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 linesrc/00_data_download.py- downloading routines01_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.txtContact
You can contact us via [email protected].
License
MIT © 2021