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[目的]建立稻飞虱发生面积的预测模型,从大气环流的角度对每年的发生面积进行预测,指导稻飞虱的防治工作。[方法]分析历年的大气环流特征量的资料,选取与中国稻飞虱发生面积显著相关的大气环流因子,采用逐步回归法,建立预测模型。[结果]筛选出了与稻飞虱发生面积呈显著相关的因子,并分别建立了基于当年10月大西洋欧洲环流型W、当年10月太平洋区极涡面积指数、当年8月北美副高强度指数、当年6月大西洋欧洲环流型W、当年2月北美大西洋副高北界、当年10月大西洋欧洲区极涡强度指数和上年11月亚洲区极涡强度指数的白背飞虱发生面积预测模型和基于当年7月东太平洋副高强度指数、上年10月北半球极涡面积指数、上年11月亚洲区极涡强度指数、当年9月北美大西洋副高北界、当年1月北非大西洋北美副高北界、上年9月太阳黑子和当年9月东太平洋副高面积指数的褐飞虱发生面积预测模型。[结论]通过逐步回归法建立的基于大气环流因子的模型拟合效果较好,可用于实际预测。
[Objective] The research aimed to establish a prediction model of the occurrence area of planthoppers, predict the annual occurrence area from the perspective of atmospheric circulation and guide the control of planthoppers. [Method] The atmospheric circulation characteristic data of the past years were analyzed. The atmospheric circulation factors that were significantly related to the occurrence area of rice planthoppers in China were selected. The regression model was established to establish the prediction model. [Result] The factors which had a significant correlation with the occurrence area of planthoppers were screened out. Based on the current situation of the European circulation in October of that year, the polar vortex area index in the Pacific Ocean in October of that year, the North American subtropical high in August of that year, In June of that year, the Atlantic European circulation pattern W, the northern boundary of the North American subtropical high in February of that year, the Polar Vortex Intensity Index in the Atlantic Ocean of Europe in October of that year and the Polar Point Intensity Polarity Index of Asia in November last year, And based on the July 2007 East Pacific Subtropical High Intensity Index, the polar vortex area index of the Northern Hemisphere in October last year, the polar vortex intensity index of the Asian region in November last year, the northern boundary of the North American subtropical high in September of that year, the North Atlantic North Atlantic High northern boundary, the sunspots of September last year, and the area-predicted model of the brown planthopper occurrence in the subtropical high in the Eastern Pacific in September of that year. [Conclusion] The model fitting based on the atmospheric circulation factor established by the stepwise regression method has a good effect and can be used for the actual prediction.