NOAA SPC Convective Outlook

Demonstrate the use of geoJSON and shapefile data with PlotGeometry in MetPy’s simplified plotting interface. This example walks through plotting the Day 1 Convective Outlook from NOAA Storm Prediction Center. The geoJSON file was retrieved from the Storm Prediction Center’s archives.

import geopandas

from metpy.cbook import get_test_data
from metpy.plots import MapPanel, PanelContainer, PlotGeometry

Read in the geoJSON file containing the convective outlook.

day1_outlook = geopandas.read_file(get_test_data('spc_day1otlk_20210317_1200_lyr.geojson'))

Preview the data.

day1_outlook

	DN	VALID	EXPIRE	ISSUE	LABEL	LABEL2	stroke	fill	geometry
0	2	202103171200	202103181200	202103170552	TSTM	General Thunderstorms Risk	#55BB55	#C1E9C1	MULTIPOLYGON (((-75.21498 35.85713, -75.12000 ...
1	3	202103171200	202103181200	202103170552	MRGL	Marginal Risk	#005500	#66A366	MULTIPOLYGON (((-85.71646 29.55317, -85.76700 ...
2	4	202103171200	202103181200	202103170552	SLGT	Slight Risk	#DDAA00	#FFE066	MULTIPOLYGON (((-85.95065 29.84763, -85.98500 ...
3	5	202103171200	202103181200	202103170552	ENH	Enhanced Risk	#FF6600	#FFA366	MULTIPOLYGON (((-88.40000 30.20000, -90.09000 ...
4	6	202103171200	202103181200	202103170552	MDT	Moderate Risk	#CC0000	#E06666	MULTIPOLYGON (((-87.07000 31.68000, -88.65000 ...
5	8	202103171200	202103181200	202103170552	HIGH	High Risk	#CC00CC	#EE99EE	MULTIPOLYGON (((-91.88000 32.99000, -89.82000 ...

Plot the shapes from the ‘geometry’ column. Give the shapes their fill and stroke color by providing the ‘fill’ and ‘stroke’ columns. Use text from the ‘LABEL’ column as labels for the shapes.

geo = PlotGeometry()
geo.geometry = day1_outlook['geometry']
geo.fill = day1_outlook['fill']
geo.stroke = day1_outlook['stroke']
geo.labels = day1_outlook['LABEL']
geo.label_fontsize = 'large'

Add the geometry plot to a panel and container.

panel = MapPanel()
panel.title = 'SPC Day 1 Convective Outlook (Valid 12z Mar 17 2021)'
panel.plots = [geo]
panel.area = [-120, -75, 25, 50]
panel.projection = 'lcc'
panel.layers = ['lakes', 'land', 'ocean', 'states', 'coastline', 'borders']

pc = PanelContainer()
pc.size = (12, 8)
pc.panels = [panel]
pc.show()