In this MetPy Monday tutorial, John Leeman from NSF Unidata demonstrates how to automatically find and plot high and low pressure centers on a weather map using MetPy. Building on the previous GFS data tutorial, this episode uses sea level pressure data from a GFS analysis and shows how MetPy’s newer find_peaks functionality can identify pressure maxima and minima automatically. 

The workflow starts by adding Cartopy and Matplotlib imports for mapping, then importing MetPy’s find_peaks calculation and scatter_text plotting helper. John explains how the peak persistence method can locate highs and lows in noisy meteorological fields, then applies it to mean sea level pressure data to find the row and column indices of pressure centers.

The tutorial then walks through creating a map with Cartopy, adding states, coastlines, borders, land, and ocean features, contouring mean sea level pressure, labeling the contours, and plotting high and low symbols directly on the map. Finally, the video shows how to use scatter_text to add the actual pressure values beneath each H and L label, producing a reusable workflow for automated weather maps, briefings, and case study graphics.