Reproject INCA data¶

In this jupyter notebook, we will show how to import and reproject a precipitation forecast from the INCA nowcasting system.

Install dependencies¶

First, let’s set up our working environment. It is recommended to use a virtual environment.

Important: In Google Colab, this notebook needs to be executed one cell at a time. Trying to excecute all the cells at once may results in cells being skipped and some dependencies not being installed.

Now, let’s install the dependendies that will allow us to read and visualize the example data. We will need xarray to work with labelled multi-dimensional arrays, pyproj for coordinate transformations, and rioxarray to extend xarray with methods from rasterio for geospatial datasets.

[1]:

!pip install xarray pyproj rioxarray

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Installing collected packages: click, snuggs, cligj, click-plugins, affine, rasterio, rioxarray
Successfully installed affine-2.3.0 click-8.0.3 click-plugins-1.1.1 cligj-0.7.2 rasterio-1.2.10 rioxarray-0.9.0 snuggs-1.4.7

Download the data¶

Now that we have the environment ready, let’s download an example dataset.

On Zenodo, we can download the ouput from a single run of INCA for precipitation (mm/h).

[2]:

!wget https://zenodo.org/record/5575197/files/RR_INCA.nc

--2021-12-15 18:01:58--  https://zenodo.org/record/5575197/files/RR_INCA.nc
Resolving zenodo.org (zenodo.org)... 137.138.76.77
Connecting to zenodo.org (zenodo.org)|137.138.76.77|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 5887704 (5.6M) [application/octet-stream]
Saving to: ‘RR_INCA.nc.1’

RR_INCA.nc.1        100%[===================>]   5.61M  5.58MB/s    in 1.0s

2021-12-15 18:02:01 (5.58 MB/s) - ‘RR_INCA.nc.1’ saved [5887704/5887704]

Reproject with pyproj¶

The Swiss CH1903 / LV03 coordinates (EPSG 21781) can be reprojected to any other reference system using pyproj. In the example below, we’ll use WGS84 as the target projection (EPSG 4326).

Note that as a result, the dataset won’t be anymore on a regular grid.

[4]:

import numpy as np
from pyproj import Transformer

chxv, chyv = np.meshgrid(ds.chx, ds.chy)
transformer = Transformer.from_crs(
    "epsg:21781",
    "epsg:4326",
    always_xy=True,
)
lon, lat = transformer.transform(chxv, chyv)
ds = ds.assign_coords({"lon": (("chy", "chx"), lon) , "lat": (("chy", "chx"), lat)})
ds.RR.isel(time=0).plot.pcolormesh("lon", "lat")  # not a regular grid anymore

[4]:

<matplotlib.collections.QuadMesh at 0x7feb84be70a0>

Reproject INCA data¶

Install dependencies¶

Download the data¶

Read the data¶

Reproject with pyproj¶

Reproject and resample with rioxarray¶

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