windrose
A wind rose is a graphic tool used by meteorologists to give a succinct view of how wind speed and direction are typically distributed at a particular location. It can also be used to describe air quality pollution sources. The wind rose tool uses Matplotlib as a backend. Data can be passed to the package using Numpy arrays or a Pandas DataFrame.
Windrose is a Python library to manage wind data, draw windroses (also known as polar rose plots), and fit Weibull probability density functions.
Learn how to plot wind roses using Python!
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! See also