A Study of the Objective and Quantifiable Forecasting Based on Optimal Factors Combinations in Precipitation in the Middle and Lower Reaches of the Yangtze River in Summer

A new approach to improve precipitation in the Yangtze River in summer by using the useful historical data is suggested. The outcomes of the model can be improved by determining the years in which there are similar prediction error fields of precipitation based on 74 circulation characteristic indexes of Weather Diagnostic Forecasting Room of National Climate Center and 40 climate indexes of NOAA, and then the fields are integrated to revise the output errors of the model. The results show that the revised errors using the above method are better than system ones. On the basis of the above conclusions, the objective and quantifiable forecasting (OQF) technique can be established. The steps are selecting pre-factors, determining optimal factor combinations (OFC) of the analogy forecasting error fields, and using the method of weighted average integration. It shows that the technique of OQF based on OFC has a better prediction skill to the regression results of independent samples between 2003 and 2009. Finally, the anomaly correlation coefficient (ACC) of historical data in the error field is analyzed. It is found that the determining of the analogy error field in different years can be improved more, and the possible way to improve is to be discussed.