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

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.