Overview of the OpenSense software ecosystem

Architecture¶

The OpenSense software ecosystem follows a layered architecture. At the foundation lies poligrain (for point, line, gid rainfall data) which provides core functionalities common to processing and analyzing CML, SML, and PWS data. This foundational layer avoids interdependencies between processing packages that would occur if one package imported another to use specific implementations.

Above poligrain sit the specialized processing packages which are focused on specific sensor data or methods:

• pycomlink is designed for processing CML data, including quality control and rainfall estimation

• pypwsqc provides quality control and bias correction for PWS data

• mergeplg is a package for merging data from multiple sensors, including CMLs, PWSs, and SMLs.

For applications requiring multi-sensor processing or data merging, these packages are imported together with other specialized tools (e.g., wradlib for radar data).

Design Principles¶

The ecosystem leverages the OpenSense common standard for data and metadata structure in NetCDF files (Fencl et al., 2023), enabling:

• Simplified function calls with assumed data/metadata structure

• Automatic handling of geographic location information

• Integration with xarray for labeled multi-dimensional arrays

Quick intro to the individual packages¶

Explore the individual packages through their quick-tour notebooks accesible from the sidebar navigation menu on the left. Each notebook gives a brief overview of the core functionality of the respective package and links to the full package documentation.

A combined workflow notebook demonstrates how the different packages can be used together in a typical analysis.

Additionally, a small example for SML data processing is provided, albeit without using a real software package because such a package does not yet exist.