Main Influencing Factors of Summer Precipitation and Prediction Method of Annual Increment in Shaanxi

Xiao Keli; Zhao Guoling; Fang Jiangang; Sun Xian

doi:10.11898/1001-7313.20170407

Vol.28, NO.4, 2017

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Xiao Keli, Zhao Guoling, Fang Jiangang, et al. Main influencing factors of summer precipitation and prediction method of annual increment in Shaanxi. J Appl Meteor Sci, 2017, 28(4): 458-469. DOI: 10.11898/1001-7313.20170407.

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Xiao Keli, Zhao Guoling, Fang Jiangang, et al. Main influencing factors of summer precipitation and prediction method of annual increment in Shaanxi. J Appl Meteor Sci, 2017, 28(4): 458-469. DOI: 10.11898/1001-7313.20170407.

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Main Influencing Factors of Summer Precipitation and Prediction Method of Annual Increment in Shaanxi

DOI: 10.11898/1001-7313.20170407

1.
Shaanxi Meteorological Training Center, Xi'an 710016
2.
Shaanxi Provincial Meteorological Society, Xi'an 710016
3.
Shaanxi Provincial Meteorological Bureau, Xi'an 710014
4.
Shaanxi Provincial Climate Center, Xi'an 710014

Received Date: 2017-01-03
Rev Recd Date: 2016-01-13
Publish Date: 2017-07-31

Abstract

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.
- annual increment;
- anomaly;
- summer precipitation

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References(46)

Figures and Tables

Fig. 1 The correlation coefficient between the index of summer precipitation in Shaanxi and the West Pacific subtropical high intensity

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Fig. 2 The correlation coefficient between the summer precipitation in Shaanxi and QBO

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Fig. 3 The correlation coefficient between the summer precipitation in Shaanxi and the low-level cross-equatorial flow

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Fig. 4 The correlation coefficient between the summer precipitation in Shaanxi and the atmospheric angular momentum

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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

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Fig. 6 The correlation coefficient between the index of the summer precipitation in Shaanxi and Niño1+2

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Fig. 7 700 hPa flow field from Jun to Aug after positive SST increment distribution(a) and negative SST increment(b) in previous autumn

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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

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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

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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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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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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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