| 基于Fisher判别的南方双季稻低温灾害等级预警 |
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| 引用本文： | 吴立,霍治国,杨建莹,肖晶晶,张蕾,于彩霞,张桂香.基于Fisher判别的南方双季稻低温灾害等级预警[J].应用气象学报,2016,27(4):396-406. |
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| 作者姓名： | 吴立 霍治国 杨建莹 肖晶晶 张蕾 于彩霞 张桂香 |
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| 作者单位： | 1.中国气象科学研究院，北京 100081 |
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| 基金项目： | 资助项目： “十二五”国家科技支撑计划课题（2011BAD32B02） |
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| 摘 要： | 为了建立南方双季稻低温灾害综合预测预警技术体系, 基于南方双季稻种植区1961—2010年708个气象站的逐日气象资料、水稻生育期资料和低温灾害发生的气象行业标准，采用Fisher判别分析法、因子膨化法、相关性分析法，利用SPSS软件构建早稻春季低温灾害高风险区 (Ⅰ区) 未来10 d、晚稻寒露风高风险区 (Ⅰ区)、主灾区 (Ⅱ区) 未来5 d的低温灾害发生等级逐日滚动预警模型。其中，1961—2009年资料用于模型构建和回代检验，2010年资料用于模型的外延预测。结果表明:早稻、晚粳稻、晚籼稻Ⅰ区平均外延预测基本一致准确率分别达到90.5%，74.2%，80.3%，晚粳稻、晚籼稻Ⅱ区平均外延预测基本一致准确率分别为89.4%和80.3%。构建的南方双季稻低温灾害逐日滚动预警模型的外延预测基本一致准确率多超过80%，等级预测检验误差总体上在1个等级以内，模型评价效果较好。
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| 关 键 词： | 双季稻 低温灾害 因子膨化 Fisher判别 |
| 收稿时间： | 2015-10-09 |
Early-warning of Low-temperature Disaster Levels on Double-cropping Rice in Southern China Based on Fisher's Discriminant |
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| Wu Li,Huo Zhiguo,Yang Jianying,Xiao Jingjing,Zhang Lei,Yu Caixia and Zhang Guixiang.Early-warning of Low-temperature Disaster Levels on Double-cropping Rice in Southern China Based on Fisher's Discriminant[J].Quarterly Journal of Applied Meteorology,2016,27(4):396-406. |
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| Authors: | Wu Li Huo Zhiguo Yang Jianying Xiao Jingjing Zhang Lei Yu Caixia and Zhang Guixiang |
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| Institution: | 1.Chinese Academy of Meteorological Sciences, Beijing 1000812.Collaborative Innovation Center of Meteorological Disaster Forecast, Early-warning and Assessment, Nanjing University of Information Science & Technology, Nanjing 2100443.Zhejiang Provincial Climate Center, Hangzhou 3100174.National Meteorological Center, Beijing 1000815.Anhui Institute of Meteorological Science, Hefei 230031 |
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| Abstract: | Rice is the main food crop in southern China. So far, low-temperature disaster has become one of the main agricultural meteorological disasters which influence the production of rice. Spring low-temperature disaster of early rice and autumn cold dew wind of late rice are the main low-temperature disasters in double-cropping rice growing areas in southern China. However, the frequency of low-temperature disaster has decreased in some regions while increased in other regions, and the damage to the rice yield even increases under the background of global warming. In order to reduce the yield loss and build comprehensive forecasting and early-warning technical architecture, the low-temperature disaster is deeply looked into. Using the software SPSS and methods of factor puffing, correlation analysis and Fisher's discriminant, a series of data are analyzed, including daily meteorological data, rice growing period data from 708 weather stations located in the planting region of double-cropping rice in the south during 1961-2010, together with meteorological industry standards. An early-warning model is established to forecast low-temperature disasters for spring rice in high risk areas (area Ⅰ) 10 days in advance, and for autumn rice in both high risk areas (areaⅠ) and main disaster areas (area Ⅱ) 5 days in advance.Based on data during 1961-2009, the model constructed is used for hindcast, and data of 2010 is used for evaluation. The average basically consistent accuracy of the early-warning model in area Ⅰ of early rice, late japonica rice and late indica rice is 90.5%, 74.2% and 80.3%, respectively. As for area Ⅱ of late japonica rice and late indica rice, the average basically consistent accuracy of the early-warning model is 89.4% and 80.3%, respectively. On the whole, the average basically consistent accuracy of the early-warning model is above 80%, and the error is within one level, showing good efficiency. |
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