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Main Influencing Factors of Summer Precipitation and Prediction Method of Annual Increment in Shaanxi
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摘要: 应用1959—2008年夏季（6—8月）NCEP/NCAR月平均500 hPa高度场、海表温度再分析资料及ERA-40气候指数、国家气候中心74项环流特征量等资料，经普查得到6个影响陕西夏季降水的主要因子，分别是西太平洋副热带高压强度指数、赤道平流层准两年振荡指数、低层越赤道气流指数、大气角动量指数、赤道太平洋海温、赤道500 hPa高度。将这些主要因子的年际增量、距平与陕西夏季降水的相关性及其所建立的预测模型进行对比分析，结果表明：因子年际增量具有明显的信号放大作用，增量因子的相关系数平均比距平相关系数高0.1左右；主要因子和夏季降水存在各自的长周期变化，造成其相关性不稳定，经过增量变换后，可以有效滤掉长周期变化，提高因子质量和预测模型的稳定性。前一年秋季赤道中东太平洋海温增量分布与陕西夏季降水相关密切，当该区域出现正增量分布时，当年夏季（6—8月）700 hPa西太平洋副热带高压位置偏北、偏西，形成陕西夏季多雨的环流形势；反之，当该区域出现负增量分布时，当年夏季700 hPa副热带高压位置异常偏东，形成陕西干旱少雨的环流形势。Abstract: Basic conditions that affect main factors of summer precipitation in Shaanxi are determined, which means that the correlation coefficient is high and the significance is verified, the physical meaning is clear, abnormalities of meteorological factors could be reflected and have lasting effect. NCEP/NCAR reanalysis data of the monthly mean 500 hPa height, sea surface temperature, ERA-40 climate index, and 74 meteorological characteristics of National Climate Center are used in the investigation. Six main climatic factors are met by the census, including the western Pacific subtropical high intensity, equatorial strata, zonal wind, lower-level equatorial airflow, atmospheric angular momentum, equatorial Pacific SST, and the equatorial 500 hPa height field. The analysis of the correlation between anomalies of inter-annual increment, the standard deviation in the six incremental factors and the summer precipitation in Shaanxi, showing that the inter-annual increment factor have obvious signal amplification effect. The standard deviation of six increment factors is 1.5 times larger than anomaly factors, and the correlation coefficient of the increment factor is about 0.1. Both predictive factors and predictive variables have long-term changes, and changes are often inconsistent, resulting in unstable factors. After incrementally transformed in meteorological elements, long-term changes of summer precipitation and main factors are effectively filtered out, and the stability of factor quality and prediction model is improved. Based on the increment and anomaly of six main factors, the summer precipitation forecasting model of Shaanxi is established. Results show that the incremental forecasting model have obvious advantages with good accuracy. The cross test of the same rate show that the increment is 70% and the anomaly is 66%. The distribution of SST in the eastern equatorial Pacific in the precious summer is closely related to summer precipitation in Shaanxi. When the annual increment of the sea area is positive, 700 hPa subtropical high is abnormally northerly or westerly in the next summer, the west periphery side of it is strong southerlies, leading to rainy circulation situation. On the contrary, 700 hPa subtropical high being abnormally easterly prone to drought circulation situation in Shaanxi.
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Key words:
- annual increment;
- anomaly;
- summer precipitation
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图 1 陕西夏季降水与西太平洋副热带高压强度指数相关系数
Fig. 1 The correlation coefficient between the index of summer precipitation in Shaanxi and the West Pacific subtropical high intensity
图 2 陕西夏季降水与QBO指数相关系数
Fig. 2 The correlation coefficient between the summer precipitation in Shaanxi and QBO
图 3 陕西夏季降水与低层越赤道气流指数相关系数
Fig. 3 The correlation coefficient between the summer precipitation in Shaanxi and the low-level cross-equatorial flow
图 4 陕西夏季降水与大气总体角动量指数相关系数
Fig. 4 The correlation coefficient between the summer precipitation in Shaanxi and the atmospheric angular momentum
图 5 陕西夏季降水与前一年10月海温增量(a)及海温距平(b)相关系数分布
(阴影区表示达到0.05显著性水平)
Fig. 5 The correlation coefficient between the summer precipitation in Shaanxi and the previous Oct SST(the shaded denotes passing the test of 0.05 level)
(a)SST increment, (b)SST anomaly
图 6 陕西夏季降水与Niño1+2区海温指数相关系数
Fig. 6 The correlation coefficient between the index of the summer precipitation in Shaanxi and Niño1+2
图 7 前一年秋季海温增量出现正分布(a)、负分布(b)后当年6—8月700 hPa流场
Fig. 7 700 hPa flow field from Jun to Aug after positive SST increment distribution(a) and negative SST increment(b) in previous autumn
图 8 陕西夏季降水与前一年12月500 hPa高度场增量(a)及其距平(b)相关系数分布
(阴影区表示达到0.05显著性水平)
Fig. 8 The correlation coefficient between the summer precipitation in Shaanxi and 500 hPa height in previous Dec(the shaded denotes passing the test of 0.05 level)
(a)500 hPa height increment, (b)500 hPa height anomaly
图 9 陕西夏季降水Marr小波变换
(a)降水增量，(b)降水距平
Fig. 9 The Marr wavelet transform of summer precipitation in Shaanxi
(a)precipitation increment, (b)precipitation anomaly
表 1 主要因子与陕西夏季降水的相关系数
Table 1 The correlation between forecast factor and summer precipitation in Shaanxi
类型 X1 X2 X3 X4 X5 X6 因子增量 0.49 0.50 0.52 0.45 0.63 0.64 因子距平 0.42 0.39 0.43 0.38 0.57 0.46 
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表 2 2009—2014年增量预测模型、距平预测模型降水距平百分率预测结果
Table 2 Results of prediction modes of increment and anomaly from 2009 to 2014
年份 增量模型预测值/% 距平模型预测值/% 实测值/% 增量预测相对误差百分率/% 距平预测相对误差百分率/% 2009 5.7 11.9 3.3 2.3 8.3 2010 5.4 -14.6 31.9 -20.0 -35.5 2011 18.8 -10.9 0.1 18.6 -11.0 2012 10.7 2.8 -2.5 13.5 5.4 2013 -5.8 -8.9 -0.1 -5.7 -8.8 2014 9.9 -1.4 -23.1 42.7 28.1
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表 3 滤掉因子长周期变化后的相关系数比较
Table 3 The correlation coefficient of factors without long-periodic variations
相关系数 X1 X2 X3 X4 X5 X6 因子距平相关系数 0.41 0.30 0.41 0.36 0.54 0.50 滤掉趋势项变化后因子距平相关系数 0.45 0.35 0.49 0.37 0.54 0.47 因子增量相关系数 0.55 0.42 0.49 0.46 0.56 0.66
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