Comparison among Forecast Models of Variation Tendency in Meteorological Data of Macao Single Station
澳门单站气象资料变化趋势的预报模型之比较

Historical data from 1952 to 2001 of two meteorological elements, rainfall and temperature, in time series of year and four seasons of Macao single station are the prime objects of this study, being taken into three statistical forecast models, that is extrapolation of harmonic analysis, open threshold auto-regression and stepwise regression of principal component factors, to execute simulation and put into the forecast trials. Besides having more thorough analysis of the variations of rainfall and temperature in Macao and thus making prediction, the pros and cons of the three models are compared in the study of the meteorological data variation tendency of Macao single station. The results reveal that the performance of predicting the annual and seasonal average temperatures of the three fore cast models are rather satisfactory but have wider gaps in simulating and forecasting the time series of rainfall. In general, with the same data to deal with, the simulation percentage of stepwise regression of principle components of climatic fields is the highest among all the three, with correlation between 0. 821 0. 911, and it performs well except in autumn.