Upper air tutorial

Kimizhao · Feb 1, 2017 · 8511557 · 8511557
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diff --git a/.gitignore b/.gitignore
@@ -18,5 +18,6 @@ MANIFEST
 
 docs/build/
 docs/examples
+docs/tutorials
 docs/api/generated
 examples/scripts
diff --git a/.landscape.yml b/.landscape.yml
@@ -4,6 +4,7 @@ ignore-paths:
   - versioneer.py
   - metpy/_version.py
   - examples
+  - tutorials
 
 max-line-length: 95
 

diff --git a/MANIFEST.in b/MANIFEST.in
@@ -4,9 +4,11 @@ include CONTRIBUTING.md
 include versioneer.py
 include metpy/_version.py
 recursive-include examples *
+recursive-include tutorials *
 recursive-include docs *
 prune docs/build
 prune docs/examples
+prune docs/tutorials
 prune docs/modules
 prune docs/source/__pycache__
 exclude .ipynb_checkpoints/*
diff --git a/docs/conf.py b/docs/conf.py
@@ -49,8 +49,8 @@
         'metpy': None,
         'matplotlib': 'http://matplotlib.org',
         'numpy': 'http://docs.scipy.org/doc/numpy-1.9.1'},
-    'examples_dirs': '../examples',
-    'gallery_dirs': 'examples',
+    'examples_dirs': ['../examples', '../tutorials'],
+    'gallery_dirs': ['examples', 'tutorials'],
     'filename_pattern': '/',
     'mod_example_dir': 'api/generated'
 }

diff --git a/docs/index.rst b/docs/index.rst
@@ -35,6 +35,7 @@ Documentation
    installguide
    units
    examples/index
+   tutorials/index
    api/index
    developerguide
 

diff --git a/setup.cfg b/setup.cfg
@@ -11,6 +11,7 @@ copyright-author = MetPy Developers
 norecursedirs = build docs
 flake8-ignore = *.py F405
                 examples/*.py D T003
+                tutorials/*.py D T003
                 versioneer.py ALL
 flake8-max-line-length = 95
 

diff --git a/tutorials/README.txt b/tutorials/README.txt
@@ -0,0 +1,7 @@
+.. _tutorials-index:
+
+MetPy Tutorials
+===============
+
+This collection of tutorials (under development) demonstrates the use of MetPy to perform
+common meteorological tasks.
diff --git a/tutorials/upperair_soundings.py b/tutorials/upperair_soundings.py
@@ -0,0 +1,211 @@
+# Copyright (c) 2008-2016 MetPy Developers.
+# Distributed under the terms of the BSD 3-Clause License.
+# SPDX-License-Identifier: BSD-3-Clause
+"""
+===========================
+Upper Air Sounding Tutorial
+===========================
+
+Upper air analysis is a staple of many synoptic and mesoscale analysis
+problems. In this tutorial we will gather weather balloon data, plot it,
+perform a series of thermodynamic calculations, and summarize the results.
+To learn more about the Skew-T diagram and its use in weather analysis and
+forecasting, checkout `this <http://homes.comet.ucar.edu/~alanbol/aws-tr-79-006.pdf>`_
+air weather service guide.
+"""
+
+from datetime import datetime
+
+import matplotlib.pyplot as plt
+from mpl_toolkits.axes_grid1.inset_locator import inset_axes
+import numpy as np
+
+import metpy.calc as mpcalc
+from metpy.io import get_upper_air_data
+from metpy.plots import Hodograph, SkewT
+from metpy.units import concatenate
+
+#########################################################################
+# Getting Data
+# ------------
+#
+# We will download data from the
+# `University of Wyoming sounding data page <http://weather.uwyo.edu/upperair/sounding.html>`_
+# , which has an extensive archive of data available, as well as current data.
+#
+# In this case, we will download the sounding data from the Veterans Day
+# tornado outbreak in 2002 by passing a ``datetime`` object and station name to the
+# ``get_upper_air_data`` function.
+
+dataset = get_upper_air_data(datetime(2002, 11, 11, 0), 'BNA')
+
+##########################################################################
+
+# We can view the fields available in the dataset. We will create some simple
+# variables to make the rest of the code more concise.
+
+print(dataset.variables.keys())
+
+p = dataset.variables['pressure'][:]
+T = dataset.variables['temperature'][:]
+Td = dataset.variables['dewpoint'][:]
+u = dataset.variables['u_wind'][:]
+v = dataset.variables['v_wind'][:]
+
+##########################################################################
+# Thermodynamic Calculations
+# --------------------------
+#
+# Often times we will want to calculate some thermodynamic parameters of a
+# sounding. The MetPy calc module has many such calculations already implemented!
+#
+# * **Lifting Condensation Level (LCL)** - The level at which an air parcel's
+#   relative humidity becomes 100% when lifted along a dry adiabatic path.
+# * **Parcel Path** - Path followed by a hypothetical parcel of air, beginning
+#   at the surface temperature/pressure and rising dry adiabatically until
+#   reaching the LCL, then rising moist adiabatially.
+
+# Calculate the LCL level
+parcel_lcl = mpcalc.lcl(p[0], T[0], Td[0])
+
+# Determine the LCL temperature by lifting a parcel from the surface
+# pressure and temperature via a dry adiabatic process.
+lcl_temperature = mpcalc.dry_lapse(concatenate((p[0], parcel_lcl)), T[0])[-1].to('degC')
+
+print(parcel_lcl, lcl_temperature)
+
+# Calculate the parcel profile.
+parcel_prof = mpcalc.parcel_profile(p, T[0], Td[0]).to('degC')
+
+##########################################################################
+# Basic Skew-T Plotting
+# ---------------------
+#
+# The Skew-T (log-P) diagram is the standard way to view rawinsonde data. The
+# y-axis is height in pressure coordinates and the x-axis is temperature. The
+# y coordinates are plotted on a logarithmic scale and the x coordinate system
+# is skewed. An explanation of skew-T interpretation is beyond the scope of this
+# tutorial, but here we will plot one that can be used for analysis or
+# publication.
+#
+# The most basic skew-T can be plotted with only five lines of Python.
+# These lines perform the following tasks:
+#
+# 1. Create a ``Figure`` object and set the size of the figure.
+#
+# 2. Create a ``SkewT`` object
+#
+# 3. Plot the pressure and temperature (note that the pressure,
+#    the independent variable, is first even though it is plotted on the y-axis).
+#
+# 4. Plot the pressure and dewpoint temperature.
+#
+# 5. Plot the wind barbs at the appropriate pressure using the u and v wind
+#    components.
+
+# Create a new figure. The dimensions here give a good aspect ratio
+fig = plt.figure(figsize=(9, 9))
+skew = SkewT(fig)
+
+# Plot the data using normal plotting functions, in this case using
+# log scaling in Y, as dictated by the typical meteorological plot
+skew.plot(p, T, 'r', linewidth=2)
+skew.plot(p, Td, 'g', linewidth=2)
+skew.plot_barbs(p, u, v)
+
+# Show the plot
+plt.show()
+
+##########################################################################
+# Advanced Skew-T Plotting
+# ------------------------
+#
+# Fiducial lines indicating dry adiabats, moist adiabats, and mixing ratio are
+# useful when performing further analysis on the Skew-T diagram. Often the
+# 0C isotherm is emphasized and areas of CAPE and CIN are shaded.
+
+# Create a new figure. The dimensions here give a good aspect ratio
+fig = plt.figure(figsize=(9, 9))
+skew = SkewT(fig, rotation=30)
+
+# Plot the data using normal plotting functions, in this case using
+# log scaling in Y, as dictated by the typical meteorological plot
+skew.plot(p, T, 'r')
+skew.plot(p, Td, 'g')
+skew.plot_barbs(p, u, v)
+skew.ax.set_ylim(1000, 100)
+skew.ax.set_xlim(-40, 60)
+
+# Plot LCL temperature as black dot
+skew.plot(parcel_lcl, lcl_temperature, 'ko', markerfacecolor='black')
+
+# Plot the parcel profile as a black line
+skew.plot(p, parcel_prof, 'k', linewidth=2)
+
+# Color regions of CAPE and CIN (the area between the actual temperature and
+# the parcel path).
+skew.ax.fill_betweenx(p, T, parcel_prof, where=T >= parcel_prof, facecolor='blue', alpha=0.4)
+skew.ax.fill_betweenx(p, T, parcel_prof, where=T < parcel_prof, facecolor='red', alpha=0.4)
+
+# Plot a zero degree isotherm
+l = skew.ax.axvline(0, color='c', linestyle='--', linewidth=2)
+
+# Add the relevant special lines
+skew.plot_dry_adiabats()
+skew.plot_moist_adiabats()
+skew.plot_mixing_lines()
+
+# Show the plot
+plt.show()
+
+##########################################################################
+# Adding a Hodograph
+# ------------------
+#
+# A hodograph is a polar representation of the wind profile measured by the rawinsonde.
+# Winds at different levels are plotted as vectors with their tails at the origin, the angle
+# from the vertical axes representing the direction, and the length representing the speed.
+# The line plotted on the hodograph is a line connecting the tips of these vectors,
+# which are not drawn.
+
+# Create a new figure. The dimensions here give a good aspect ratio
+fig = plt.figure(figsize=(9, 9))
+skew = SkewT(fig, rotation=30)
+
+# Plot the data using normal plotting functions, in this case using
+# log scaling in Y, as dictated by the typical meteorological plot
+skew.plot(p, T, 'r')
+skew.plot(p, Td, 'g')
+skew.plot_barbs(p, u, v)
+skew.ax.set_ylim(1000, 100)
+skew.ax.set_xlim(-40, 60)
+
+# Plot LCL as black dot
+skew.plot(parcel_lcl, lcl_temperature, 'ko', markerfacecolor='black')
+
+# Plot the parcel profile as a black line
+skew.plot(p, parcel_prof, 'k', linewidth=2)
+
+# Color regions of CAPE and CIN (the area between the actual temperature and
+# the parcel path).
+skew.ax.fill_betweenx(p, T, parcel_prof, where=T >= parcel_prof, facecolor='blue', alpha=0.4)
+skew.ax.fill_betweenx(p, T, parcel_prof, where=T < parcel_prof, facecolor='red', alpha=0.4)
+
+# Plot a zero degree isotherm
+l = skew.ax.axvline(0, color='c', linestyle='--', linewidth=2)
+
+# Add the relevant special lines
+skew.plot_dry_adiabats()
+skew.plot_moist_adiabats()
+skew.plot_mixing_lines()
+
+# Create a hodograph
+# Create an inset axes object that is 40% width and height of the
+# figure and put it in the upper right hand corner.
+ax_hod = inset_axes(skew.ax, '40%', '40%', loc=1)
+h = Hodograph(ax_hod, component_range=80.)
+h.add_grid(increment=20)
+h.plot_colormapped(u, v, np.hypot(u, v))  # Plot a line colored by wind speed
+
+# Show the plot
+plt.show()