Tired of downloading the same sounding data over and over? This week we show you how to build a local cache for NWS soundings using Python’s Path library and Siphon! Learn how to automate your data retrieval and streamline your workflow in just a few minutes.

Wind roses are a powerful tool for visualizing wind patterns, but what if you could overlay them on real-world maps for better geographic context? In this week's MetPy Monday, we take wind data analysis to the next level by plotting wind roses on OpenStreetMap layers using CartoPy. By integrating Python’s windrose package with CartoPy image tiles, we create a geospatial visualization that combines meteorology and mapping.

In this tutorial, you’ll learn how to extract wind speed and direction data, generate wind rose plots, and overlay them onto OpenStreetMap using customized map layers. Whether you're working in meteorology, environmental analysis, or GIS, this approach provides deeper insight into regional wind patterns. Watch the full video to see how Python can help you bridge the gap between weather data and spatial analysis!

Learn how to plot wind roses using Python!

Discover how to animate GOES satellite imagery of Hurricane Helene using Python's powerful libraries! In this MetPy Monday episode, we dive into the goes2go library to fetch GOES-16 ABI data, create stunning animations with Matplotlib’s FuncAnimation, and exploit the data archive available for free on AWS!

New MetPy Monday! Extract and visualize weather data from GRIB files with Python! Get point forecasts with just a few lines of code!