Wang Chunzhi, Zhang Lei, Guo Anhong, et al. Long-term meteorological prediction model on the occurrence and development of rice leaf roller based on atmospheric circulation. J Appl Meteor Sci, 2019, 30(5): 565-576. DOI:  10.11898/1001-7313.20190505.
Citation: Wang Chunzhi, Zhang Lei, Guo Anhong, et al. Long-term meteorological prediction model on the occurrence and development of rice leaf roller based on atmospheric circulation. J Appl Meteor Sci, 2019, 30(5): 565-576. DOI:  10.11898/1001-7313.20190505.

Long-term Meteorological Prediction Model on the Occurrence and Development of Rice Leaf Roller Based on Atmospheric Circulation

DOI: 10.11898/1001-7313.20190505
  • Received Date: 2019-05-10
  • Rev Recd Date: 2019-07-24
  • Publish Date: 2019-09-30
  • To understand the possible influencing mechanism of atmospheric circulation on the occurrence and development of rice leaf roller in China, relationships between atmospheric circulation characteristic indices and ratios of the occurrence area of rice leaf roller in China are fully analyzed from 1980 to 2016. 74 atmospheric circulation characteristic indices and their combinations are analyzed by factor puffing. Results show that 46 indices of these atmospheric circulation characteristic ones have significant influences on the ratio of occurrence area of rice leaf roller, and main influencing periods are from July to September, as well as last July to March. Indices of subtropical high category are most influential, followed by polar vortex category, circulation category, trough category and then others. Among 46 significant atmospheric circulation characteristic factors, 27 subtropical high factors and 10 polar vortex factors, accounting for 59% and 22% of the total, respectively, are the main factors influencing the ratio of the occurrence area of rice leaf roller. 10 key atmospheric circulation characteristic indices that directly influence the ratio of occurrence area of rice leaf roller are determined, and 7 of them have great change at 4 occurrence levels of rice leaf roller as light, partially light, partially severe and severe. 9 prediction models for ratios of the occurrence area of rice leaf roller are established to predict at the beginning of January and March to October. The hindcast of 9 models from 1980 to 2014 are good and accuracies in extending prediction years of 2015-2016 are 86.6%, 90.5%, 91.8%, 93.4%, 93.4%, 94.0%, 94.0%, 94.3% and 95.4%, respectively. Key atmospheric circulation characteristic factors represent climate background for the occurrence area of rice leaf roller very well in China. In the rice-planted area the atmospheric circulation influences the temperature, precipitation, etc., and thus affects the ratio of occurrence area of rice leaf roller. The ratio of the occurrence area of rice leaf roller in dry-warm and wet-warm years is usually larger than that in dry-cold years.
  • Fig. 1  Significant circulation characteristic factors influencing the ratio of occurrence area of rice leaf roller in China

    Fig. 2  Main influencing periods of 46 significant circulation characteristic factors

    Fig. 3  The scatter plot between the occurrence area of rice leaf roller and the corresponding loss of rice production in China

    Fig. 4  Scatter plots between the occurrence area, the ratio of occurrence area of rice leaf roller in China and the average temperature, the average maximum temperature in South China from May to Sep

    (a)the scatter plot between the occurrence area of rice leaf roller in China and the average temperature in South China from May to Sep, (b)the scatter plot between the occurrence area of rice leaf roller in China and the average maximum temperature in South China from May to Sep, (c)the scatter plot between the ratio of occurrence area of rice leaf roller in China and the average temperature in South China from May to Sep, (d)the scatter plot between the ratio of occurrence area of rice leaf roller in China and the average maximum temperature in South China from May to Sep

    Table  1  Key circulation characteristic factors for different occurrence levels of rice leaf roller in China

    关键环流特征因子 关键环流特征因子含义 稻纵卷叶螟发生面积率等级指标
    偏轻 偏重
    51s10d1 上年10月至当年1月亚洲区极涡强度指数 86 83 78 74
    52s3s8 上年3—8月太平洋区极涡强度指数 53 50 46 44
    52d5d6 当年5—6月太平洋区极涡强度指数 49 45 41 35
    31s1d9 上年1月至当年9月南海副高脊线 18 16 13 10
    12s7s10 上年7—10月北半球副高强度指数 183 240 330 391
    66s9s10 上年9—10月东亚槽强度 257 264 275 281
    42s3d8 上年3月至当年8月南海副高北界 22 20 16 10
    64d2d3 当年2—3月亚洲经向环流指数 71 68 62 57
    68d3d4 当年3—4月西藏高原指数 689 701 720 732
    39d2d3 当年2—3月东太平洋副高北界 22 15 4 0
    注:亚洲区和太平洋区极涡强度指数、南海副高脊线和副高北界、亚洲经向环流指数、东太平洋副高北界与中国稻纵卷叶螟发生面积率均呈显著负相关关系;北半球副高强度指数、东亚槽强度、西藏高原指数与之则均呈显著正相关关系;且上述相关系数均达到0.001的显著性水平(样本量为35)。
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    Table  2  Prediction time and periods of prediction factors in prediction models of the ratio of occurrence area of rice leaf roller in China

    模型 预报时间 所用因子时段
    1 当年1月初 上年1—12月
    2 当年3月初 上年1月至当年2月
    3 当年4月初 上年1月至当年3月
    4 当年5月初 上年1月至当年4月
    5 当年6月初 上年1月至当年5月
    6 当年7月初 上年1月至当年6月
    7 当年8月初 上年1月至当年7月
    8 当年9月初 上年1月至当年8月
    9 当年10月初 上年1月至当年9月
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    Table  3  Prediction models of the ratio of occurrence area of rice leaf roller in China for Jan, Mar to Oct

    模型 预报模型 关键环流因子 复相关系数
    x1 x2 x3 x4
    1 =41.48-1.33x1+0.25x2+0.05x3-1.09x4 52s3s8 66s9s10 12s7s10 41s11s12 0.8483
    2 =57.13-1.34x1+0.20x2+0.10x3-1.74x4 52s3s8 66s9s10 12s7s10 42s3d2 0.8602
    3 =86.81-1.29x1+0.23x2-1.48x3-0.39x4 52s3s8 66s9s10 39d2d3 64d2d3 0.8705
    4 =-150.80-1.30x1+0.27x2-1.56x3+0.28x4 52s3s8 66s9s10 28d2d3 68d3d4 0.8665
    5 =-150.80-1.30x1+0.27x2-1.56x3+0.28x4 52s3s8 66s9s10 28d2d3 68d3d4 0.8665
    6 =97.73-1.12x1+0.16x2-1.40x3-0.66x4 52s3s8 66s9s10 39d2d3 52d5d6 0.8662
    7 =97.73-1.12x1+0.16x2-1.40x3-0.66x4 52s3s8 66s9s10 39d2d3 52d5d6 0.8662
    8 =86.44-1.60x1+0.15x2+0.09x3-1.72x4 52s3s8 66s9s10 12s7s10 42s3d8 0.8690
    9 =124.01-0.21x1-0.87x2+0.13x3-2.84x4 51s10d1 64d2d3 12s7s10 31s1d9 0.8695
    注:模型1~9中,各回归方程的复相关系数均达到0.001显著性水平(样本量为35)。
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    Table  4  The hindcast accuracy of prediction models of the ratio of occurrence area of rice leaf roller in China from 1980 to 2014

    模型 预报时间 最大准确率/% 最小准确率/% 平均准确率/%
    1 当年1月初 99.4 55.5 83.7
    2 当年3月初 99.7 59.7 85.2
    3 当年4月初 99.2 60.8 86.1
    4 当年5月初 99.5 55.2 85.2
    5 当年6月初 99.5 55.2 85.2
    6 当年7月初 99.5 58.4 87.6
    7 当年8月初 99.5 58.4 87.6
    8 当年9月初 99.9 65.6 85.5
    9 当年10月初 99.7 65.8 86.1
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    Table  5  The extrapolated accuracy of prediction models of the ratio of occurrence area of rice leaf roller in China from 2015 to 2016

    模型 预报时间 2015年准确率/% 2016年准确率/% 两年预测平均准确率/%
    1 当年1月初 81.9 91.2 86.6
    2 当年3月初 91.7 89.3 90.5
    3 当年4月初 94.1 89.4 91.8
    4 当年5月初 94.9 91.9 93.4
    5 当年6月初 94.9 91.9 93.4
    6 当年7月初 95.6 92.4 94.0
    7 当年8月初 95.6 92.4 94.0
    8 当年9月初 95.2 93.5 94.3
    9 当年10月初 97.9 92.9 95.4
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    Table  6  The year type for larger ratios of the occurrence area of rice leaf roller in China from 1980 to 2016

    区域 年型 偏重发生年份 偏重发生年数 各年型年数 各年型偏重发生年份占比/%
    南方15省(区、市) 干冷年 1991,2004 2 9 22
    干暖年 2003,2006,2007,2009,2011,2013 6 9 67
    湿冷年 1999,2002 2 8 25
    湿暖年 2005,2008,2010,2012,2014,2015 6 11 55
    南方4省(华南3省/区及云南省) 干冷年 2004 1 11 9
    干暖年 1991,2003,2007,2009,2011,2012 6 9 67
    湿冷年 1999,2002 2 9 22
    湿暖年 2005,2006,2008,2010,2013,2014,2015 7 8 88
    注:以稻纵卷叶螟发生面积率不低于48%定为偏重发生年份。
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    • Received : 2019-05-10
    • Accepted : 2019-07-24
    • Published : 2019-09-30

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