High-resolution climate reconstruction from historical Chinese weather records using optimized natural language processing.

ABSTRACT: Reconstructing high-resolution climate data from historical documents is hindered by subjectivity and a lack of standardization. This study develops and validates a novel framework to overcome these challenges. In this paper, a historical weather classification lexicon is constructed by optimizing natural language processing (NLP) techniques. Leveraging semantic clustering and dynamic expansion, this lexicon effectively captures the linguistic diversity associated with weather events across different regions and intensity levels. Building on this lexicon, we propose a multi-dimensional index system to quantify historical weather grades. This system includes indicators such as weather intensity, agricultural impact, economic impact, social impact, and population casualties. For each indicat

SUBMITTER: Li T 

PROVIDER: S-EPMC12739121 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature