Visualizing meteorological data with Python: Use cases with Siphon and MetPy

Date and Time: 
Friday, April 8th, 2016
Location: 
Center Green
Speaker: 
Ryan May, Sean Arms, and Kevin Goebbert

Title: 

Authors: 
Abstract:
 
This tutorial will demonstrate new Python technologies available specifically for use with meteorological datasets. Many of these datasets are available from organizations using Unidata's THREDDS data servers. The Siphon project, under active development at Unidata, streamlines remote access to THREDDS servers within Python scientific computing environments. Remote access capabilities through Siphon and THREDDS includes index-based subsetting using OPeNDAP, as well as the subsetting using longitude, latitude, and time through the NetCDF subset service; this eliminates the need to transfer large datasets locally. MetPy is a recently announced meteorological toolkit for Python; similar to projects like astropy and biopython, this project aims to be a community-developed package serving the needs of the meteorology community. The current capabilities include basic computations, reading weather data file formats, and domain specific plotting, such as skew-T log-P and station model plots. The content of the course will consist of hands-on time with the tools to produce high-quality weather visualizations suitable for both classroom and publication use.
Speaker Description: 

Ryan May has a Ph.D. in radar meteorology and works as a Software Engineer at Unidata. His primary work is on the THREDDS data server and a wide array of Python efforts at Unidata: these include the MetPy and Siphon packages, putting together training materials, and contributing to other open source libraries to smooth the way for using Python in meteorology. 
 
Sean Arms is a boundary-layer guy by training (PhD), and Software Engineer by Luck (TM) at UCAR/UCP/Unidata. His primary work is focused on THREDDS related projects, such as netCDF-Java, the THREDDS Data Server, Rosetta, and most recently, Siphon.

Dr. Kevin Goebbert is an Associate Professor of Meteorology at Valparaiso University where he teaches a broad spectrum of meteorology courses including synoptic meteorology, numerical weather prediction, and meteorological computer applications, in which he teaches Fortran and Python to upper-level undergraduate students. In addition, he currently serves on the Unidata Users Committee.

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