Modernizing Open Data Access at DWD: Implementing an OGC EDR API for Spatiotemporal Subsetting of NWP Data

Providing efficient, web-friendly access to meteorological data is an ongoing priority for national weather services. With the Environmental Data Retrieval (EDR) API standard, the Open Geospatial Consortium (OGC) offers a practical approach to modernizing data delivery, allowing users to query precise spatial and temporal subsets without the need to download large, monolithic files or familiarize themselves with handling specialized meteorological file formats. To leverage these benefits specifically for Numerical Weather Prediction (NWP) data, the German Meteorological Service (Deutscher Wetterdienst, DWD) is actively developing an OGC EDR API implementation to deliver its Open Data in a more modern way. 

We outline the recent progress, architectural choices, and technical challenges encountered during the development of the API. To build a minimum viable product, we focused on DWD's high-frequency forecast model ICON-D2-RUC (Rapid Update Cycle) and its ensemble counterpart, ICON-D2-RUC-EPS. As the API response format, we provide CoverageJSON. However, working within this standard required us to address the specific structural complexities of the ICON models. This involved solving the challenge of presenting parameters that vary vastly in temporal resolution, ranging from 5-minute intervals to hourly steps, within a single response. Beyond these challenges related to temporal resolution, we also had to address the spatial representation. By utilizing a MultiPolygonSeries domain within our CoverageJSON output, we maintain the native ICON triangular grid, providing a standardized method to represent the model cells without requiring interpolation.

This project is a collaboration between DWD's open data team and the team for digital transformation of data storage and data delivery at DWD. Together, we built a solution relying on our new data lakehouse architecture. It features Zarr, which is a storage format providing highly efficient access to multidimensional gridded data, alongside Icechunk for safe transactions in our distributed architecture. This cloud-optimized storage layer uses object storage hosted within a sovereign cloud and is continuously populated with operational data, forming the foundation of our current internal minimum viable product. Drawing from this experience, in this contribution we will share practical insights gained from building this service and discuss our ongoing roadmap, including the status of a public alpha release.