In this MetPy Monday tutorial, John Leeman from NSF Unidata compares three common ways to visualize wind and flow fields in Python: streamlines, quiver plots, and wind barbs. Instead of using real weather data, this episode builds artificial wind fields with NumPy so the differences between each plotting method are easier to see and understand. 

The tutorial walks through creating simple synthetic wind fields, including uniform flow, jet-like flow, and curved flow with a strong speed gradient. John then uses Matplotlib to plot each case three different ways: streamplot for streamlines, quiver for arrows, and barbs for traditional meteorological wind barbs.

Along the way, the video explains what each plotting method communicates well and where each one can become confusing. Streamlines are useful for showing the overall shape and structure of flow, especially in curved patterns, but they usually need color to show wind speed. Quiver plots are intuitive because they use arrows, but they can become cluttered or hard to interpret when wind speeds vary a lot. Wind barbs are the standard meteorological option for compactly showing speed and direction, but they may be less intuitive for some audiences.