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Comparison of the Applicability of Mainstream Objective Circulation Type Classification Methods in China

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Publicado no:Atmosphere vol. 16, no. 11 (2025), p. 1231-1249
Autor principal: Ma Minjin
Outros Autores: Chen, Ran, Zhang Xingyu
Publicado em:
MDPI AG
Assuntos:
China
Weather forecasting
Climate change
Islands
Seasonal variation
Classification
Forecast accuracy
Principal components analysis
Atmospheric circulation
Weather
Sea level pressure
Seasonal variations
Climatic classifications
Atmospheric sciences
Circulation patterns
Precipitation
Climate and weather
Linkage analysis
Self organizing maps
Circulation
Climate change research
Circulation types
Methods
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Resumo:Circulation type classification (CTC) is an important method in atmospheric sciences, which reveals the relationship between atmospheric circulation and regional weather and climate. Accurate circulation classification helps to improve weather forecasting accuracy and supports climate change research. China has complex topography and significant spatiotemporal variability in its circulation patterns, making the study of circulation type classification in this region highly significant. This study aims to evaluate the applicability of several mainstream objective CTC methods in the China region. We applied methods including T-mode principal component analysis (PCT), Ward linkage, K-means, and Self-Organizing Maps (SOM) to classify the sea-level pressure daily mean fields from 1993 to 2023 in the study area, and compared the classification results in terms of internal metrics, continuity, seasonal variation, separability of related meteorological variables (e.g., temperature, precipitation), and stability to spatiotemporal resolution. The results show that each method has its advantages in different contexts, with the K-means method showing the best overall performance. Additionally, an optimized approach combining PCT and K-means is proposed.
ISSN:2073-4433
DOI:10.3390/atmos16111231
Fonte:Publicly Available Content Database