{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# MHKiT Metocean Data\n", "\n", "Metocean data is a useful addition to wave and current ocean data for the design for offshore structures, including wave energy converters (WECs). Metocean data primarily includes information pertaining to the wind, wave, and climate conditions within and over the ocean at a given location.\n", "\n", "MHKiT's `wave.io.ndbc` module includes functions to request and manipulate metocean data from the National Data Buoy Center, including spectral wave density, standard meteorological data and continuous wind speed. The `wave.io.hindcast.wind_toolkit` module includes function to request and manipulate metocean data from the WIND Toolkit datasets including precipitation rate, relative humidity and vertical profiles of wind speed, wind direction, precipitation, temperature, and pressure.\n", "\n", "As a demonstration, this notebook will walk through the following steps to compare the surface wind speed and direction at a given location using both NDBC and WIND Toolkit data, and then plot a vertical air temperature profile with WIND Toolkit data.\n", "\n", " 1. Request Continous Wind Data from NDBC\n", " 2. Request Surface Wind Data from WIND Toolkit\n", " 3. Compare NDBC and WIND Toolkit Data\n", " 4. Request Temperature Data from WIND Toolkit\n", " 5. Visualize Temperature Data\n", "\n", "We will start by importing the necessary python packages (`pandas`, `numpy`, `matplotlib`), and MHKiT submodule (`wave.io`)." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "from mhkit.wave.io import ndbc\n", "from mhkit.wave.io.hindcast import wind_toolkit\n", "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 1. Request Continuous Wind Data from NDBC\n", " \n", "MHKiT can be used to request historical data from the National Data Buoy Center ([NDBC](https://www.ndbc.noaa.gov/)). This process is split into the following steps:\n", "\n", "- Query available NDBC data \n", "- Select years of interest \n", "- Request data from NDBC\n", "- Convert the DataFrames to DateTime Index\n", " \n", "\n", "### Query available NDBC data \n", "Looking at the help for the `ndbc.available_data` function (`help(ndbc.available_data)`) the function requires a parameter to be specified and optionally the user may provide a station ID as a string. A full list of available historical parameters can be found [here](https://www.ndbc.noaa.gov/data/historical/) although only some of these are currently supported. We are interested in historical continuous wind data `'cwind'`. Additionally, we will specify the buoy number as `'46022'` to only return data associated with this site." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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idyearfilename
121146022199646022c1996.txt.gz
121246022199746022c1997.txt.gz
121346022199846022c1998.txt.gz
121446022199946022c1999.txt.gz
121546022200046022c2000.txt.gz
121646022200146022c2001.txt.gz
121746022200246022c2002.txt.gz
121846022200346022c2003.txt.gz
121946022200446022c2004.txt.gz
122046022200546022c2005.txt.gz
122146022200646022c2006.txt.gz
122246022200746022c2007.txt.gz
122346022200846022c2008.txt.gz
122446022200946022c2009.txt.gz
122546022201046022c2010.txt.gz
122646022201146022c2011.txt.gz
122746022201246022c2012.txt.gz
122846022201346022c2013.txt.gz
122946022201446022c2014.txt.gz
123046022201546022c2015.txt.gz
123146022201646022c2016.txt.gz
123246022201746022c2017.txt.gz
123346022201846022c2018.txt.gz
\n", "
" ], "text/plain": [ " id year filename\n", "1211 46022 1996 46022c1996.txt.gz\n", "1212 46022 1997 46022c1997.txt.gz\n", "1213 46022 1998 46022c1998.txt.gz\n", "1214 46022 1999 46022c1999.txt.gz\n", "1215 46022 2000 46022c2000.txt.gz\n", "1216 46022 2001 46022c2001.txt.gz\n", "1217 46022 2002 46022c2002.txt.gz\n", "1218 46022 2003 46022c2003.txt.gz\n", "1219 46022 2004 46022c2004.txt.gz\n", "1220 46022 2005 46022c2005.txt.gz\n", "1221 46022 2006 46022c2006.txt.gz\n", "1222 46022 2007 46022c2007.txt.gz\n", "1223 46022 2008 46022c2008.txt.gz\n", "1224 46022 2009 46022c2009.txt.gz\n", "1225 46022 2010 46022c2010.txt.gz\n", "1226 46022 2011 46022c2011.txt.gz\n", "1227 46022 2012 46022c2012.txt.gz\n", "1228 46022 2013 46022c2013.txt.gz\n", "1229 46022 2014 46022c2014.txt.gz\n", "1230 46022 2015 46022c2015.txt.gz\n", "1231 46022 2016 46022c2016.txt.gz\n", "1232 46022 2017 46022c2017.txt.gz\n", "1233 46022 2018 46022c2018.txt.gz" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Specify the parameter as continuous wind speeds and the buoy number to be 46022\n", "ndbc_dict = {'parameter':'cwind','buoy_number':'46022'} \n", "available_data = ndbc.available_data(ndbc_dict['parameter'], ndbc_dict['buoy_number'])\n", "available_data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Select years of interest\n", "\n", "The `ndbc.available_data` function has returned a DataFrame with columns 'id', 'year', and 'filename'. The year column is of type int while the filename and id (5 digit alpha-numeric specifier) are of type string. In this case, the years returned from `available_data` span 1996 to the last year the buoy was operational (currently 2018 for 46022 wind data). For demonstration, we have decided we are interested in the data from 2018, so we will create a new `years_of_interest` DataFrame which only contains the year 2018." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/html": [ "
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idyearfilename
123346022201846022c2018.txt.gz
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" ], "text/plain": [ " id year filename\n", "1233 46022 2018 46022c2018.txt.gz" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Slice the available data to only include 2018 and more recent\n", "years_of_interest = available_data[available_data.year == 2018]\n", "years_of_interest\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Request Data from NDBC\n", "\n", "The filename column in our `years_of_interest` DataFrame and the parameter is needed to request the data. To get the data we can use the `ndbc.request_data` function for each buoy id and year in the passed DataFrame. This function will return the parameter data as a dictionary of DataFrames which may be accessed by buoy id and then the year for multiple buoys or just the year for a single buoy. " ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'2018': #YY MM DD hh mm WDIR WSPD GDR GST GTIME\n", " 0 2017 12 31 23 0 206 7.8 999 99.0 9999\n", " 1 2017 12 31 23 10 202 8.3 999 99.0 9999\n", " 2 2017 12 31 23 20 199 8.2 999 99.0 9999\n", " 3 2017 12 31 23 30 194 7.6 999 99.0 9999\n", " 4 2017 12 31 23 40 188 6.6 999 99.0 9999\n", " ... ... .. .. .. .. ... ... ... ... ...\n", " 18319 2018 5 8 16 10 107 0.9 999 99.0 9999\n", " 18320 2018 5 8 16 20 210 0.3 999 99.0 9999\n", " 18321 2018 5 8 16 30 271 1.1 999 99.0 9999\n", " 18322 2018 5 8 16 40 275 1.4 999 99.0 9999\n", " 18323 2018 5 8 16 50 277 1.4 281 2.4 1642\n", " \n", " [18324 rows x 10 columns]}" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Get dictionary of parameter data by year\n", "ndbc_dict['filenames'] = years_of_interest['filename']\n", "requested_data = ndbc.request_data(ndbc_dict['parameter'], ndbc_dict['filenames'])\n", "requested_data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Convert the DataFrames to DateTime Index\n", "\n", "The data returned for each year has a variable number of columns for the year, month, day, hour, minute, and the way the columns are formatted (this is a primary reason for return a dictionary of DataFrames indexed by years). A common step a user will want to take is to remove the inconsistent NDBC date/ time columns and create a standard DateTime index. The MHKiT function `ndbc.to_datetime_index` will perform this standardization by parsing the NDBC date/ time columns into DateTime format and setting this as the DataFrame Index and removing the NDBC date/ time columns. This function operates on a DateFrame therefore we will only pass the relevant year of the `ndbc_requested_data` dictionary.\n", "\n", "Additionally, NDBC uses '99', '999', and '9999' as NaN values. We will replace these values with `numpy.NaN` to prevent errors when manipulating the data." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/html": [ "
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WDIRWSPDGDRGSTGTIME
date
2017-12-31 23:00:00206.07.8NaNNaNNaN
2017-12-31 23:10:00202.08.3NaNNaNNaN
2017-12-31 23:20:00199.08.2NaNNaNNaN
2017-12-31 23:30:00194.07.6NaNNaNNaN
2017-12-31 23:40:00188.06.6NaNNaNNaN
..................
2018-05-08 16:10:00107.00.9NaNNaNNaN
2018-05-08 16:20:00210.00.3NaNNaNNaN
2018-05-08 16:30:00271.01.1NaNNaNNaN
2018-05-08 16:40:00275.01.4NaNNaNNaN
2018-05-08 16:50:00277.01.4281.02.41642.0
\n", "

18324 rows × 5 columns

\n", "
" ], "text/plain": [ " WDIR WSPD GDR GST GTIME\n", "date \n", "2017-12-31 23:00:00 206.0 7.8 NaN NaN NaN\n", "2017-12-31 23:10:00 202.0 8.3 NaN NaN NaN\n", "2017-12-31 23:20:00 199.0 8.2 NaN NaN NaN\n", "2017-12-31 23:30:00 194.0 7.6 NaN NaN NaN\n", "2017-12-31 23:40:00 188.0 6.6 NaN NaN NaN\n", "... ... ... ... ... ...\n", "2018-05-08 16:10:00 107.0 0.9 NaN NaN NaN\n", "2018-05-08 16:20:00 210.0 0.3 NaN NaN NaN\n", "2018-05-08 16:30:00 271.0 1.1 NaN NaN NaN\n", "2018-05-08 16:40:00 275.0 1.4 NaN NaN NaN\n", "2018-05-08 16:50:00 277.0 1.4 281.0 2.4 1642.0\n", "\n", "[18324 rows x 5 columns]" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Convert the header dates to a Datetime Index and remove NOAA date columns for each year\n", "ndbc_dict['2018'] = ndbc.to_datetime_index(ndbc_dict['parameter'], requested_data['2018'])\n", "\n", "# Replace 99, 999, 9999 with NaN\n", "ndbc_dict['2018'] = ndbc_dict['2018'].replace({99.0:np.NaN, 999:np.NaN, 9999:np.NaN})\n", "\n", "# Display DataFrame of 46022 data from 2018\n", "ndbc_dict['2018']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2. Request Surface Wind Data from WIND Toolkit\n", "\n", "MHKiT can be used to request historical data from [WIND Toolkit](https://www.nrel.gov/grid/wind-toolkit.html). The WIND Toolkit is a high-spatial-resolution dataset of meteorological parameters covering several offshore regions including California, Hawaii, the Northwest Pacific, and the Mid-Atlantic. The offshore datasets span 2000-2019 (or to 2020 for the Mid-Atlantic region). \n", "\n", "\n", "### Included Variables: \n", "- Dataset variables included are indexed by **'lat_lon'** (latitude and longitude), and a **'time_interval'**. The following variables can be accessed through the `request_wtk_point_data` function and are available at both '5-minute' and '1-hour' time intervals and in all offshore regions:\n", "\n", "| Variable Name | Units | Height(s) above sea level (m) |\n", "| :------------ | :---: | :--------: |\n", "| Precipitation rate | mm | 0 |\n", "| Roughness length| meters | none |\n", "| Sea surface temperature | degrees Celsius | none |\n", "| Inverse Monin-Obukhov length | per meter | 2 |\n", "| Relative humidity | % | 2 |\n", "| Friction velocity | meters per second | 2 |\n", "| Wind speed | meters per second | 10, 20, 40, 60, 80, 100, 120, 140, 160, 180, 200 |\n", "| Wind direction | degrees true | 10, 20, 40, 60, 80, 100, 120, 140, 160, 180, 200 |\n", "| Temperature | degrees Celsius | 2, 10, 20, 40, 60, 80, 100, 120, 140, 160, 180, 200 |\n", "| Pressure | meters | 0, 100, 200 |\n", "\n", "### Setting up Access to WIND Toolkit\n", "To access the WIND Toolkit, you will need to configure h5pyd for data access on HSDS. \n", "To get your own API key, visit https://developer.nrel.gov/signup/. \n", "If you have already accessed WPTO Hindcast data, you may skip this step.\n", "\n", "To configure h5phd type:\n", "\n", " hsconfigure\n", " \n", "and enter at the prompt:\n", "\n", " hs_endpoint = https://developer.nrel.gov/api/hsds\n", " hs_username = None\n", " hs_password = None\n", " hs_api_key = {your key}\n", "\n", " \n", "## Using the WIND Toolkit MHKiT Functions\n", "The process of obtaining and manipulating WIND Toolkit data with MHKiT is split into the following steps:\n", "- Choose input parameters \n", "- Request data from WIND Toolkit\n", "\n", "### Choose input parameters\n", "Looking at the help for the `wind_toolkit.request_wtk_point_data` function shows four required input parameters:\n", "* time interval\n", "* parameter\n", "* location\n", "* year\n", "\n", "A full list of available historical parameters can be found [here](https://github.com/NREL/hsds-examples/blob/master/datasets/WINDToolkit.md#model). Here we are interested in historical surface wind data `'windspeed_10m'`, `'winddirection_10m'`. Additionally, we will use the latitude and longitude of NDBC buoy `'46022'` to later compare to the NDBC dataset. The buoy location can be found [here](https://www.ndbc.noaa.gov/data/stations/station_table.txt). The `elevation_to_string` can be used to easily combine an array of elevations with a parameter name to create the correctly formatted parameter string. This is demonstrated for the array of temperature parameters." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "['temperature_2m',\n", " 'temperature_20m',\n", " 'temperature_40m',\n", " 'temperature_60m',\n", " 'temperature_80m',\n", " 'temperature_100m',\n", " 'temperature_120m',\n", " 'temperature_140m',\n", " 'temperature_160m']" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Input parameters for site of interest\n", "temperatures = wind_toolkit.elevation_to_string('temperature',[2, 20, 40, 60, 80, 100, 120, 140, 160])\n", "temperatures" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "wtk_inputs = {'time_interval':'1-hour',\n", " 'wind_parameters':['windspeed_10m','winddirection_10m'],\n", " 'temp_parameters':temperatures,\n", " 'year':[2018],\n", " 'lat_lon':(40.748, -124.527)}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Visualize WIND Toolkit Region\n", "The offshore WIND Toolkit contains four possible regions, each corresponding to separate hindcast simulations: \"Offshore_CA\", \"Hawaii\", \"NW_Pacific\", \"Mid_Atlantic\". This is automatically determined by MHKiT based on the user-defined latitude-longitude pair. Note that the \"NW_Pacific\" and \"Offshore_CA\" region overlap. If you desire to use a location in this overlap region, you must specify the preferred region when calling `request_wtk_point_data`. \n", "\n", "If you are unsure of the appropriate region, `region_selection` function will return the region that a given latitude-longitude pair corresponds to. MHKiT also provides the `plot_region` function so that users can visualize where their chosen latitude-longitude pair lies in a given region. Note that regions are not rectangular on a latitude-longitude grid. Comparing the location and region is recommended before requesting data. These functions are demonstrated here." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'Offshore_CA'" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "requested_region = wind_toolkit.region_selection(wtk_inputs['lat_lon'])\n", "requested_region" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "wind_toolkit.plot_region(requested_region,lat_lon=wtk_inputs['lat_lon'])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Request data from the WIND Toolkit\n", "To get the data we can use the `wind_toolkit.request_wtk_point_data` function with multiple parameters, locations and years. If multiple locations are input, they must correspond to the same hindcast region. If multiple parameters are input they must be available for the same time interval. \n", "\n", "This function will return the parameter data as a DataFrame which may be accessed by parameter name and index of the location. Here we only use the single location defined above, so the relevant DataFrame key is `'wind_speed_10m_0'`. " ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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windspeed_10m_0winddirection_10m_0
time_index
2018-01-01 00:00:00+00:007.78179.199997
2018-01-01 01:00:00+00:007.81190.649994
2018-01-01 02:00:00+00:006.89191.690002
2018-01-01 03:00:00+00:007.58190.720001
2018-01-01 04:00:00+00:008.10183.199997
.........
2018-12-31 19:00:00+00:0015.04359.070007
2018-12-31 20:00:00+00:0014.59358.470001
2018-12-31 21:00:00+00:0014.76358.489990
2018-12-31 22:00:00+00:0014.41358.269989
2018-12-31 23:00:00+00:0014.34359.769989
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8760 rows × 2 columns

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" ], "text/plain": [ " windspeed_10m_0 winddirection_10m_0\n", "time_index \n", "2018-01-01 00:00:00+00:00 7.78 179.199997\n", "2018-01-01 01:00:00+00:00 7.81 190.649994\n", "2018-01-01 02:00:00+00:00 6.89 191.690002\n", "2018-01-01 03:00:00+00:00 7.58 190.720001\n", "2018-01-01 04:00:00+00:00 8.10 183.199997\n", "... ... ...\n", "2018-12-31 19:00:00+00:00 15.04 359.070007\n", "2018-12-31 20:00:00+00:00 14.59 358.470001\n", "2018-12-31 21:00:00+00:00 14.76 358.489990\n", "2018-12-31 22:00:00+00:00 14.41 358.269989\n", "2018-12-31 23:00:00+00:00 14.34 359.769989\n", "\n", "[8760 rows x 2 columns]" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "wtk_wind, wtk_metadata = wind_toolkit.request_wtk_point_data(\n", " wtk_inputs['time_interval'],wtk_inputs['wind_parameters'],\n", " wtk_inputs['lat_lon'],wtk_inputs['year'])\n", "wtk_wind" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 3. Compare NDBC and WIND Toolkit Data\n", "\n", "Wind conditions may be characterized by the speed and direction over a day. A hourly time series of wind speed is a useful way of visualizing the diurnal variation on a give date. A wind rose can visualize variation in wind direction over the same period. Using the historical continuous wind data from NDBC and surface wind data from WIND Toolkit, we can calculate these variables in MHKiT. \n", "\n", "### Plot the hourly mean wind speeds on January 11, 2018\n", "The NDBC data for January 11, 2018 is given in 10 minute intervals. We can get the instantaneous hourly wind data using the DataFrame `resample().nearest()` function. The WIND Toolkit data is already given as instantaneous hourly data. Then, we can plot the speeds vs the hour they occur. Some variation is seen due to difference in method and height." ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Get WIND Toolkit and NDBC wind data for 2018-01-11\n", "ndbc_hourly_data = ndbc_dict['2018']['2018-01-11'].resample('h').nearest()\n", "wtk_hourly_wind = wtk_wind['2018-01-11']\n", "\n", "# Plot the timeseries\n", "fig = plt.figure()\n", "ax = fig.add_subplot(111)\n", "ax.set_xlabel('Time, UTC (h)')\n", "ax.set_ylabel('Speed (m/s)')\n", "ax.set_title('Hourly mean wind speeds on January 11, 2018')\n", "ax.grid()\n", "ax.set_ylim([5, 14])\n", "ax.set_xlim([0, 24])\n", "line1 = ax.plot(ndbc_hourly_data.index.hour,ndbc_hourly_data['WSPD'].values,'o',label='NDBC 4m wind speed')\n", "line2 = ax.plot(wtk_hourly_wind.index.hour,wtk_hourly_wind['windspeed_10m_0'].values,'x',label='WIND Toolkit 10m wind speed')\n", "ax.legend()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Create a mean wind speed wind rose for January 11, 2018\n", "To complement the timeseries of wind speed, we can visualize the variation in wind direction over the day with a wind rose. The MHKiT `plot_rose` function will do this for us. Some variation is seen between NDBC and WIND Toolkit, possibly due to method and height. Users can further investigate different source of metocean data as desired." ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "scrolled": true }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Set the rose bin widths\n", "width_direction = 10 # in degrees\n", "width_velocity = 1 # in m/s\n", "\n", "# Plot the wind rose\n", "ax = ndbc.plot_rose(ndbc_hourly_data['WDIR'],ndbc_hourly_data['WSPD'],\n", " width_direction,width_velocity)\n" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "scrolled": true }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "ax2 = ndbc.plot_rose(wtk_hourly_wind['winddirection_10m_0'],wtk_hourly_wind['windspeed_10m_0'],\n", " width_direction,width_velocity)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Plot vertical temperature profile\n", "The air temperature at several vertical levels can be downloaded from the WIND Toolkit dataset. More or less vertical levels can be defined in the parameter input to `request_wtk_point_data` to increase resolution or decrease computation expense as desired. Note that times are given in UTC, can can optionally be converted to local time by finding the time zone of the chosen latitude/longitude pair. " ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "WARNING:urllib3.connectionpool:Retrying (Retry(total=6, connect=10, read=10, redirect=None, status=None)) after connection broken by 'ProxyError('Cannot connect to proxy.', ConnectionResetError(10054, 'An existing connection was forcibly closed by the remote host', None, 10054, None))': /api/hsds/datasets/d-bf1ee746-f22af1ee-ce40-863b0e-18a71b?domain=%2Fnrel%2Fwtk%2Foffshore_ca%2FOffshore_CA_2018.h5&api_key=x9f0SNincVSAIeKKuGDUOhyvfRYmrTzg06vZyeuw\n", "WARNING:urllib3.connectionpool:Retrying (Retry(total=6, connect=10, read=10, redirect=None, status=None)) after connection broken by 'ProxyError('Cannot connect to proxy.', ConnectionResetError(10054, 'An existing connection was forcibly closed by the remote host', None, 10054, None))': /api/hsds/datasets/d-bf1ee746-f22af1ee-3ec7-709e83-7740a7?domain=%2Fnrel%2Fwtk%2Foffshore_ca%2FOffshore_CA_2018.h5&api_key=x9f0SNincVSAIeKKuGDUOhyvfRYmrTzg06vZyeuw\n", "WARNING:urllib3.connectionpool:Retrying (Retry(total=4, connect=10, read=10, redirect=None, status=None)) after connection broken by 'ProxyError('Cannot connect to proxy.', ConnectionResetError(10054, 'An existing connection was forcibly closed by the remote host', None, 10054, None))': /api/hsds/datasets/d-bf1ee746-f22af1ee-8082-2ff043-910c51?domain=%2Fnrel%2Fwtk%2Foffshore_ca%2FOffshore_CA_2018.h5&api_key=x9f0SNincVSAIeKKuGDUOhyvfRYmrTzg06vZyeuw\n" ] }, { "data": { "text/plain": [ "" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "wtk_temp, wtk_metadata = wind_toolkit.request_wtk_point_data(\n", " wtk_inputs['time_interval'],wtk_inputs['temp_parameters'],\n", " wtk_inputs['lat_lon'],wtk_inputs['year'])\n", "# wtk_temp = wtk_temp.shift(-7) # optionally UTC to local time\n", "\n", "# Pick times corresponding to stable and unstable temperature profiles \n", "stable_temp = wtk_temp.at_time('2018-01-11 03:00:00').values[0]\n", "unstable_temp = wtk_temp.at_time('2018-01-11 15:00:00').values[0]\n", "\n", "# Find heights from temperature DataFrame columns\n", "heights = []\n", "for s in wtk_temp.keys():\n", " s = s.removeprefix('temperature_')\n", " s = s.removesuffix('m_0')\n", " heights.append(float(s))\n", "heights = np.array(heights)\n", "\n", "# Plot the profiles\n", "fig = plt.figure()\n", "ax = fig.add_subplot(111)\n", "ax.set_xlabel('Temperature (C)')\n", "ax.set_ylabel('Height (m)')\n", "ax.set_title('Temperature profiles from January 11, 2018')\n", "ax.grid()\n", "line1 = ax.plot(stable_temp,heights,'o-',label='time=03:00:00 UTC')\n", "line2 = ax.plot(unstable_temp,heights,'x-',label='time=15:00:00 UTC')\n", "ax.legend()" ] } ], "metadata": { "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": "3.9.12" } }, "nbformat": 4, "nbformat_minor": 4 }