中国农业气象

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新疆棉花低温冷害逐步回归预测模型

陈玥熤;郭建平;   

  1. 中国气象科学研究院;
  • 出版日期:2008-08-10 发布日期:2008-08-10
  • 基金资助:
    “十一五”国家科技支撑计划重点项目(2006BAD04B02)

Stepwise Regression Prediction Model for Cotton Cold Damage in Xinjiang Uygur Autonomous Region

CHEN Yue-yi,GUO Jian-ping(Chinese Academy of Meteorological Sciences,China Meteorological Administration,Beijing 100081,China)   

  • Online:2008-08-10 Published:2008-08-10

摘要: 为及时采取防御措施和减轻低温冷害对新疆棉花生产的严重影响,利用1961-2005年逐日平均温度资料、棉花多年产量和发育期资料,计算了新疆主要棉区棉花的热量指数,确定了低温冷害的热量指数指标,可以较好地判断预报年新疆主要棉区的冷害发生情况及灾害程度。在此基础上以74类大气环流特征量为预测因子,从棉花的播种期开始到停止生长,逐月滚动建立了各个棉区热量指数的逐步回归模型。各月模型的预测准确率达到90%以上,能较好地预测该区棉花生长季内的热量状况;且可以看出,预报月前期的高纬度极涡环流系统的特征对新疆棉花生长的热量条件有着重要影响。从研究结果可知,通过运用滚动预报的方法,可以有效地提高预测棉花生长季内热量指数的准确率,从而更准确地预测冷害发生年,为棉花生产布局和及时采取防冻措施提供参考。

关键词: 棉花, 热量指数, 逐步回归, 滚动预报

Abstract: In order to make relevant agricultural precaution in time and reduce the impacts of the cold disaster on cotton production,the cotton heat indexes were calculated and the cool injury indexes were defined in the main cotton production regions in Xinjiang Uygur Autonomous Region,by using the data of mean daily air temperature,cotton growing period and local cotton yields from 1961 to 2005.The occurrence status and extend of the cool injury were well decided in main cotton regions in Xinjiang during the predicted year.Considering 74 types of atmospheric circulation characteristics(ACC),the stepwise regression models of cotton heat indexes were set up,which was monthly calculated from the cotton seeding to stopping growth in the main cotton regions of Xinjiang.The results showed that each model could well forecast heat status in each region during the cotton growing period,and the all of the accuracy rate was above 90%.The characteristics of polar vortex in high latitude before the predicted month had important effect on the heat conditions of cotton growth in Xinjiang.The validation showed that the predicting accuracy rate for cotton heat indexes was effectively improved and the cold years were predicted more accurately by the method of rolling forecasting monthly.This study provided a favorable basis for the arrangement and measures of the cotton production.

Key words: Cotton, Cotton, Heat index, Stepwise regression, Rolling forecast