Ergodicity Analysis of Air Temperature Variation Process of Shanghai
Wenyi Zeng · Journal of Tianjin University Science and Technology · 2010
Estimation of statistic properties of infinite air temperature process with finite temperature materials is significant and fundamental to mid-term and long term climate forecast and global climate change studies.Therefore,ergodicity analysis of air temperature is an important research topic.In this paper,a commonly applicable ergodic property analysis model based on fuzzy-rough C-means clustering method(FRCM),autocorrelogram,advanced Dickey and Fuller(ADF) and fuzzy least square regression(FLSR) has been proposed.The air temperature time series(1873—1997) from Shanghai hydrology station has been calculated and analyzed according to the proposed model.Results show that month-highest and month-lowest air temperatures in July and August have not only mean ergodic properties but also covariance ergodic properties.Thus the air temperature variation process is ergodic.In the long run,month-highest and month-lowest air temperatures in July and August will not keep on rising.Instead,they will fluctuate around the mean value.In the last section,the above conclusion has been confirmed by further analysis and temperature variations in Shanghai are further discussed,which corroborates some previous studies from the point of ergodicity.