xarray IRIS backend

Contents

xarray IRIS backend#

In this example, we read IRIS (sigmet) data files using the xradar iris xarray backend.

import glob
import gzip
import io
import wradlib as wrl
import wradlib_data
import warnings
from IPython.display import display

import matplotlib.pyplot as plt
import numpy as np
import xradar as xd
import xarray as xr

warnings.filterwarnings("ignore")

Load IRIS Volume Data#

fpath = "sigmet/SUR210819000227.RAWKPJV"
f = wradlib_data.DATASETS.fetch(fpath)
vol = xd.io.open_iris_datatree(f, reindex_angle=False)

Downloading file 'sigmet/SUR210819000227.RAWKPJV' from 'https://github.com/wradlib/wradlib-data/raw/main/data/sigmet/SUR210819000227.RAWKPJV' to '/home/docs/.cache/wradlib-data'.

Georeferencing#

swp = vol["sweep_0"].to_dataset(inherit="all_coords")
swp = swp.assign_coords(sweep_mode=swp.sweep_mode)
swp = swp.wrl.georef.georeference()

Create simple plot#

Using xarray features a simple plot can be created like this. Note the sortby('time') method, which sorts the radials by time.

For more details on plotting radar data see under Visualization.

swp.DBZH.sortby("time").plot(x="range", y="time", add_labels=False)

<matplotlib.collections.QuadMesh at 0x73bdf72a5550>

../../../_images/d533141c7f5c1e4568dfc32ba0f24d5b60765114c2dd8201593ac130803ce021.png

fig = plt.figure(figsize=(5, 5))
pm = swp.DBZH.wrl.vis.plot(crs={"latmin": 3e3}, fig=fig)

../../../_images/654665ee5e3a249ae8cbdd08401e1ac082b357fd56f62d162e93fb348cbe5590.png