为减小年际间气温变化对昆虫有效积温预测误差的影响，以新疆石河子垦区121 团棉铃虫Helicoverpa
armigera(Hübner)羽化高峰期为例，利用single sine 模型分别计算12 年2 种有效积温范围(10 ～ 30℃和10 ～ 35℃ )
的累计有效积温值，并获得其多年平均值，依此进行棉铃虫羽化高峰期预测;通过当年与12 年(有效积温＞ 0 日期
至羽化高峰日期)平均气温之差，对预测误差进行校正。结果表明:当年平均气温与12 年平均值差值越大，预测
误差也越大;各代直线回归校正模型均达到显著水平(P ＜ 0. 05) ;2 种有效积温范围下，校正后各代平均预测误差
天数均有所减少，对越冬代误差校正效果最优，校正后各代历史符合率分别为83. 33% 、100% 、100% 和100% 、
100% 、93. 33% 。该校正方法能够显著提高预测准确度，尤其适用于年际间棉铃虫发育期间平均气温变化较大的
代别和地区，同时可为多种害虫预测误差校正提供了依据。

In order to reduce the effect of year temperature variations on effective accumulated temperature forecasting
error，we calculated the effective accumulated temperatures of 12 years separately and the average level in two effective
accumulated temperature ranges ( 10 － 30℃，10 － 35℃ ) with a single sine model in Farm 121，Xinjiang． We then
predicted eclosion peaks of Helicoverpa armigera ( Hübner) in different years based on the average level． Finally，we
corrected the number of forecasted error days through the difference between the average temperature of the forecasted year
and that of the 12 year period ( date from effective accumulated temperature above 0℃ to eclosion peak) ． The results
indicate that the prediction error was larger when there were larger gaps between single years and 12 year average
temperatures． A linear regression model of all generations was significant level ( P ＜ 0． 05 ) ． In the two effective
accumulated temperature ranges，the number of corrected forecasted error days was fewer than uncorrected in all
generations． The method was more effective for overwintering generations; historical coincident rates of all generations
were 83. 33% ，100% ，100% and 100% ，100% ，93. 33% ，respectively． This method can improve forecasting
accuracy，especially for generations and regions in which average temperatures vary greatly between years． It also can
provide a theoretical foundation for reducing the forecasting error for many other pests．