SkewT 0.1.4

Plots and analyses atmospheric profile data from UWyo database

SkewT provides a few useful tools to help with the plotting and analysis of upper atmosphere data. In particular it provides some useful classes to handle the awkward skew-x projection (provided by Ryan May, see notes in source code and LICENSE.txt).

It’s most basic implementation is to read a text file of the format provided by the University of Wyoming’s website:

http://weather.uwyo.edu/upperair/sounding.html

Typical usage often looks like this:

#!/usr/bin/env python

from skewt import SkewT
sounding = SkewT.Sounding(filename="soundingdata.txt")
sounding.plot_skewt(color='r',lw=2)

Alternatively you may input the required data fields in a dictionary. The dictionary must have as a minimum the fields PRES and TEMP corresponding to pressure (hPa) and temperature (deg C). Soundings will typically have a dew point temperature trace and wind barbs as well, so it’s best to include the dewpoint temp DWPT (deg C), wind speed SKNT (knots) and wind direction in degrees WDIR. Other fields may be included as per the docstring:

#!/usr/bin/env python

from skewt import SkewT
sounding = SkewT.Sounding(data=data_dict)
sounding.plot_skewt(color='r',lw=2)

One thing on my to-do list is to make the package a bit more user-friendly in that it will accept one of a number of moisture fields (e.g. dew-point temperature relative humidity, mixing ratio or vapour partial pressure) and fill in the others for you. For any moisture calculations, the module looks for DWPT, and if it’s not there it complains.

News

Thanks for your interest in this package and I’d love to hear your feedback: thomas.chubb AT monash.edu

Here’s a summary of what’s new in Version 0.1.4:

• A major-ish change to the layout. I’m planning on adding more diagnostics as time goes by so I decided to get the test from the parcel and the column diagnostics out of the plot area.

• The new release contains a diagnostic for Total Precipitable Water (TPW). This is simply the total column-integrated water vapour, based on mixing ratio derived from DWPT. It uses a trapezoidal approximation for integration and gives values within about one percent of the values in the UWyo text files (I have no idea how UWyo do their diagnostic). More diagnostics to come!

Regarding the Examples in the Tarball

Unfortunately, If you pip install this package I don’t think you get the examples that are in the tarball (see the big green “Download SkewT-xxx.tar.gz button?). I’m going to try my darndest to get them up here on pypi as independent files, but in any case using the __main__ invocation (i.e. python SkewT.py) doesn’t really make sense when you have SkewT.py installed in a system directory. The very easiest way to run the examples would be as per the typical usage above (e.g. in IPython) after having downloaded one of the example sounding files and placed it in you current directory.

Sounding Files

The format for the sounding files is very specific (sorry). You are best off using the example in “examples” as a template. Here’s a sample of the first few lines:

94975 YMHB Hobart Airport Observations at 00Z 02 Jul 2013

-----------------------------------------------------------------------------
   PRES   HGHT   TEMP   DWPT   RELH   MIXR   DRCT   SKNT   THTA   THTE   THTV
    hPa     m      C      C      %    g/kg    deg   knot     K      K      K
-----------------------------------------------------------------------------
 1004.0     27   12.0   10.2     89   7.84    330     14  284.8  306.7  286.2
 1000.0     56   12.4   10.3     87   7.92    325     16  285.6  307.8  286.9
  993.0    115   12.8    9.7     81   7.66    311     22  286.5  308.1  287.9

The script defines columns by character number so you really do have to get the format exactly right. One day I will get around to writing a routine to output the text files properly.

Parcel Ascent

Simple routine to calculate the characteristics of a parcel initialised with pressure, temperature and dew point temperature. You could do it like this:

from skewt import SkewT

sounding=SkewT.Sounding("examples/94975.2013070200.txt")
sounding.make_skewt_axes()
sounding.add_profile(color='r',lw=2)
sounding.lift_parcel(1004.,17.4,8.6)
draw()

Automatic Parcel Definition (New in version 0.1.3!)

You can still manually input a parcel as in the example above, but there is a new routine to automagically define a parcel from the sounding itself. You define a layer depth that you would like to characterise (say 100mb). The routine surface_parcel then returns

1. The surface pressure (just the pressure of the lowest level)

2. The characteristic dew-point temperature (from the average Qv in the layer)

3. The characteristic temperature (from the maximum Theta in the layer)

You could do it like this:

from skewt import SkewT

sounding=SkewT.Sounding("examples/94975.2013070200.txt")
sounding.make_skewt_axes()
sounding.add_profile(color='r',lw=2)
parcel=sounding.surface_parcel(mixheight=100.)
sounding.lift_parcel(*parcel)
draw()

The above steps are also now included in the Sounding.plot_skewt() wrapper for your convenience, so all of the above can be condensed with:

from skewt import SkewT

sounding=SkewT.Sounding("examples/94975.2013070200.txt")
sounding.plot_skewt(color='r',lw=2)

To-Do List

• More diagnostics.

• The Sounding.readfile() routine is STILL a bit of a mess.

• User-friendly moisture variable handling. At the moment it’s best to just make sure that you include DWPT.

• Hodographs? Anyone?

Contributors

• Simon Caine.

• Hamish Ramsay (Monash) has promised to at least think about adding some extra diagnostics.

• The initial SkewX classes were provided by a fellow called Ryan May who was a student at OU. I have not made contact with Ryan other than to download his scripts and modify them for my own purposes.

Thanks Also

• Thanks to Douglas Miller of UNC-Asheviller, who prompted me to get the TPW routine up for a class exercise (yay!)