环渤海夏蝗发生程度气象集成预报方法

姚树然; 关福来; 李春强

环渤海夏蝗发生程度气象集成预报方法

1.
河北省气象与生态环境重点实验室河北省气象科学研究所, 石家庄 050021
2.
河北省气象局, 石家庄 050021

资助项目:

科技部农业转化资金项目 2007GB24160444

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出版历程
- 收稿日期: 2009-11-02
- 修回日期: 2010-07-06
- 刊出日期: 2010-10-31

An Integrated Bio meteorological Forecasting Method for the Occurrence Level of Locust Around the Bohai Sea of China

1.
Hebei Provincial Key Lab for Meteorological and Eco-environment, Hebei Provincial Meteorological Institute, Shijiazhuang 050021
2.
Hebei Provincial Meteorological Bureau, Shijiazhuang 050021)

摘要

摘要: 东亚飞蝗发生程度与气象条件关系密切，该文使用1980—2008年的飞蝗资料和气象资料，选择了环渤海4种典型（沿海、水库、洼淀、内涝）蝗区，利用秩相关系数法筛选影响飞蝗发生程度的气象因子，确定了影响不同蝗区夏蝗发生程度的气象因子指标集。利用权重修正气象距离法，建立了气象距离指标预报模型；依据飞蝗自身生物学特性，建立了生物学预报模型。在此基础上，基于蝗虫生物学和气象条件影响的共同作用，建立了夏蝗发生程度的生物气象集成长期预报模型。结果表明：在环渤海飞蝗区域，不同类型蝗区影响气象因子有一定差别，集成预报模型趋势预报准确率高于其他模型。
- 夏蝗发生程度;
- 气象条件;
- 距离模型;
- 集成预报
Abstract: Locust is an important loss causing pest around the Bohai Sea of China, and its occurrence degree is close related with weather and climate conditions. In order to study the relationship objectively, four typical locust areas around the Bohai Sea are chosen as experimental areas, which are coast, reservoir, depression shallow lake and water logging areas, respectively. Based on the observed climate and locust data from 1980 to 2008, Spearman order correlation method is used to analyze the meteorological factors affecting the occurrence degree of locust. The results show that meteorological factors have accumulated effects on locust. The temperature in July and August has a significant effect on summer locust of the next year in four locust areas, and higher temperature is more favorable for locust growth and reproduction. October is the key time for the egg life of autumn locust in three areas (reservoir, depression shallow lake and water logging areas), and sufficient rainfall is favorable for the development of locust egg, increasing the occurrence degree of summer locust in the next year. In addition, air temperature in winter and spring and rainfall affect the extent of summer locust in four areas before locust eggs hatch and come out of soil. The historical modeled accuracy are 81%—93% and 78%—89% by the Euclidean distance model modified with the weights of meteorological factors and biological model based on locust bio characteristics for predicting the locust extent, respectively. The extended forecast result of last two years is fairly accurate, i.e., one level difference for one area of the former model and one level difference for two areas of the latter model, and correct in all other areas. Then a comprehensive model is established by integrating the meteorological and biological models to forecast the locust occurrence extent and its historical modeled accuracy are 85%—96%. There is only one level difference in one area for the two years extended forecast, showing that the accuracy of integrated model is better than the single models.
- locust occurrence extent;
- meteorological conditions;
- Euclidean distance model;
- integrated predicting

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表 1 影响环渤海不同蝗区的主要气象因子及秩相关系数

Table 1 ajor meteorological factors and rank correlation coefficient affecting the locust-infested areas around the Bohai Sea

表 2 基于气象距离比的环渤海不同蝗区夏蝗发生程度等级指标

Table 2 he indexes of meteorological Euclidean distance ratio for predicting the locust occurrence extent

表 3 环渤海不同蝗区夏蝗自身潜能预报模型

Table 3 The self-biotic predicting model of locust around the Bohai Sea

表 4 不同预报模型的夏蝗发生程度历史拟合率比较

Table 4 Historical fitting accuaracy of three types of predicting models for the locust extent

表 5 不同预报模型的夏蝗发生程度延伸预报与实际情况比较

Table 5 Forecasting effects for different models of locust

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