ML Weather Prediction Access and Plotting

Use MetPy to access machine learning weather prediction (MLWP) data in AWS S3 and plot using the simplified plotting interface.

from datetime import datetime

from metpy.plots import MapPanel, PanelContainer, RasterPlot
from metpy.remote import MLWPArchive

###################
# Access the GraphCast forecast closest to the desired date/time
dt = datetime(2025, 2, 15, 18)
ds = MLWPArchive().get_product('graphcast', dt).access()

###################
# Plot the data using MetPy's simplified plotting interface.
raster = RasterPlot()
raster.data = ds
raster.field = 't2'
raster.time = dt
raster.colorbar = 'horizontal'
raster.colormap = 'RdBu_r'

panel = MapPanel()
panel.area = 'co'
panel.projection = 'lcc'
panel.layers = ['coastline', 'borders', 'states']
panel.plots = [raster]
panel.title = f"{ds[raster.field].attrs['long_name']} @ {dt}"

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

pc.show()