中国农业气象

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江苏省褐飞虱迁入量的中长期预测模型

包云轩,薛周华,刘 垚,蒋 蓉,谢晓金,杨荣明,朱 凤   

  1. 1南京信息工程大学气象灾害预报预警与评估协同创新中心,南京 210044;2.江苏省农业气象重点实验室/南京信息工程大学,南京 210044;3.福建省福安市气象局,福安 355000;4.江苏省植物保护站,南京 210013
  • 收稿日期:2015-05-04 出版日期:2016-02-20 发布日期:2016-02-24
  • 作者简介:包云轩(1963-),博士,教授,主要研究方向为气候变化与防灾减灾、应用气象、病虫害测报学。 E-mail:baoyx@nuist.edu.cn; baoyunxuan@163.com
  • 基金资助:

    国家自然科学基金面上项目(41075086;41475106);江苏省农业科技自主创新项目[SCX(12)3058];江苏省高校自然科学研究重大项目(14KJA170003);江苏省高校优势学科建设工程

Medium and Long-term Forecasting Models of Nilaparvata lugens (st?l)’s Immigration Amount in Jiangsu Province

BAO Yun-xuan, XUE Zhou-hua, LIU Yao, JIANG Rong, XIE Xiao-jin, YANG Rong-ming, ZHU Feng   

  1. 1.Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China;2.Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044;3.Meteorological Bureau of Fu’an City in Fujian Province, Fu’an 355000;4.Jiangsu Province Plant Protection Station, Nanjing 210013
  • Received:2015-05-04 Online:2016-02-20 Published:2016-02-24

摘要:

根据1983-2010年江苏省褐飞虱灯诱资料及1982-2010年全球海温场资料和美国国家环境预测中心(NCEP)气象再分析资料,对江苏稻区代表站高邮、通州和宜兴的褐飞虱迁入量与前一年1月-当年6月太平洋海温场、前一年12月-当年6月中南半岛近地表气温场和前一年7月-当年6月北半球大气环流特征量的相关关系进行分析,并运用逐步回归方法建立一系列褐飞虱年总迁入量的预测预报方程。结果表明:(1)高邮、通州和宜兴3站的褐飞虱迁入量在不同时空阈限内与太平洋海温场、中南半岛气温场和北半球大气环流特征量之间存在不同程度的相关性。3站褐飞虱迁入量的对数值与前一年海温场呈负相关,其中与通州和宜兴站褐飞虱迁入量对数值相关显著的海温区主要分布在北、中太平洋,高邮站则在南太平洋;高邮站褐飞虱迁入量的对数值与前一年12月和当年4月中南半岛西南部的近地表气温场呈正相关,通州站与前一年12月和当年2、3月中南半岛北部的近地表气温场呈负相关,宜兴站与当年1、3月中南半岛西南部的近地表气温场呈正相关、与当年4月中南半岛大部的近地表气温场呈负相关;3站褐飞虱迁入量的对数值主要与前一年7月-当年6月的各副高指数、各极涡指数、大西洋欧洲环流型、亚洲纬向环流指数、东亚槽强度、冷空气强度、西太平洋编号台风强度、南方涛动指数等相关显著。(2)从上述海温场、气温场和环流特征量中筛选出显著相关(P<0.05)的因子作为预测因子,建立褐飞虱年迁入量的预测模型,并筛选出回检正确率70%以上、预检正确率66.7%以上模型17个,适用性评估表明,各模型的预报结果与实测值基本吻合,表明模型可应用于单站褐飞虱年迁入量的预测。

关键词: 褐飞虱迁入量, 海平面温度距平, 中南半岛气温场, 大气环流特征量, 相关分析

Abstract:

In order to predict the annual total immigration heads of brown planthoppers (BPH), Nilaparvata lugens (st?l), at a station in a rice-growing region by using the atmospheric background fields in the earlier stages and provide a basis for the early warning of BPH’s catastrophic immigrations and their effective prevention and controlling, the BPH’s lighting catches of all plant protection stations in Jiangsu Province during the period from 1983 to 2010 and the reanalyzed meteorological data from the National Center of Environmental Predicting (NCEP) in USA during the period from 1982 to 2010 were collected to analyze the teleconnections between the BPH’s annual total immigration heads of Gaoyou, Tongzhou and Yixing as the representative plant protection stations in the different rice-growing regions of Jiangsu Province and the sea surface temperature anomalies (SSTA) on the Pacific Ocean from January of the preceding year to June of the present year, the temperature field of Indo-China Peninsula (T-INP) from December of the preceding year to June of the present year and the atmospheric circulation characteristic variables (ACCV) from July of the preceding year to June of the present year. A stepwise regression method was used to establish a series of the forecasting models for the annual total immigration heads of BPH at the three stations. The results showed as follows: (1) there were the correlations of different extents between the BPH’s immigration heads of Gaoyou, Tongzhou and Yixing and the SSTA on the Pacific Ocean, the T-INP and the ACCV on the Northern Hemisphere in the different temporal and spatial thresholds. The significant negative correlations exist between the logarithms of BPH’s annual total immigration heads at the three stations and the SSTA in the preceding year. Among them, the remarkable correlative regions between the logarithms of BPH’s annual total immigration heads at Tongzhou and Yixing and the SSTA on the Pacific Ocean mainly distributed on the northern and middle Pacific Ocean and the obvious correlative regions at Gaoyou situated in the southern Pacific. There were the positive correlations between the logarithms of BPH’s annual total immigration heads at Gaoyou and the T-INP in December of the preceding year and April of the present year, the negative correlations between the logarithms of BPH’s annual total immigration heads at Tongzhou and the T-INP in December of the preceding year, February and March of the present year and the positive correlations between the logarithms of BPH’s annual total immigration heads at Yixing and the T-INP in January and March of the present year, but the negative correlations between the logarithms of BPH’s annual total immigration heads at Yixing and the T-INP in April of the present year. The logarithms of BPH’s immigration heads at the three stations had the significant relationships with the characteristic indices of all subtropical highs, the characteristic indices of all polar vortexes, the atmospheric circulation types on the Atlantic Ocean and Europe, Zonal circulation indices on Asia, the strength of East Asian trough, the strength of cold air in East Asia, the strength of serial number typhoons on West Pacific and the indices of Southern Oscillation during from July of the preceding year to June of the present year. (2)Some significant factors (P<0.05) screened from the above factors were used as the key predictors to establish the forecast models for the BPH’s annual total immigration heads of the three stations and 17 forecast equations with the historical fitting accordance of more than 70% and the pre-examination accuracy rate of more than 66.7% were selected from the established models. The results of applicability evaluation on these equations displayed that the fitting values of these models were identical to the observed values on the whole and the models were feasible in the predicting practice of BPH’s annual total immigration amount at a station in a rice-growing region.

Key words: Immigration heads of Nilaparvata lugens (St?l), SSTA (sea surface temperature anomaly), T-INP temperature field of Indo-China Peninsula), ACCV (atmospheric circulation characteristic variable), Correlation analysis