A Coordinated Bidirectional Data Fusion Processing System for Meteorological Applications

This study proposes a coordinated bidirectional meteorological data fusion processing system for controlled data exchange across the intranet, demilitarized zone (DMZ), and Internet. The system adopts a three-layer isolation architecture and integrates Apache MiNiFi, Apache NiFi, and Apache Kafka to coordinate edge preprocessing, DMZ-based fusion processing, asynchronous message buffering, and Internet service publication. Kerberos authentication, access control, and operational monitoring support outbound data-product services and inbound user-request-driven workflows. Operational evaluation at the National Meteorological Science Data Center showed that edge preprocessing reduced cross-domain data volume by an average of 95%; representative bidirectional workflows were completed within minutes; and the average Kafka message-processing success rate over three consecutive months was 99.77%. The system has supported the automated generation and external publication of human comfort index products, while its core mechanisms have been generalized into a reusable software stack for cross-domain scientific data applications. The results indicate that the proposed architecture provides a practical and deployable approach to efficient and controlled bidirectional meteorological data fusion without changing existing network security boundaries.