forked from 3rdparty/wrf-python
Bill Ladwig
9 years ago
22 changed files with 2083 additions and 93 deletions
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.. _diagnostic-table: |
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Table of Available Diagnostics |
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================================= |
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.. include:: _templates/product_table.txt |
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Installation |
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============ |
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Required Dependencies |
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---------------------- |
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- Python 2.7, 3.4, or 3.5 |
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- numpy (1.9 or later) |
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- wrapt (1.10 or later) |
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Highly Recommended Packages |
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---------------------------- |
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- xarray (0.7.0 or later) |
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- PyNIO (1.4.3 or later) |
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- netCDF4-python (1.2.0 or later) |
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Plotting Packages |
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------------------------- |
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- PyNGL (1.4.3 or later) |
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- matplotlib (1.4.3 or later) |
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- cartopy (0.13 or later) |
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- basemap (1.0.8 or later) |
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Installing via Conda |
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--------------------- |
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The easiest way to install wrf-python is using |
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`Conda <http://conda.pydata.org/docs/>`_:: |
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$ conda install -c bladwig wrf-python |
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Installing via Source Code |
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-------------------------- |
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Installation via source code will require a Fortran and C compiler in order |
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to run f2py. You can get them |
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`here <https://gcc.gnu.org/wiki/GFortranBinaries>`_. |
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The source code is available via github: |
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https://github.com/NCAR/wrf-python |
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To install, change to the wrf-python directory and run:: |
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$ pip install . |
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What's New |
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=========== |
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v1.0a3 |
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----------- |
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- Alpha release 3 |
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- Added docstrings |
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- Now uses CoordPair for cross sections so that lat/lon can be used |
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- Renamed some functions and or arguments |
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Plotting Examples |
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================= |
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The examples below show how wrf-python can be used to make plots with |
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matplotlib (with basemap and cartopy) and PyNGL. None of these examples |
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make use of xarray's builtin plotting functions, since additional work is most |
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likely needed to extend xarray in order to work correctly. This is planned |
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for a future release. |
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Matplotlib With Cartopy |
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------------------------- |
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Cartopy is becoming the main tool for base mapping with matplotlib, but you should |
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be aware of a few shortcomings when working with WRF data. |
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- The builtin tranformations of coordinates when calling the contouring functions |
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do not work correctly with the rotated pole projection. The |
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transform_points method needs to be called manually on the latitude and |
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longitude arrays. |
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- The rotated pole projection requires the x and y limits to be set manually |
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using set_xlim and set_ylim. |
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- You can't place latitude and longitude labels on the axes when using |
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any projection other than Mercator or LatLon. |
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Plotting a Two-dimensional Field |
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ |
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.. image:: _static/images/cartopy_slp.png |
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:scale: 100% |
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:align: center |
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.. code-block:: python |
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from __future__ import (absolute_import, division, print_function, unicode_literals) |
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from netCDF4 import Dataset |
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import matplotlib.pyplot as plt |
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from matplotlib.cm import get_cmap |
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import cartopy.crs as crs |
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from cartopy.feature import NaturalEarthFeature |
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from wrf import npvalues, getvar, smooth2d |
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ncfile = Dataset("wrfout_d01_2016-10-07_00_00_00") |
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# Get the sea level pressure |
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slp = getvar(ncfile, "slp") |
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# Smooth the sea level pressure since it tends to be noisy near the mountains |
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smooth_slp = smooth2d(slp, 3) |
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# Get the numpy array from the XLAT and XLONG coordinates |
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lats = npvalues(slp.coords["XLAT"]) |
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lons = npvalues(slp.coords["XLONG"]) |
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# Get the wrf.WrfProj object |
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wrf_proj = slp.attrs["projection"] |
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# The WrfProj.cartopy() method returns a cartopy.crs projection object |
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cart_proj = wrf_proj.cartopy() |
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# Create a figure that's 10x10 |
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fig = plt.figure(figsize=(10,10)) |
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# Get the GeoAxes set to the projection used by WRF |
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ax = plt.axes(projection=cart_proj) |
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# Download and add the states and coastlines |
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states = NaturalEarthFeature(category='cultural', scale='50m', facecolor='none', |
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name='admin_1_states_provinces_shp') |
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ax.add_feature(states, linewidth=.5) |
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ax.coastlines('50m', linewidth=0.8) |
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# Make the contour outlines and filled contours for the smoothed sea level pressure. |
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# The transform keyword indicates that the lats and lons arrays are lat/lon coordinates and tells |
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# cartopy to transform the points in to the WRF projection set for the GeoAxes. |
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plt.contour(lons, lats, npvalues(smooth_slp), 10, colors="black", transform=crs.PlateCarree()) |
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plt.contourf(lons, lats, npvalues(smooth_slp), 10, transform=crs.PlateCarree()) |
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# Add a color bar |
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plt.colorbar(ax=ax, shrink=.47) |
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# Set the map limits |
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ax.set_xlim(wrf_proj.cartopy_xlim()) |
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ax.set_ylim(wrf_proj.cartopy_ylim()) |
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# Add the gridlines |
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ax.gridlines() |
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{ |
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"cells": [ |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"metadata": { |
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"collapsed": true |
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}, |
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"outputs": [], |
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"source": [ |
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"%matplotlib inline" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"metadata": { |
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"collapsed": false |
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}, |
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"outputs": [], |
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"source": [ |
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"from __future__ import (absolute_import, division, print_function, unicode_literals)\n", |
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"\n", |
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"import numpy as np\n", |
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"import matplotlib.pyplot as plt\n", |
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"from matplotlib.cm import get_cmap\n", |
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"import cartopy.crs as crs\n", |
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"import cartopy.feature as cfeature\n", |
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"from netCDF4 import Dataset as nc\n", |
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"\n", |
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"from wrf import npvalues, getvar, smooth2d\n", |
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"\n", |
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"# Open the output NetCDF with netcdf-python\n", |
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"filename = \"/Users/ladwig/Documents/wrf_files/wrfout_d01_2016-10-07_00_00_00\"\n", |
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"ncfile = nc(filename)\n", |
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"\n", |
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"# Get sea level pressure and cloud top temperature\n", |
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"slp = getvar(ncfile, \"slp\")\n", |
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"ctt = getvar(ncfile, \"ctt\")\n", |
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"\n", |
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"# Smooth the SLP\n", |
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"smooth_slp = smooth2d(slp, 3)\n", |
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"\n", |
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"# Extract the latitude and longitude coordinate arrays as regular numpy array instead of xarray.DataArray\n", |
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"lons = npvalues(slp.coords[\"XLONG\"])\n", |
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"lats = npvalues(slp.coords[\"XLAT\"])\n", |
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"\n", |
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"# Get the cartopy projection class\n", |
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"wrf_proj = slp.attrs[\"projection\"]\n", |
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"cart_proj = wrf_proj.cartopy()\n", |
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"\n", |
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"# Create the figure\n", |
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"fig = plt.figure(figsize=(4,4))\n", |
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"ax = plt.axes([0.1,0.1,0.8,0.8], projection=cart_proj)\n", |
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"\n", |
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"# Download and create the states, land, and oceans using cartopy features\n", |
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"states = cfeature.NaturalEarthFeature(category='cultural', scale='50m', facecolor='none',\n", |
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" name='admin_1_states_provinces_shp')\n", |
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"land = cfeature.NaturalEarthFeature(category='physical', name='land', scale='50m', \n", |
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" facecolor=cfeature.COLORS['land'])\n", |
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"ocean = cfeature.NaturalEarthFeature(category='physical', name='ocean', scale='50m', \n", |
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" facecolor=cfeature.COLORS['water'])\n", |
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"\n", |
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"# Make the pressure contours.\n", |
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"contour_levels = [960, 965, 970, 975, 980, 990]\n", |
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"c1 = plt.contour(lons, lats, npvalues(smooth_slp), levels=contour_levels, colors=\"white\", \n", |
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" transform=crs.PlateCarree(), zorder=3, linewidths=1.0)\n", |
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"\n", |
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"# Add pressure contour labels\n", |
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"#plt.clabel(c1, contour_levels, inline=True, fmt='%.0f', fontsize=7)\n", |
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"\n", |
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"# Create the filled cloud top temperature contours\n", |
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"contour_levels = [-80, -70, -60, -50, -40, -30, -20, -10, 0, 10]\n", |
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"plt.contourf(lons, lats, npvalues(ctt), contour_levels, cmap=get_cmap(\"Greys\"),\n", |
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" transform=crs.PlateCarree(), zorder=2)\n", |
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"\n", |
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"plt.plot([-80,-77.8], [26.75,26.75], color=\"yellow\", marker=\"o\", transform=crs.PlateCarree(), zorder=3)\n", |
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"\n", |
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"# Create the label bar for cloud top temperature\n", |
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"#cb2 = plt.colorbar(ax=ax, fraction=0.046, pad=0.04)\n", |
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"cb2 = plt.colorbar(ax=ax)\n", |
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"\n", |
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"# Draw the oceans, land, and states\n", |
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"ax.add_feature(ocean)\n", |
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"ax.add_feature(land)\n", |
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"ax.add_feature(states, linewidth=.5, edgecolor=\"black\")\n", |
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"\n", |
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"# Crop the domain to the region around the hurricane\n", |
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"ax.set_extent([-85., -75.0, np.amin(lats), 30.0], crs=crs.PlateCarree())\n", |
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"ax.gridlines(crs=crs.PlateCarree(), draw_labels=False)\n", |
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"\n", |
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"# Add the title and show the image\n", |
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"#plt.title(\"Hurricane Matthew Cloud Top Temperature (degC) \")\n", |
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"plt.savefig(\"/Users/ladwig/Documents/workspace/wrf_python/doc/source/_static/images/matthew.png\",\n", |
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" transparent=True, bbox_inches=\"tight\")\n", |
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"plt.show()\n" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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"execution_count": null, |
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"metadata": { |
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"collapsed": false |
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}, |
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"outputs": [], |
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"source": [ |
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"%matplotlib inline\n", |
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"\n", |
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"from __future__ import (absolute_import, division, print_function, unicode_literals)\n", |
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"\n", |
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"import numpy as np\n", |
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"import matplotlib.pyplot as plt\n", |
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"from matplotlib.cm import get_cmap\n", |
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"import cartopy.crs as crs\n", |
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"from cartopy.feature import NaturalEarthFeature\n", |
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"from Nio import open_file\n", |
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"\n", |
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"from wrf import npvalues, getvar, smooth2d, ll_to_xy, CoordPair, vertcross, getproj, get_proj_params, to_xy_coords\n", |
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"\n", |
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"# Open the output NetCDF file with PyNIO\n", |
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"filename = \"/Users/ladwig/Documents/wrf_files/wrfout_d01_2016-10-07_00_00_00\"\n", |
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"pynio_filename = filename + \".nc\"\n", |
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"ncfile = open_file(pynio_filename)\n", |
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"\n", |
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"# Extract pressure and model height\n", |
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"z = getvar(ncfile, \"z\", timeidx=0)\n", |
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"dbz = getvar(ncfile, \"dbz\", timeidx=0)\n", |
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"\n", |
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"wspd = getvar(ncfile, \"uvmet_wspd_wdir\", units=\"kt\")[0,:]\n", |
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"Z = 10**(dbz/10.)\n", |
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"\n", |
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"start_point = CoordPair(lat=26.75, lon=-80.0)\n", |
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"end_point = CoordPair(lat=26.75, lon=-77.8)\n", |
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"\n", |
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"# Compute the vertical cross-section interpolation. Also, include the lat/lon points along the cross-section.\n", |
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"z_cross = vertcross(Z, z, wrfin=ncfile, start_point=start_point, end_point=end_point, latlon=True, meta=True)\n", |
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"wspd_cross = vertcross(wspd, z, wrfin=ncfile, start_point=start_point, end_point=end_point, latlon=True, meta=True)\n", |
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"dbz_cross = 10.0 * np.log10(z_cross)\n", |
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"\n", |
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"# Create the figure\n", |
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"fig, axes = plt.subplots(nrows=2, ncols=1, figsize=(4,4))\n", |
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"#ax = plt.axes([0.1,0.1,0.8,0.8])\n", |
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"\n", |
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"# Define the contour levels [0, 50, 100, 150, ....]\n", |
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"levels = [5 + 5*n for n in range(15)]\n", |
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"\n", |
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"# Make the contour plot\n", |
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"a = axes[0].contourf(npvalues(wspd_cross))\n", |
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"# Add the color bar\n", |
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"fig.colorbar(a, ax=axes[0])\n", |
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"\n", |
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"b = axes[1].contourf(npvalues(dbz_cross), levels=levels)\n", |
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"fig.colorbar(b, ax=axes[1])\n", |
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"\n", |
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"# Set the x-ticks to use latitude and longitude labels.\n", |
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"coord_pairs = npvalues(dbz_cross.coords[\"xy_loc\"])\n", |
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"x_ticks = np.arange(coord_pairs.shape[0])\n", |
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"x_labels = [pair.latlon_str() for pair in npvalues(coord_pairs)]\n", |
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"axes[0].set_xticks(x_ticks[::20])\n", |
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"axes[0].set_xticklabels([], rotation=45)\n", |
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"axes[1].set_xticks(x_ticks[::20])\n", |
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"axes[1].set_xticklabels(x_labels[::20], rotation=45, fontsize=6) \n", |
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"\n", |
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"\n", |
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"# Set the y-ticks to be height.\n", |
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"vert_vals = npvalues(dbz_cross.coords[\"vertical\"])\n", |
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"v_ticks = np.arange(vert_vals.shape[0])\n", |
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"axes[0].set_yticks(v_ticks[::20])\n", |
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"axes[0].set_yticklabels(vert_vals[::20], fontsize=6) \n", |
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"axes[1].set_yticks(v_ticks[::20])\n", |
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"axes[1].set_yticklabels(vert_vals[::20], fontsize=6) \n", |
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"\n", |
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"# Set the x-axis and y-axis labels\n", |
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"axes[1].set_xlabel(\"Latitude, Longitude\", fontsize=7)\n", |
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"axes[0].set_ylabel(\"Height (m)\", fontsize=7)\n", |
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"axes[1].set_ylabel(\"Height (m)\", fontsize=7)\n", |
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"\n", |
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"# Add a title\n", |
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"axes[0].set_title(\"Cross-Section of Wind Speed (kt)\", {\"fontsize\" : 10})\n", |
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"axes[1].set_title(\"Cross-Section of Reflectivity (dBZ)\", {\"fontsize\" : 10})\n", |
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"\n", |
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"plt.savefig(\"/Users/ladwig/Documents/workspace/wrf_python/doc/source/_static/images/matthew_cross.png\",\n", |
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" transparent=True, bbox_inches=\"tight\")\n", |
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"plt.show()" |
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] |
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}, |
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{ |
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"cell_type": "code", |
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|
"execution_count": null, |
||||||
|
"metadata": { |
||||||
|
"collapsed": false |
||||||
|
}, |
||||||
|
"outputs": [], |
||||||
|
"source": [ |
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"%matplotlib inline\n", |
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"\n", |
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"from __future__ import (absolute_import, division, print_function, unicode_literals)\n", |
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"\n", |
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"import numpy as np\n", |
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"import matplotlib.pyplot as plt\n", |
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"from matplotlib.cm import get_cmap\n", |
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"import cartopy.crs as crs\n", |
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"import cartopy.feature as cfeature\n", |
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"from Nio import open_file\n", |
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"\n", |
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"from wrf import getvar, npvalues, vertcross, smooth2d, CoordPair\n", |
||||||
|
"\n", |
||||||
|
"# Open the output NetCDF file with PyNIO\n", |
||||||
|
"filename = \"/Users/ladwig/Documents/wrf_files/wrfout_d01_2016-10-07_00_00_00\"\n", |
||||||
|
"pynio_filename = filename + \".nc\"\n", |
||||||
|
"ncfile = open_file(pynio_filename)\n", |
||||||
|
"\n", |
||||||
|
"# Get the WRF variables\n", |
||||||
|
"slp = getvar(ncfile, \"slp\")\n", |
||||||
|
"smooth_slp = smooth2d(slp, 3)\n", |
||||||
|
"ctt = getvar(ncfile, \"ctt\")\n", |
||||||
|
"z = getvar(ncfile, \"z\", timeidx=0)\n", |
||||||
|
"dbz = getvar(ncfile, \"dbz\", timeidx=0)\n", |
||||||
|
"Z = 10**(dbz/10.)\n", |
||||||
|
"wspd = getvar(ncfile, \"uvmet_wspd_wdir\", units=\"kt\")[0,:]\n", |
||||||
|
"\n", |
||||||
|
"# Set the start point and end point for the cross section\n", |
||||||
|
"start_point = CoordPair(lat=26.75, lon=-80.0)\n", |
||||||
|
"end_point = CoordPair(lat=26.75, lon=-77.8)\n", |
||||||
|
"\n", |
||||||
|
"# Compute the vertical cross-section interpolation. Also, include the lat/lon points along the cross-section.\n", |
||||||
|
"z_cross = vertcross(Z, z, wrfin=ncfile, start_point=start_point, end_point=end_point, latlon=True, meta=True)\n", |
||||||
|
"wspd_cross = vertcross(wspd, z, wrfin=ncfile, start_point=start_point, end_point=end_point, latlon=True, meta=True)\n", |
||||||
|
"dbz_cross = 10.0 * np.log10(z_cross)\n", |
||||||
|
"\n", |
||||||
|
"# Extract the latitude and longitude coordinate arrays as regular numpy array instead of xarray.DataArray\n", |
||||||
|
"lons = npvalues(slp.coords[\"XLONG\"])\n", |
||||||
|
"lats = npvalues(slp.coords[\"XLAT\"])\n", |
||||||
|
"\n", |
||||||
|
"# Get the cartopy projection class\n", |
||||||
|
"wrf_proj = slp.attrs[\"projection\"]\n", |
||||||
|
"cart_proj = wrf_proj.cartopy()\n", |
||||||
|
"\n", |
||||||
|
"# Create the figure which will have 3 subplots\n", |
||||||
|
"fig = plt.figure(figsize=(7,5))\n", |
||||||
|
"ax_ctt = fig.add_subplot(1,2,1,projection=cart_proj)\n", |
||||||
|
"ax_wspd = fig.add_subplot(2,2,2)\n", |
||||||
|
"ax_dbz = fig.add_subplot(2,2,4)\n", |
||||||
|
"\n", |
||||||
|
"## Plot the cloud top temperature\n", |
||||||
|
"\n", |
||||||
|
"# Download and create the states, land, and oceans using cartopy features\n", |
||||||
|
"states = cfeature.NaturalEarthFeature(category='cultural', scale='50m', facecolor='none',\n", |
||||||
|
" name='admin_1_states_provinces_shp')\n", |
||||||
|
"land = cfeature.NaturalEarthFeature(category='physical', name='land', scale='50m', \n", |
||||||
|
" facecolor=cfeature.COLORS['land'])\n", |
||||||
|
"ocean = cfeature.NaturalEarthFeature(category='physical', name='ocean', scale='50m', \n", |
||||||
|
" facecolor=cfeature.COLORS['water'])\n", |
||||||
|
"\n", |
||||||
|
"# Make the pressure contours.\n", |
||||||
|
"contour_levels = [960, 965, 970, 975, 980, 990]\n", |
||||||
|
"c1 = ax_ctt.contour(lons, lats, npvalues(smooth_slp), levels=contour_levels, colors=\"white\", \n", |
||||||
|
" transform=crs.PlateCarree(), zorder=3, linewidths=1.0)\n", |
||||||
|
"\n", |
||||||
|
"# Create the filled cloud top temperature contours\n", |
||||||
|
"contour_levels = [-80.0, -70.0, -60, -50, -40, -30, -20, -10, 0, 10]\n", |
||||||
|
"ctt_contours = ax_ctt.contourf(lons, lats, npvalues(ctt), contour_levels, cmap=get_cmap(\"Greys\"),\n", |
||||||
|
" transform=crs.PlateCarree(), zorder=2)\n", |
||||||
|
"\n", |
||||||
|
"ax_ctt.plot([start_point.lon, end_point.lon], [start_point.lat, end_point.lat], color=\"yellow\", \n", |
||||||
|
" marker=\"o\", transform=crs.PlateCarree(), zorder=3)\n", |
||||||
|
"\n", |
||||||
|
"# Create the label bar for cloud top temperature\n", |
||||||
|
"cb_ctt = fig.colorbar(ctt_contours, ax=ax_ctt, shrink=.5)\n", |
||||||
|
"cb_ctt.ax.tick_params(labelsize=5)\n", |
||||||
|
"\n", |
||||||
|
"# Draw the oceans, land, and states\n", |
||||||
|
"ax_ctt.add_feature(ocean)\n", |
||||||
|
"ax_ctt.add_feature(land)\n", |
||||||
|
"ax_ctt.add_feature(states, linewidth=.5, edgecolor=\"black\")\n", |
||||||
|
"\n", |
||||||
|
"# Crop the domain to the region around the hurricane\n", |
||||||
|
"ax_ctt.set_extent([-85., -75.0, np.amin(lats), 30.0], crs=crs.PlateCarree())\n", |
||||||
|
"ax_ctt.gridlines(crs=crs.PlateCarree(), draw_labels=False)\n", |
||||||
|
"\n", |
||||||
|
"## Plot the cross sections\n", |
||||||
|
"\n", |
||||||
|
"# Make the contour plot for wspd\n", |
||||||
|
"wspd_contours = ax_wspd.contourf(npvalues(wspd_cross))\n", |
||||||
|
"# Add the color bar\n", |
||||||
|
"cb_wspd = fig.colorbar(wspd_contours, ax=ax_wspd)\n", |
||||||
|
"cb_wspd.ax.tick_params(labelsize=5)\n", |
||||||
|
"\n", |
||||||
|
"# Make the contour plot for dbz\n", |
||||||
|
"levels = [5 + 5*n for n in range(15)]\n", |
||||||
|
"dbz_contours = ax_dbz.contourf(npvalues(dbz_cross), levels=levels)\n", |
||||||
|
"cb_dbz = fig.colorbar(dbz_contours, ax=ax_dbz)\n", |
||||||
|
"cb_dbz.ax.tick_params(labelsize=5)\n", |
||||||
|
"\n", |
||||||
|
"# Set the x-ticks to use latitude and longitude labels.\n", |
||||||
|
"coord_pairs = npvalues(dbz_cross.coords[\"xy_loc\"])\n", |
||||||
|
"x_ticks = np.arange(coord_pairs.shape[0])\n", |
||||||
|
"x_labels = [pair.latlon_str() for pair in npvalues(coord_pairs)]\n", |
||||||
|
"ax_wspd.set_xticks(x_ticks[::20])\n", |
||||||
|
"ax_wspd.set_xticklabels([], rotation=45)\n", |
||||||
|
"ax_dbz.set_xticks(x_ticks[::20])\n", |
||||||
|
"ax_dbz.set_xticklabels(x_labels[::20], rotation=45, fontsize=4) \n", |
||||||
|
"\n", |
||||||
|
"\n", |
||||||
|
"# Set the y-ticks to be height.\n", |
||||||
|
"vert_vals = npvalues(dbz_cross.coords[\"vertical\"])\n", |
||||||
|
"v_ticks = np.arange(vert_vals.shape[0])\n", |
||||||
|
"ax_wspd.set_yticks(v_ticks[::20])\n", |
||||||
|
"ax_wspd.set_yticklabels(vert_vals[::20], fontsize=4) \n", |
||||||
|
"ax_dbz.set_yticks(v_ticks[::20])\n", |
||||||
|
"ax_dbz.set_yticklabels(vert_vals[::20], fontsize=4) \n", |
||||||
|
"\n", |
||||||
|
"# Set the x-axis and y-axis labels\n", |
||||||
|
"ax_dbz.set_xlabel(\"Latitude, Longitude\", fontsize=5)\n", |
||||||
|
"ax_wspd.set_ylabel(\"Height (m)\", fontsize=5)\n", |
||||||
|
"ax_dbz.set_ylabel(\"Height (m)\", fontsize=5)\n", |
||||||
|
"\n", |
||||||
|
"# Add a title\n", |
||||||
|
"ax_ctt.set_title(\"Cloud Top Temperature (degC)\", {\"fontsize\" : 7})\n", |
||||||
|
"ax_wspd.set_title(\"Cross-Section of Wind Speed (kt)\", {\"fontsize\" : 7})\n", |
||||||
|
"ax_dbz.set_title(\"Cross-Section of Reflectivity (dBZ)\", {\"fontsize\" : 7})\n", |
||||||
|
"\n", |
||||||
|
"plt.savefig(\"/Users/ladwig/Documents/workspace/wrf_python/doc/source/_static/images/matthew.png\",\n", |
||||||
|
" transparent=True, bbox_inches=\"tight\")\n", |
||||||
|
"plt.show()" |
||||||
|
] |
||||||
|
}, |
||||||
|
{ |
||||||
|
"cell_type": "code", |
||||||
|
"execution_count": null, |
||||||
|
"metadata": { |
||||||
|
"collapsed": true |
||||||
|
}, |
||||||
|
"outputs": [], |
||||||
|
"source": [ |
||||||
|
"# SLP\n", |
||||||
|
"from __future__ import (absolute_import, division, print_function, unicode_literals)\n", |
||||||
|
" \n", |
||||||
|
"from netCDF4 import Dataset \n", |
||||||
|
"import matplotlib.pyplot as plt\n", |
||||||
|
"from matplotlib.cm import get_cmap\n", |
||||||
|
"import cartopy.crs as crs\n", |
||||||
|
"from cartopy.feature import NaturalEarthFeature\n", |
||||||
|
"\n", |
||||||
|
"from wrf import npvalues, getvar, smooth2d\n", |
||||||
|
"\n", |
||||||
|
"ncfile = Dataset(\"/Users/ladwig/Documents/wrf_files/wrfout_d01_2016-10-07_00_00_00\")\n", |
||||||
|
"\n", |
||||||
|
"# Get the sea level pressure\n", |
||||||
|
"slp = getvar(ncfile, \"slp\")\n", |
||||||
|
"\n", |
||||||
|
"# Smooth the sea level pressure since it tends to be noisey near the mountains\n", |
||||||
|
"smooth_slp = smooth2d(slp, 3)\n", |
||||||
|
"\n", |
||||||
|
"# Get the numpy array from the XLAT and XLONG coordinates\n", |
||||||
|
"lats = npvalues(slp.coords[\"XLAT\"])\n", |
||||||
|
"lons = npvalues(slp.coords[\"XLONG\"])\n", |
||||||
|
"\n", |
||||||
|
"# Get the wrf.WrfProj object\n", |
||||||
|
"wrf_proj = slp.attrs[\"projection\"]\n", |
||||||
|
"\n", |
||||||
|
"# The cartopy() method returns a cartopy.crs projection object\n", |
||||||
|
"cart_proj = wrf_proj.cartopy()\n", |
||||||
|
"\n", |
||||||
|
"# Create a figure that's 10x10\n", |
||||||
|
"fig = plt.figure(figsize=(10,10))\n", |
||||||
|
"# Get the GeoAxes set to the projection used by WRF\n", |
||||||
|
"ax = plt.axes(projection=cart_proj)\n", |
||||||
|
"\n", |
||||||
|
"# Download and add the states and coastlines\n", |
||||||
|
"states = NaturalEarthFeature(category='cultural', scale='50m', facecolor='none',\n", |
||||||
|
" name='admin_1_states_provinces_shp')\n", |
||||||
|
"ax.add_feature(states, linewidth=.5)\n", |
||||||
|
"ax.coastlines('50m', linewidth=0.8)\n", |
||||||
|
"\n", |
||||||
|
"# Make the contour outlines and filled contours for the smoothed sea level pressure.\n", |
||||||
|
"# The transform keyword indicates that the lats and lons arrays are lat/lon coordinates and tells \n", |
||||||
|
"# cartopy to transform the points in to grid space.\n", |
||||||
|
"plt.contour(lons, lats, npvalues(smooth_slp), 10, colors=\"black\", transform=crs.PlateCarree())\n", |
||||||
|
"plt.contourf(lons, lats, npvalues(smooth_slp), 10, transform=crs.PlateCarree())\n", |
||||||
|
"\n", |
||||||
|
"# Add a color bar\n", |
||||||
|
"plt.colorbar(ax=ax, shrink=.47)\n", |
||||||
|
"\n", |
||||||
|
"# Set the map limits\n", |
||||||
|
"ax.set_xlim(wrf_proj.cartopy_xlim())\n", |
||||||
|
"ax.set_ylim(wrf_proj.cartopy_ylim())\n", |
||||||
|
"\n", |
||||||
|
"# Add the gridlines\n", |
||||||
|
"ax.gridlines()" |
||||||
|
] |
||||||
|
} |
||||||
|
], |
||||||
|
"metadata": { |
||||||
|
"kernelspec": { |
||||||
|
"display_name": "Python 2", |
||||||
|
"language": "python", |
||||||
|
"name": "python2" |
||||||
|
}, |
||||||
|
"language_info": { |
||||||
|
"codemirror_mode": { |
||||||
|
"name": "ipython", |
||||||
|
"version": 2 |
||||||
|
}, |
||||||
|
"file_extension": ".py", |
||||||
|
"mimetype": "text/x-python", |
||||||
|
"name": "python", |
||||||
|
"nbconvert_exporter": "python", |
||||||
|
"pygments_lexer": "ipython2", |
||||||
|
"version": "2.7.12" |
||||||
|
} |
||||||
|
}, |
||||||
|
"nbformat": 4, |
||||||
|
"nbformat_minor": 1 |
||||||
|
} |
||||||
Loading…
Reference in new issue