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基于气候适宜度的江苏水稻气候年景预测方法
徐敏1, 张佩1, 高苹1, 吴洪颜1, 徐经纬2
(1.江苏省气象局;2.南京信息工程大学气象灾害教育部重点实验室/气候与环境变化国际合作联合实验室/气象灾害预报预警与评估协同创新中心/资料同化研究与应用中心)
The Long-term Prediction Method of Rice Annual Agricultural Climate Statusin Jiangsu Province based on Climatic Suitability.
XU Min1, ZHANG Pei1, GAO Ping1, WU Hongyan1, XU Jingwei2
(1.Meteorological Bureau of Jiangsu Province;2.Key Laboratory of Meteorological Disaster,Ministry of Education KLME/Joint International Research Laboratory of Climate and Environment Change ILECE/ Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters CIC-FEMD/ Center for Data Assimilation Research and Application CDARA,Nanjing University of Information Sciences Technology NUIST)
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投稿时间:2018-01-21    修订日期:2018-07-24
中文摘要: 在改进气候适宜度模型参数的基础上,利用1961-2016年70个站的气象观测资料和农业资料,应用统计方法,确定了温度、日照、降水适宜度对水稻气象产量的影响权重,由此构建了年景综合指数及其预测模型。结果表明:日照和降水适宜度与相对气象产量之间存在显著的相关关系,影响权重分别为0.460、-0.428,由于热量资源充足,温度适宜度对气象产量的影响权重偏小(0.113);基于气候适宜度构建的年景综合指数与相对气象产量的相关系数达0.411,说明该指数能较好地表征气候条件对产量形成的综合影响;基于大气环流特征量和太平洋海温等大尺度预报因子,采用最优相关和逐步回归等方法,建立了水稻年景综合指数的预测模型,经过历史拟合和试报检验,效果理想,可投入业务应用,预测结果将为水稻产量分析预测提供科学依据。
Abstract:The influence of temperature, sunshine and precipitation climatic suitability on rice meteorological output was determined based on the meteorological data and agricultural data from 1961 to 2016 by using the statistical analysis and the climate suitability model, which was improved on parameters. The comprehensive index of annual agricultural climate status and its prediction model were constructed. The results show that(1)there is a significant correlation between sunshine and precipitation suitability and relative meteorological output. The influence weight about sunshine and precipitation suitability is 0.460 and -0.428, respectively. Due to sufficient heat resources, the temperature suitability has a small influence on meteorological output (0.113).(2)The correlation coefficient of the composite index of annual agricultural climate status and relative meteorological output based on climate suitability is 0.411, which indicates that the index can better characterize the comprehensive effect of climatic conditions on yield formation.(3)Prediction model of composite index of annual agricultural climate is established by large scale forecast factors such as atmospheric circulation characteristics and Pacific SST using optimal correlation and stepwise regression. Through history matching and try to test, Prediction model’s effect is ideal and can be put into business applications. The prediction results will provide scientific basis for the analysis and prediction of rice yield.
文章编号:201801210047     中图分类号:    文献标志码:
基金项目:江苏省气象局科研基金(KM201707);公益性行业(气象)科研专项(GYHY201306035)。
引用文本:
徐敏,张佩,高苹,吴洪颜,徐经纬,0.[en_title][J].Meteor Mon,():-.
XU Min,ZHANG Pei,GAO Ping,WU Hongyan,XU Jingwei,0.The Long-term Prediction Method of Rice Annual Agricultural Climate Statusin Jiangsu Province based on Climatic Suitability.[J].Meteor Mon,():-.