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Research Papers

Applying a Machine Learning Technique to Classification of Japanese Pressure Patterns

Authors
  • H Kimura
  • H Kawashima
  • H Kusaka
  • H Kitagawa

Abstract

In climate research, pressure patterns are often very important. When a climatologists need to know the days of a specific pressure pattern, for example "low pressure in Western areas of Japan and high pressure in Eastern areas of Japan (Japanese winter-type weather)," they have to visually check a huge number of surface weather charts. To overcome this problem, we propose an automatic classification system using a support vector machine (SVM), which is a machine-learning method. We attempted to classify pressure patterns into two classes: "winter type" and "non-winter type". For both training datasets and test datasets, we used the JRA-25 dataset from 1981 to 2000. An experimental evaluation showed that our method obtained a greater than 0.8 F-measure. We noted that variations in results were based on differences in training datasets.
Year: 2009
Volume 8
Page/Article: S59-S67
DOI: 10.2481/dsj.8.S59
Published on Apr 1, 2009
Peer Reviewed