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Data formats and standards for opportunistic rainfall sensors.

Martin Fencl1, Roberto Nebuloni2, Jafet C M Andersson3

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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.

Keywords:
commercial microwave linksdata formatdata standardsnaming conventionsopportunistic rainfall sensingpersonal weather stationssatelllite microwave links

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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.