📖 Documentation: disdrodb.readthedocs.io
💻 Software repository: DISDRODB
DISDRODB is an international initiative to index, collect, and harmonize drop size distribution (DSD) data from disdrometers around the world.
The project also aims to establish a global standard for sharing disdrometer observations, following:
- FAIR data principles (Findable, Accessible, Interoperable, Reusable)
- CF conventions (Climate & Forecast metadata standards)
By adopting these standards, DISDRODB facilitates the processing, analysis, and visualization of disdrometer data across diverse datasets and institutions.
This repository hosts the DISDRODB Metadata Archive, which serves as the central registry for:
-
📍 Station Inventory: catalog of all available disdrometer sites
-
🛠️ Station Status: a record of problematic timesteps or time periods affected by station malfunctions
-
💾 Raw Data Archives: URLs linking to the original disdrometer data repositories
By using GitHub, the community can collaboratively:
- Improve and correct station metadata
- Track sensor performance over time
- Enhance data quality with a transparent, reproducible workflow
All metadata follow a comprehensive standardized schema to ensure consistency.
Contributors can also report instrument malfunctions or erroneous measurements through dedicated issues YAML files, making it easy to document anomalies.
Click on the image below to access the full-screen interactive map of all DISDRODB stations:
The DISDRODB Metadata Archive is organized by data sources and campaigns.
Each <DATA_SOURCE> (e.g., EPFL) contains one or more <CAMPAIGN_NAME> (e.g., HYMEX_LTE_SOP3), which in turn contain station-level metadata.
📁 DISDRODB
├── 📁 METADATA
├── 📁 <DATA_SOURCE>
├── 📁 <CAMPAIGN_NAME>
├── 📁 issue
├── 📜 <station_name_1>.yml
├── 📜 <station_name_2>.yml
├── 📁 metadata
├── 📜 <station_name_1>.yml
├── 📜 <station_name_2>.yml
- Metadata YAML files → contain station information (device type, position, reader, data URLs, etc.) needed for integration and processing.
- Issue YAML files → document time periods of malfunctioning instruments or erroneous data that must be excluded during processing.