Fingerprint-Based Historical Analog Weather Retrieval Technique and Its Implementation
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Abstract:
Addressing the persistent demand for historical analogue references in operational weather forecasting and the deficiencies of traditional retrieval methods in efficiency and objectivity, this paper proposes a rapid retrieval technology for similar historical weather events based on image fingerprinting and multi-element synergy. Technology initially employs fingerprint similarity detection algorithms from imageology to establish a similarity quantification method for single weather element fields. Subsequently, guided by synoptic principles and considering the coupling characteristics between upper-air circulation and surface element fields, a multi-element synergistic query algorithm is designed to more accurately identify historical precipitation fields and corresponding circulation patterns like a target weather process. Based on these techniques, a historical similar weather retrieval platform was developed using a "Cloud + Client" architecture, enabling efficient retrieval of historical analogues. The platform has been operationally trialed at the National Meteorological Center, demonstrating good application potential and practical value in forecasting several weather events. Statistical verification indicates that the similar cases retrieved by this method significantly outperform climatological states in terms of anomaly correlation coefficient and root mean square error. Finally, this paper discusses future development directions for technology, particularly in algorithm optimization, objective evaluation, and deepening application.