香山红叶变色日气象统计预测方法研究

采用香山公园逐日黄栌树叶变色率以及相应的气象资料研究了黄栌树叶变色的气象条件,并建立了香山红叶变色日的气象统计预测模型。(1)黄栌树叶变色与临近几天的温度变化关系非常密切,根据气象条件闭值回报变色目的可信度比较高。(2)黄栌树叶平均变色日是10月4—5日,最早为9月27日,最晚为10月13日。(3)黄栌树叶变色日与7月的最低气温、平均气温和最高气温均存在显著的负相关。值得注意的是,黄栌树叶变色日的年际增量与7月降水的年际增量之间存在显著的正相关。(4)选择7月的平均温度和最高温度的年际增量作为预报因子建立模型,1999—2010年回报的平均误差为3d左右。(5)通过2011年独立样本检验和2012年预报试验的结果,可以认为香山红叶变色日气象统计模型具有比较高的准确率和可操作性。

Statistical Prediction Based on Meteorology of Cotinus Coggygria Leaves Discoloration Day in the Fragrant Hill

Based on daily discoloration percentage and meteorological datasets, the meteorological conditions of cotinus coggygria leaves discoloration (CCLD) are studied and the staticstical prediction model is built. The results are as follows: (1) CCLD has a close relationship with temperature variation in the near several days, and the reliability of CCLD Day forecast by meteorological threshold is high. (2) The mean CCLD Day is between October 4 and 5, the earliest CCLD Day is September 27, and the latest one is October 13. (3) There is significant negative correlation between CCLD Day and the mean temperature (also minimum temperature and maximum temperature) in July. It should be noticed that the annual increment of CCLD Day has significant positive correlation with that of precipitation in July. (4) Choosing the annual increment of mean and maximum temperature in July as predictors, the statistical prediction model based on meteorology is built, and the mean error is around 3 days. (5) According to the 2011 independent sample verification and the 2012 forecast experiment, the prediction model of CCLD Day is proved to be usable.