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Data formats and standards for opportunistic rainfall sensors.
Martin Fencl1, Roberto Nebuloni2, Jafet C M Andersson3
1Department of Hydraulics and Hydrology, Czech Technical University in Prague, Prague 6, 16629, Czech Republic.
Open Research Europe
|February 26, 2024
Summary
Opportunistic sensing (OS) data for rainfall measurement face format challenges. New guidelines for data and metadata collection, naming, and storage are proposed to improve sharing and automated processing.
Area of Science:
- Environmental Science
- Data Science
- Meteorology
Background:
- Opportunistic sensors are increasingly used for rainfall measurement.
- Diverse data formats and lack of standards hinder data sharing and processing.
Purpose of the Study:
- To review current practices for collecting and storing opportunistic sensing (OS) precipitation data.
- To propose common guidelines for data and metadata collection, naming conventions, and file formats for OS rainfall data.
Main Methods:
- Review of current practices within the OpenSense Cost Action community.
- Focus on three prominent OS precipitation sensors: Commercial Microwave Links (CML), Satellite Microwave Links (SML), and Personal Weather Stations (PWS).
- Development of guidelines for data and metadata storage, focusing on historical time series.
Main Results:
- Identified challenges in OS rainfall data standardization.
- Proposed common guidelines for data/metadata collection, naming conventions, and file formats.
- Guidelines accepted by the OpenSense community for historical time series data.
Conclusions:
- The proposed conventions are a significant step towards automated processing of OS raw data.
- These guidelines will facilitate community development of joint OS software packages.
- The conventions aim to improve the practical usage and integration of OS rainfall data into standard observation systems.
