№ files_lp_4_process_3_081085
A research article presenting a variational autoencoder-based clustering method for analyzing small-sample geophysical fluid circulation data, demonstrating improved identification of circulation modes during extreme coastal events.
Year: 2026
Region: Coastal Japan
Topic: Geophysical fluid dynamics, extreme events
Document type: Research article
Institution: Meteorological Research Institute, Japan Meteorological Agency; Graduate School of Science, Kyoto University
Authors: Kunihiro Aoki, Hideyuki Nakano, Nariaki Hirose, Norihisa Usui, Kei Sakamoto, Takahiro Toyoda, Shogo Urakawa, Yuma Kawakami
Target audience: Atmospheric and oceanic scientists, data scientists
Methodology: Variational autoencoder with principal-component-scaled augmentation
Data scope: Approximately 150 samples of coastal ocean velocity fields during Kyucho events
Results: Identification of four distinct circulation modes
Application period: Kyucho event study period
Abstract type: Clustering and pattern analysis in small-sample geophysical datasets
Journal context: Geophysical research, extreme event prediction
Price: 8 / 10 USD
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