Track 2: PYTHON | Room: 1151 | Level: Intermediate ★★
Tech Requirements: None
Don Morton, Owner/Manager, Boreal Scientific Computing; Adjunct Professor of CISC, Harrisburg University
This instruction has a primary goal of introducing beginning and intermediate Python programmers to some of the various tools and techniques available for taking raw output from numerical weather prediction (NWP) models and creating meaningful products that aid in making forecasts. The session will begin with an overview of the NWP process leading to the generation of raw output data, and then to the production of user-friendly graphical products. To generate the products, a workflow that involves Python, NumPy, Matplotlib, Basemap, as well as other tools, will be presented. The production of these graphics requires a logical sequence of data extraction and handling for efficiency, transforming raw data into forms useful by stakeholders, visualizing the transformed data, and then, mapping the data to geographical contexts. The instruction will be aimed at demonstrating and inspiring a Python way of processing raw geographic data into products that make sense to scientists and the public. A broad range of attendee Python experience will be considered, though those with more experience will likely find more meaning.