Finding a temperature trend in DWD data: regression vs. universal kriging

In this example we are going to interpolate temperature data from the german weather service (DWD) downlaoded through the python package wetterdienst.

In order to find a north-south trend in the data we will compare results from regression and universal kriging provided by GSTools.

Structure

The workflow is organized by the following structure:

• data/ - downloaded temperature data and german border line
• src/
  • 00_data_download.py - downloading routines
  • 01_dwd_krige.py - interpolation and comparison plot generation
• results/ - all produced results

Python environment

Main Python dependencies are stored in requirements.txt:

gstools==1.3.1
matplotlib
cartopy==0.18.0
geopandas==0.8.1
wetterdienst==0.13.0

You can install them with pip (potentially in a virtual environment):

pip install -r requirements.txt

Contact

You can contact us via [email protected].

License

MIT © 2021