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Based on the adaptive network fuzzy inference system (ANFIS), methods to filter out the noise of impact factors from the main signal are discussed. Focusing on the abnormal weather conditions in 2010, we use the delay-relevant method to analyze the five members of the summer monsoon system that had the largest effect on the subtropical high anomalies from the observational data. ANFIS is suitable for research and simulation of subtropical highs that are difficult to describe accurately with dynamics, allowing the effect of five factors on the subtropical high anomalies to be examined. Our results show that the Mascarene cold high, the Indian monsoon latent heat flux, and the South China Sea monsoon trough had the largest effect on the subtropical high anomalies. Diagnostic analysis, with genetic algorithms (GA) and dynamical reconstruction theory, reconstructed the nonlinear dynamical model of the subtropical high and its main factors objectively and accurately from the sequence of observations in 2010. Furthermore, a dynamically extended forecast experiment is performed. The forecasts for the subtropical high area index, the Mascarene cold high index, the Indian monsoon latent heat flux, and the South China Sea monsoon trough index all show a strong short-term effect over less than 25 days. The forecasting trend is accurate, and the error rate is no more than 7%. Our results provide new insight and methods for research on the association between the western Pacific subtropical high and the East Asian summer monsoon system, and for the prediction of the western Pacific subtropical high index. 相似文献
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