week09c-ndbc-wind.ipynb

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    "## NDBC data - analysis of wind vector time series\n",
    "\n",
    "This notebook demonstrates common time series analysis techniques with a two-dimensional data set: wind velocity from a meteorological buoy offshore of Monterey Bay. The buoy is maintained by the National Data Buoy Center (NDBC).\n",
    "\n",
    "The goal of this analysis is to rotate the wind data into an alongshore component (the wind blowing parallel to shore) and a cross-shore component (the wind blowing perpendicular to shore). This is useful because it is the alongshore component of wind stress that is responsible for coastal upwelling.\n",
    "\n",
    "Functions are provided for analysis routines that are useful for a wide range of data sets. They are based on functions in a larger package located at https://github.com/physoce/physoce-py.\n",
    "\n",
    "The example here is for wind data, but the same techniques can also be applied to ocean currents or any type of vector time series. As you go through the tutorial, try the exercises to check your understanding.\n",
    "\n",
    "\n",
    "\n",
    "#### Outline\n",
    "* [Load data and packages](#load-data-and-packages)\n",
    "* [Working with vector data](#working-with-vector-data)\n",
    "* [Calculating wind stress](#calculating-wind-stress)\n",
    "* [Coordinate system rotation](#coordinate-system-rotation)\n",
    "* [Conclusion](#conclusion)\n",
    "\n",
    "\n",
    "\n"
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    "### Load data and packages\n",
    "\n",
    "#### Data source\n",
    "\n",
    "The data from Monterey NDBC buoy 46042 can be accessed from two different locations (we will be using the second here):\n",
    "\n",
    "* [Main page for buoy 46042 with real time data](https://www.ndbc.noaa.gov/station_page.php?station=46042)\n",
    "* [NDBC Thredds server](https://dods.ndbc.noaa.gov/thredds/catalog.html)\n",
    "\n"
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    "#### Load Python packages\n",
    "\n",
    "This notebook uses the [xarray](http://xarray.pydata.org/en/stable/index.html) package, which is useful for working with multi-dimensional arrays. We will use xarray to load data in NetCDF format, which is a common data format used for large data sets in the earth sciences (CDF literally stands for \"common data format\").\n",
    "\n",
    "This notebook also uses functions specifically developed for oceanographic time series analyis in the [physoce](https://github.com/physoce/physoce-py) package."
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   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import xarray as xr"
   ]
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    "#### Load wind data\n",
    "\n",
    "We can use xarray to access the data on NDBC's OpenDap server. This type of data server allows NetCDF data sets to be accessed online without ever having to download a file."
   ]
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   "source": [
    "ncfile = 'https://dods.ndbc.noaa.gov/thredds/dodsC/data/stdmet/46042/46042h2019.nc'\n",
    "#ncfile = 'data/NDBC/46042h2019.nc'"
   ]
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   "source": [
    "ds = xr.open_dataset(ncfile)"
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    "#### Data structure\n",
    "\n",
    "NetCDF files and xarray datasets are organized around coordinates. In this dataset, there are three coordinates:\n",
    "\n",
    "* time\n",
    "* latitude\n",
    "* longitude\n",
    "\n",
    "Since this buoy is a single point, the latitude and longitude coordinates have only one value each."
   ]
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:                  (time: 14855, latitude: 1, longitude: 1)\n",
       "Coordinates:\n",
       "  * time                     (time) datetime64[ns] 2019-01-01T00:50:00 ... 20...\n",
       "  * latitude                 (latitude) float32 36.78\n",
       "  * longitude                (longitude) float32 -122.4\n",
       "Data variables: (12/13)\n",
       "    wind_dir                 (time, latitude, longitude) float64 359.0 ... 315.0\n",
       "    wind_spd                 (time, latitude, longitude) float32 9.8 9.8 ... 4.5\n",
       "    gust                     (time, latitude, longitude) float32 12.5 ... 6.9\n",
       "    wave_height              (time, latitude, longitude) float32 3.03 ... nan\n",
       "    dominant_wpd             (time, latitude, longitude) timedelta64[ns] 00:0...\n",
       "    average_wpd              (time, latitude, longitude) timedelta64[ns] 00:0...\n",
       "    ...                       ...\n",
       "    air_pressure             (time, latitude, longitude) float32 1.015e+03 .....\n",
       "    air_temperature          (time, latitude, longitude) float32 13.0 ... 13.6\n",
       "    sea_surface_temperature  (time, latitude, longitude) float32 13.9 ... 13.7\n",
       "    dewpt_temperature        (time, latitude, longitude) float32 nan ... 11.9\n",
       "    visibility               (time, latitude, longitude) float32 nan nan ... nan\n",
       "    water_level              (time, latitude, longitude) float32 nan nan ... nan\n",
       "Attributes:\n",
       "    institution:                     NOAA National Data Buoy Center and Parti...\n",
       "    url:                             http://dods.ndbc.noaa.gov\n",
       "    quality:                         Automated QC checks with manual editing ...\n",
       "    conventions:                     COARDS\n",
       "    station:                         46042\n",
       "    comment:                         MONTEREY - 27NM WNW of Monterey, CA\n",
       "    location:                        36.785 N 122.398 W \n",
       "    DODS_EXTRA.Unlimited_Dimension:  time</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-199814c9-bb42-455f-8427-9fb28e29c7a3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-199814c9-bb42-455f-8427-9fb28e29c7a3' 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>: 14855</li><li><span class='xr-has-index'>latitude</span>: 1</li><li><span class='xr-has-index'>longitude</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-961d2a67-04b4-48f0-a906-6cee728332c3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-961d2a67-04b4-48f0-a906-6cee728332c3' class='xr-section-summary' >Coordinates: <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 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'>2019-01-01T00:50:00 ... 2019-12-...</div><input id='attrs-0a76a5ce-41f5-4087-9d5e-9a13c69c96be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a76a5ce-41f5-4087-9d5e-9a13c69c96be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3656ee5f-ddc2-4c18-9b39-31970c8fe508' class='xr-var-data-in' type='checkbox'><label for='data-3656ee5f-ddc2-4c18-9b39-31970c8fe508' 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>Epoch Time</dd><dt><span>short_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-01-01T00:50:00.000000000&#x27;, &#x27;2019-01-01T01:50:00.000000000&#x27;,\n",
       "       &#x27;2019-01-01T02:50:00.000000000&#x27;, ..., &#x27;2019-12-31T23:30:00.000000000&#x27;,\n",
       "       &#x27;2019-12-31T23:40:00.000000000&#x27;, &#x27;2019-12-31T23:50:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>36.78</div><input id='attrs-6d0dea44-04ba-4909-9f4c-217bec1918f1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d0dea44-04ba-4909-9f4c-217bec1918f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8dc9c312-e18b-4951-8322-4054e68d2593' class='xr-var-data-in' type='checkbox'><label for='data-8dc9c312-e18b-4951-8322-4054e68d2593' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>short_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([36.785], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-122.4</div><input id='attrs-6a550fd7-bcb6-4b82-9cfa-cebefddcfa86' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a550fd7-bcb6-4b82-9cfa-cebefddcfa86' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-990ab942-56ac-41d8-84d1-9d2c95928b58' class='xr-var-data-in' type='checkbox'><label for='data-990ab942-56ac-41d8-84d1-9d2c95928b58' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>short_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-122.398], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2bbed55c-7902-4e3a-924c-19190fb8b31b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2bbed55c-7902-4e3a-924c-19190fb8b31b' class='xr-section-summary' >Data variables: <span>(13)</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>wind_dir</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a103b886-a3da-4009-922b-225fc1638df8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a103b886-a3da-4009-922b-225fc1638df8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cecb9dd2-3f78-4374-9e7d-675010d15a48' class='xr-var-data-in' type='checkbox'><label for='data-cecb9dd2-3f78-4374-9e7d-675010d15a48' 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>Wind Direction</dd><dt><span>short_name :</span></dt><dd>wdir</dd><dt><span>standard_name :</span></dt><dd>wind_from_direction</dd><dt><span>units :</span></dt><dd>degrees_true</dd></dl></div><div class='xr-var-data'><pre>array([[[359.]],\n",
       "\n",
       "       [[357.]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[316.]],\n",
       "\n",
       "       [[315.]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wind_spd</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-be72f578-ddc5-4d27-b018-adc622c6b948' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-be72f578-ddc5-4d27-b018-adc622c6b948' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1aee5642-84c3-4739-bad8-72bbb09ec205' class='xr-var-data-in' type='checkbox'><label for='data-1aee5642-84c3-4739-bad8-72bbb09ec205' 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>Wind Speed</dd><dt><span>short_name :</span></dt><dd>wspd</dd><dt><span>standard_name :</span></dt><dd>wind_speed</dd><dt><span>units :</span></dt><dd>meters/second</dd></dl></div><div class='xr-var-data'><pre>array([[[9.8]],\n",
       "\n",
       "       [[9.8]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[4.4]],\n",
       "\n",
       "       [[4.5]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gust</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e2d5cf6a-3a1b-4c6b-ac96-a0f91127e023' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e2d5cf6a-3a1b-4c6b-ac96-a0f91127e023' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-494fdad5-b794-4f19-b1a5-eb15ebc3a49e' class='xr-var-data-in' type='checkbox'><label for='data-494fdad5-b794-4f19-b1a5-eb15ebc3a49e' 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>Wind Gust Speed</dd><dt><span>short_name :</span></dt><dd>gst</dd><dt><span>standard_name :</span></dt><dd>gust</dd><dt><span>units :</span></dt><dd>meters/second</dd></dl></div><div class='xr-var-data'><pre>array([[[12.5]],\n",
       "\n",
       "       [[11.5]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[ 6.8]],\n",
       "\n",
       "       [[ 6.9]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wave_height</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a0e342a2-3f06-4651-9dbe-d4c85502ca1d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a0e342a2-3f06-4651-9dbe-d4c85502ca1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-adc962ed-23f8-42bc-9baa-2d3cc351f347' class='xr-var-data-in' type='checkbox'><label for='data-adc962ed-23f8-42bc-9baa-2d3cc351f347' 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>Significant Wave Height</dd><dt><span>short_name :</span></dt><dd>wvht</dd><dt><span>standard_name :</span></dt><dd>significant_height_of_wave</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>array([[[3.03]],\n",
       "\n",
       "       [[2.97]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[3.82]],\n",
       "\n",
       "       [[ nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dominant_wpd</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ae195fd2-cb83-46e4-9079-a4f956f6c555' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ae195fd2-cb83-46e4-9079-a4f956f6c555' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-873670e4-405a-49ad-b2d1-c7024d098c47' class='xr-var-data-in' type='checkbox'><label for='data-873670e4-405a-49ad-b2d1-c7024d098c47' 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>Dominant Wave Period</dd><dt><span>short_name :</span></dt><dd>dpd</dd><dt><span>standard_name :</span></dt><dd>dominant_wave_period</dd></dl></div><div class='xr-var-data'><pre>array([[[10000000000]],\n",
       "\n",
       "       [[ 9090000153]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[13789999962]],\n",
       "\n",
       "       [[      &#x27;NaT&#x27;]]], dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>average_wpd</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-06ccec08-d62d-41fd-a854-d1c94a9291be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-06ccec08-d62d-41fd-a854-d1c94a9291be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e840fc58-dae6-4765-9550-df0d05af548b' class='xr-var-data-in' type='checkbox'><label for='data-e840fc58-dae6-4765-9550-df0d05af548b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Average Wave Period</dd><dt><span>short_name :</span></dt><dd>apd</dd><dt><span>standard_name :</span></dt><dd>average_wave_period</dd></dl></div><div class='xr-var-data'><pre>array([[[6440000057]],\n",
       "\n",
       "       [[6730000019]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[9819999695]],\n",
       "\n",
       "       [[     &#x27;NaT&#x27;]]], dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean_wave_dir</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0f0c8049-513a-4856-83c4-8829e26cace4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0f0c8049-513a-4856-83c4-8829e26cace4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-155515ca-e213-4fb8-9b01-84b0c307a79f' class='xr-var-data-in' type='checkbox'><label for='data-155515ca-e213-4fb8-9b01-84b0c307a79f' 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>Mean Wave Direction</dd><dt><span>short_name :</span></dt><dd>mwd</dd><dt><span>standard_name :</span></dt><dd>mean_wave_direction</dd><dt><span>units :</span></dt><dd>degrees_true</dd></dl></div><div class='xr-var-data'><pre>array([[[323.]],\n",
       "\n",
       "       [[331.]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[290.]],\n",
       "\n",
       "       [[ nan]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>air_pressure</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-725e49a9-a906-4b6c-a33a-8ff9699eedd6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-725e49a9-a906-4b6c-a33a-8ff9699eedd6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe45a829-a4f5-4a0f-b4d9-54558ff6f086' class='xr-var-data-in' type='checkbox'><label for='data-fe45a829-a4f5-4a0f-b4d9-54558ff6f086' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Level Pressure</dd><dt><span>short_name :</span></dt><dd>pres</dd><dt><span>standard_name :</span></dt><dd>air_pressure_at_sea_level</dd><dt><span>units :</span></dt><dd>hPa</dd></dl></div><div class='xr-var-data'><pre>array([[[1014.6]],\n",
       "\n",
       "       [[1015.4]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[1020.1]],\n",
       "\n",
       "       [[1020.2]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>air_temperature</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-50966ae9-a874-4393-80ca-6e62e30e188d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-50966ae9-a874-4393-80ca-6e62e30e188d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ed27f0bd-c8f2-4ac7-907c-ca5c22505da4' class='xr-var-data-in' type='checkbox'><label for='data-ed27f0bd-c8f2-4ac7-907c-ca5c22505da4' 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>Air Temperature</dd><dt><span>short_name :</span></dt><dd>atmp</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>units :</span></dt><dd>degree_Celsius</dd></dl></div><div class='xr-var-data'><pre>array([[[13. ]],\n",
       "\n",
       "       [[12.8]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[13.6]],\n",
       "\n",
       "       [[13.6]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sea_surface_temperature</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d39e7af1-00b6-4589-968c-1a2907028ecd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d39e7af1-00b6-4589-968c-1a2907028ecd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ff914cee-c8d2-401d-b60d-f32804bb6b01' class='xr-var-data-in' type='checkbox'><label for='data-ff914cee-c8d2-401d-b60d-f32804bb6b01' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Surface Temperature</dd><dt><span>short_name :</span></dt><dd>wtmp</dd><dt><span>standard_name :</span></dt><dd>sea_surface_temperature</dd><dt><span>units :</span></dt><dd>degree_Celsius</dd></dl></div><div class='xr-var-data'><pre>array([[[13.9]],\n",
       "\n",
       "       [[13.8]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[13.7]],\n",
       "\n",
       "       [[13.7]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dewpt_temperature</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a7b728b3-e048-412a-b0b8-755061d60239' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a7b728b3-e048-412a-b0b8-755061d60239' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52aaecd6-b7e7-4a04-9d5a-e78b67d74c31' class='xr-var-data-in' type='checkbox'><label for='data-52aaecd6-b7e7-4a04-9d5a-e78b67d74c31' 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>Dew Point Temperature</dd><dt><span>short_name :</span></dt><dd>dewp</dd><dt><span>standard_name :</span></dt><dd>dew_point_temperature</dd><dt><span>units :</span></dt><dd>degree_Celsius</dd></dl></div><div class='xr-var-data'><pre>array([[[ nan]],\n",
       "\n",
       "       [[ nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[11.8]],\n",
       "\n",
       "       [[11.9]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>visibility</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-de9f6c91-6757-4d51-85ee-4ea81cf710e8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-de9f6c91-6757-4d51-85ee-4ea81cf710e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-16479e9d-5b89-475c-a454-63aaa7bac7c4' class='xr-var-data-in' type='checkbox'><label for='data-16479e9d-5b89-475c-a454-63aaa7bac7c4' 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>Visibility</dd><dt><span>short_name :</span></dt><dd>vis</dd><dt><span>standard_name :</span></dt><dd>visibility_in_air</dd><dt><span>units :</span></dt><dd>US_statute_miles</dd></dl></div><div class='xr-var-data'><pre>array([[[nan]],\n",
       "\n",
       "       [[nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[nan]],\n",
       "\n",
       "       [[nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-307d13b4-dcf3-45ba-a857-3edc15b58202' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-307d13b4-dcf3-45ba-a857-3edc15b58202' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f4a938f-b6c1-4cde-aeae-209774c679c8' class='xr-var-data-in' type='checkbox'><label for='data-4f4a938f-b6c1-4cde-aeae-209774c679c8' 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>Tide Water Level</dd><dt><span>short_name :</span></dt><dd>tide</dd><dt><span>standard_name :</span></dt><dd>water_level</dd><dt><span>units :</span></dt><dd>feet</dd></dl></div><div class='xr-var-data'><pre>array([[[nan]],\n",
       "\n",
       "       [[nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[nan]],\n",
       "\n",
       "       [[nan]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8917aa46-24d3-4874-9cb8-e174b7fbcc55' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8917aa46-24d3-4874-9cb8-e174b7fbcc55' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>institution :</span></dt><dd>NOAA National Data Buoy Center and Participators in Data Assembly Center</dd><dt><span>url :</span></dt><dd>http://dods.ndbc.noaa.gov</dd><dt><span>quality :</span></dt><dd>Automated QC checks with manual editing and comprehensive monthly QC</dd><dt><span>conventions :</span></dt><dd>COARDS</dd><dt><span>station :</span></dt><dd>46042</dd><dt><span>comment :</span></dt><dd>MONTEREY - 27NM WNW of Monterey, CA</dd><dt><span>location :</span></dt><dd>36.785 N 122.398 W </dd><dt><span>DODS_EXTRA.Unlimited_Dimension :</span></dt><dd>time</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                  (time: 14855, latitude: 1, longitude: 1)\n",
       "Coordinates:\n",
       "  * time                     (time) datetime64[ns] 2019-01-01T00:50:00 ... 20...\n",
       "  * latitude                 (latitude) float32 36.78\n",
       "  * longitude                (longitude) float32 -122.4\n",
       "Data variables: (12/13)\n",
       "    wind_dir                 (time, latitude, longitude) float64 ...\n",
       "    wind_spd                 (time, latitude, longitude) float32 ...\n",
       "    gust                     (time, latitude, longitude) float32 ...\n",
       "    wave_height              (time, latitude, longitude) float32 ...\n",
       "    dominant_wpd             (time, latitude, longitude) timedelta64[ns] ...\n",
       "    average_wpd              (time, latitude, longitude) timedelta64[ns] ...\n",
       "    ...                       ...\n",
       "    air_pressure             (time, latitude, longitude) float32 ...\n",
       "    air_temperature          (time, latitude, longitude) float32 ...\n",
       "    sea_surface_temperature  (time, latitude, longitude) float32 ...\n",
       "    dewpt_temperature        (time, latitude, longitude) float32 ...\n",
       "    visibility               (time, latitude, longitude) float32 ...\n",
       "    water_level              (time, latitude, longitude) float32 ...\n",
       "Attributes:\n",
       "    institution:                     NOAA National Data Buoy Center and Parti...\n",
       "    url:                             http://dods.ndbc.noaa.gov\n",
       "    quality:                         Automated QC checks with manual editing ...\n",
       "    conventions:                     COARDS\n",
       "    station:                         46042\n",
       "    comment:                         MONTEREY - 27NM WNW of Monterey, CA\n",
       "    location:                        36.785 N 122.398 W \n",
       "    DODS_EXTRA.Unlimited_Dimension:  time"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ALIY2F0FHAmQ"
   },
   "source": [
    "To make all of the variables functions of time only, rather than time and space, we can \"squeeze\" the dataset. This removes the latitude and longitude dimensions of the data set (although they are kept as coordinates)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "id": "ohOHem1wHAmQ"
   },
   "outputs": [],
   "source": [
    "ds = ds.squeeze()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "3rP0HG-iHAmX"
   },
   "source": [
    "#### Labeled arrays\n",
    "\n",
    "One powerful feature of xarray is the ability to store metadata with each array. This can help you keep track of units."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "id": "p0KNTrv_HAmZ"
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   "outputs": [
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       "array([ 9.8,  9.8, 10.6, ...,  4.1,  4.4,  4.5], dtype=float32)\n",
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       "    short_name:     wspd\n",
       "    standard_name:  wind_speed\n",
       "    units:          meters/second</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'wind_spd'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 14855</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-cbb4c23a-3fb2-405e-a896-bbb0b193efc7' class='xr-array-in' type='checkbox' checked><label for='section-cbb4c23a-3fb2-405e-a896-bbb0b193efc7' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>9.8 9.8 10.6 9.2 9.5 7.5 6.9 6.8 ... 7.3 7.1 6.0 5.5 4.7 4.1 4.4 4.5</span></div><div class='xr-array-data'><pre>array([ 9.8,  9.8, 10.6, ...,  4.1,  4.4,  4.5], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-e5ca218d-47bb-45c0-bf05-9a69ccea125f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e5ca218d-47bb-45c0-bf05-9a69ccea125f' class='xr-section-summary' >Coordinates: <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 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'>2019-01-01T00:50:00 ... 2019-12-...</div><input id='attrs-3476e624-7f15-4a72-ac2a-c6fd0f8f44fa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3476e624-7f15-4a72-ac2a-c6fd0f8f44fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9137c062-ca13-414d-8d2a-842eb15631ec' class='xr-var-data-in' type='checkbox'><label for='data-9137c062-ca13-414d-8d2a-842eb15631ec' 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>Epoch Time</dd><dt><span>short_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-01-01T00:50:00.000000000&#x27;, &#x27;2019-01-01T01:50:00.000000000&#x27;,\n",
       "       &#x27;2019-01-01T02:50:00.000000000&#x27;, ..., &#x27;2019-12-31T23:30:00.000000000&#x27;,\n",
       "       &#x27;2019-12-31T23:40:00.000000000&#x27;, &#x27;2019-12-31T23:50:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>36.78</div><input id='attrs-83f6202f-fa9d-417a-a485-93f9fc8ac0bb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-83f6202f-fa9d-417a-a485-93f9fc8ac0bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9def36a3-89f5-4885-9f9a-ab79e6ce424f' class='xr-var-data-in' type='checkbox'><label for='data-9def36a3-89f5-4885-9f9a-ab79e6ce424f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>short_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array(36.785, dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-122.4</div><input id='attrs-8a6c2d41-a868-4e8d-a014-cf62641ebd74' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a6c2d41-a868-4e8d-a014-cf62641ebd74' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-610f81ae-3b35-47ca-819f-4e78e299c374' class='xr-var-data-in' type='checkbox'><label for='data-610f81ae-3b35-47ca-819f-4e78e299c374' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>short_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array(-122.398, dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5612b6ce-faec-4113-9288-ba5b8c05403a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5612b6ce-faec-4113-9288-ba5b8c05403a' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Wind Speed</dd><dt><span>short_name :</span></dt><dd>wspd</dd><dt><span>standard_name :</span></dt><dd>wind_speed</dd><dt><span>units :</span></dt><dd>meters/second</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'wind_spd' (time: 14855)>\n",
       "array([ 9.8,  9.8, 10.6, ...,  4.1,  4.4,  4.5], dtype=float32)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 2019-01-01T00:50:00 ... 2019-12-31T23:50:00\n",
       "    latitude   float32 36.78\n",
       "    longitude  float32 -122.4\n",
       "Attributes:\n",
       "    long_name:      Wind Speed\n",
       "    short_name:     wspd\n",
       "    standard_name:  wind_speed\n",
       "    units:          meters/second"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds['wind_spd']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "RHisz1fcHAmf"
   },
   "source": [
    "##### *Exercise*\n",
    "\n",
    "What are the units of air pressure in this dataset?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "id": "9d44N6kCHAmg"
   },
   "outputs": [],
   "source": [
    "# insert code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "4H7u3hKmHAmm"
   },
   "source": [
    "#### Time series plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 298
    },
    "id": "QXtpFroGHAmn",
    "outputId": "f21d69d5-a1a4-461f-895b-9333739d02c3"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, '[m/s]')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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SjapP51ba5346f50tRlQUWB4waaNlQ5AalcPnxUblAkQghQVYgdxOc58bGSP0vTW1vg0viT60Y6smWudV1dTiyufL8KMnpvifrEFQldGO3VV4YVK5Uph/vnA95q3ZFkfRmHqKjspI1rrC2Nmys5HAVyYHCwQDIYAHxy52HZ+weAPGfbM+kfyynyW/11gkQklRkeuYkyRHGbods3laubGZSFSs9d2wYw/+9flSz5nbbe/Mwy3vzMMkSxwaK5c+Mw2jHpoYS9mY+onQ6KVlbTDcDKHwdEaFuZN8PlAsT/+xEdOk/N5RkbN4d9Ya6XF5A1OtWfBueYmoWfKkurHKv+tenYmJSzZiWO+OOMSys52VLZV7AWSiUzJMGMKO2kMJhGxehSMReIZgEMW1UtfeUK0Y4cuObvtOfyu+pHHOEPrtK7cpmPcwLvlhva87dmfuR3WtOiKsOUvyOIVhPMmqjDxm3HK30/ASwbaFZvBUYoUFgsEWx16oQR5wlNGB6vp/fb40+9m6CjkfhlZnnj07yl1ezfO8VFtBCJqOGRo83y8VE5xP56/D716fle9iaEUIkKlQoy5MW70144ixY3d1+IRigAWCwSvTVoS+NmoHJBM+qtlEPnC+AGk5RdhugSXT616dicfGL3VfYEy9ef1C3ePK58vw+vRV+S6G79oAIoptYZqVBz9dBCBjK8snLBAMNu3ca/sepE8JtShFCFz85BTc/u48aWtSjY7z4WXkTFNVhu2741Vz2Tp2y+e3Z6zGvR984zqf4zlF591Za3DYnR+jqqaB6t2MthN0K9ooC9Nen76qYFxPWSDEQNj+Z+KSjXj2q3LpNNVLVy4j1xkmsH7CtUZDft6CCvU6iTDIRvpeL05uNzmWCGG587352FJZhS279vqfXA8x38Ugbqe7q2pCtbgZK7aGuCpZWCAYRAldEdmGYPlmLkhTzhAU6SXpqeCsn2r0GLeqJnDE16zKyP3b3NW8/kCHYqNHiFNjeegdH+PCxyfFl2CCHH3PWM/fZW/Zxp17QvUBb81Y7ZluPmCBYBDJyyjiiNTamEa/NRsAsLcmWJrfVVW70ooLZ+cwVrEuwzqTiGPtRm1Qo3K2M3NfN2HxxsjlSYqaWoFtlYXhVabbfoLMILZ9V4XJyzaHLFF+8NLgOGfMRISlG3Zqpbunuga79hiG4wKcyLJAMFGsQ9C61OPclZsrfdU41l9fK8sY1r5YtEGRV+bsNVu/sx1/eWom4FYSBlVdgbe7Kjdz+HxhDALBFt7Dn6zbqeTkAlHRSrlrzHwceufHqNybXw8TK17368O5FTjsT5+grDx8J7+7qgbrt8cT4iQZ9BtMEQEvTlqude6ohyZiwG0fAchEHig0WCAYuAynMYjvaeWbMfy+cYroiNbPwfPatVf+QiXhnKRbvJ+/9HXumhjyrbXdo8x/r9fU/E12PwtYHuA9Y8Hirj11Y0HdlG8zgmDWqvBquMuemYYj/+ytnsknKoG4Y3c1vnHEFCMQZmuqJJes15tJ5AsWCAZRjLGqS5caD//r5VtDXS891/J5c6V72q4zQ1i5uRIrNunHbfJKc+bKrbkpcMyYdhQivVDBKs+QXXuqMWvV1riLFxt1zSvKDIdeE2EFoCq8SKGgcv98wHAPdRJUvVmosEBQEKyTlp9s9k/ShSwJKRB1Gubw+8bhuL+Oi5zX9t1VOOfRL/Grl2dETkuGKaSLLL7fXsZz1f3+9Ssz8P6ctYmU0Y9VWyoxa+VWrXMLQa1VP7q1ZOnduaXtexHVn1DtLBAMojxO9W6X6jd87upcTPV1QXSpPgVNYqAiE2jjFq7PxgyandDo2+oCKNv83Ik5Q3AWd3YE1UZUhv1lHM5+9EvPcwqpK8l3vLU6uW0q+a+qH7tgHdZuK2SbSQZfgUBEP9D4OyONwiaJX0fq9TCVlxpv1Tsz17hUNOf+66vs5/Me83bJU72cMoGTxEjFmuQPh3QHkNEBW0uSBOZLVkTk22kKIfC24cbnfJZJj7xfmboi0h4Qmw2PnQKYIGTR8coK6uqsoz//ooC9wVQQ5KuXrVzxXBm+/0/1wGBnQmrXoOjMEJ4AcCaAszz+Hk6qgIXCxU+pY/xP/VauDzVfl701tTjz4QmxlMOqapJ1dG8msPzf2sGmuXuaOTPJ7GPrbUOwGjhdboEJdrUV277D6Lfm4Krnp0dOq5DGxtcnEFdoT7XcaG59XknZo+LE7XaqF3erwmNQ6TRU5wud8NcfCCEu9zqBiF6MqTx5w2/HtI071TFG9lb7G9e2pxS0arXDHTUOrPeiJLccGO/NqgDgfW+iUGuxIZioOnfrM3C+mknOEKqqM7lt8rkHny9cjxF9O3ueEzRcgsmUZZuwaN0O/PiY0lDXm6zfvjvQswxqB1M9O+urVlRI0yQFrvYFYLdF2AkhCiYURVB8ZwhCiIvjOCffBFkLIMP78Sb38Pdt3dT2Pd/RTostb+yf/jdf65qwmIOuIvK3IVg7EvcMIT527qnGda/OxFaHh5ff+3+pTcVmp0lJNFPeDx+fjFvemRcpDQAY/dYcrfPC9nVFimom97Ti4fzDu9kPuFSShK2WhYWrttgHZXXJLqLdEonofCJqZXy+mYjeIqLByRUtXnyfSYSFaUkOBuyx0uNtWLreQdZ8S1IcwuVURqQRhdJ6XXJlemHScrw9YzUG3flJbGmaxc13x5F0hF31DMFbDVroOIvs3Msk6GP96QvT89YWggxNbhFC7CCiYQBOA/AcgH8lU6z4STIksu5Uv1cn+T4CXjhTFh6/BeW9WWu0Gp7NhqAa5iVArXUdgobbqYmzSnFO3xNxFxa2f3kjqKwP+krJHoMQ9jvarFFxsERTwFnNZT5bxH441+7ivDbgiuwP561NdFDjRZC321SSjQLwLyHEOwAax1+kZPC7wc4XPcjziDrl98KrHHH0c3s07B+PfLYk+7k4RUdlm9upcayQRpCnPfCFcqFSGPKtWSjWvLlhBSwB2Fq5F71uHJM95tz0qV1zdZfy5ZKN6HnjGJe6rtCYX7Hd9n3M7IrAadSFGcJqIvo3gAsAvE9ETQJen1f8Zgh+99/rJejarpleIWJ4xnG3Ex01gdVQneoMwaoyMj8rzp2+fEv2s1W4f71iSyKGdgBYuG5H1tU1Dk+mfKuMijSnCGHLSQTMW7PdNjirEcL2vLxmYI+NXwoh3CEzvlqyEaWjx2DlZv3V90EIWt3PHIEdw8wq68IM4QIAHwEYKYTYCqA9gN8lUai4qK0VSlc3J1WO6KIutYPHtboNJswz9kq7xOicdVfCytMXGLtgHUpHj8EyjYiNuqPIuJHNEJZvyk3d/ztjjfQ6M05QbOVI8EUtdJVRdU2t78Y55/3rKxxy+0fS3+au3u6a4dUKYbunXh3h/DWZkbfTzftVI1aYdVCQJJ1aNbF993tuYWLY5Svwnc7CtDIiehDAcQDeF0IsBgAhRIUQ4uOkCxiFP749B31v/hCA/wzh0wXrbN+dUr1QVBXWcpkePxMWyyOj6qWXm9L6vVD//vHhKElxHYLtkWU/5/KfrBEPJ+41CEluHJOUnau2VmDjzj3ZBXAq/Gxhw/4yDv1v/dBztly2fItyX+Cvlm506ded4ZC8Zh+bjPIvXGsfuDh3O4wbZ1/QtJG723SGs7AS5rkefJtcqCaNzgzhaABvAxgBYDwRvU9EvyaiPomWLAZemZaLMhp1CuYdiVIv8Sjb7CWFEDl1mF9OR/VsH9pXPgx2VYKbP7wpd5O03uY4i7t22248OfFb5e/bd1dFWpORlJrg4c+WYMhdn2Lwnz7xDJPi92zXbt/tmkkHoYgIYxfY1SnOztIr9XMG7QfAPnibuXIrJi6Jtrq5tlbYZpsuXNoC933a6bHOqC4FvtNZh1AthPhcCDFaCHEUgCsA7ABwFxHNIKJ/Jl7KGAgqpZ2nf1cVPTRxkBI0b5zztrC5nsbdtoR+p0lE2kblWASZZe1BTpjK09VZnxAVL28RImDovZ9hyF2fhk4/KRvC2G9yHej67R4CK+C9CvpOyJ6RU2XkdQ9kwuj2d3PrL8K2uccnLMPxf/0cCxzG4CB4tY2vlhZ2ZFcrgS2EhqroaSHEBQAOB/CS7DwiepqI1hPRXMux9kT0CREtNv63C1/0gOVOUCWnasNOg22Q990UCF7XmC+YcwofpGOxvUQ+lxUXUcozBPfnOPrMsOER/O6rSlWin77375t37Q21FajfEyvfuAvlG3dpe8OYcXf+8eli5TkqA6/LhlDrmAl63APreeaIfqbFfha2bZgb/TgXlJk4nRJcHok+GS9eXxhhKXQIsjBtCBG9TURfE9FsIpoNYKYQQhWx6VkAIx3HRgMYK4Q4EMBY43sqBJ4hxHDun99fEChPKyrvH9s6BEXnHHS3t+zGMj61LiK5m2q/fVvpZxgSs06y2zJvzTYs2yCf8svu0U9fjB53yMnyAPtLqPB7bmc/OhFnPjxR+fub01fJO2LLPZA94xF/+xwj/va5bjGxe6//zGD4feNcx1Zv3e3qdF0zBI80redtTMBuoOrYzQ2Bwqcb6fJUCTJDeAnAMwDOhT2wnRQhxBcAnHfybGQWtMH4f06A/CORj2fiHDEGmdLWGNPjMOUOIvwEgP/OzLhO+l1WRIS/frTQdTypuC32jiLzxVm39+dUYNRDE23qC7/aTwm5v2/QZ+HU16sioqrq5mTlZm/32etfnyXtiONG9z4sXLvDZviXbQtb41iY5qVvt94fM5jcif2840M5WbRuBya5VDh6NrTc2cHae9i+56N5a1MPmR1EIGwQQrwrhPhWCLHc/AuY3z5CiAogo3oCoHyaRHS14eFUtmFDeC8aI6/glv4gnaqu22mAIijDWFuOPz5+qdStNkhN56zeltXN+l3XOMCqtBcnr4hsTJOpEtY7drKybtvpOllBWJe+oE3ofEdY8588NdU7/aAFSpEdu3PhGHQiewLAaf/4Ahc+PtnznMwMwdt5IPubxFlgYLc2WmUxOfWBL3DRE/YymWklNZIPaxu65oXpOP/fX/mfGCNBBMJtRPQkEV1k3QshqYIJIR4XQgwRQgzp1KlTxLSSDV0RpBy6mOX1uua5Scvxz3FLXTrOIHXdYx1ZKy678Iju2Kd1ExQVETq21F+c/r85wVdoWrEbGzP/gwglIO5QacHa0MotdvWNaoGcOeJMo42GdcO9471cIMPqCFtnOsnYEHJ43QLnCmAnVTW1+NtHCwPvLWBVqIXB76oo4yK/WWHcBHm7LgMwCBm7gKkuOjNgfuuIqAsAGP/X+5wfG4EnCIHOje9FNjtc5QTB8f3BsYtR4TR6BSiOdV2Bqh728MTuDkXVxeyO4Jk1ZdkmPPPlt670dbRTXsbOKGz/LpkQ5uZ9f+zzpXrn52FwYw0XUR3B9dSJjpfRg58uxoKK7VKjr/X0t75ejUfGLcH9HwcLJxJ1hvCdj00lyvNKe/1TEIFwqDFiv0QIcZnx57lPgoR3AVxifL4EwDsBrw/EdSdnlkoIFMYMQQezmHqT6AzjFtpVaoEEgiUUhVoIiezIUiYQlNlFuOU/fHyyrV7mS6XzHDft2pvbHyHGF0pXVQIAlXurA3cwr2tubrQj5U1kHh67GJ9a1g+YHnBH9WwfOe1aIWztxHnLqmtq8cCni3D6g/YNptzvSc4RI6g7rLmdrTNv1YDmkmNLbd9fnBJUc65P2uthgwiEyUTUX/dkInoZwCQAfYloFRFdAeBeAKcQ0WIApxjfE6NsecZ4WF1bG3jaFtRTR+88/xNzqiL3uc5AYMp8AvTE1v0NVOXLLF5zn58WWyqrsNUIKayrrUh6QZ8fspAZO3ZXo2JbdBXA21+vDn1tmPvy90/sI+7/zszUrVu75qHLYRLE7dTKlc9Ny7RXywVhVT+mKm+7I2y1ivYtGtm+O21lpR3s96VuDEUzBBEIwwDMJKKFhtvpHMP1VIoQ4iIhRBchRCMhRDchxFNCiE1CiJOEEAca/6P5c/lg7gu7fvuewNO2fHUoWyqrsGtPbnS5cefe7JJ9Xaztc8n6HTjcY4Wqrsuf+bK1btZI+lucaownJyxzHas0puW6M73THvjCKFs8AuyeDxZoRzbdXVWjzPfZr8oD5727qgbD7/ss+72mVuB7j0zEGwlsl2rlD28oX28A8cy63W6nemlu313tcoGOqvrRvezzhd5OLj8bcYA93Qi3Ke2d14IIhJEADgRwKnL2A6XbaSFhjaefBHEHt1tQsd32so2XqE68y5M759mvyrFp1158PG+t9FyrN5OO3eL3I/sq8vQtljZ3jVGv39DthMpjWBdg5d/jl2HeGr2VrF7RVb/0CbNgPrsP5lSgdPQYVO6txqotlTbjYq0QmL1qG254fRam+vjI766qCR380AwapyKICk2ZhtPtNIgnXq1cfMTVFlV98TszvQMmNnI4PkS5TwWnMiKirwHA6mrqdDs1zylUSoqKIoeuiINAaqgI+VjbX/azonVb78tt786Tu7GK3EilVRP3NtzzK7ar3WRj5pkvy1PJJzKKN9nUV6swb6Opplm15TtXu2neOPcMnvaIrQRk3Iqj8JKHfjyOGYJwup0GXENjc0XNricINmjKHdPO2sYTE7yfQV2xXwJ6M4SDzJXJir85ADomXdAw/OrE3gAyG9gkGV9Kd5obRA2lUuVopWA56T9TVgDIGOdkOPWfZnRYe3IWPa2io9ursdGOyZkPT8BARYhkP8ZLFjd5UShRanUxOw9rmGnnM++/X+vsZ7/6rVaEY9Dln+PUnk+uwHQhOj5ns7Sm8OHcteh90wfKazO7rdkkglEu/3xlkQDcISn805GXy/5dZxOqQsE93HPTT+Oc6JHfEqBDC8OFEwmHrohZ2ERNTlZXVTRG3emsKm6SiSxOvkoAmqPk6ppalKS5BVuKhJVD5uPwCoVRuTf3LP0EQphtW3Vxtp0w9hFHl24TKn57WTgjAZgdr877uLWyyrWvgexVCLqmAYjXiFxwbqcqVZHjL1nrVkiyYZ0d09J8EXZFs2yBluf1kmMqlY6WoHQPwlzIZgh+Bt3fv+lttIyDfE0QwhoD3aNu9zP/0RNTcvkkXMPtu9WeN84xQLitIjPhJKzfs599utZj7/3Mdr5pK9GZiR9xt15U2nztS2CS9PN1Uj+HZwbmO7m3pjb4wrQkbAia57k7aSH5pKZcEttd1bB0ojgI5O6lKtppGBvCWxHcJwuZoK+w1x4Db0z3NuwmPYL0iuDqbKdlIXYsEwJYYZkNxTH4CcuXi+0G//AqI/8LF68rzAio9VogPDQ2s2L1mHs+y9sepVbCzhCC8oN/uuOfqDoOvw4nU57cwjRVOhMXu71n8r0WQJdv1m6PNYhYFK8SZyf7xaKNnvcxbbdEK20kLshBERC2NmWtv5ZAkLoZhSvLhwpPvCRYo9veUn68OjaEOos1RG5wG0I4A3AceBm3dFVfU5ZtQo8O/guHFlT4j1R0ZghJbWQfFZ3+cuQ/Mqtgy+8dFUuejUuK8JqPy6aKWmF3AFi4bodn+4p7z+ggtGoavfsQAujaNtdO7S6o/m194Vq311ZcXj1z14Tz0NLJXbefT1vc12uBYKUwXL80vZFiKOoPH5+MZo0su64pzpO5mcrwa5iyQbFfPZJe9JyvrQs/XbDed32AilohfN0YCwXrO/VRyNH1jBVbcFiP3D5ZugslTZxhW+Ik9F7NhdDVhKReq4ysBO1kx33jH3dvW2UVnpywTN/tVLMMQVw4vbDGdCHKdP7/cgRQ03GJ8wtuB6jdWvNJjUXVlSZ/+t98/5MUiFr3Pgpe7ebw/YNtOhjnuMgqb695IdymQ7e8M8/2XQRUGdVVtmqGySg4L6P6QtAZwqJ1O13H/vS/+dnOuqqmFofe+THuGrMg9IYrKp6c6A7dAEQfeDw54Vv85cNvbMd07ktGZWQEt1O0GNUOb37pJsliyTMsdIK20zR2q1Nhdt5RPfhsdgN7DqHSi69dhc3f/zq/sCAm7GWUEHGMNp6a+C2+98hECCFsy9eXbsh0PP27tFZdmimDZj7undYsn0PWg4ikYXpVweLGLliHl6euMPIU2WapaqCydQj5pqqmts4tTBOINy5UkphtJ8xgwIrKsyjsbXhn5ppQe0+nSdCIrGnRYARCXDaEb9buQPmmSpuKxPQq8et8dDvNOOPNW5FFKlW5i17xXBlufGtO7kDWqCxPO6kyR6Ew7EbBqBXu8WWYxVEmSd4C8/5GjWmkMiRHSdW693R1TS1+++pMTA/oFhvXSuW6RIMxKn9f4ooZF+b74Bca2sun256eukVFceUskQkEjZfZeoZK6OnuovXOzPTWHnRu3TS1vOLCGf0TAF6dFs5jSUacfZXZdKJ2gCohENdMafH6nXhrxmq8NSNY2wube5z3OO2ZRIOZIcSNtWM0oy/EpbMOu+fvBUO6KX8jAorCuvWInJeROnSF3mvw61dm5pKVXDJ71dZgZfPAquoCgBtO7RNb2kkhuydeg4CvV2wNmH6cGnZjhhAxTZVbdSGsHWposEAIyR/ezKlT+uyTMezFJc2dXka6nhfO2CxxcPu784zFQ8bCNMV5cXkZPTZebxtJHZz3qkubZp7nl290r/BOG9ns0GtF9wKffYbd6QcukhKzqNFVc/L2nW95ELZaN741B0vWF+ZKZD9YIMRA3DrDVk3VK0C9slK5hALAxh178dePFgYuixmwzExZlUdVTD1NnF4VtZm43dnvfiq9q18okx6P28jrlV6tSNr2EV/abxsqmKjrPVTxi+K676FtARHu1QuTlqN09Bj8b3b+Fg6GgQVCCHY5jHxxv8BnDuxi+67rZeQVxmDhOv2RpDPEtC3mvCIL5z0BwnU9cXoFOfspv7RlrsZA/ALfy24jhEhUVXLuvybFnmZUo7L1ciEyAeVG/uOLiKUCbntnLkpHjwl9fZTnvtCIVfTi5Oj7Lc8MucFRGFgghMDqwQDkvEBO6NsplvTDjoy8BsBBkvxkvn3VqXWgrRrBy7YV3JOgQUxnb2enoF4Rche1uPvnL5duUucl4s0xDbVLVAHmVInu3FONb9buiDzQem5S9M44KnHMeCd5tJe4YYEQAw9/tgRAJoZNHKhesFVbvvO0U3g1vq8CNCqnWkgg3Irf298LvmJXtwvQ8o5yGJUrQwqouGeAL0wq98xLtl4kCLst9UxjTUPU+6NyO124Nh49/NbKcCEo8m3DyAcsEGJEZ9Sqg+oFW1CxPRvBVUaY7Du2dBuincnYZgh1aKGXU2b07Bhus5i4BcKnC9RhUWoF0DJi0Lifv5Tb0TaNTi26ykjudroxbCwhBz96cor/SRKiCFPz0rr0vgAsEHxpEmDUH1co4rDvVxi3Uut2jCb5DKmsi0yQOXF25Afv18b3GlnnluZCoziEz2eWOFx+yU1eFl0dEbnMQvGZSR0WCD4EaZ9eXj5BCOu1ESb7GsmCMrfKKFoeSaAj+2prgU/mr8t+779fa/TbtxWG9VZvAf7pgnWuY3793bSbTvYvjCZxG5X91C5R91wG1OFPdLHLg7ohEfzeA7MWS9ZHX5uU5j1hgeBHgGcRVzjnsJt9F4forWUjYmc9Miojc4OchCWCZl11hO+Kzbsw3+Gn37JJiecLtn67e+MSrxHwoO5tY7MdATC2zIyvA/jj23M8f1+2MXqHFXVhWtBNcdLC06PP9+LMv/U79sRVnFSo1wKheeNi/5N8CCKdw3TIMkKrjELkLxvduZOxBrcrDHTsNbv2uI2zRD4jWsk99BIIRNEHAh1aNLbkFX3EHYRHx4VfCDi4R1sAMRiV87gYzWvfipemqL2U6oJaNQz1WiAc5BN91I+gqpv4bAgpqowkec2RRIoMW7WkvFxUYbhteUuOEVHgKbisGVhXhUdRFe6prsGmXfad/ZJWEQgh8MAni1CxLZq6SAB4c/qqQB5sqnRMXkjZVfSCf6vXZUwr3xI63boYWBGo5wIhamc0tXxzoClsbCojR566jStMxyQLXex0MdVZmKbCzwNl7uptuP/j4CuodWZjsvtGcC6EEq7fXUiq8MAFg7LnR/Eue80RuK424YVpADC/YjseHLsYv/rPjEjpCAFc//os3PLfuZHSsT4np4qvUPFr13V1AlG/BULE62WhiL1Iyqj8rWaMnTDZy2ZBJcVuo7LfwjRl+j438KxHJuIhYx1HJi+9O16us8hMklQRke24U2bI7qFMsFjLGeWxO3esy9gQwqeng6mS2q25fWriJFTfbu28Y1clSZTZRT6p3wIh5VmbjhpDh7AjxDAjVdlIp3GxvSLCshVl0M7Pb3YT9zO68IjuuS+SshYV2cukM/tynvP9w7ra9quOy3Zk5pW4yiim9OMqZVL19RugvT1jVSL51mXqtUBo0SS4UblVE/uioCBqpxaN49lewtkBtWyil24YG4asQzyujz0Ex7iFGywzhGAccvtH2quKAeD9OeE2azc5/ZBcHChZWQnkEAju3504z/ntKX2ynkXtmjcONTP88VNTpKqyNGYIJpHDKuQ5+JwfKzZ7zyKve3VWMhnHTJoD23otEC4+av/A11w2tNT2PcizOOvQ/bTPfeiiw5S/mR3WEaWZDdQHaCyoAsKNVGU2BKfKKApVNSLSjl9BsZZcakOwa4xco1PZLXSeU1REOKRrG9zxvQH42/mHhlIZTVi8EQ99tkRqL0o63ESh2Tt534PCoV4LhJLi6NUL8vIUF5HvvsomVpWDE7MjG9wjIxB0p9RhqisbvTeSJDR7leF5FEZWGFmkEVenmcXVWLZpDxG5omuqEEbn7DyniDLpXHJsKdq1aBzJu8z5bOM0Knu5TXoxQLJ6XUZsKqNCk1AFRpoG6notEEJhuftOg5/OpXE0bXN/4mzHrJlomI5JHqrBw+8+hEQQENhdVYObPLxR4ugTTujbCa0scYBuluRXRPbMnLMIa+163vg+vvfIl5Jzgt2D609R79TmrPfPX/o6NpfFpyZ8Kz1uzgBVe3zrqsBkIc/DwOLAG1YZpUC75upNaEx090A2iWtzF3Nka764uu0hrpXKXiPUMKMVIYB+t3yI/0xZEfziAAw7sJPvMyhyzBBUdd1WWQUgsybDeU5Q2/0vTuitfe667Xuwfnuyq1u37KpS/tatXTPt+F1LN8SzwxzPEAqHei0QvN5b1WjaejRoQy0qAgZ119P3OzsVq4ucma/ZweuOGMN4GUldKr0Egk96ww90xwnSKX1cXYKfwMqsQ8jl5lqHQJktTKev2OxxTrD77BV0UFbvqeXq1bM6mO1AdU8vfkoe/fOBHx6KMdcOR3NNJ4a4qKvywGsP87pKvRYIXh2p6h21vuszAm5gTiCcO1ivkRABX44+Eb07twQA/P38Q7O/mauHzY5E94UJM3qXGZVlAe9yeXhncsOpfV3H0hoBCiF8R+9ElL2fyzftwtpt9thFBMJt787F5c/mttOU2RBkHN8n+AZJSdyasOvkSju0QJtmjVIPT1Jo8qCuLiqLg3otEMzOVobOKM/cT1iXoA2pa9vc9NwaIM1U45gjvblr3KEkZISLZeR+Ha0LxYIim6Wk+8J73wOi3EDh+L9+jlMecG/VOHmZfYTuHFjI7vOsW0/FEz8ZErSwifjghzVy5ys+T6GFedBVvVY7nBbuPHtAEsVJlXotEHp1UgsE5QwhwvgozMhM6uZotDOzYS7T1NWGURlZ4+iYbPCI0BjKyUjjfY9rFuH3LvveInLX0W1DcCfSpnmjUFFPd0fcHU3GXk1nCKXaNGW5UGDyQHtg5Zxdq2wvLZuUoO8+rSKXKw3SVRYaEFE5gB0AagBUCyGCD60ionro0V4G/YvNl2CTsSuU9eU0R0xBy9KueWP/kyLiV6bu7Zu7jqUVz10I/yfgXJimOMmRrmv1WmxEmY15IYTQDnmSbwpMHmCvwvvKSbVDtbp2m3wgtXNPNTbtqhthsPM5QzhBCDEoH8IAUAuEKNsBFhHQZ99WWh25eU6FocNeZ4nDb3ZYQVVATRsl/zj9ZlBtmkm8t3RmCCHLY09D+Ko9ioq8R6S1tcI1I4vqZZQP/vDmbN9znNWYs2qr9HjS1FUvI6fKaMNO914aJnFtB5o09VplFAbZHgo/GNxV61oiQuumjfDtPaN8zy1xBD6yCiJzgBJUBZSKDjiM22n8pVCiY1T2miGMmVPhOrbSEQLB+ex0KL/Xv03EyWtlweP07K7KNLy0bQl1VB64Bo9V1XW0IhbyJRAEgI+JaDoRXS07gYiuJqIyIirbsGFD7AVQtXnZqLyX5ubsOq/RuYO74ZheHXBEaXvlOaaXT9A9ktMYuYZdhxCUa0/U99234jeDcaxLc1Ep0elf9uw02/c0ZmJp4HyWaW7VOGT/dnnJN04uPLKH7XtbjbVNhU6+WvZQIcRgAKcD+AURHec8QQjxuBBiiBBiSKdOwd35gnD+4TlXUVnj1O2YdVQ8U77dhJevPtoWYsHJuIUZARh0oVlcC+PiRueFd66a7W8Jn2B1yfXMR+gYlcmzNNOXb/HNx2sE/fSlag3o5UN7+qbtxXOXH4mB3fTWuYTBFJR3nXMwzh3cLdHw0bee1d+Vb12jfQt9AaAboDLf5EUgCCHWGP/XA3gbwJFpl8H6TvfdtxWuGp57WX8/0u5LH2d44yA2iqAj/gLVGGnF5vnGsRm8tdN1Rl9VoXNnrW6nYbhimHenfmK/fXBSv87S324edZDr2HmH6y9uOr5PJ1xyTKn2+X6o2st+bZvh7xccGute0a68LS2prga3c5bbqxppBniMQuoCgYhaEFEr8zOAUwFE23IpRoQAurWze8ro6vKjTH1lfVRQlVEqAiFEJjo7ajmFrvV7kNsgK96lx5bi1auPNtKiSCPSKMJE9jx1QqhYOXvQfrj2pANDlyEISTYn63Oqq0Zl5+CuaYICNC3yUYN9AEwkolkApgIYI4T4MO1CONUrZkcn4H4R4toJzQtZpxd0ZpJGOcPk8Nk3633PcQrd4mKrQNAUyEJ+7pkDu+CoXh0AAN/trcGKzZV4Z+ZqrTSd6OyzneRjKCkuwm89guVFwVluWdTbuLA+p9+94e8RVYg4Bwdau/gVOKkLBCHEMiHEocbfACHE3WmXAXA3fvOrbLCiPUMIMdAxw2U3ldgUgnsZBc8/KEnlQQTc88GC7HerMPTL89T++wAw3U5laecOrtqaeWn/OW5pqHIWqnpjvzZNI6fhHCR1atUkcpoq4tpdMJ84I7x8sTh+5xdAvrYnKerBY4kJy7vgHGXqqm7C9BVeL11wL6PwvfXd3z9Y67ykDNe1tcC/xy/LfrcKQ5ma6pxBuc2IenbKeYHJymdNy/QdD7OqG4g/zEJcyV3q2NhJB6cfvdN7yrzvsoCFUSlUB4gg1Dgenu4K8aD07KDn5RgHLBAkOPufT+ev07ouki5UZkMIalQOnzsO697O/yQFd3wvegyXsx6ZaPte5DNDUC30kZ1rvY+m8Xp+xXbbOUd6uAFb0RMIAVasa5/pl2Pwp+805LvTzHDJMaV46cqjQpRKTSEv7tPdIMgZBHJ3VfxhSADeICcVVPdYwB0xc/KyTVpphnm5zYctM0gHdjtNw4YgycK6KU1cWLfxlNXKGjfG7AxVoSt0Zk7tW+iF/Yiykj1J4nj0qpoRAcce0CF6Bo40CxXdnRadES4KtGkEouEKBEeLtHUqjt90p8xhJghe74VuTJVsWhFesnxdq8I+Q3BnUFQkn0HIztUpn66HmM5Lb83Pa6tUAPhqqd5gw4+B3dpGTqPfvvaRsVkPomCDjT+d469+TMMBIiy6W4o7Bwf99q0bAey8aLACwQtne9D3FffvLVRCQ3Y86Gg0FS8jqUom/nxtNgTZ7wGCE1rL10ExE9AV5jpeRla+vuUUz98XOFRXYTmyZ3vtWY4K56I3L0cLL5ZrBNULa8NJA92y9XREMLjIsXK5LtJgBYLzkVs7EmcHpzs66tw6uKeHV9pBO9o0XjGZrjro3tM6lChmAABwzfG9lF4qsnvgN4MA9NV9TkOiH14r0v34w8h+gc7/zcnxrk8Iq4LcLAmp7kq7gI3Kulvndmlrf9/DhDT55Qm9cc3xvQJflxQNViA422NuNCRcnY1Ox9ypVRO0bho+lomsnwn6PjrL2bWtfugB3bzSmul73fNiIltnZb13vtFOFT9rzxBS1BMHXSn8k4irmIO4Ynuhu2K8UNGtr/O8FiHCU1TV1qJRAfngFk5J8oxtFOmQFknObr2SDjxDcL7QKb10QbPp1q6Z74YhdpWRPQfn4kFT/0+kmCFYjq5Xbv6ja0NITyJY63L/BXrxnIJitXG4F2tm/getsY6qs5AFQommEaGFY/YXZiGf1dUayL/3FQsEwDXadDbWNHTzslcoqkBYteU7/Ws1u3XZWVG8q1RY3y1XVE7HiuSLj9of3do1w/cP6yq9Zzq3cfTpeuoZHdfiuFqLlxozLr5LwFVSR2gGrY8Z4kM38nAUdL2MnOfFMVZYJgmdz26nKWAbYQqR8zKCzIbgn17YxuCVdvDgduFbjq6XTRyurTJPLideHYbTNbh7++aY+IcT0aVNM2lvrFPi3p1bSffCcBLE0B91QZe13FFu+xmH7Kt1nrsNmJ53meM63kOZdPwJWh8zzZ8cs3+wCwEM7d0hUOTWktDD9GRmj84V0UnScAWCo0Wa08TiIkp0hqBKSjbyDG5DCFGggHhlce5g/cidfoMwz4VpiphF0nMdeLkGyvZCcBJEIPzfUcE7LytFPqu1ddGZ/V1zXC80LnauVM78N2usXQKNWxT2nQrT5b505dGBBILOwEBGUtrEheu8FxDGSYMVCEvW78x+JiJcfVwvXDa0FJcP7ekOXRGjQHC7tHmlHdTLKNlOA/DucIPcpmIfQ5pNIMhsCCqBELFc8RKshxjW2z6jINs9sGPdYMaKdKN3n/o3KSnCjWccJFmbk8HZ0fm5V+qojII+k6iP0Bmmw4s0YwfpEH7GEpwGKxCcNG9cgtvOGoBmjYslMwT/6zfu1NtEWyVc5DYErSRDn29F38vIfeLyTRm/88UWIQt4zxj8t7pU/yaEezW5V/ms3Yns91EDu3gXJiVOPsi+j4K1jrqDkjHXDo+tPLksheO7NzqbwQQdZJnvR9hReJll4yO/nc2cxmJdknI3YBtCyqzfYd8cWxUaOw6cM4TstFwayyjlYVRIxszO7EM8a+VW2/GzLQHonPjVrdhjHYLXzmi+gkZyTNfv3Mzbj7DNxZl0m2a5jmvh2u2e55r07twyXOYeuOvsfRMu09gZLp/ONNef2tfz99MG6NlcnCQV3C7NVd0sEADMXb3N9t3ZqcS5qtKZlFfKQfON0nCi1NArBo70fCFwQCdvbxG7G7A7P6UNQVITv9uyanNhxrEffmBup7jXylaFTifss7U6Wti++wjFRh5um0N7d8BLVx4VetFlHKPwcp+V1GEHgEmtvuYZQp4JGnY6CAd2Vhk1ZSvTgqWdz1FXUO4829tjxSuWkZeXkuywn7dOofrEW8vVLmJYCt18dI4D7m1mdenerjmG9u6oLRCc4SHi2F1t6rebPX8vtPaQ5qpuFggSnLc/zgiXPxtxgD0vj2etirujIsmp5d88NroP84429Qn6Zjcqy36XXycbpdmMs1KBoH/f0gxoaS3VEaV2I3Ka2046syIKtgoeAC5xuIuSZs/jFAgA8PF1xwXK24nU8G6hwORBqovVWCDA32YQ5+pU1bRSlkXQly6KPPC7tm0ztSFOtYZBNbLRuZstmlhW0DptCBDK+yhdmOZTpkLrAEy8vIzSyT/zP8pe4Sb9jJ0BzXauWx/Z8+zjs8rdD7+QIGmEkQ9CmuVpsALB6raXZsgHp3A5oW/Gs0RmDAy+Ujl3ftnNJ4conRqvLkElL5WqCI38mjdWe6qo9k4G5KOpds3jU7ekOTK3q7oi2IdCXuu0GZgbxxx7QPAFd84S6JYpiW2d4wo5HgdF5N/fsA0hBbxGCUmqXtZus3s0/fCI7ph166k4UDLqCexkZDm/Y8ug++GGr/NxfTLGzy4x7OsrI8geB0SED39jd71sY3EzlF3ndJfNF+5OU/4ZSEl15cjz0O5tMevWU3HWoWrvMcBn8BCw5Oa7aLaBOOTx0b28d8dLc35QRORbp1TLk2JeBYX1IezrCFutq7MLE3/eGTiLiGwdlvO3IETyMorQ6oYaI8bDerQNn0hAvAxtrTyizqb5ckXtvKx1TNKw6Je2tRqqtmqy4M6R8jwCeNdZSWJwds6grtLjC+8aiWV/PiN0uof6bFIkS1+neqwySpmWji0gXStjFS/2+UP0QzWYNC7WX/Ti1Q6cq1qBaJ1dlNG9c9Q3rHdHHN+nU2JdmJ/axjPfkC9Xn30yKr2fHFvqe27Yztu1UthjhpAGWVfPAJLNL5Jz1oagWR+Z/SgqquB1TUqKUVREoYTQFcN6okcH7xXOZvpWZG1lsGNglYTaTEWDFQhEyMZukXlRaKUR4sX32mDl2hN7O9JX86Jk0/Moo6nmjUtc2z0e2VNv4/mcoZCyZXvu8iOV52/S2EAlCl634fpT+oRKs3Orpii/d1TW5uPF1cf3QpOSIu37p0N+jMrqXJV2I8hVIM41Dbo423QcKiOvdRJAusJXlldrhwMHzxBSQAjgj2f0Mz7bW5lz5XKYUcmJ/eQdh5fH0m8dKyiDNoSo7cZVT8tXrVGiZv5Rd1jzK4mXoDbtHUEJsjZlcI92WHjX6egQ2I5jx/o8nfnfcmb/xPfwDdOcVG3wlP77oFfHFvjp8QcYaeulblY7bNN+8MJBrmNh9i3wI2z5ZIO4HzhCvvBK5ZQwXzLnMgPdQFhez+npS4+QHg+yJ68z+RF9vTuzMO3mkmP2x2MXHy79zSogrKW+8IjuePrSIa7fUtXPe4iFJN6f+Wu2xZ+oA3cMLZJ+BjJC58Pf6Pnj+90Opduw6XYaYDykyqtdi8b47IYRWW863WfkmiHoFwUAcLbEXpBEsLiwExfpDMGlwk6PBi0QzBvtHLUn6cERZITqbCzPXqZWwwDuUddpA/bxzeOOsw/GyIMzsVucL76qI7j33IE21Yk5e0hjanvBkG647uQ+np1UEqXYuDNZNddbPz/W7WVk+Rx0O80g7K6Sz9iyNoQAbwQRxaLnt6aXKUN8NPFZFJkmxZJ3xrUrBbudpoSisTnjwsfpeh5kuuo3rTZ3kbp51EEYc+0wl3fUUInh2Tu9nNfUv398uOdLqNX5u8rTIVB5ZNx33qFo16KxtworxhcoabWMyeAe7VzHrPf48qGlqZRDln8cM4TwZYg5QcgdMpLO8yiFPalIsv+K88Xj0BUpUZSdEtufwPGao/ikH5Nfw3z750Nx9/cPxpXDe2HAfm1cnfSFR/TAbwMYUV+75pjs5/5dWtuMb3EIxaArr71o47Fy2m84GWQDlCSihypxehlZPvuF+vDjHz8cFOl6XcJ6D6lYUJGJ8rrZcESIox36BaGL0gG3UoT+7tBS7qJOJJmZpxogxU6DFgi5B2FvALoGxPw9tgylHVvYduVyFrtxSRGuPelA7fScbnP7tNZzRTUFkV+IjzijQf7C4ZFlxe+5BFlp26tTegLBpTKKye2UCDjnMLnvvU55As0QiFzeamEwdzibt8Ye9ttsY89cJrfRxUGUe/3+r+X7UbRQrLyXZZXiYngXDVogmKt59/fxH87X8wm+Ujm+DreoiLSD+nUy7mMPn52m4vSWaFKi7nTijD3Vskn+9M32WEbR792zlk7UXFfhXYDMv6B3c/8OLfDYxYN9kvauz1s/O9ZWXicjQnqL6aCzwY8Ts82pdlsbpFi0WURulVFYN/g4aNAC4bQB++CpS4bgquG9Ql2fD9/wtGjeqNi2s1Tn1moXymMO6IBnLj3CVz2VVLx4J/kcYSVFHJ3CCIsjwKtXH+Nxph2ZvcZPrTHyYO9d6Lzq89XoE9G5dVOM6NsZow7JpGMO2sxBSpIODGG20Azb5ogIpR3sEV2d7xp7GSXIdSfnOi0iwkkH7ePbUaUZ0MxKEsYkp8FcRbsWjVFVnan3+Yd3kxo9rZzQr7OvwbxFiJFXGOKcIaRp0LP2cXd8b4CjHPGis79C2MVkOnjNFvez2JrM00xvHK9Z6+c3jAAAtGoavZ0dZERnjQtVOzp8/7b4wWC7Om9gt7a++1YnRYMTCGZc+XwabryYbolSGtcgqL+lcXdrr2/Y3V1dAyAzA1Dh3AfYivMl8AqhHSf+8sD7BGuMqqQGojLjo/V+OT3E8hGSOZul5HbVODxV/fYYcFJcRBhndODeZSBbWbyEfWnHFph044mY+PsTcWSp3KtHt6MPsl4IsA8aLz5avzP/zcl9QEQ41vGO2cJXsMqo8Bh+oNsQeWTP9ph56yme1x3ctbWtk/fDurrV2g5m336qdhpO3vr5sdnP1pGZX2iFPYZ/usrDZdpNJ+PR//PWFVvRtSGMDLmnrYlfADY/Jvz+BHRulXkOSXXEH/xGbnwEMl5uut5NjYoJTRsl8xp71dxpg5h9+6mBQ6737NgCX44+EV/87gRMu0l+rVmGI4wOfoiiozfp0qYZ2jRvhOevOFL63ul6mJ1xiF3lVepjZ7TKj+7t9FVOpuPG05ceEaifSAoWCAqs0zgB4JlLj8D8O0/LHpt600kY0bcz2hq++7Ip3vw7T8PbPx8aOoSB2RkVEdDaI4KnH00bFWcFmqkd++8vhuIlSTwkK6cfkumYD96vjfT3Tq2aeBp3nej0rfPvPA2P/Ogw7TRltG7aCHPvOM3/RAUtmpRk3VqTGpzJPHEG798WAPDjo/d3/aYqx5zbT8PMW70HC9Zr/Va7y5DNpgd2a5sNM96lTVM0KSl2hVxXRT610rVtM/To0BydWsnfkTOMNnjl8F6Yffup2i7hTRsV2967vkZ4eV0PqF9ZvNg6WlxGnaHVo2LORp3lzdcmPekodQsJzfv89/MPxYYdezBh8UYAmQiJ1iiJnVvlXDKX/fkMaWfntcmLFyVFhDMHdsl23r8+KVxANivPX34khABOf3ACgMwU30/nf/agrjhr4H6x7TF9dC//hWmqe9akpAinBpg5eHmK6JgYzFPitoO3a94IWyqrbMfMkMj99m2NZX8+Q3q/Vf2D1/qExiVF2OuIG/XMpUdoG0D9QleY91h1i5oFWO+hYuTBXZT3JAg3nNYXVz1fpq3aKioiTL3pJBx591jbcdUAKEkVdJp2rIYnEDQhIlw1vBcmLN6IQ7rKR8gmcXWYJkssMdPL7x0VS5pkuLcFjU8TZ92iGOoW3nV6bOW4bGhPjP1mffa7V4iPuEdqsvSs91h1v4OU48yBXfC/2RUYekAHjFu4wZVOXNF8c6Gsk+2w4miDg7q3BQBcGmDFd9tmmdH7Daf2xWPjl3qee+7g4KHwvbDa7dKcLLBA8OC4Pp1i65ALBVOPH6cnjgpnQw7qdjr69H74YO7aGEuUYdiBHVF+7yj86InJ+GrpJvzkmFLXObn4TJnvfrtsJcV95w3EI58tCXRNNthgxJ4kO3hQ/N65dRN0btUEt57VP1I+YbliWE+s2FyJji0b+0bQ7dSqSeB3uXFJUfaaji2bYPRbs5X7hhxm8cKT3fagj6Jr22Z4+aqjcfULZei/X7weT17kRSAQ0UgADwIoBvCkEOLepPPct3VTXDGsJwZ1b4v+XVrjj2ccFCqdf/7fYLwybWXMpdPnpjMOwrKNu5S/n3xQZ5w5UL3FYZgIlmE5tFtbDNivtWu1qeu87m0xa+VWvHr10bbjPz3+gGy45DD88oTenvtP/PGMg/D7N2Znd3r72YgDsiqie34wEHe/vwBnH9oVr05bGbq9OPnHDwfh4c8WZ21PflwwpDsuGNI9WCaOjexVgmFgtzaYvWqbMhm/ttKkpBhTFcbgMFw1vCdaNtG3ld1yZnqC6OT++6Csf8aBxNpOdDkthKPEMQd0wJzbw9vCwpC6QCCiYgCPAjgFwCoA04joXSHE/CTznfzHk7KfVcvLdTjjkC4uD4Q0ueo470V0T17ivaT//gsG4aGxi9Gvizxo26M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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
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     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(ds['time'],ds['wind_spd'])\n",
    "plt.title('wind speed')\n",
    "plt.ylabel('[m/s]')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "GtGEueY6HAmz"
   },
   "source": [
    "##### *Exercise*\n",
    "\n",
    "Make a plot for wind *direction*, including title and axis label."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "id": "chUcxNaJHAm0"
   },
   "outputs": [],
   "source": [
    "# insert code here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "GpYro6SLHAm5"
   },
   "source": [
    "### Working with vector data\n",
    "\n",
    "Vectors, like wind velocity, are characterized by a magnitude and direction. Scalars, like temperature, only have a magnitude. Vectors can be described in different ways. For example, instead of speed and direction, we can describe a wind vector in terms of its eastward and northward components.\n",
    "\n",
    "#### Calculating vector components\n",
    "\n",
    "NDBC provides data on wind speed and direction. Following typical meteorological convention, the direction describes the direction the wind is blowing from, clockwise from true north. We can convert the data to eastward and northward components. \n",
    "\n",
    "The eastward component describes how hard the wind is blowing towards the east. We will call this the $u$ component, where positive $u$ represents wind blowing toward the east and negative $u$ represents wind blowing toward the west.\n",
    "\n",
    "Similarly, the northward component describes how hard the wind is blowing towards the north. We will call this the $v$ component, where positive $v$ represents wind blowing toward the north and negative $v$ represents wind blowing toward the south.\n",
    "\n",
    "The function `wind_uv_from_spddir` converts wind vectors from speed and direction, as reported by NDBC, to eastward and northward components."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "id": "kWB-2nTwHAm6"
   },
   "outputs": [],
   "source": [
    "def wind_uv_from_spddir(wspd,wdir):\n",
    "    '''Convert wind speed and direction to eastward and northward components.\n",
    "    \n",
    "    Inputs\n",
    "    wspd - wind speed\n",
    "    wdir - wind direction (wind is blowing FROM this direction, \n",
    "                           clockwise from true north)\n",
    "    \n",
    "    Output:\n",
    "    u - eastward velocity component (TOWARDS the east)\n",
    "    v - northward velocity component (TOWARDS the north)\n",
    "    '''\n",
    "    \n",
    "    theta = np.array(wdir) # direction CW from true north\n",
    "    theta = theta*np.pi/180. # convert to radians\n",
    "    x = -np.sin(-theta)\n",
    "    y = np.cos(-theta)\n",
    "    theta_cart = np.arctan2(y,x) # direction CCW from east (Cartesian)\n",
    "    u = -wspd*np.cos(theta_cart) # eastward component\n",
    "    v = -wspd*np.sin(theta_cart) # northward component\n",
    "    \n",
    "    return u,v"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "id": "oE-chVuVHAm-"
   },
   "outputs": [],
   "source": [
    "ds['wind_east'],ds['wind_north'] = wind_uv_from_spddir(ds['wind_spd'],ds['wind_dir'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "id": "MMVqprwOHAnD"
   },
   "outputs": [
    {
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       "\n",
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       "\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;wind_east&#x27; (time: 14855)&gt;\n",
       "array([0.17103359, 0.51289238, 1.84067075, ..., 2.58021354, 3.0564969 ,\n",
       "       3.18198052])\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 2019-01-01T00:50:00 ... 2019-12-31T23:50:00\n",
       "    latitude   float32 36.78\n",
       "    longitude  float32 -122.4</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'wind_east'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 14855</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-5077f7d1-0289-493a-8254-e31a15bb18b5' class='xr-array-in' type='checkbox' checked><label for='section-5077f7d1-0289-493a-8254-e31a15bb18b5' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.171 0.5129 1.841 2.226 1.158 -1.431 ... 3.31 2.829 2.58 3.056 3.182</span></div><div class='xr-array-data'><pre>array([0.17103359, 0.51289238, 1.84067075, ..., 2.58021354, 3.0564969 ,\n",
       "       3.18198052])</pre></div></div></li><li class='xr-section-item'><input id='section-79ddcba1-cfdc-4e32-a4a4-503883c251d1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-79ddcba1-cfdc-4e32-a4a4-503883c251d1' class='xr-section-summary' >Coordinates: <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 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'>2019-01-01T00:50:00 ... 2019-12-...</div><input id='attrs-859b4c29-9665-450c-8132-cd062cab8f8b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-859b4c29-9665-450c-8132-cd062cab8f8b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-839b765c-0225-4bb1-aa9c-b87f9613ba20' class='xr-var-data-in' type='checkbox'><label for='data-839b765c-0225-4bb1-aa9c-b87f9613ba20' 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>Epoch Time</dd><dt><span>short_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-01-01T00:50:00.000000000&#x27;, &#x27;2019-01-01T01:50:00.000000000&#x27;,\n",
       "       &#x27;2019-01-01T02:50:00.000000000&#x27;, ..., &#x27;2019-12-31T23:30:00.000000000&#x27;,\n",
       "       &#x27;2019-12-31T23:40:00.000000000&#x27;, &#x27;2019-12-31T23:50:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>36.78</div><input id='attrs-6e80518f-626c-4299-b8f4-61b52cf32fdf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6e80518f-626c-4299-b8f4-61b52cf32fdf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-181d08d3-9ac8-4eb0-87b0-f315b8c5f234' class='xr-var-data-in' type='checkbox'><label for='data-181d08d3-9ac8-4eb0-87b0-f315b8c5f234' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>short_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array(36.785, dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-122.4</div><input id='attrs-3d75606f-9fb9-40ac-99da-83ce932f6b50' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d75606f-9fb9-40ac-99da-83ce932f6b50' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4efdeef8-4b2e-4cfe-9ba5-ad8c863ec652' class='xr-var-data-in' type='checkbox'><label for='data-4efdeef8-4b2e-4cfe-9ba5-ad8c863ec652' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>short_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array(-122.398, dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-83872271-6669-47b0-909e-d86ac2315626' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-83872271-6669-47b0-909e-d86ac2315626' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'wind_east' (time: 14855)>\n",
       "array([0.17103359, 0.51289238, 1.84067075, ..., 2.58021354, 3.0564969 ,\n",
       "       3.18198052])\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 2019-01-01T00:50:00 ... 2019-12-31T23:50:00\n",
       "    latitude   float32 36.78\n",
       "    longitude  float32 -122.4"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds['wind_east']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_SEZ5hR5HAnI"
   },
   "source": [
    "#### Plot the vector components"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "2NPDdkYJHAnI"
   },
   "source": [
    "Plot the time series of eastward velocity and northward velocity (time on the x-axis, both eastward and northward velocity on the y-axis)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 298
    },
    "id": "rvDKs8BEHAnK",
    "outputId": "bf463f9d-d8b5-45bf-b920-87aa2dab9eb4"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fb472110d30>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,4))\n",
    "plt.plot(ds['time'],ds['wind_east'])\n",
    "plt.plot(ds['time'],ds['wind_north'])\n",
    "plt.ylabel('[m/s]')\n",
    "plt.title('wind velocity')\n",
    "plt.legend(['eastward','northward'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "wkqWKIe8HAnP"
   },
   "source": [
    "##### *Exercise*\n",
    "\n",
    "Identify a time when wind is blowing from the northwest and towards the southeast. This direction is favorable for upwelling along the California coast."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "S2-_mSahHAnP"
   },
   "source": [
    "*(insert text here)*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_IZ3uLjjHAnR"
   },
   "source": [
    "#### Alignment of wind velocity"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "TQjg9G8fHAnR"
   },
   "source": [
    "By plotting eastward wind vs. northward wind, we can see that the wind off Monterey Bay tends to blow towards the southeast (upwelling-favorable) or towards the northwest (downwelling-favorable). This is because the wind tends to be steered parallel to the local coastline by coastal mountain ranges along the west coast."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 279
    },
    "id": "5OspyiueHAnS",
    "outputId": "d502c784-8c86-4b40-a84e-5eff8178b711"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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g1d58tj1oVxqOSfiTcUVtkysPHnp/cWEBsycXdZlx5TjCa7uPBtftCLVDzWSyPpcsJXNJDS8sIG1kjS01jXFuFp9sT9SOuCv4+xeU8mfXzewXQwTw9Jv7AXd1/vSb++nwJnA/JhFOad1S00g0wQA0tbQxb3ox95RPS5IS94nFlPYEY9dTBdbetjY11dfhhRkHI2ssnDXO1TbKkIgjSf8he/D2gCsuHMPqhxfy7TuvoLrhdLfn9+IjUhKNKWsq692JP2G7VN1wmtXbOns/LJw1jvy8zrstiEiwq1gytySozpaE8UUTqskF+q2ILVFe3ArnhjZdupVE5OUMrnFCVb/YN8MxhhK7DzfTEY0P0KbTU8pzhBW3z4nrjSy4E/079ad69Lm7QgahbMrolFlR+RHhbz1V1eaz7efUT8LXbnJ7Vn/Iw9fPZES+E8QaFILvwV9xP7roYlY/7Ep/J1ZRA4GSbOK3lagTNaYwn/vKp52ze8cK54xEuos5XAY81MVxAZ7ou+EYQ4nEWoZJo0dw8OTHwfOIAxpz/egrbp/DAwtKmT25iO0HTgQB05njz+uxcWiPKl954R0QoSbUP9qfWCOO8GfXzaTq0CkE+ODIuWVMhSfraEx5+s39SYbO//zwirsrHaVEl1NwD+Ju9/3DJ1tcw1Y67jweWFDa47FX1DaxprKeFyrqg2woK5wzoHvj8Jiqvt7VCSLyt304HmMIkVjL8OiiS6hrPMMvqg/zmbLJfKpsctwq1F+9hmUjHt+4J+6aRSMjnGmNdpvhFM7w8fHfEo1pj3cKk4tGcLi5NaNzozENpLV9Q4cIE84v4I6rL0yaXBNX7QtnjYsLSjvilm8oBDuqxB3EhqqGHhsHP8U4vJuz9FbDp0vjoKo/TXxNRBzgfFU9ne4cwwCCycqfKP3nX/3sZcE5iTn/re0xIt5OYt704iS30M2fmMR5I/I42tzKW/uO81FrtF/uJVPDAO6k/cYHx9la08hNsyey+3AztSdaOHy6NWmVny4DaPXSa1lTWc9x73Nf2300CEQndoAD1xD3BD+TLGwY+jN+YQx8MkplFZFVwJeAKFABjBGRH6jq987lw0XkR8CtwFFVneO9dgHwHDADOAB8XlWtzn+Q4ruKttQ0UlHb1KXGkO+j7/Bac86eXETRqPy489a/2xBkQA30+oi2qKYsoAuv8tMVpfnfk284HEe4aOL5HDj+EaruJP7Fa2dQ3XA6zvBmSmImWUTgvvmlLEmIfRjDl0zrHC5X1dMi8iDw78BXcI3EORkH4MfAPwP/Fnrtq8CvVPU7IvJV7/lXzvFzjByRaW78wlnj4no+x1QDV8vIfLdoS0SC/P7BjL/Kr6ht4uDJs0QcQaOapMMUNhyxqLLv6Efk5zncPa8kKYCdiq6CzH7mkV+w58d8fN0lCzgbmRqHfBHJB+4A/llV20XknP9GVXWziMxIePl24Cbv8U+A1zDjMGgJT3Ct7TEe37iHL99yadLEM296MStunxMns5EoVV1cWJDkChmM1DWeSenvD+tC+YYjL+IEneQU6OiIceHYUd3GLbozyqkyj6zIzQiTqXF4EtfF8w6wWUSmA90nkPeOSaraAKCqDSIyMdVJIrIUWApQWtrzLA2jfyguLAjcP74vfvuBEyknnrALKrxyTcyQ+dqLO/tr+Fnhyc01OAKJCUkdMQ0Ky8KaS9fMKA56W8dI7j6XalLPREMp8Xs13SUjTJdFcCJyrYiIqv6jql6oqp9VVQXqgEX9M8TUqOpKVS1X1fIJEybkcihGFzS1tCUFT/0GOmF8dwaQVL0blph+YEEp18wY3BOWkmwYwA0IL5w1jidf38fHnjx4NKaMyI8E36HgfqdhUk3qvSlYsyI3I0x3O4cvAE+IyB7gF8AvVPWwZyA6sjSmIyIyxds1TAGOZulzjH5g4axxcQVh4K5+m8+2B+ekylTqKpvnzt8rYfuBoZejoCR3xxNHGHdeQfDdKW7mUnhnla6FaFcFa6niEVbkZoQRzUD/XkQ+ASwGPg2MATbhGovfqOo55RJ6MYf1oWyl7wGNoYD0Bar6X7u6Rnl5ue7YseNchmFkkYraJh7fuIc3PzgeTHKOwDfvuIIHFpTyxKa9/P0vdwfH8hzhuUeuZd70Yp7YtJfvv7KbmLoZNffOL41TMx0sjBmVx6mzPV9PlYwdSV7E4UBjS9zrI/OT5b8zndQttmD4iEiFqpanOpZRzEFV3wfeB/5BREbhupTuAX4ApLxwhgNbjRt8Hi8i9cB/B74D/FRE/gzXfXVPb69vDAzmTS/my7dcylv7GkPZSATpqomZSlHP9+4XhIVXxYIb2AbXxXJlyRhG5DkcOnmW+lD19UBjQtFIPvr4o5TupK5Id09t7bFAxylsENZU1vPk6/u8zxyRMjU17IZqs9iCkYaMJbtFpBiY5r3nMPC/VfX/P5cPV9X70xy6+Vyuaww8/GykcG+HmGcEHl10MQ9dPzOoWlY6g66+q2NNZT2CK4sddrHce00pDywo5bEXd/LM1rr+vq2M2Xv0o16JCPoIUHxePifOuO64GPDTHR8Si7mZXctuLWP5y1VJUt/PV9Sz+uH4nUE4SSCmrovP0leNRDItgvsG8EWghnhNsD/IzrCMoYgfR1i2rsqd1PJd//iqrXX8ovpwcJ5DctB1bWV9kJPvS0c44p5XUdvE86HeCAOV3mbg+hLki+dMYfW2ukBCI+pVTLd3xNhQ1UB7im1JOOvIdz0dPHk2+A4FV2o83KXPDIQBme8cPg9cpKp917ndGJYkpqvuPtwcl5oqgBMRXqk+THFhAQ8sKI1zg6CK4wixmJLnFY1tqWkcVLUPPel+d8Ml4zl1tp2Jo0dSNnVM4GLzvwPFzSxaPGcKW2sak3YOeZ4UeFxL0ohDfsQtKBQRYqpBHcp3N7zHiPxIr6qujaFFpsahChiLZQ4ZfUA4vz5RWM93nbxTf4p36l2jEY47RCIOsZi3efWSKcLVvv1tI64uGUNdU0vg7smEnozxN/v83hCneH33UZZ/bg6v7T7Kr9474gbpHWHZrWWB0V1TWc/eI83sqG1CtVODKWxgo9EY980vZerYURQXFrD8Z9W0eYV2fj3FGx8c57XdR3nkxouC95vbaXiRqXH4O+B3IlIFBApkqvq5rIzKGDYkKrdeUFgQN9Gu3LyP73/+6iDF8uDJszy7rS7QYPJjFs88tJDHN+5J2bshm7zdQzlxn0RV1XSEmwa1RZWXfldPRW1TENiOqQYuON/oPrFpr2sc6AzuJxpYhWCyrzp0itVb65LG88quI7y2+yiIZCTnbQwtMu0E9xPgu7iZRN8P/RjGOfHAglK+fecVfPKS8Xz7ziv40+tnxR2vbWzhwae3sPuw23Nh9Ii8uGDqB0eag+K5xXOmnFPQtz8pvaCwV+/bdqApLuPJL5wLk6qYzQ/s3ze/FFR5NtSV7q65JYzId1J2xGuPKu3WGnRYkunO4biq/mNWR2IMWx5YUJrk3165eR+1jS0o8HF7jMe8uEQkYfZ/6e1DrtR0RECkS5dNQahHQq6pPdHS/UkZcPNlk1LKYqQqZps3vTiIz/gxhrWV9XzrziuC8z840syWmkaOfdQKntsKEaLRmFVNDzMyNQ4VIvJ3wMvEu5UqszIqY9hSUdtEU0sbS2+4iBXrq4NiN39K74hpkktGwZv0u574B4ph6CsijlvLkEoKPV3HtoWzxpEXcYIYw3Pb6yibOoamljaKCwv4RfXhQNPpnmumsWRuCWAxh+FIpsbh97x/F4Zes1RW45zoTkn0i9fO4MnNNUlTfnd9lYcaEYHZk4s4caaNw6fDTYeE1dvqWFNZn3EsYN70Ym68dAKvehIdHTH4+os7g9TgmNdxLhpTpobUX3tTiW0MbjKtkM6pyJ4x9MhESbS6oWvhXwE+dfkkjpz+mHfrTwV5+6UXFPaZ26Yrpl9QSN2JlqwapgvOy+fU2XbeP9yMJAQF/GB1umrpdEwsGhH33C9cinoSJZBaeM9kN4YXXRoHEblVVdef6zmGkUiiIVhbWY8CeREn8G/7PZjT6SgpUFgQoerQ6WCCjkSE+qbsGwaA+pNns75jiUuRTfNhMeDZbW51eCaT9pK5JTxfUe81UIpPrb35sklcNW1sSiNjkt7Di+52Dt8TkYMkt6wN823AjIPRI8KplY4jPOtV/uZHJK5d5ezJRaz4WTXvpEkZffmdQ3GTW9mU0bzby/TSnqL9XFSRFxE60sRN/KFkopU0b3oxqx92d2rNZ9t56s39RGNKxBFumj0xbfFbKvVXY+jSnXE4giuu1xUf9NFYjGGEn1GztrKeZ7fVBemZHdFOX7fv3540eiSQesIPz88RgUmjR5IfOR1MolPHjuTQyY/JhoarOIL0U9vS+TOK+criy9h9uJm/f+X9tEV3vlZSmHTy3OA2FYqFBA9XrK9m9uQidh9uZkNVQ1yldCaS3haTGDp0aRxU9aZ+GocxDPFTK8MTvOPEyz20tsdwJL3kRJ7jyj+I996N7x0hL+Jw8+UTeX3PsYyUWnsb0I72485hR20TX3nhHW65bBInW7quxl75Rg2l484LekKnixP4bqLwXbR3xHjy9X1BTwm/qDBsIHzD/ZgXyPb7WVtMYmiRsSqrYWSD4sKCuMnpoetnBlW+foOgqIIIFI2I0Nza2T5EgBW3z6GppY1DJ88GonTRaIyP26O0d2S2XxgMmU4xhb3HzrD3WE1G5/py6IlxgnDgOlF2xMENRB85HW9QN1Q1xLmaKmqbuP8p1wgAvLDjQ1YvvdZiEkMMMw5GTvHbiCru5FQ0Kh8gqceDKnzUGt9X6pbLJ8V1jFtTWR/4wxfPmcKbe48Pjpk/C/jSInGyGY7wQkV9nBSG7yYqLiygqaUtEEP0da3ArTwPs6WmMc7wtkeTPytdTMLcToMHMw5GTvHbiCZOKKn6P4AbV/AD11/yROH8CWfZrWXBBAeusTmnNoWDnJ+/e4iFs8YFBiC8u/JX9on9uqEzHpEYc/BZOGsc+d6OA9zfRarWpEBcnwhzOw0uuktlXdLVcVVd27fDMYYjd80tifNd+6Tq/xA2AIkTTp4j3FM+DXBXtz0tiO6JlHYuGTsqH4RuYw+7Gpr5/JNv8Y3b5/DooouTdlfFhQV87cWdCCR1jAtLqydWYPvZTn76cfj3Fo5JdFfHYm6ngU13O4fbvH8nAr8P/Np7vgh4DTDjYPSaxAnkLk+qIUx4kgq7PvwJ6PGNezpbXkaVZ7bW8XxFPZ+dM7nH4xkMhgHg5NnM5cGjMWXZuirAdeH5xrW4sCCuc1y4Y1xFbRNrK+t5fseHdHh9M+6eV5LSCKQi8ffiGwJLhR1cdJet9CcAIrIeuFxVG7znU4Ansj88YyiT6UoynHbpG5Jlt5axYn11ELQO09YR46W3D/XDHQwOfAMR7va2paYxrnNcWHH1wae3xBUetnXEWL21jrUJMh2p4gfhLDNfkiNRGdZiDoODTGMOM3zD4HEEuDQL4zGGET1ZSa6trA8mHL8tZjgN84LCfE5042bJjwjRqPZpzcNg0HXye19A/Co+P6RS63//ayvrU1akK66ReHzjHr58i/unnyp+EE6PdYDrLh7Pl2+5NKMdhzGwyNQ4vCYivwRW4/4/uQ/YlLVRGcOCTFeSfo9ofxIWR5LaYp76uHtXSzSmSB8GFgZLjCJMxKsjAbinfBpHm1uZWDQiUF99bntd8nvE/aOPKbz5wXG2HzjBkrklKXd9C2eNI88R2qNKXkTiDIMxuMhUeO/PveD0J72XVqrqi9kbFojIAaAZN+GkQ1XLs/l5Rm7IZCWZ6AJRdVVK7ymfxiqvg1kstNh1BMqnF1N3ooXiwgL2HT9DNBpDRHpduJZoCAS44LwCjn80uNqq3zR7IkBSEH/34Wae215HYmlIQZ7D8tvKeG57He944oZtHTGON7fiiKDq9qEuLizofJN4+6lEpUBjUJFxKquXmdTfAehFqtq/fR+NAUdyzYObV79kbkmQfRNuShNxhLfrT9ERjXHybDvLb+sMwq5YX01bewyVoAV1RozMj9DS1pkYqzDoDAPAa7uPMqFoRFIQPx1+v+5dIYXcmMKv3z8SGBJfdgPc9NeOqFe8GLWMpMFMRsbB2zV8FzdrSbwfVdXRWRybYQCdNQ/hoGq6vPpU+fxNLW08uuhiAOoaz7DyjZoeGQYgzjAMNgrzHVq8OELU04JyHCGWQa5vRwx+9Jv9cTs39zqdjxW3q9yydVWBARdSy34bg4dMdw7/A7hNVd/L5mASUOAVEVHgSVVdGT4oIkuBpQClpalVJI2hQzilNZzKmkpQzs/nb+uIxbk8KmqbePrN/YMuTnCufN3L7Gprd7+P0SPyArG9TNh79KO453kR152UaCA6QtcUgWW3ltmuYRDjZHjekX42DADXqepcYDHwqIjcED6oqitVtVxVyydMmNDPQzNywbzpxUFFr58y+f1XdvPg01uoqG2KO2/ZrWU4XoxhxfrqwJB0DDfLALz0u3pKxo4CgZhqSgN54diRGV3rqpIxrPjcHLpW8Xdddk0tg8/tZnSSqXHYISLPicj9IrLE/8nmwFT1kPfvUeBFYH42P88YXKSqkQjT1NJGTDVIffWL6IYj2w40sffYGWKK96NJf/i3XTmVgkjXE36eIyzz4jfd7TwU4r5vX8X1ay/ujDPkXVFR28QTm/ZmfL7Rt2RqHEYDLcAf4lZN3wbcmq1Bich5IlLkP/Y+typbn2cMPvwaiYik9m2nOm4rWRdHhPIZne4eX/DwT6+bmfY9EXEVcOdNL6b5bHu3tR1C587BV3F9Zmsdq7bWcf/Kt7qd8LvaGRr9Q6aprH+S7YEkMAl4UdxUuDxglar+op/HYAxg/GD0msr6lA6OcDOhD440s+Jn1VzrFX4lBleHMucVRDiTEEyPxpS3609REHHdbr7O0j+8uifp/RdPPJ/5My8IpDNWba1j5RupZcPD6b7hnUM6Fdeu4hGmw5R7uhPe+6+q+j9E5J9IUQiqqn+RjUGpag1wVTaubQxeUgWg13qB5zUJ0g4+z+34MOgK9079qW485UOPRMMABK62T13e2S96S01jUg1IROC7d10JuJP1q9WHWflGTbxKriPc/ImJjC8agUCQJeZI584hnYprV6Sqnje57/6lu52DH4Teke2BGEZXhEX6HJGgyU+q1aU/iRw8eTap5/Lw2TN0jeLWPDxy40XBRBuuJQF39+UL8LVHk9uhOgLfuH1O0HFubWU9eU7nbiQsv55OxTUdqdKUTe67f+lOeO9n3sM3vNW8YeSEsJshpq6Q3Irb56RcXQbVvxGHiBOfk290Eo11unfmTS/moetn8sPNnX/m2w40se1Aal+/I/DNO65IakWaF3G4+TJ3JxGmN5pK4fc8sWmvuZn6mUzrHH4sIhcC24HNuMZiZzfvMYw+Y+GscTji9osGiMWUppa2JG2m8CQSjca4b34pW2sa2XvsTI7vYGDhtwQtLiwIGvL4Xfi6QnB3GCtun8PsyUU8sWkvB0+ejZu4f/XeERSSVFzPBZP77n8yDUjfICIFwDXATcDPReR8Vb0gm4MzhifpituCKmmv8Y9/PDz5FBcW4HjaPvl5DkvmllA2dQxff3Fnn6qxDlYcgaWfnMXp1g6ON7ey/GfVQdvQZbeWURBSavWJOMK910xjztQxcZ327n9qC+0dMfIiEgSj/Z7f0LcrfJP77n8ylc+4Hld075PAWGA98Eb2hmUMV7pqJZmqSjrxvctfdiUcBCgZO4pXqw/zo9/sz9gwjMxz+DhRfW4IEVNobu1Ikub2ZUZWL72WH76+j1+/f5RYTINdAriKrRNHjwykvf0Ac3tUKRk7koMnP+5UzqXv5TNM7rt/ydSt9DpuUPrvgH9XVUsYN7JCdymMXU0Qayrrg1WvAnuPnWHvscxDZXkOtA6DAMUHR5qTejY4Tmcf6Kf+uDxu97b7cDNfe9H3Ip/i1+8fYea48+Lef+jkx+TnOUSjMRxHuHzKaO69ptQm80FMpsZhHHAdcAPwFyISA95S1b/J2siMYUdFbROHTp5NmfGSCeeSpnph8SjGn1fAO/WnzuEqg4PtKYLMl08ZnaRX5YsVPr4xvv4hGiMphqPAZZOLmDR6JK/tPsrOg6fYfaSa2ZOLzEAMUjKNOZwUkRpgGlCC20+6++iVYWRIYsbLvfOnZZTyGGbJ3BKer+h0dyQiwO1XT2Xd24eS0jIPNp3lYNPZ3t/AICJVOu+915QmufT8ftPjzutedkSBnQdPUX3odKD8allFg5tMYw77gN24cYYfAn9iriWjLwm7k6LRGBeOHdWr1Ec/n/7Z7XVJKawK/OzdBqt1SOCOq6fS1NLGk6/vC1qxtrbH+PpLO1HtvjZk8ugRHG1u9Yrj3DiFas93fsbAIlO30iWqOvSdsUbO8FMVE2W2e4ofk1gyt4QtNY2sf+cQ7x1uDo73thPcUGX+jGJ+UX2Yl985FFf5rKRuhiS4GU/hhKZjza3kRdx4Q35ox2FZRYObTN1KZhiMPicxZXXZrWUsW1cVyGyn8ldnKqHgH3ul+nBW72GwU3eiJdixZcItl09CgFd2HQleiyr8waUTuHraWIoLC+IMQ/j3BVgq6iAi4zahhtGXpEpZTSWzHZ5EfHVPvxBq9cPpC6z86ydm5RjxHD7dCnitHTM4X4DX9hxLev31PcdYNHui21QoFLPwn+dFHFClI6YmfzFIyFSy2zD6lFQpq93JcPu59X6T+7WV9WmvvyYhj9/onsunFHV7Ts3xM3EKqz7RaIznttfR2t75O91Q1RD3O26PavB4TWW99WoY4HSnyvqfuzquqj/o2+EYA5m+VMVMJYfQXRVs4so23Uq3oraJ53d8eE7jG24o8H5Dc7fn7T/+UfC9RxwBb6cXcYRdDafjji2eM4XtB07Q3hEj4u0col5h3QsV9UFltu0iBibduZX8pcRsXOmMl73nt+FqLBnDhK4ql3tDOkPQVZHbXXNLeMFTCM2PCHfNLUl53paaxmHVs6GvyGSf5WeACYC6O4GII9w0eyIb3zsSHLunfFpSRTu4v5tDJ88G0t7+LiKs2OqfZ7GJ3NKdKuvfAojIK8BcVW32ni8Hns/66IwBQ2+br3S12+ipHMK86cWsXnptlxOHX0hnZA8Ht6Lar2dQb/cg4u4kHEcomzom7fvLpo4Jdo0RRwJJcICfbq/DcZw4vSfLfMoNmQakS4FwXUMbMKPPR2MMWHqjitnXu43EzBdfTRQIekSvWF9Nq8UazokJ5xcwc/x57KhtQhUk1OHNEbju4vEsnjOFFeurgwn+td1HgzThaEz5m3VV1DWe4cdvHUgZkPYn/UMnz7Jqa13w2R0xkJgXV2qPuUKLakHsXJCpcfg/wDYReRHXPXkn8JOsjcoYcPRGFbMvWz0mVlD7E03EEaJRJUanfIY5lM6NxjNt/PCPyoF4o+svDBbPmUJTS1vaCR5cA/HkGzVBrYQfxPYz0Zpa2nh00cVufChU1Z7ngOO4NRPiSbRbD4fc0K1xELeR878BG3BVWcGtkP5dNgdmDDzCbqBMgtN9qcGfaGh8AxALxRbMKPQNMSVuhzZ7chFfvHYGv6g+TOkFhUEtyoh8dzUP8e1YfcJFdHkRQSCjLnGQ2ihZtXX/0q1xUFUVkZdUdR5Q2Q9jMvqR3mQgZeou6ksN/nAFtRU5Z58PjjTzT7/+IKhY911GBxpbgnM+bnfTiZfMLelS9FAgUGmtOnSK482trPHSkP0FR6p4lM+GqgYWz5liu4Z+JlO30hYRuUZVt2d1NEa/0tuYwNrK+kCDJ3G7n62KWN/QPL5xD298cPycrmV0z+YPjgW/45Q6Gh7Pba9j6/4TKbPDIg5ozM2Cerf+FNWHdiIiwbkv7PiQ1Uuv7bKQ0S+i237ghCm89jOZGodFwCMiUgucwSuoVNUrszYyI+t0FRPwJ/mwHAK4huG57XWd+eyRzu1+urhAXwUT500v5su3XMpb+xrpsO1Dn5LvQDiOf+JMe0bv64jB3qMfJb0uwJypYzjT2sHeY2dQ79yw8689ql3GEfoyZmX0nEyNw+KsjiIFIvIZ4H8CEeBpVf1Of49hqJMuJuBP8v7K0RGCyb49qnHdvu6e1ymrnfjHDKSVwugt4Xahfiqlce70ZYKXL8Xxbv0pJMHf5LcTBciPSJdxBOsbnVsyFd6rBRCRicDIrI7I/ZwI8ATwKaAe2C4iL6vqrmx/9nAiXUzAn+SDoG/CZA+dbSDBNSbzphfH/TGHK2L7+g87XFz1+u6jbEvRvCadVtD5IyJ81Brts7EMRwQ3vVVEEAH1ssbuKZ9G2dQxbKhq4M0PjqdUdr35sklMLBoRBJ+7E0+0vtG5I9N+Dp8Dvg9MBY4C04H3gLIsjWs+sFdVa7zPfxa4HTDj0MekCgYGwd/2WJAi6jihiSDicNOlE3ht91Ge3VbH2sr6wG0U/mOG7Fa6Hjp5lsq61No8ClxdMoa3Ezq7mWHIjLGj8jh5tiPlscumFPEfrpza5e/4rX2NRGOKI4C4ldURgfMKItSdaMk4wGx9o3NHpm6lbwALgY2q+nsisgi4P3vD4kIgLI5TDywInyAiS4GlAKWlpVkcyvAjPMk3n23n6Tf3uzuAiHDP/NKgV8LG944k+YMT/5j78g+7oraJNZX1HG9u5bXdR4N+0elINAxG5qQzDAB7jjTzjQTJE59VW+tYtq4qiAlF1TUKEUeIxZSX3j4EECQVPLCg67/dvtTzMnpGpsahXVUbRcQREUdVN4nId7M4rlSZcXEzgaquBFYClJeXm+v5HEn8I/R/nti0N5DRjsaUqaEObf3pD66obeKuf/ltVj/DSE04TgDuLiBVDKmitom/eWkniTY7mhCI9tlQ1dClcejrCnujZ2RqHE6KyPm4YnvPiMhRIP3S4typx+1X7VMCHMri5w1ruvojTBcU7G9/8H9+7u2sXt9Ijd/5LeJ0pqD6geTEtOUVP6tOMgw+/s4hfHjxnClA+t2BZSvllkyNw+3AWeA/AQ8CY4AV2RoUsB24RERmAgeB+4AHsvh5w5rwH2Fru6uSGXYZpDMCXfmDV22tY0NVA2VTRlM0Kv+cDUjDKRPTywUKxGJw34JpQZDfr2JOTFtOVevgJy4sv82V2mg+2051w2kWz5nCAwtKe7UwMfqHTI3DvcAbqvoB/aCppKodIvLnwC9xU1l/pKrV2f7c4crCWePIc4Q2L031ue0fMmfqmOCPN5Vh6MoX/J1/f48fbq4BXN+y4K42b5o9kQlFI1jSTZZKujFutuK3nBCD4P8DuL/7xzfuiSuEhNTZYddfMp4v33Jpr2oZLFspt4h2Uf0YnCSyArgeV4l1B/AGrrF4O5uDy5Ty8nLdsWNHrocxqHnsxZ08ExJPy3OEFbfPiWv76K/q0q32/IDx6m11XRXVUtBNi890LPz2xqCtJcD4ogImnDeC9w5336TG6D0CfGJyEWfbo1w9bSy/qD4cTOh+Jhto0OshzLfvvKLbRcaDT3e2frW4Qv8iIhWqWp7qWKZ1Dsu8C40CHgb+C/A47qreGAIsmVvCc9s/7MwyiSkrN+9LuapLtdoDuP+pLYG6Zlf01n/8B5dNilP//MPLJyNgxiHLKJ3fcVhbya93iPlWIgXPbXd/X8t/1imgF14Y2O5g4JJRD2kR+bqIbABeAS4G/ho3SGwMEfzK4zxHAt/ygcYWYuoGJMM+31S9nv3+zmEcgTuunsoDC0rJi3TOHr31H981t4QCT92zwOsE11VTGePcGD0yL62gnr9jiCkpi9183qk/xddf2tll72+/gHJLTaP1lB5AZBpzWIKbnfRz4HVgi6p+nLVRGTnBrzx+fOOeoMLVwW3uEvYbp1rtrUn4g7+qZAzLbisL3nPX3JKgRmFC0YhejS9VJ7gtNY1pq6GNc8MRN1aUqp7ET23OhMTTjja3xj23lNWBSaZupbkiUoQbd/gU8JSIHFHV67M6OqPf8cXt/Mbw+XlOyoBiYqZSYn/nsGHwz4fODJc1oarqno4v/J6Fs8YRccSE+LKAXwjXU+MrAk5I5jvx/RMTFgdrulD5NXJHpvIZc3Ab/dwIlONWL7+RxXEZOaQ3fuBM+jv3JG8908rYedOLeej6mUF2lNH3hPW0zstEm0ohFvIzKZ11Dvl5DkvmdnqkK2qbeKGivlPl1+lajM/oPzJ1K30XtwDuH4HtqpqZnq8xaOmNpk1370mVt57KCPTUzVA0Kt9cS/2AAhdPOL9bWZJUO7k5U0dTduEYBNh9uDn4nW+paaTDS3MS4J7yaT36f2fyGtkjU7fSf8j2QIyhTyphPl8aPOKlzj6woLTHlbELZ41jRH6nUGBPiQhpK3uNeDLRq7r1yimsf/cQ4fyEEXkOz22vi0t3LYgIf3rdzCAmodCjBAOLVWSXTN1K1wHLcdVY8+hs9jMre0MzhiLh3cXXXtzJx14jgY6YsmxdFbMnFyVJfx88eTaQBU93Td/oFBcW8Nz2Ot7JUHRP8FweUTcdM4OyH6MbXn77EN+88wo27T7K/mMfsb/xTEpZ9bao8lYoocABmlraMv4ck9fILhmlsgL/CvwANyB9DW7c4ZpsDcoY+vi+5jAx7ewM9sxDC7lvfimo8uy2Oh58ekuXaY7zphfz6KKLeWBBKctuK6Mgzwkqsz91+SRXOjrE+PML+MPLJ3H/glI6PM0fMcPQJ8SATbuP8qUbL+K8EXkpi+N8Jo0eyYh8Ny26IL9nKc6pUqqNviPTmMMpVd2Q1ZEYw4qwrxncFXxBgrDflhq3HWhPV4bzphez+uH4gPqqrXU89uJO1wgAd88toWhUPsWFBcEuxa3oMgvRF+w/9hEPPr0l2BmmIuIIj9x4EY/ceFGcq/GJTXsziiFYAV126dI4iMhc7+EmEfkesBYIkpRVtTKLYzOGMImuo7vnlSR1BjsX4bXE4HjYXaHADzfXIMCIfIdlt5ZRfehUXPW10TNKxo6k/mRn6dOsCeez79iZtOeLwDdunxNXO1NR28T9K98K0qFXL702IwNhRiE7dLdz+H7C87AGhwJ/0LfDMYYLmaz6Ml0ZZpKxkqoews+rb2ppY+rYURmP3ZGuq4KHI75hEOD2q6cyf+Y4Xtl1JP0bNDm+sKayPii4a4tqnDqw0f90aRxUdRGAiMzyW3b6iIgFo41zItWqL13ToXRkmrHiy4MsW1dF1I8x4PZBLi4sYPbkIkbkO0ExVip8yQhB4zJxIo4bybaMJ9dornvnEFUHT3WZXiwCxYUF8a8lnpOF8RmZk2lA+oUUrz3flwMxDH+i//4ru7sNQPukEwFMxQMLSnnukWv560/P5ks3zHKzlFRZsd5Vg3/moYX89adn8+07r0g5Ud2/oJR7r5mWHJZQ5ebLJpGXGPUepqjC3mNnuqw7iSmsWF8d9zteMrck0ODKi0hcsZzR/3QXc/gEUAaMEZEloUOjgZHZHJgxtPF3CMWFBTS1tAUFUT1NTexpXCKx/Wn4sx5ddDHgGpxPTC6KU3stn1HMt++8goraJldk0Kup8EUJH7nxIm6aPbFHabRDhQvHjuTgyZ5LrbW2x3jy9X1cNW1sxvEkK3rrP7qLOcwGbgXGAreFXm/Gle42jB4TdgX5as9+YLinAejeZqykq9YOdzfzi+PyHPjq4suSPi/c1QwIel8k9lwe6owZlc+x5taUAn2p8L8fBV7ZdYRXdx1hRL7DJy+ZQId3jY6o8sPX9/HUH3eGOa3orX/pLuawTkTWA19R1W/305iMIU54hwDuJNHW7gaGezPR91bqI/Gznti0NxhXNBrjvvmlTB07KmV7VOgUEdx+4AR3zS2JM3bDiV0NzYwrzKexJVlV58LiURxsim/xmmg4fSnvo6fjdx8b3zvCqq11QQc6K3rrX7qtc1DVqIh8CjDjYPQJ/qo9HPyNkRygzDapFF7Du4mu2pkmTlQKwXtFkrWF8hzigthDjVSGIeIIh5pS9/5ODFY7Itx7TSlVh6oCNVdVgqp5v+eD9ZTuPzItgvutiPwz8BwQJC9bnYPRG/xVe1zfCIGqQ6dStiXt73FlsnMpLizAEXeKy89zuGuuW6fhx1GWrauKMxBD2TCko6t+D7dfPZX17zYQjWmcrhbA11/aGewuYrHOqnkreutfMjUOv+/9uyL0mtU5GL0mVd+I482tXer690cwMhMXVUVtEyvWVwcT27JbywCSxhZOmzU6iTjwR9fO4I+uncGayvrADedXRn/zjitYtq6KWEyTJDWs6K3/yFSVdVG2B2IMPxIF85a/XNWp6x+JnxQGUjDSdym5hXCacsfjd9VbW1nPM8O88toRKJ9ezPYDTSgQi8HaynqWzC1hbajRjyME399zj3TdG8TIPpn2kB4jIj8QkR3ez/dFJCvNe0VkuYgcFJG3vZ/PZuNzjIGBL5jX1NIW54a58dIJcZNC2Mff1hHj8Y17ctZvOFHwTSBlrcW86cV8684ruOPqqTkZZy4piAgOkOcI37zjCr6y+DLy89zpRoHnd3wY9B0P4k4JgeZHF11shiGHZOpW+hFQBXzee/5HwP/G7S2dDf5BVf8+S9c2BiALZ40jz+nsV/z6nmNxMt3+hOxPwm9+cJztB07kZAeRqi/Fmsr6tE2MCkdk+mc2dLhowvkU5Dnce427g9pS08iNl05g464jQf9pP4ifWDNigeaBQab/ay9S1btCz/9WRN7OwniMYcq86cXcUz6NVVvr3Mkj2rkC991OS+aWUH3wFO/Wn8p5v+FE33eqJka+m+mGSyb0+/hyjV9AWHWoCkGJxiASESKhrK05U8fEBfH9YkjbLQwMMjUOZ0XkelV9E4LmP6lz1PqGPxeRPwZ2AH+lqkn+AxFZCiwFKC0tzeJQjP5iydySuBV4cWFB0CnO90nnOUIkIkGxVH+nv6YjbCzC9RLtHTHGF40gPyK0R3XYtTMNZyx1hIrkogrLf1bN6ocXBpXpxsAiU+PwJeDfvDiDACeAL/b2Q0VkIzA5xaHHgH8BvoH7N/QNXGXYP008UVVXAisBysvLh9Pf25Al0V0TDvyC65PuiHZm/0QVlr1cRfWhU5RNHTNgVp6J+fhzpo7hBT70hP5MzdWnzQrZBjSZZiu9A1wlIqO956fP5UNV9ZZMzhORp4D15/JZxuAi0V2T6JMW4itsO6Ialw0UEbj5skncNHtizoxFKiPnd5szw9BJxBGLLwxgMu0hPQK4C5gB5Im4mcmquqKLt/UKEZmiqg3e0ztxA+HGMCQx1bWppY13PjzZZZ+AqLp6Pa/sOhKn2dTfhiJs5HYfbg4K5iKO614a7jgJzX6MgUembqV1wCmgglAnuCzxP0Tkaly30gHgkSx/njGASdxJVNQ28druo7Rl4L/3NZuWrasippqT+ojEgrlFsyfyqpexM5wRYPbkolwPw+iCTI1Diap+Jqsj8VDVP+qPzzEGJ/OmF7N6qVsgdfDkWVZ72U2QrNfjN+dJlObuT+OQWDA3vmhEt02FhiLjzy/gZEt7UMsSVXh84x6+fMultnsYoGTa7Oe3InJFVkdiGBniF0jdNbeEEfluMdrIfIdv3XkFn7p8EhFHEFyf9kPXzwwK1iKOcOjk2aTiuYraJp7YtJdVW+t4YtPetMV1/nk9Kb5LLJi7a24Jy24tY7j1BZpbWsxD18+Me+3ND47z4NNbuv3ejdyQ6c7heuCLIrIf160kgKrqlVkbmWF0QyohtqaWNn713pFgpV40Kp9nHlrImsp6XqioZ/W2OtZU1gfupVS9JfLzHO6e5wrpQWedxfKfVQcZSKsfTu+eStSAShzjlprGYdXvIeIICryV0KVvILj9jPRkahwWZ3UUhtFLupPdDk/IHdHkXgApe0t0xFi9tY4XdnwIInREXRluP2e/rSPG2sr6lJNYOg2o8LnFhQXDxqUUEVdZ9dVQEoHv/nPElerOpdvPSE+mqay12R6IYfQF6WSdw0YjEnE46LmXigsLkBTFBwpeVpFXV5HieCoyaUjT1NI2bIrhEhOzBLiyZAyTRo9kfNEI5kwdw4r11dajYQAy/ERfjCFPKlln32israzn+R0f8uy2zp1BYt8BwQ9mgyLEEmS38yISuJwSXUiZNKQZTjuHRCIRYVfDad6tPxXEYKxHw8DEjIMxbAjcSzHPjeHtDFLi9zlWjatqFuDz5dOS4hVhF1J3k11TS1vW7nEgM39GMWMLC4I6Fd899607rzCjMADJNFvJMIYEcdlDESHfe1yQ53BVyRgccc1FTD3jgGsY8hwhIm5RXThQnU6qO1FuOpzp5I9huFFZdzLpteG6gxoM2M7BGFakkttOVFNNrEHw21gmVlln2tM41Q5j9cOui0uBvUea2XbATeP0ffJjRuWz+YPj2foacoLvnouIG4uIiKvMagxMRIeA2Et5ebnu2LEj18MwhgAVtU1B2mtHNIYj8f2NU53fnb/8ay/uDIr1IgL/+Q9nB0qkq7bWxfVMzosIKz43hxXrq/m4fWg1nnYgcNd5DxmRnzp9tT9awhogIhWqWp7qmO0cDCOEH8z2+wx0Nzl119O4oraJFyrqO9ufhsTmKmqb+Jt1VXE1D7GY8truo7QOMcMAEIM4P5KfNrymsj7uux5ILWGHM2YcDCMFvWlkn2q169dXgLtSvscLZvvHEjOlYkpQxDdU6CptN6Zuy9BoTINdWlNLW7fpwEb2GX5RMcPIAv5q9/uv7ObBp7cEUhDhAPiIfIclXjA7fCyMQ2dtgACXTS4a1FIbF5yX3+057VE3e6wjpnz9pZ00n22Pkxyx2ofcYDsHw+gD1lTWB4HscObSlprGtJLh86YXs/rhhTz5+j5qjn1E8XkFrlEJVWvfeOkEvnnnFXxnw3tsPzD4tIcmFY3kxJn2uNe620k8/eb+lAkARv9ixsEwzpFUcQW/xWkmfvPNHxyjrSOGNLYkaS6tfKMGgJ0HT2XxDrLD/BnFtHYkx04UkmpHwrfdEVM27T7KU3+cMk5q9BPmVjKMcyRVXCGV3zzde/3zEuMP4K6kV75RMygD1BdPKuLea9L0d9fOzn6pdhGv7jrCqlCHP6P/sZ2DYZwjifUOflwhkxqI4sKCbhVafbXYwUSeA3fNLQl2SxuqGiibMprqhtP8Zu9x957U3WVFE+RJfDZUNaRNITayjxkHwzhH0klmZKIZVHUo3l00VAT5ykLFbQ8sKOWBBaVU1DZxurWDvIhDNOoazWW3lrFp91F+/f7RpJ3T4jlT+nvYRggzDobRB6QT++sumJq4I0hnGATXTz9Y+kC8U3+Ke598KyggDNcu5DnCffNLWTK3hN2Hm9nkGQYBrioZQ9GofBbPmWK7hhxjMQfDyCFL5pZQkOcguNXRqTSX/GMyyHxLHTFl2bqqoP4jHFuZOnYUAMvWVQWtQxV4u/6UGYYBghkHw8ghfjrrX396Ns8tvZblt5URCRmBiCN86vJJlI47j+jgi0kTjWnQSc8RwfFqF4oLC3h8456UQfgNVQ05GKmRiLmVDCOHJFZVb6lpjHMtqSq/fv8IKTJCuXjCeexvPJMzo5EqPjIqP8LZ9mjnOQLNZ9v5p19/QDSmRBzhi9fO6FI7qmzK6OwN2siYnBgHEbkHWA5cBsxX1R2hY/8N+DMgCvyFqv4yF2M0jGyT6Ie/afbEpMnWlw5PJC8ifPfuqwD4ygvvsPfYmewPOIQfH3i7Pj6g/nHIMEBnUZufkaSqVDecTpuaK0DRqO6rqo3skyu3UhWwBNgcflFELgfuA8qAzwD/S0Qi/T88w8g+YT98W1R5ZdcRXt11JKOgs+MFIOZNL+a7d19FQUT6Nd3Vjw+kej2RDm/H4MthLJ4zhUgKTRAHV2LE5DIGBjnZOajqe4Dbuzee24FnVbUV2C8ie4H5wFv9O0LDyD6+H141dZ5/IuGq4mi0U5Bu3vRiVi+9li01jbzz4Ule3TWwhPscIaUcxmMv7owb5xUlY1h2W5nJZQwQBlrM4UJgS+h5vfdaEiKyFFgKUFpqmQ3G4KKitokV66s9NVJS9rJOwmuQA52CdOGYxaOLLqaitimQ4/CL53JtKJZ+clZS9tEDC0p5bffRoGUowKTRI+O66Rm5JWvGQUQ2ApNTHHpMVdele1uK11L+31bVlcBKcJv99GqQhpEjfJeS/x/33mumBRP56BF5vFXTyIg8h7GFBUFAWgHHERbNnsj4ohHsPtzMivXVaXtYFxcWUHXoFHuPNLP9QFO/G4kZ4wpZesNFSYbBN2g3zZ7Ia7uP0h5VIhHhtd1H2fjeEevhMEDImnFQ1Vt68bZ6YFroeQlwqG9GZBj9R3edzBIlN8JSE4k89uJOVnmd5KIx5dfvHyWmbv+DmGpS3wP/x9+dJLY97S8+UzY5pWEICxL+6XUzqW44zaj8CBvfOxJ3L7sPN7OhqsHqHnLEQHMrvQysEpEfAFOBS4BtuR2SYfSMdJ3MEg1GJvIa4BbKramsp70jhkhIi0gVxxEETanflLg76W+qG07HPa+obeLxjXsCY9XWEePpN/cTUyXPkThZjeaz7Xzvl7sBeMPrpW0Gon/JVSrrncA/AROAn4vI26r6aVWtFpGfAruADuBRVY12dS3DGGiEs5DCiqypDEYmrpNEV9GK9dXBjiNdrwjo3J3kaufQcPIsq7bW8cCCUlZtrWPZuqrAsDm4GVf+82hMuXf+NC4cO4qFs8bx+MY9cdcyEb7+J1fZSi8CL6Y59i3gW/07IsPoOxJdRgtnjUtpMHriUw8bktmTi5J6LqcK5PpG5cnX98UFfrPBDZeM5zd7jwdd7AD2HjvD117cybb9jax/tyGQyRDgukvGs3jOlDhDF3atLZ4zJdgx+M+N/mWguZUMY9CTzmWUiYR3ptf3r5nOhRU+96ppY7Oe3nrqbDv3zS9FgeqDp3gnVAPx0tvxYcOIIyyeM4Wmlra0Ox9/l2Axh9xhxsEwskCiy6gnMYaekMmOZOGsceRHhLZo9szDu/Wn2HnwFAV5Dl+8dkaccQgTEXjo+pkps6wS8aW+jdxgwnuG0U/Mm17Mo4su7tMUTd+F5Vcfp9qRzJtezD3l0+LyxPu6mlpxpTLaOmIUjcrnSzfMSvkZ980vpWhUfkZd8ozcYjsHwxjEpNqRpEqjXTK3hOcr6mnzFPyytYdwRILPbW7t4JmEVp9lU8cwe3JRn7nYjOxhxsEwBjmZxCDmTS/m7nklrPbqJbJBxJPJAHhi017Kpo4hz5G4QHRTSxvgthBV6LK+w8gtZhwMY4DRXQFdV3QVg7hrbglrK+vTSmWfK/fNL2X25KLAODki3HrlFNa/20BMlQKvj0PYeN3l9ds2Bh5mHAxjANFd9lF3pEqj9fFdUD98fR+vZiG1tWhEXlyRW0yV9e82xInunWtKr9F/mHEwjAFEX9RDdJUVNW96MU/9cTmrttaxoaqBUfmRPktzferN/cRi8QqzsZjS1NLGo4suDl6zeMPgwIyDYQwgulr5Z0omldezJxfR1NJGcWGBq+LaHnMlwUndXCgToqHYgngqggX5qXcvfZ3Sa/Q9opor5ZW+o7y8XHfs2NH9iYYxCDiXmEOm1w+7rsKFaLsPN/M3L+0MKp0db5LPNEohuA17upL1MAYOIlKhquWpjtnOwTAGGJlqLvUGX/wu7LoKu33mTS9m9uQi1lTWI7gpsAD3r3wroyK6T10+iUduvMgMwhDAjINhDBP8HYMfMHa8wrniwgKe2LQ3WOWnMk6rl17L2sp6ntteRzQGjgNzpo5hRJ4T9IpwBK6aNtYMwxDBjINhDBPCEt4ClF5QyGfKJmckZTFvejFbahqJKZ6KqiuZkR8R8vM6pbYtwDx0MONgGMMEP9jtu5RqG1uCfgqJUhapYh6JEuCppLZt1zB0MONgGMMEP1Po8Y17ePOD425mUiy+YVC4SC3PEe4pn8YSr4rZf//aynqe3/Eh0Zh228XOGLxYtpJhDDP82EOqhkFbahr5/iu7g3RWP/so0d2U7Ywqo3+wbCXDMAK6qzVIdB2lKsbLZkaVMTAw42AYw5B0k7tvONZU1vNCRb0FmocxZhwMw4jDNxx3zS0x19EwxoyDYRgpMdfR8MY6wRmGYRhJ5MQ4iMg9IlItIjERKQ+9PkNEzorI297PD3MxPsMwjOFOrtxKVcAS4MkUx/ap6tX9OxzDMAwjTE6Mg6q+ByDS123ODcMwjL5gIMYcZorI70TkdRH5ZLqTRGSpiOwQkR3Hjh3rz/EZhmEMebK2cxCRjcDkFIceU9V1ad7WAJSqaqOIzANeEpEyVT2deKKqrgRWglsh3VfjNgzDMLJoHFT1ll68pxVo9R5XiMg+4FKgS22MioqK4yJS26uBDh7GA8dzPYh+Zrjd83C7Xxh+9zzQ7nd6ugMDqs5BRCYAJ1Q1KiKzgEuAmu7ep6oTsj64HCMiO9JpoAxVhts9D7f7heF3z4PpfnOVynqniNQD1wI/F5FfeoduAN4VkXeAF4AvqeqJXIzRMAxjOJOrbKUXgRdTvL4GWNP/IzIMwzDCDMRsJSM1K3M9gBww3O55uN0vDL97HjT3OyT6ORiGYRh9i+0cDMMwjCTMOBiGYRhJmHEY4IjI90TkfRF5V0ReFJGxoWP/TUT2ishuEfl0DofZZ6QTZfSODbn79RGRz3j3tVdEvprr8fQ1IvIjETkqIlWh1y4QkVdF5APv3yGjDy4i00Rkk4i85/1//kvv9UFzz2YcBj6vAnNU9UpgD/DfAETkcuA+oAz4DPC/RCSSs1H2Hb4o4+bwi0P4fvHu4wlgMXA5cL93v0OJH+P+3sJ8FfiVql4C/Mp7PlToAP5KVS8DFgKPer/TQXPPZhwGOKr6iqp2eE+3ACXe49uBZ1W1VVX3A3uB+bkYY1+iqu+p6u4Uh4bk/XrMB/aqao2qtgHP4t7vkEFVNwOJNUu3Az/xHv8EuKM/x5RNVLVBVSu9x83Ae8CFDKJ7NuMwuPhTYIP3+ELgw9Cxeu+1ocpQvt+hfG9dMUlVG8CdTIGJOR5PVhCRGcDvAVsZRPc8oOQzhiuZiBSKyGO4W9Vn/LelOH9Q5CX3UpRx0N5vBgzlexvWiMj5uIW9X1bV04OpTYEZhwFAdyKFIvIF4FbgZu0sTKkHpoVOKwEOZWeEfUtvRBkZxPebAUP53rriiIhMUdUGEZkCHM31gPoSEcnHNQzPqOpa7+VBc8/mVhrgiMhngK8An1PVltChl4H7RGSEiMzEFSnclosx9hND+X63A5eIyEwRKcANvL+c4zH1By8DX/AefwFIt2scdIi7RfhX4D1V/UHo0KC5Z6uQHuCIyF5gBNDovbRFVb/kHXsMNw7Rgbtt3ZD6KoMHEbkT+CdgAnASeFtVP+0dG3L36yMinwUeByLAj1T1W7kdUd8iIquBm3Alq48A/x14CfgpUArUAfcMFaFNEbkeeAPYCcS8l7+GG3cYFPdsxsEwDMNIwtxKhmEYRhJmHAzDMIwkzDgYhmEYSZhxMAzDMJIw42AYhmEkYcbBMAzDSMKMgzGkEZE7+kPhVEQOiMj4Xrzv6Z6OT0Q+SvHaDBE5KyJv92IM+SJS0cXxZ0TkhIjc3dNrG4MXMw7GUOcOXBnsPkNE+kx2RlUfUtVdfXS5fap6dS/edz3w23QHVfVBhkfFthHCjIMxYBGR/ygi20TkbRF50u/fICL/IiI7vCYqfxs6/zsisstrjPT3IvL7wOeA73nXWOCvkEXkKhFRESn1nu8TkUIRuU1EtorI70Rko4hM8o4vF5GVIvIK8G8iMk5EXvHOe5IU4nki8nkR+YH3+C9FpMZ7fJGIvOk9fs1vaiQiH4nIt0TkHRHZEvrsmSLylohsF5FvZPjdzRC3SdTTIlLlrf5vEZHfeI1mwnLnnwE2iMh5IvJz7/OrROTenvy+jKGFGQdjQCIilwH3Atd5q+Eo8KB3+DFVLQeuBG4UkStF5ALgTqDMa4z0TVX9Le6K97+o6tWquhUYKSKjgU8CO4BPish04KinXfUmsFBVfw+3r8J/DQ1rHnC7qj6AK//wpnfey7hyCIls9j4H799GEbkQd6X+Rorzz8OVR7nKe+/D3uv/E/gXVb0GOJzRF+hysffeK4FPAA94n/3XuFIOPouA13CNxCFVvUpV5wC/6MFnGUMMMw7GQOVm3Ml4u+dHvxmY5R37vIhUAr/D7Qx3OXAa+Bh4WkSWAC1JV3T5LXAdcAPwbe/fT9I5WZcAvxSRncB/8a7v87KqnvUe3wD8XwBV/TnQlPhBqnoYOF9EinBVV1el+LwwbcB673EFMMN7fB2w2nv8f9LcVyr2q+pOVY0B1bgdyBRX72cGgIhMBU54hnEncIuIfFdEPqmqp3rwWcYQw4yDMVAR4Cfeiv9qVZ2tqss9Rda/xpUvvxL4OTDS65Y3H1ci+Q7Sr3rfwJ2cp+MqYl6Fu5r225L+E/DPqnoF8AgwMvTeMwnXykSY7C3gT4Ddoc++FvhNinPbQ5LsUeIl9XsjgtYaehwLPY+Frr0Y+CWAqu7BNcg7gb8TkWW9+ExjiGDGwRio/Aq4W0QmQtCYfTowGneSPuX55Bd7x88HxqjqvwNfBq72rtMMFIWuuxn4j8AH3or6BPBZOifrMcBB7/EXSM9mPDeXiCwG0jWK34xrzDbj7nQWAa09XJX/BlfGGzpda33FZ/C6C3q7iBZV/b/A3wNz+/izjEGENfsxBiSquktEvg68IiIO0A48qqpbROR3uG6SGjon9SJgnYiMxN11/Cfv9WeBp0TkL4C7VXWfK7Uf7BTeBEpU1XcLLQeeF5GDuD27Z6YZ4t8Cqz331uu48supeAPXpbRZVaMi8iHwfk++C+AvgVUi8pe4O6M+wQvwX6Kq/niuwA3ex3C/7/+vrz7LGHyYZLdhDAHE7VO83gskZ/qe64H/6PcH6ebcH3vXf6HXgzQGFeZWMoyhQRQY05MiOFV9M0PD8AxwI27A3xgm2M7BMAzDSMJ2DoZhGEYSZhwMwzCMJMw4GIZhGEmYcTAMwzCS+H8Je1j7uG94LwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(ds['wind_east'],ds['wind_north'],'.')\n",
    "plt.xlabel('eastward wind [m/s]')\n",
    "plt.ylabel('northward wind [m/s]')\n",
    "plt.axis('equal'); # make the scale equal on the x and y axes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Yzedsc0EHAnu"
   },
   "source": [
    "### Coordinate system rotation\n",
    "\n",
    "#### Rotating wind stress vectors"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Bk1r6q7RHAnu"
   },
   "source": [
    "The northward and eastward components of wind stress are not always the most useful for studying upwelling. It is the alongshore component of wind stress (the component parallel to shore) that is most important for upwelling. The direction parallel to shore is not always conveniently aligned in the north-south or east-west directions.\n",
    "\n",
    "To calculate the alongshore component of wind stress, the vectors are rotated from geographic coordinates (east and north) to \"natural\" coordinates (cross-shore and alongshore). The `rot` function rotates vectors to a new coordinate system defined by the user."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "id": "zUtmMZcPHAnv"
   },
   "outputs": [],
   "source": [
    "def rot(u,v,theta):\n",
    "    \"\"\"\n",
    "Rotate a vector counter-clockwise OR rotate the coordinate system clockwise.\n",
    "Usage:\n",
    "ur,vr = rot(u,v,theta)\n",
    "Input:\n",
    "u,v - vector components (e.g. u = eastward velocity, v = northward velocity)\n",
    "theta - rotation angle (degrees)\n",
    "Output:\n",
    "ur,vr - rotated vector components\n",
    "Example:\n",
    "rot(1,0,90) returns (0,1)\n",
    "    \"\"\"\n",
    "\n",
    "    w = u + 1j*v             # complex vector\n",
    "    ang = theta*np.pi/180    # convert angle to radians\n",
    "    wr = w*np.exp(1j*ang)    # complex vector rotation\n",
    "    ur = np.real(wr)         # return u and v components\n",
    "    vr = np.imag(wr)\n",
    "    return ur,vr"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "basR5F1eHAnz"
   },
   "source": [
    "See what happens when the vectors are rotated 20 degrees clockwise."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "id": "d_rexLy0HAnz"
   },
   "outputs": [],
   "source": [
    "rotation_angle = -20\n",
    "ds['wind_x'],ds['wind_y'] = rot(ds['wind_east'],ds['wind_north'],rotation_angle)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 297
    },
    "id": "Or4-CPRaHAn4",
    "outputId": "4f2ea59e-e115-4d23-acd5-6eff59b82db7"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8,4))\n",
    "plt.subplot(121)\n",
    "plt.plot(ds['wind_east'],ds['wind_north'],'.')\n",
    "plt.axis('equal')\n",
    "plt.xlabel('eastward wind velocity ($\\\\tau^{se}$)')\n",
    "plt.ylabel('northward wind velocity ($\\\\tau^{se}$)')\n",
    "plt.title('geographic coordinates')\n",
    "\n",
    "plt.subplot(122)\n",
    "plt.plot(ds['wind_x'],ds['wind_y'],'.')\n",
    "plt.axis('equal')\n",
    "plt.xlabel('velocity in $x$-direction ($\\\\tau^{sx}$)')\n",
    "plt.ylabel('velocity in $y$-direction ($\\\\tau^{sy}$)')\n",
    "plt.title('rotated coordinates')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "-Utzgv_6HAn7"
   },
   "source": [
    "##### Exercise\n",
    "\n",
    "Modify the `rotation_angle` variable above and re-run the analysis. What angle makes the wind stress most aligned along the $y$ axis? What angle makes the wind stress most aligned along the $x$ axis?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "b-WgzucpHAn7"
   },
   "source": [
    "#### Principal axis angle\n",
    "\n",
    "Instead of trial and error, a principal axis analysis can be used to find the angle along which the wind stress is aligned. On the west coast, this typically corresponds with the local coastline. On the east coast, this is not necessarily case.\n",
    "\n",
    "The `princax` function can be used to find the pricipal axis angle. The variance of the data is maximized along this axis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "id": "35josaYjHAn8"
   },
   "outputs": [],
   "source": [
    "def princax(u,v=None):\n",
    "    '''\n",
    "Principal axes of a vector time series.\n",
    "Usage:\n",
    "theta,major,minor = princax(u,v) # if u and v are real-valued vector components\n",
    "    or\n",
    "theta,major,minor = princax(w)   # if w is a complex vector\n",
    "Input:\n",
    "u,v - 1-D arrays of vector components (e.g. u = eastward velocity, v = northward velocity)\n",
    "    or\n",
    "w - 1-D array of complex vectors (u + 1j*v)\n",
    "Output:\n",
    "theta - angle of major axis (math notation, e.g. east = 0, north = 90)\n",
    "major - standard deviation along major axis\n",
    "minor - standard deviation along minor axis\n",
    "Reference: Emery and Thomson, 2001, Data Analysis Methods in Physical Oceanography, 2nd ed., pp. 325-328.\n",
    "Matlab function: http://woodshole.er.usgs.gov/operations/sea-mat/RPSstuff-html/princax.html\n",
    "    '''\n",
    "\n",
    "    # if one input only, decompose complex vector\n",
    "    if v is None:\n",
    "        w = np.copy(u)\n",
    "        u = np.real(w)\n",
    "        v = np.imag(w)\n",
    "\n",
    "    # only use finite values for covariance matrix\n",
    "    ii = np.isfinite(u+v)\n",
    "    uf = u[ii]\n",
    "    vf = v[ii]\n",
    "\n",
    "    # compute covariance matrix\n",
    "    C = np.cov(uf,vf)\n",
    "\n",
    "    # calculate principal axis angle (ET, Equation 4.3.23b)\n",
    "    theta = 0.5*np.arctan2(2.*C[0,1],(C[0,0] - C[1,1])) * 180/np.pi\n",
    "\n",
    "    # calculate variance along major and minor axes (Equation 4.3.24)\n",
    "    term1 = C[0,0] + C[1,1]\n",
    "    term2 = ((C[0,0] - C[1,1])**2 + 4*(C[0,1]**2))**0.5\n",
    "    major = np.sqrt(0.5*(term1 + term2))\n",
    "    minor = np.sqrt(0.5*(term1 - term2))\n",
    "\n",
    "    return theta,major,minor"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "IyszXTExHAoA"
   },
   "source": [
    "Use this function on the wind stress data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "id": "2a7JXAD8HAoA"
   },
   "outputs": [],
   "source": [
    "theta,major,minor = princax(ds['wind_east'],ds['wind_north'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "sj3NHoKHHAoD"
   },
   "source": [
    "Rotate the wind data based on the principal axis angle. Note that it is common among oceanographers on the west coast to align the alongshore coordinate with the $y$-axis, but this is up to you."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "id": "yaV3jPOeHAoE"
   },
   "outputs": [],
   "source": [
    "ds['wind_x'],ds['wind_y'] = rot(ds['wind_east'],ds['wind_north'],-theta-90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 316
    },
    "id": "pP-JBb9ZHAoG",
    "outputId": "5a86fac4-4a2f-4f90-c0ef-b8b300255840"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'rotated coordinates')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(ds['wind_x'],ds['wind_y'],'.')\n",
    "plt.axis('equal')\n",
    "plt.xlabel('velocity in $x$-direction ($\\\\tau^{sx}$)')\n",
    "plt.ylabel('velocity in $y$-direction ($\\\\tau^{sy}$)')\n",
    "plt.title('rotated coordinates')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_En7hQ2FHAoJ"
   },
   "source": [
    "Plot the time series. The negative values of the alongshore wind stress ($\\tau^{sy}$) indicate upwelling-favorable winds. The positive values indicate downwelling favorable winds."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 298
    },
    "id": "d-T9yxb1HAoK",
    "outputId": "a66b7d1f-23e4-4463-cd75-9e52b2473ca0"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fb47691abb0>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,4))\n",
    "plt.plot(ds['time'],ds['wind_x'])\n",
    "plt.plot(ds['time'],ds['wind_y'])\n",
    "plt.ylabel('[N/m$^2$]')\n",
    "plt.title('wind stress')\n",
    "plt.legend(['$\\\\tau^{sx}$','$\\\\tau^{sy}$'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "qEm-jSI_HAoO"
   },
   "source": [
    "##### Exercise\n",
    "\n",
    "Apply this same analysis to another NDBC buoy on the west coast. \n",
    "\n",
    "* Find the buoy ID number using the map interface at https://www.ndbc.noaa.gov/\n",
    "* In the `ncfile` variable above, replace 46042 with the new buoy ID number.\n",
    "* Identify a time when the wind is favorable for upwelling.\n",
    "* What rotation angle did you use?"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "include_colab_link": true,
   "name": "NDBC-wind-analysis.ipynb",
   "provenance": [],
   "toc_visible": true
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}