":["<matplotlib.figure.Figure at 0x7f663d04e090>"]},"metadata":{"tags":[]}}]},{"metadata":{"id":"KUbF7OLHu6uo","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":376},"outputId":"68203a88-f095-42d3-ec2a-44543ac4a836","executionInfo":{"status":"ok","timestamp":1527176391658,"user_tz":240,"elapsed":1017,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["plt.plot(ds_cnsm['time'],ds_cnsm['met_salsurf_qc_results'],'.')\n","\n","plt.title('CP01CNSM, OOI QC Results SSS')\n","plt.ylabel('Salinity')\n","plt.xlabel('Time')\n","plt.show()\n","#this doesn't look right either..."],"execution_count":0,"outputs":[{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAfUAAAFnCAYAAAC/5tBZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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ePAgRo8eDQDo27cv5s+f36htEhER2TOrSr179+5YsWIFevXqBa1WqzweGBhY5xitVgudTgcASE5O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\nOhERkSRY6kRERJL4f8CfIsjnXekIAAAAAElFTkSuQmCC\n","text/plain":["<matplotlib.figure.Figure at 0x7f663273a590>"]},"metadata":{"tags":[]}}]},{"metadata":{"id":"4BVg5MHXzu6_","colab_type":"text"},"cell_type":"markdown","source":["Some strangeness with the QC results, scattered low salinity things that aren't in a pattern"]},{"metadata":{"id":"_YOWcGtHz3xo","colab_type":"text"},"cell_type":"markdown","source":["## Offshore Surface Mooring CP04OSSM\n","Now to check if the salinity is affected by the plume this far out onto the shelf."]},{"metadata":{"id":"DzJ_F7YP0MRR","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":["beginDT = '2017-02-01T00:00:00.000Z'\n","endDT = '2017-09-01T00:00:00.000Z'\n","#Larger time period \n"],"execution_count":0,"outputs":[]},{"metadata":{"id":"o0n1nf6p0MH4","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":111},"outputId":"965f4382-d7ff-45e6-c29f-819c66b336fd","executionInfo":{"status":"ok","timestamp":1527176629800,"user_tz":240,"elapsed":615,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["data_request_url = ASSET_API + '/events/deployment/query'\n","params = {                                   # checking if available for spring 2018\n","  'beginDT':beginDT, \n","  'endDT':endDT,\n","  'refdes':site3+'-'+node+'-'+instrument,   # change site between site1, site2, site3\n","}\n","\n","# Grab the information from the server\n","r = requests.get(data_request_url, params=params, auth=(USERNAME, TOKEN))\n","data = r.json()\n","\n","df = pd.DataFrame() # Setup empty array\n","for d in data:\n","  df = df.append({\n","      'deployment': d['deploymentNumber'],\n","      'start': convert_time(d['eventStartTime']),\n","      'stop': convert_time(d['eventStopTime']),\n","      'latitude': d['location']['latitude'],\n","      'longitude': d['location']['longitude'],\n","      'sensor': d['sensor']['uid'],\n","      'asset_id': d['sensor']['assetId'],\n","    }, ignore_index=True)\n","df"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>asset_id</th>\n","      <th>deployment</th>\n","      <th>latitude</th>\n","      <th>longitude</th>\n","      <th>sensor</th>\n","      <th>start</th>\n","      <th>stop</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>290.0</td>\n","      <td>5.0</td>\n","      <td>39.937070</td>\n","      <td>-70.886970</td>\n","      <td>CGINS-METLGR-00016</td>\n","      <td>2016-10-12 14:26:00</td>\n","      <td>2017-06-08 12:05:00</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>235.0</td>\n","      <td>6.0</td>\n","      <td>39.939367</td>\n","      <td>-70.876817</td>\n","      <td>CGINS-METLGR-00038</td>\n","      <td>2017-06-06 14:51:00</td>\n","      <td>2017-11-02 14:15:00</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   asset_id  deployment   latitude  longitude              sensor  \\\n","0     290.0         5.0  39.937070 -70.886970  CGINS-METLGR-00016   \n","1     235.0         6.0  39.939367 -70.876817  CGINS-METLGR-00038   \n","\n","                start                stop  \n","0 2016-10-12 14:26:00 2017-06-08 12:05:00  \n","1 2017-06-06 14:51:00 2017-11-02 14:15:00  "]},"metadata":{"tags":[]},"execution_count":228}]},{"metadata":{"id":"FHwVUo0Q0L-8","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":["# Offshore Surface Mooring, site3 and node\n","# DO NOT RERUN B/C ALREADY REQUESTED\n","#data_request_url ='/'.join((DATA_API,site3,node,instrument,method,stream))\n","#params = {\n","#    'beginDT':beginDT,\n","#    'endDT':endDT,   \n","#}\n","#r = requests.get(data_request_url, params=params, auth=(USERNAME, TOKEN))\n","#data = r.json()"],"execution_count":0,"outputs":[]},{"metadata":{"id":"LJWqaI-n0Lzg","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":136},"outputId":"5e5822b5-d37e-4de2-ab15-942862208466","executionInfo":{"status":"ok","timestamp":1527176652060,"user_tz":240,"elapsed":282,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["#data"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["{u'allURLs': [u'https://opendap.oceanobservatories.org/thredds/catalog/ooi/molly.james@uconn.edu/20180524T154404-CP04OSSM-SBD11-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered/catalog.html',\n","  u'https://opendap.oceanobservatories.org/async_results/molly.james@uconn.edu/20180524T154404-CP04OSSM-SBD11-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered'],\n"," u'numberOfSubJobs': 8,\n"," u'outputURL': u'https://opendap.oceanobservatories.org/thredds/catalog/ooi/molly.james@uconn.edu/20180524T154404-CP04OSSM-SBD11-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered/catalog.html',\n"," u'requestUUID': u'0fdd530d-e653-4fe9-807a-1444c4606d05',\n"," u'sizeCalculation': 32989787,\n"," u'timeCalculation': 60}"]},"metadata":{"tags":[]},"execution_count":230}]},{"metadata":{"id":"uc21tjGR0lVT","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":34},"outputId":"269c4729-fa20-44ea-dcc8-5f0b9a00d9d3","executionInfo":{"status":"ok","timestamp":1527177096426,"user_tz":240,"elapsed":280,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["#data['allURLs'][0]"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["u'https://opendap.oceanobservatories.org/thredds/catalog/ooi/molly.james@uconn.edu/20180524T154404-CP04OSSM-SBD11-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered/catalog.html'"]},"metadata":{"tags":[]},"execution_count":234}]},{"metadata":{"id":"Y554VF-q0lLD","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":105},"outputId":"ec086d8a-4875-4620-dde3-9457ef6ed9cf","executionInfo":{"status":"ok","timestamp":1527177140976,"user_tz":240,"elapsed":410,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["#Parse the thredds server to get a list of all NetCDF files. Each deployment is seperated into a seperate netcdf file.\n","\n","url = 'https://opendap.oceanobservatories.org/thredds/catalog/ooi/molly.james@uconn.edu/20180524T154404-CP04OSSM-SBD11-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered/catalog.html'\n","tds_url = 'https://opendap.oceanobservatories.org/thredds/dodsC'\n","datasets = requests.get(url).text\n","urls = re.findall(r'href=[\\'\"]?([^\\'\" >]+)', datasets)\n","x = re.findall(r'(ooi/.*?.nc)', datasets)\n","for i in x:\n","    if i.endswith('.nc') == False:\n","        x.remove(i)\n","for i in x:\n","    try:\n","        float(i[-4])\n","    except:\n","        x.remove(i)\n","datasets3 = [os.path.join(tds_url, i) for i in x]\n","datasets3"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["[u'https://opendap.oceanobservatories.org/thredds/dodsC/ooi/molly.james@uconn.edu/20180524T154404-CP04OSSM-SBD11-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered/deployment0006_CP04OSSM-SBD11-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered_20170606T145118.029000-20170831T235945.852000.nc',\n"," u'https://opendap.oceanobservatories.org/thredds/dodsC/ooi/molly.james@uconn.edu/20180524T154404-CP04OSSM-SBD11-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered/deployment0006_CP04OSSM-RID26-04-VELPTA000-recovered_host-velpt_ab_dcl_instrument_recovered_20170606T150000-20170815T150000.nc',\n"," u'https://opendap.oceanobservatories.org/thredds/dodsC/ooi/molly.james@uconn.edu/20180524T154404-CP04OSSM-SBD11-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered/deployment0005_CP04OSSM-SBD11-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered_20170201T000045.266000-20170608T104658.593000.nc',\n"," u'https://opendap.oceanobservatories.org/thredds/dodsC/ooi/molly.james@uconn.edu/20180524T154404-CP04OSSM-SBD11-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered/deployment0005_CP04OSSM-RID26-04-VELPTA000-recovered_host-velpt_ab_dcl_instrument_recovered_20170201T000014-20170608T103029.nc']"]},"metadata":{"tags":[]},"execution_count":235}]},{"metadata":{"id":"a5vGisp10k_C","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":71},"outputId":"73b4f287-22bf-4de6-87f1-176f08f7e092","executionInfo":{"status":"ok","timestamp":1527177178837,"user_tz":240,"elapsed":298,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["# only looking at the METBK package not the VELPT\n","data_url3 = datasets3[0],datasets3[2]\n","data_url3"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(u'https://opendap.oceanobservatories.org/thredds/dodsC/ooi/molly.james@uconn.edu/20180524T154404-CP04OSSM-SBD11-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered/deployment0006_CP04OSSM-SBD11-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered_20170606T145118.029000-20170831T235945.852000.nc',\n"," u'https://opendap.oceanobservatories.org/thredds/dodsC/ooi/molly.james@uconn.edu/20180524T154404-CP04OSSM-SBD11-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered/deployment0005_CP04OSSM-SBD11-06-METBKA000-recovered_host-metbk_a_dcl_instrument_recovered_20170201T000045.266000-20170608T104658.593000.nc')"]},"metadata":{"tags":[]},"execution_count":236}]},{"metadata":{"id":"d0MvVP3U2jwD","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":2618},"outputId":"30f2b38f-1f31-4abe-9411-d55f01769ab3","executionInfo":{"status":"ok","timestamp":1527177436980,"user_tz":240,"elapsed":206161,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["#Load all files into a single xarray dataset.\n","\n","ds_ossm = xr.open_mfdataset(data_url2)\n","ds_ossm = ds_ossm.swap_dims({'obs': 'time'})\n","ds_ossm = ds_ossm.chunk({'time': 100})\n","ds_ossm = ds_ossm.sortby('time') # data from different deployments can overlap so we want to sort all data by time stamp.\n","ds_ossm"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<xarray.Dataset>\n","Dimensions:                               (time: 304922)\n","Coordinates:\n","    obs                                   (time) int64 0 1 2 3 4 5 6 7 8 9 ...\n","  * time                                  (time) datetime64[ns] 2017-02-01T00:00:59.314000384 ...\n","    lat                                   (time) float64 40.13 40.13 40.13 ...\n","    lon                                   (time) float64 -70.78 -70.78 ...\n","Data variables:\n","    deployment                            (time) int32 6 6 6 6 6 6 6 6 6 6 6 ...\n","    id                                    (time) |S64 '5b3d928c-f989-4c39-88d7-492d057fec77' ...\n","    air_temperature                       (time) float32 7.299 7.375 7.39 ...\n","    barometric_pressure                   (time) float32 1008.05 1008.05 ...\n","    dcl_controller_timestamp              (time) object 'empty' 'empty' ...\n","    driver_timestamp                      (time) datetime64[ns] 2017-10-21T20:15:36.599900160 ...\n","    eastward_wind_velocity                (time) float32 1.29 1.99 1.64 1.06 ...\n","    ingestion_timestamp                   (time) datetime64[ns] 2017-10-21T20:16:28.013000192 ...\n","    internal_timestamp                    (time) datetime64[ns] 1900-01-01 ...\n","    longwave_irradiance                   (time) float32 289.0 323.7 331.6 ...\n","    northward_wind_velocity               (time) float32 4.2 2.55 3.84 3.07 ...\n","    port_timestamp                        (time) datetime64[ns] 2017-02-01T00:00:59.314000384 ...\n","    precipitation                         (time) float32 11.8 11.8 11.79 ...\n","    preferred_timestamp                   (time) object 'port_timestamp' ...\n","    provenance                            (time) |S64 '4bf83803-1d07-4701-8aec-ada9b4a7ae8d' ...\n","    relative_humidity                     (time) float32 80.573 80.596 ...\n","    sea_surface_conductivity              (time) float32 3.6456 3.6452 3.645 ...\n","    sea_surface_temperature               (time) float32 9.53 9.525 9.523 ...\n","    shortwave_irradiance                  (time) float32 3.1 3.4 3.5 3.8 3.9 ...\n","    met_barpres                           (time) float32 100805.0 100805.0 ...\n","    met_windavg_mag_corr_east             (time) float64 0.2139 1.299 0.6419 ...\n","    met_windavg_mag_corr_north            (time) float64 4.388 2.962 4.126 ...\n","    met_netsirr                           (time) float32 2.9294999 3.213 ...\n","    met_salsurf                           (time) float64 33.77 33.77 33.77 ...\n","    met_spechum                           (time) float32 5.120335 5.1485806 ...\n","    ct_depth                              (time) float64 1.067 1.067 1.067 ...\n","    eastward_velocity                     (time) float64 -0.2335 -0.2333 ...\n","    northward_velocity                    (time) float64 0.0532 0.05169 ...\n","    met_current_direction                 (time) float64 282.8 282.5 282.3 ...\n","    met_current_speed                     (time) float64 0.2394 0.239 0.2387 ...\n","    met_relwind_direction                 (time) float64 5.891 27.77 12.12 ...\n","    met_relwind_speed                     (time) float64 4.358 3.289 4.168 ...\n","    met_heatflx_minute                    (time) float64 nan nan nan nan nan ...\n","    met_latnflx_minute                    (time) float64 nan nan nan nan nan ...\n","    met_netlirr_minute                    (time) float64 nan nan nan nan nan ...\n","    met_sensflx_minute                    (time) float64 nan nan nan nan nan ...\n","    barometric_pressure_qc_executed       (time) float32 29.0 29.0 29.0 29.0 ...\n","    barometric_pressure_qc_results        (time) float32 29.0 29.0 29.0 29.0 ...\n","    relative_humidity_qc_executed         (time) float32 29.0 29.0 29.0 29.0 ...\n","    relative_humidity_qc_results          (time) float32 29.0 29.0 29.0 29.0 ...\n","    air_temperature_qc_executed           (time) float32 29.0 29.0 29.0 29.0 ...\n","    air_temperature_qc_results            (time) float32 29.0 29.0 29.0 29.0 ...\n","    longwave_irradiance_qc_executed       (time) float32 29.0 29.0 29.0 29.0 ...\n","    longwave_irradiance_qc_results        (time) float32 29.0 29.0 29.0 29.0 ...\n","    precipitation_qc_executed             (time) float32 29.0 29.0 29.0 29.0 ...\n","    precipitation_qc_results              (time) float32 13.0 13.0 13.0 13.0 ...\n","    sea_surface_temperature_qc_executed   (time) float32 29.0 29.0 29.0 29.0 ...\n","    sea_surface_temperature_qc_results    (time) float32 29.0 29.0 29.0 29.0 ...\n","    sea_surface_conductivity_qc_executed  (time) float32 29.0 29.0 29.0 29.0 ...\n","    sea_surface_conductivity_qc_results   (time) float32 13.0 13.0 13.0 13.0 ...\n","    shortwave_irradiance_qc_executed      (time) float32 29.0 29.0 29.0 29.0 ...\n","    shortwave_irradiance_qc_results       (time) float32 29.0 29.0 29.0 29.0 ...\n","    eastward_wind_velocity_qc_executed    (time) float32 29.0 29.0 29.0 29.0 ...\n","    eastward_wind_velocity_qc_results     (time) float32 29.0 29.0 29.0 29.0 ...\n","    northward_wind_velocity_qc_executed   (time) float32 29.0 29.0 29.0 29.0 ...\n","    northward_wind_velocity_qc_results    (time) float32 29.0 29.0 29.0 29.0 ...\n","    met_barpres_qc_executed               (time) float32 29.0 29.0 29.0 29.0 ...\n","    met_barpres_qc_results                (time) float32 29.0 29.0 29.0 29.0 ...\n","    met_current_direction_qc_executed     (time) float32 29.0 29.0 29.0 29.0 ...\n","    met_current_direction_qc_results      (time) float32 29.0 29.0 29.0 29.0 ...\n","    met_current_speed_qc_executed         (time) float32 29.0 29.0 29.0 29.0 ...\n","    met_current_speed_qc_results          (time) float32 29.0 29.0 29.0 29.0 ...\n","    met_relwind_direction_qc_executed     (time) float32 29.0 29.0 29.0 29.0 ...\n","    met_relwind_direction_qc_results      (time) float32 29.0 29.0 29.0 29.0 ...\n","    met_relwind_speed_qc_executed         (time) float32 29.0 29.0 29.0 29.0 ...\n","    met_relwind_speed_qc_results          (time) float32 29.0 29.0 29.0 29.0 ...\n","    met_netsirr_qc_executed               (time) float32 29.0 29.0 29.0 29.0 ...\n","    met_netsirr_qc_results                (time) float32 29.0 29.0 29.0 29.0 ...\n","    met_salsurf_qc_executed               (time) float32 29.0 29.0 29.0 29.0 ...\n","    met_salsurf_qc_results                (time) float32 29.0 29.0 29.0 29.0 ...\n","    met_spechum_qc_executed               (time) float32 29.0 29.0 29.0 29.0 ...\n","    met_spechum_qc_results                (time) float32 29.0 29.0 29.0 29.0 ...\n","Attributes:\n","    _NCProperties:                      version=1|netcdflibversion=4.4.1.1|hd...\n","    node:                               SBD12\n","    comment:                            \n","    publisher_email:                    \n","    sourceUrl:                          http://oceanobservatories.org/\n","    collection_method:                  recovered_host\n","    stream:                             metbk_a_dcl_instrument_recovered\n","    featureType:                        point\n","    creator_email:                      \n","    publisher_name:                     Ocean Observatories Initiative\n","    date_modified:                      2018-05-24T15:01:30.683753\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:                       2018-05-24T15:01:30.683746\n","    id:                                 CP01CNSM-SBD12-06-METBKA000-recovered...\n","    requestUUID:                        eefba1c8-ae03-4b39-bd61-d2ba37800b06\n","    contributor_role:                   \n","    summary:                            Dataset Generated by Stream Engine fr...\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:                               eefba1c8-ae03-4b39-bd61-d2ba37800b06\n","    creator_name:                       Ocean Observatories Initiative\n","    title:                              Data produced by Stream Engine versio...\n","    sensor:                             06-METBKA000\n","    standard_name_vocabulary:           NetCDF Climate and Forecast (CF) Meta...\n","    acknowledgement:                    \n","    Conventions:                        CF-1.6\n","    project:                            Ocean Observatories Initiative\n","    source:                             CP01CNSM-SBD12-06-METBKA000-recovered...\n","    publisher_url:                      http://oceanobservatories.org/\n","    creator_url:                        http://oceanobservatories.org/\n","    nodc_template_version:              NODC_NetCDF_TimeSeries_Orthogonal_Tem...\n","    subsite:                            CP01CNSM\n","    processing_level:                   L2\n","    history:                            2018-05-24T15:01:30.683675 generated ...\n","    Manufacturer:                       Star Engineering\n","    ModelNumber:                        ASIMET\n","    SerialNumber:                       LGR007\n","    Description:                        Bulk Meteorology Instrument Package: ...\n","    FirmwareVersion:                    Not specified.\n","    SoftwareVersion:                    Not specified.\n","    AssetUniqueID:                      CGINS-METLGR-00007\n","    Notes:                              Not specified.\n","    Owner:                              Not specified.\n","    RemoteResources:                    []\n","    ShelfLifeExpirationDate:            Not specified.\n","    Mobile:                             False\n","    AssetManagementRecordLastModified:  2018-05-21T12:22:39.322000\n","    time_coverage_start:                2017-06-09T14:24:45.583000\n","    time_coverage_end:                  2017-08-31T23:59:25.584000\n","    time_coverage_resolution:           P60.00S\n","    geospatial_lat_min:                 40.13981667\n","    geospatial_lat_max:                 40.13981667\n","    geospatial_lat_units:               degrees_north\n","    geospatial_lat_resolution:          0.1\n","    geospatial_lon_min:                 -70.77115\n","    geospatial_lon_max:                 -70.77115\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:                        36\n","    DODS.dimName:                       string36\n","    DODS_EXTRA.Unlimited_Dimension:     obs"]},"metadata":{"tags":[]},"execution_count":237}]},{"metadata":{"id":"l5hl7mhv2jm5","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":376},"outputId":"5385d289-d775-4607-a735-8516844562f4","executionInfo":{"status":"ok","timestamp":1527177729831,"user_tz":240,"elapsed":1071,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["plt.plot(ds_ossm['time'],ds_ossm['met_salsurf'],'r.')\n","plt.title('CP04OSSM, Sea Surface Salinity')\n","plt.ylabel('Salinity')\n","plt.xlabel('Time')\n","# plt.xlim(['2017-03-01T00:00:00.000Z','2017-06-01T00:00:00.000Z'])\n","plt.show()"],"execution_count":0,"outputs":[{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAfUAAAFnCAYAAAC/5tBZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\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sRGv5R1adcqpbL2eftLiD6WdoPMhKPXDEnvfddHtTpTA0mWlHjQFWr6p0jmkBgOKRR5D9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\n","text/plain":["<matplotlib.figure.Figure at 0x7f6636737590>"]},"metadata":{"tags":[]}}]},{"metadata":{"id":"uBYc3CmB2jcF","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":376},"outputId":"0108f3ed-2e26-449f-cc0e-3b148a246293","executionInfo":{"status":"ok","timestamp":1527177747462,"user_tz":240,"elapsed":976,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["\n","plt.plot(ds_ossm['time'],ds_ossm['met_salsurf_qc_executed'],'b.')\n","\n","plt.title('CP04OSSM, OOI QC Executed SSS')\n","plt.ylabel('Salinity')\n","plt.xlabel('Time')\n","plt.show()"],"execution_count":0,"outputs":[{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAfUAAAFnCAYAAAC/5tBZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n6Slvb28NG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wCgPBlJGUpM/ONbCgjwvei8MpX6W2+99bt2vG3bNi1dulSvvvqqfH195evr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\nBwDAEpQ6AACW+P8AQkmuWuXYcNkAAAAASUVORK5CYII=\n","text/plain":["<matplotlib.figure.Figure at 0x7f663269b7d0>"]},"metadata":{"tags":[]}}]},{"metadata":{"id":"Lsmgb8jl4p8b","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":376},"outputId":"595d2bfb-ec27-479c-c18e-82fc62ce682f","executionInfo":{"status":"ok","timestamp":1527177768929,"user_tz":240,"elapsed":1020,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["\n","plt.plot(ds_ossm['time'],ds_ossm['met_salsurf_qc_results'],'.')\n","\n","plt.title('CP04OSSM, OOI QC Executed SSS')\n","plt.ylabel('Salinity')\n","plt.xlabel('Time')\n","plt.show()"],"execution_count":0,"outputs":[{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAfUAAAFnCAYAAAC/5tBZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nEBYvXqys8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kRERLeORkt96tSpAIDly5c3yWSIiIjo5ln0I21btmzBp59+iqKiIgghlOW7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\nIiJJsNSJiIgkwVInIiKSBEudiIhIEv8Pc0NYOkB50qoAAAAASUVORK5CYII=\n","text/plain":["<matplotlib.figure.Figure at 0x7f6635470250>"]},"metadata":{"tags":[]}}]},{"metadata":{"id":"z3G0_f_fUWtj","colab_type":"text"},"cell_type":"markdown","source":["# Satellite data for peak discharge LIS\n","[Connecticut River Plume viewed from Satellite, 555 nm](https://drive.google.com/file/d/1WMORja_-R_cCKqvs_du7gSw5wV0vFq08/view?usp=sharing)\n","\n","[2017/04/16\n","](https://drive.google.com/file/d/1O4Z12mJV4k3gHYuVcEIF0GzBveq-If5l/view?usp=sharing)\n","\n","[2017/04/18\n","](https://drive.google.com/file/d/1lkwUK7yFpEioCnxHTUmkvtNQq7xRPFX_/view?usp=sharing)\n","\n","[2017/05/04\n","](https://drive.google.com/file/d/1GNOPNc1b6YMzScnoM35x1jWTbHna7x-n/view?usp=sharing)\n","\n","[2017/05/18](https://drive.google.com/file/d/1clzfsulHnVLl-dVkdP13IMdWFafjZrOb/view?usp=sharing)\n","\n","\n","Yellow shading within the Long Island Sound is the evidence of the plume in MODIS satellite color data from [NASA](https://oceancolor.gsfc.nasa.gov/cgi/browse.pl?sen=am). Downloaded the NetCDF files for days in April and May which had enough coverage (not blocked by clouds). These days are after the peack discharge: April 16, April 18, May 04, and May 18, 2017. The red box on the plots is the location of the Inshore Surface Mooring. \n","\n","\n"]},{"metadata":{"id":"C_vd0hGFp-Hk","colab_type":"text"},"cell_type":"markdown","source":["# CTD at 7m on ISSM\n","Check data at the ISSM Near Surface Frame CTD which is at (planned) depth of 7m. Maybe this will be able to detect the plume. I think it is unlikely because the plume is probably quite thin on the shelf. "]},{"metadata":{"id":"GWUW5S5xqCoa","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":["site1 = 'CP03ISSM'                          # inshore surface mooring\n","node = 'RID27'                              # Near Surface Instrument Frame\n","instrument = '03-CTDBPC000'                 # CTD\n","method = 'recovered_inst'                   # recovered instrument\n","# method = 'telemetered'                     # telemtered data missing for time period wanted...\n","\n","stream = 'ctdbp_cdef_instrument_recovered'  \n","\n","beginDT = '2017-02-01T00:00:00.000Z'\n","endDT = '2017-09-01T00:00:00.000Z'\n","#this is all in deployment 5 "],"execution_count":0,"outputs":[]},{"metadata":{"id":"Q27MmWWquISA","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":["# Inshore Surface Mooring \n","# DO NOT RERUN B/C ALREADY REQUESTED\n","#data_request_url ='/'.join((DATA_API,site1,node,instrument,method,stream))\n","#params = {\n","#    'beginDT':beginDT,\n","#    'endDT':endDT,   \n","#}\n","#r = requests.get(data_request_url, params=params, auth=(USERNAME, TOKEN))\n","#data = r.json()"],"execution_count":0,"outputs":[]},{"metadata":{"id":"elqwwZBaqDZ1","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":136},"outputId":"4316a7aa-a306-46ee-80ed-35f30006e63d","executionInfo":{"status":"ok","timestamp":1527192821589,"user_tz":240,"elapsed":281,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["#data"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["{u'allURLs': [u'https://opendap.oceanobservatories.org/thredds/catalog/ooi/molly.james@uconn.edu/20180524T201333-CP03ISSM-RID27-03-CTDBPC000-recovered_inst-ctdbp_cdef_instrument_recovered/catalog.html',\n","  u'https://opendap.oceanobservatories.org/async_results/molly.james@uconn.edu/20180524T201333-CP03ISSM-RID27-03-CTDBPC000-recovered_inst-ctdbp_cdef_instrument_recovered'],\n"," u'numberOfSubJobs': 30,\n"," u'outputURL': u'https://opendap.oceanobservatories.org/thredds/catalog/ooi/molly.james@uconn.edu/20180524T201333-CP03ISSM-RID27-03-CTDBPC000-recovered_inst-ctdbp_cdef_instrument_recovered/catalog.html',\n"," u'requestUUID': u'11b54a43-5606-44bb-9c8e-1b26f6248677',\n"," u'sizeCalculation': 315524,\n"," u'timeCalculation': 60}"]},"metadata":{"tags":[]},"execution_count":261}]},{"metadata":{"id":"UQXZehkvy0Wi","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":34},"outputId":"0052fa99-85e9-44d4-bf24-d6946e34ab8c","executionInfo":{"status":"ok","timestamp":1527192965383,"user_tz":240,"elapsed":272,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["#data['allURLs'][0]"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["u'https://opendap.oceanobservatories.org/thredds/catalog/ooi/molly.james@uconn.edu/20180524T201333-CP03ISSM-RID27-03-CTDBPC000-recovered_inst-ctdbp_cdef_instrument_recovered/catalog.html'"]},"metadata":{"tags":[]},"execution_count":262}]},{"metadata":{"id":"OFQ9k6tGy0Jb","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":1938},"outputId":"2cd72c10-4647-485e-d7de-5e41f7040b63","executionInfo":{"status":"ok","timestamp":1527256003961,"user_tz":240,"elapsed":4802,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["url = 'https://opendap.oceanobservatories.org/thredds/catalog/ooi/molly.james@uconn.edu/20180524T201333-CP03ISSM-RID27-03-CTDBPC000-recovered_inst-ctdbp_cdef_instrument_recovered/catalog.html'\n","tds_url = 'https://opendap.oceanobservatories.org/thredds/dodsC'\n","datasets = requests.get(url).text\n","urls = re.findall(r'href=[\\'\"]?([^\\'\" >]+)', datasets)\n","x = re.findall(r'(ooi/.*?.nc)', datasets)\n","for i in x:\n","    if i.endswith('.nc') == False:\n","        x.remove(i)\n","for i in x:\n","    try:\n","        float(i[-4])\n","    except:\n","        x.remove(i)\n","datasets4 = [os.path.join(tds_url, i) for i in x]\n","\n","ds_issm_ctd = xr.open_mfdataset(datasets4)\n","ds_issm_ctd = ds_issm_ctd.swap_dims({'obs': 'time'})\n","ds_issm_ctd\n"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<xarray.Dataset>\n","Dimensions:                                  (time: 5245)\n","Coordinates:\n","    obs                                      (time) int32 0 1 2 3 4 5 6 7 8 ...\n","  * time                                     (time) datetime64[ns] 2017-02-01 ...\n","    pressure                                 (time) float64 ...\n","    lat                                      (time) float64 ...\n","    lon                                      (time) float64 ...\n","Data variables:\n","    deployment                               (time) int32 ...\n","    id                                       (time) |S64 ...\n","    conductivity                             (time) float64 ...\n","    ctd_time                                 (time) datetime64[ns] ...\n","    driver_timestamp                         (time) datetime64[ns] ...\n","    ingestion_timestamp                      (time) datetime64[ns] ...\n","    internal_timestamp                       (time) datetime64[ns] ...\n","    port_timestamp                           (time) datetime64[ns] ...\n","    preferred_timestamp                      (time) object ...\n","    pressure_temp                            (time) float64 ...\n","    provenance                               (time) |S64 ...\n","    temperature                              (time) float64 ...\n","    ctdbp_seawater_temperature               (time) float64 ...\n","    ctdbp_seawater_pressure                  (time) float64 ...\n","    ctdbp_seawater_conductivity              (time) float64 ...\n","    practical_salinity                       (time) float64 ...\n","    density                                  (time) float64 ...\n","    conductivity_qc_executed                 (time) float32 ...\n","    conductivity_qc_results                  (time) float32 ...\n","    pressure_qc_executed                     (time) float32 ...\n","    pressure_qc_results                      (time) float32 ...\n","    ctdbp_seawater_temperature_qc_executed   (time) float32 ...\n","    ctdbp_seawater_temperature_qc_results    (time) float32 ...\n","    ctdbp_seawater_pressure_qc_executed      (time) float32 ...\n","    ctdbp_seawater_pressure_qc_results       (time) float32 ...\n","    ctdbp_seawater_conductivity_qc_executed  (time) float32 ...\n","    ctdbp_seawater_conductivity_qc_results   (time) float32 ...\n","    density_qc_executed                      (time) float32 ...\n","    density_qc_results                       (time) float32 ...\n","    practical_salinity_qc_executed           (time) float32 ...\n","    practical_salinity_qc_results            (time) float32 ...\n","Attributes:\n","    _NCProperties:                      version=1|netcdflibversion=4.4.1.1|hd...\n","    node:                               RID27\n","    comment:                            \n","    publisher_email:                    \n","    sourceUrl:                          http://oceanobservatories.org/\n","    collection_method:                  recovered_inst\n","    stream:                             ctdbp_cdef_instrument_recovered\n","    featureType:                        point\n","    creator_email:                      \n","    publisher_name:                     Ocean Observatories Initiative\n","    date_modified:                      2018-05-24T20:16:14.918634\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:                       2018-05-24T20:16:14.918632\n","    id:                                 CP03ISSM-RID27-03-CTDBPC000-recovered...\n","    requestUUID:                        d9cc8ad2-f860-4f71-b5d5-bad26a9ea004\n","    contributor_role:                   \n","    summary:                            Dataset Generated by Stream Engine fr...\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:                               d9cc8ad2-f860-4f71-b5d5-bad26a9ea004\n","    creator_name:                       Ocean Observatories Initiative\n","    title:                              Data produced by Stream Engine versio...\n","    sensor:                             03-CTDBPC000\n","    standard_name_vocabulary:           NetCDF Climate and Forecast (CF) Meta...\n","    acknowledgement:                    \n","    Conventions:                        CF-1.6\n","    project:                            Ocean Observatories Initiative\n","    source:                             CP03ISSM-RID27-03-CTDBPC000-recovered...\n","    publisher_url:                      http://oceanobservatories.org/\n","    creator_url:                        http://oceanobservatories.org/\n","    nodc_template_version:              NODC_NetCDF_TimeSeries_Orthogonal_Tem...\n","    subsite:                            CP03ISSM\n","    processing_level:                   L2\n","    history:                            2018-05-24T20:16:14.918600 generated ...\n","    Manufacturer:                       Sea-Bird Electronics\n","    ModelNumber:                        SBE 16plus V2\n","    SerialNumber:                       16-50109\n","    Description:                        CTD Pumped: CTDBP Series C\n","    FirmwareVersion:                    Not specified.\n","    SoftwareVersion:                    Not specified.\n","    AssetUniqueID:                      CGINS-CTDBPC-50109\n","    Notes:                              Not specified.\n","    Owner:                              Not specified.\n","    RemoteResources:                    []\n","    ShelfLifeExpirationDate:            Not specified.\n","    Mobile:                             False\n","    AssetManagementRecordLastModified:  2018-05-21T12:22:43.774000\n","    time_coverage_start:                2017-02-01T00:00:00\n","    time_coverage_end:                  2017-04-01T03:33:02\n","    time_coverage_resolution:           P974.33S\n","    geospatial_lat_min:                 40.36192\n","    geospatial_lat_max:                 40.36192\n","    geospatial_lat_units:               degrees_north\n","    geospatial_lat_resolution:          0.1\n","    geospatial_lon_min:                 -70.87827\n","    geospatial_lon_max:                 -70.87827\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:                        36\n","    DODS.dimName:                       string36\n","    DODS_EXTRA.Unlimited_Dimension:     obs"]},"metadata":{"tags":[]},"execution_count":58}]},{"metadata":{"id":"ZrI1CnT6yz8v","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":376},"outputId":"23e506e4-32b4-4970-957b-101fbff15a9f","executionInfo":{"status":"ok","timestamp":1527256531695,"user_tz":240,"elapsed":491,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["## plotting\n","\n","plt.plot(ds_issm_ctd['time'],ds_issm_ctd['practical_salinity'],'r.',label='practical salinity')\n","plt.plot(ds_issm_ctd['time'],ds_issm_ctd['practical_salinity_qc_executed'],'b.',label='QC executed')\n","plt.plot(ds_issm_ctd['time'],ds_issm_ctd['practical_salinity_qc_results'],'.',label='QC results')\n","\n","plt.title('CP03ISSM, 7m CTD, recovered')\n","plt.ylabel('Salinity')\n","plt.xlabel('Time')\n","plt.legend()\n","\n","plt.xlim(['2017-03-01T00:00:00.000Z','2017-06-01T00:00:00.000Z'])\n","\n","plt.show()\n","#practical_salinity\n","#practical_salinity_qc_executed\n","#practical_salinity_qc_results"],"execution_count":0,"outputs":[{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAgYAAAFnCAYAAADdf4HCAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nmAAAAABJRU5ErkJggg==\n","text/plain":["<matplotlib.figure.Figure at 0x7fe1300dc5d0>"]},"metadata":{"tags":[]}}]},{"metadata":{"id":"CXtzEGWC0z5u","colab_type":"text"},"cell_type":"markdown","source":["The data from the CTD on the Near Surface Instrument Frame is missing for the time period of interest, April and May 2017.  Wasn't able to see if there was a freshwater signal below the surface."]},{"metadata":{"id":"gIICET0QyztH","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":[""],"execution_count":0,"outputs":[]},{"metadata":{"id":"9RzkezCUnIi9","colab_type":"text"},"cell_type":"markdown","source":["# Cruise Data from Deployments\n","Perhaps look at the CTD casts during the cruises for deployments 5, 6, and 7 at the times closest to April and May 2017. \n","\n","* [CTD cast from Offshore, Cruise 8 Leg 1, 2017-06-01](https://alfresco.oceanobservatories.org/alfresco/d/d/workspace/SpacesStore/1ed1b498-7f06-4495-86b6-8098ebd8acef/3204-00802_Quick_Look_Cruise_Report_Coastal_Pioneer_8_Leg_1_2017-06-03_Ver_1-00.pdf)\n","* No data available for [Pioneer-07b_SI_2017-04-18](https://alfresco.oceanobservatories.org/alfresco/faces/jsp/browse/browse.jsp)"]},{"metadata":{"id":"7vQOSxMH9Z_q","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":["import pandas as pd\n"],"execution_count":0,"outputs":[]},{"metadata":{"id":"H_fi-OC_4pyL","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":["# First, specify the data file for the cruise CTD cast\n","# Down and Up Casts\n","cruise_data_file = 'https://alfresco.oceanobservatories.org/alfresco/d/d/workspace/SpacesStore/976c0631-48c8-4add-9d04-c95a066f56c4/ar18a009.asc'\n","\n","# Read in the data file without headers due to a bug in the file (two of the header names run together)\n","cruise_data = pd.read_table(cruise_data_file, delim_whitespace=True, header=None, skiprows=1)\n","\n","# Add back the necessary headers\n","cruise_data = cruise_data.rename(columns={0:'Pressure', 1:'Temperature', 13:'Salinity'})\n","cruist_data.head"],"execution_count":0,"outputs":[]},{"metadata":{"id":"Miw_KAhw4psA","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0},"base_uri":"https://localhost:8080/","height":376},"outputId":"2c88e8f9-aa23-4c3b-c853-16b1c0d7a1e3","executionInfo":{"status":"ok","timestamp":1527196259945,"user_tz":240,"elapsed":494,"user":{"displayName":"Molly James","photoUrl":"//lh6.googleusercontent.com/-zxGvnJYOslk/AAAAAAAAAAI/AAAAAAAAAAk/MjdTty3E624/s50-c-k-no/photo.jpg","userId":"118440168816468865461"}}},"cell_type":"code","source":["plt.gca().invert_yaxis()\n","\n","plt.plot(cruise_data.Salinity,cruise_data.Pressure,'.')\n","\n","plt.title('Ship Board CTD at Offshore Site on 06/01/2017')\n","plt.ylabel('Depth (m)')\n","plt.xlabel('Salinity (psu)')\n","\n","plt.show()\n"],"execution_count":0,"outputs":[{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAfIAAAFnCAYAAABdOssgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ngg==\n","text/plain":["<matplotlib.figure.Figure at 0x7f662f43b510>"]},"metadata":{"tags":[]}}]},{"metadata":{"id":"7cR9nhWB4piK","colab_type":"code","colab":{"autoexec":{"startup":false,"wait_interval":0}}},"cell_type":"code","source":[""],"execution_count":0,"outputs":[]},{"metadata":{"id":"_FN9LecjqEyL","colab_type":"text"},"cell_type":"markdown","source":["# Summary\n","* salinity from 3 surface buoys METBK instruments\n","* data not available at inshore mooring for near surface CTD, 7m\n","* timing of peak discharge from with USGS river portal for CT River\n","* tracked plume with NASA MODIS ocean color\n","* shipboard CTD profile measurements for April/May not available at the moment\n"]},{"metadata":{"id":"-CIkmz2EqJzL","colab_type":"text"},"cell_type":"markdown","source":["# Conclusions\n","\n","* According to the buoy measurements, the Connecticut River plume for 2017 was detected by at the Inshore site, but not the Central nor Offshore sites. \n","* Not sure what the OOI quality control measures are, some strange scatter in the graphs from the qc_results parameters\n","* Once shipboard data is available for April/May 2017 should look at it\n","* Once near surface CTD is available at inshore site should look at it\n","* Probable biofouling on the instruments, can see deployment switch in data\n","* Should perhaps look at the surface temperature data to see a signal as well\n","* More to look at!"]},{"metadata":{"id":"HKsCDCDVoJex","colab_type":"text"},"cell_type":"markdown","source":[""]}]}