sounderpy

WELCOME! thank you for visiting SounderPy!

This script is used to access vertical profile data for calculations or plotting of a vertical profile (sounding).

Thank you for visiting SounderPy.

Why SounderPy?

• Sometimes data is tough to find, and often times is even tougher to get in the format you like. SounderPy gets you this data!
• The code needed for loading and parsing vertical data (especially from models) can be large and messy. SounderPy keeps it hidden away in a separate file -- just import and call sounderPy functions to keep your code clean!

SounderPy is used for:

• Accessing and loading raw vertical profile data from the sources listed above
• Parsing these raw data into a clean & simple-to-use format for calculations and plotting
• SounderPy offers a built-in quick MetPy plotting function, but sounderPy itself is meant as a source for accessing data -- not for plotting (that may be a future package ;) )

SounderPy is currently capable of accessing and processing data from:

• ECMWF CDS ERA5 reanalysis [1940-present] *note: you must set up an account through the CDS to unlock ERA5 data. (see: https://cds.climate.copernicus.eu/api-how-to)
• UNIDATA THREDDS TDS RAP reanalysis [2005-present]
• UNIDATA THREDDS TDS RUC reanalysis [2005-2020]
• The University of Wyoming RAOB archive [1973-present, depending on station]
• Iowa State University's RAOB archive [1945-present, depending on station]

How to use SounderPy:

1. Make sure your environment has the required dependencies:
   • metpy
   • xarray
   • urllib
   • numpy
   • siphon
   • cartopy
   • datetime
   • cdsapi
   • pandas

2. pip install sounderpy
   

3. import sounderpy as spy
   

4. year  = '2014'
   month = '06'
   day   = '16'
   hour  = '20'
   latlon = [41.9, -97.01]
   method = 'rap'
   

5. raw_data = spy.get_model_data(method, latlon, year, month, day, hour)
   

6. clean_data = spy.parse_data(raw_data)
   

and boom! Now you have a callable dictionary of vertical profile data including...

1. Temperature
2. Dewpoint
3. Relative Humidity
4. Pressure
5. Height
6. Height AGL
7. Vertical Velocity
8. U-component Wind
9. V-component Wind

You can make a quick plot of the data using built-in MetPy plotting functions!, just call... spy.metpy_sounding(clean_data)