摘要
选择上年1月至当年4月为预报时段,采用预报因子膨化技术,将大气环流特征量按月依次组合成不同时段,计算出不同膨化时段的74项大气环流特征量距平值。从这些值中选出与全国小麦条锈病发病面积率距平相关显著的关键时段关键环流因子,建立了全国小麦条锈病发病面积率距平预报模型Ⅰ。与未采用因子膨化技术建立的预报模型Ⅱ相比,模型I的预报准确率有显著的提高。同时发现,大气环流特征量与全国小麦条锈病发生流行之间存在着很好的相关性。
By using predictor puffing method, this paper calculated and analyzed the anomalies of 74 atmospheric circulation characteristics during various periods which were puffed from last January to April of this year. The key atmospheric circulation factors and corresponding key periods, which were significantly related to incidence area rate anomaly of wheat stripe rust, were selected to establish forecasting model Ⅰ which can predict the incidence area rate anomaly of wheat stripe rust. In contrast with forecasting model Ⅱwithout predictor puffing, the prediction accuracy of forecasting model Ⅰis greatly enhanced. There is a remarkable relation between 74 atmospheric circulation characteristics and wheat stripe rust incidence.
出处
《自然灾害学报》
CSCD
北大核心
2006年第6期109-113,共5页
Journal of Natural Disasters
基金
中国气象局预测减灾应用技术开发推广项目资助(CMATG2005Z02)
关键词
小麦条锈病
大气环流特征量
因子膨化
发病面积率预报
wheat stripe rust
atmospheric circulation characteristics
factor puffing
incidence area rate forecast
