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May 3, 2026International Journal of Climatology0 citations

Incorporating Crowdsourced Data Into Operational Products: A Perspective From a National Meteorological Service

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IGIrene Garcia‐MartíCBChristopher W. BrownASAlessandro Spinuso

Key Points

  • This research aims to explore how integrating crowdsourced data can enhance meteorological and climate services through advanced methodologies.
  • Analyzed the integration of second- and third-party data (23PD) at KNMI.
  • Focused on aspects of internal adaptation, including defining vision, objectives, and value identification.
  • Emphasized the role of digital infrastructure, Open Science, and governance in successful implementation.
  • Successful integration of crowdsourced data improves high-resolution weather reports.
  • Enhanced forecasting through AI/ML methods shows promise for hyperlocal climate services.
  • Establishment of governance structures supports effective use of new digital infrastructure.

Abstract

ABSTRACT Future advances in the fields of meteorology and climate science will require scientists to increasingly adopt AI/ML methods and simultaneously strive towards the provision of new high‐resolution services. In this context, the development of new products and services (e.g., data fusion, nowcasting, data assimilation, validation and verification of NWP) may greatly benefit from the adoption of second‐and‐third‐party data (23PD) as a source of high‐resolution observations. In this document, we share KNMI's experience at integrating 23PD in the organisation looking into aspects of internal strategic adaptation (e.g., defining vision and clear objectives, identifying value for the weather chain) to crowdsourcing, digital infrastructure, Open Science, and governance. We think the successful adoption of 23PD might be relevant for AI/ML forecasting, devising new hyperlocal climate services and enable impact‐based analyses at the urban scales.

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Cite This Study

Garcia‐Martí et al. (2026) studied this question.

synapsesocial.com/papers/69f6e6968071d4f1bdfc74d6https://doi.org/10.1002/joc.70408
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