基于BP神经网络的义乌市梅雨量的预测研究
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摘要
针对梅雨量的多寡可决定水库蓄水量的多少,而有助于判定人工增雨作业时机这一现实问题,通过构建具有明确的气候背景的义乌市梅雨量BP神经网络预报模型,并以相同的预报因子所组成的历史样本,建立了逐步回归预报模型作为预测效果对比模型,对未来一年(2010年)义乌市梅雨量进行了分析和预测。主要的研究成果有：
(1)义乌市梅雨总体上存在着以11a为准周期的相对丰水期、枯水期变化特征,同时也与太阳活动的22 a周期存在着对应关系。
(2)义乌市梅雨量对厄尔尼诺/拉尼娜现象存在着较为显著的响应关系。
(3)影响义乌市梅汛期雨量的北半球500 hPa高度场的3项因子和全球海温场的7项因子分别集中在北半球中高纬度和赤道附近太平洋中北部地区。
(4)影响义乌市梅汛期雨量的500 hPa大气环流因子主要集中在北半球高纬度,从而验证了长江中下游梅雨期的持续稳定与乌拉尔山和鄂霍次克海高压脊或者阻塞高压的建立和维持密切相关；前期海温异常与义乌市梅汛期降水量具有较好的相关关系,最显著的相关区为上一年12月份至次年4月份的西太平洋暖池附近、北大西洋,上一年12月份至次年2月的赤道中东部太平洋的加纳利寒流区,以及1月份的赤道附近南印度洋海区。但作为先兆信号的前期初选预报因子如何影响义乌市梅雨量的物理过程有待进一步探究。
(5)和传统的逐步回归预报模型相比,BP神经网络预报模型对义乌市梅雨量的预报具有一定优势,可利用其预报未来一年的义乌市梅雨量。最后,制定了梅雨量的分级标准和步骤,对试报效果较好的BP神经网络预报模型的预测值进行分级评定,并用预测值对梅雨量的基本等级进行修正,综合得出预测值区间。在具体业务预报中,对梅雨量分级预测需要考虑此年的周期性因素以及海气状况,即关注厄尔尼诺(拉尼娜)事件是否确实发生。
(6)2010年义乌市不需要在梅雨季节时实施人工增雨,该区域天然降水量基本可满足在伏旱季节实际生产和生活用水的需要。
The amount of Meiyu rainfall could decide how much water to be stored in reservoirs and could help to determine the exact moment of artificial precipitation operation. Therefore, aim at this practical problem, this paper constructed the BP neural network forecast model of Meiyu rainfall with the definitive climate background to analyze and forecast the Meiyu rainfall of the coming year (2010) in Yiwu city. At the same time, it had established the stepwise regression forecast model by the historical samples that consist of the same predictor, which was as a model for comparison to compare the various results. Main research results were as follows:
(1) The Meiyu in Yiwu city generally existed relative change characteristics of flood period and dry season over an quasi-periodic 11-year cycle, and there were corresponding relationship of sun's activity waxes and wanes on an 22-year cycle.
(2) There were relatively remarkable response relationship of the Meiyu rainfall in "Yiwu city to El nino/la Nina.
(3) The 3 items factor of the northern hemisphere 500-hPa geopotential height field and the 7 items factor global SST field,which affected the Meiyu rainfall in Yiwu, respectively concentrated in the northern hemisphere middle and high latitudes and the north-central areas of northern Pacific Ocean near the equator.
(4) The 3 items factor of the northern hemisphere 500-hPa geopotential height field,which affected the Meiyu rainfall in Yiwu, mainly concentrated in the northern hemisphere high latitudes, thus validated that the persist stabilization of the Meiyu period of the lower-middle reaches of the Yangtze River correlated closely to the establishing and maintaining of the ridge of high pressure or blocking high above the Urals and the Sea of Okhotsk; The prophase abnormality of SST had a strong correlation with the Meiyu rainfall in Yiwu, and the most correlated zones were as follows:the Western Pacific Warm Pool and the North Atlantic between last December to the following April, Canary cold snap zone of the north-central areas of northern Pacific Ocean near the equator between last December to the following February, and the southern Indian Ocean near the equator on January. But as a omen signal of the previous primaries predictor,the physical process which is how to affect the Meiyu rainfall in Yiwu needed to be further explored.
(5) Compared with the traditional stepwise regression forecast model, the BP neural network forecast model for the forecasting of Meiyu rainfall in Yiwu city had certain advantages,which could be used to forecast the Meiyu rainfall of the coming year in Yiwu city. Finally, it had set a standard and process for the classification of the Meiyu rainfall,in order to rate and evaluate the predictive values which were the results from the BP neural network forecast model that had the better result of test forecast. That in turn modified the basic grades of the Meiyu rainfall and obtained the intervals of forecast data by the synthesis of the processing results. In operational practice forecasting, to the grading prediction of Meiyu rainfall, there were cyclical factors and the heating state above the surface between sea and atmosphere in the year, concentrating on whether the El nino/la Nina actually happened, that had to be taken into account.
(6) In 2010, the natural precipitation in this region could basically meet the water demands of actual productive and domestic uses in summer drought season. Therefore, it did not need to take artificial precipitation operation in Yiwu city this year.
(1)义乌市梅雨总体上存在着以11a为准周期的相对丰水期、枯水期变化特征,同时也与太阳活动的22 a周期存在着对应关系。
(2)义乌市梅雨量对厄尔尼诺/拉尼娜现象存在着较为显著的响应关系。
(3)影响义乌市梅汛期雨量的北半球500 hPa高度场的3项因子和全球海温场的7项因子分别集中在北半球中高纬度和赤道附近太平洋中北部地区。
(4)影响义乌市梅汛期雨量的500 hPa大气环流因子主要集中在北半球高纬度,从而验证了长江中下游梅雨期的持续稳定与乌拉尔山和鄂霍次克海高压脊或者阻塞高压的建立和维持密切相关；前期海温异常与义乌市梅汛期降水量具有较好的相关关系,最显著的相关区为上一年12月份至次年4月份的西太平洋暖池附近、北大西洋,上一年12月份至次年2月的赤道中东部太平洋的加纳利寒流区,以及1月份的赤道附近南印度洋海区。但作为先兆信号的前期初选预报因子如何影响义乌市梅雨量的物理过程有待进一步探究。
(5)和传统的逐步回归预报模型相比,BP神经网络预报模型对义乌市梅雨量的预报具有一定优势,可利用其预报未来一年的义乌市梅雨量。最后,制定了梅雨量的分级标准和步骤,对试报效果较好的BP神经网络预报模型的预测值进行分级评定,并用预测值对梅雨量的基本等级进行修正,综合得出预测值区间。在具体业务预报中,对梅雨量分级预测需要考虑此年的周期性因素以及海气状况,即关注厄尔尼诺(拉尼娜)事件是否确实发生。
(6)2010年义乌市不需要在梅雨季节时实施人工增雨,该区域天然降水量基本可满足在伏旱季节实际生产和生活用水的需要。
The amount of Meiyu rainfall could decide how much water to be stored in reservoirs and could help to determine the exact moment of artificial precipitation operation. Therefore, aim at this practical problem, this paper constructed the BP neural network forecast model of Meiyu rainfall with the definitive climate background to analyze and forecast the Meiyu rainfall of the coming year (2010) in Yiwu city. At the same time, it had established the stepwise regression forecast model by the historical samples that consist of the same predictor, which was as a model for comparison to compare the various results. Main research results were as follows:
(1) The Meiyu in Yiwu city generally existed relative change characteristics of flood period and dry season over an quasi-periodic 11-year cycle, and there were corresponding relationship of sun's activity waxes and wanes on an 22-year cycle.
(2) There were relatively remarkable response relationship of the Meiyu rainfall in "Yiwu city to El nino/la Nina.
(3) The 3 items factor of the northern hemisphere 500-hPa geopotential height field and the 7 items factor global SST field,which affected the Meiyu rainfall in Yiwu, respectively concentrated in the northern hemisphere middle and high latitudes and the north-central areas of northern Pacific Ocean near the equator.
(4) The 3 items factor of the northern hemisphere 500-hPa geopotential height field,which affected the Meiyu rainfall in Yiwu, mainly concentrated in the northern hemisphere high latitudes, thus validated that the persist stabilization of the Meiyu period of the lower-middle reaches of the Yangtze River correlated closely to the establishing and maintaining of the ridge of high pressure or blocking high above the Urals and the Sea of Okhotsk; The prophase abnormality of SST had a strong correlation with the Meiyu rainfall in Yiwu, and the most correlated zones were as follows:the Western Pacific Warm Pool and the North Atlantic between last December to the following April, Canary cold snap zone of the north-central areas of northern Pacific Ocean near the equator between last December to the following February, and the southern Indian Ocean near the equator on January. But as a omen signal of the previous primaries predictor,the physical process which is how to affect the Meiyu rainfall in Yiwu needed to be further explored.
(5) Compared with the traditional stepwise regression forecast model, the BP neural network forecast model for the forecasting of Meiyu rainfall in Yiwu city had certain advantages,which could be used to forecast the Meiyu rainfall of the coming year in Yiwu city. Finally, it had set a standard and process for the classification of the Meiyu rainfall,in order to rate and evaluate the predictive values which were the results from the BP neural network forecast model that had the better result of test forecast. That in turn modified the basic grades of the Meiyu rainfall and obtained the intervals of forecast data by the synthesis of the processing results. In operational practice forecasting, to the grading prediction of Meiyu rainfall, there were cyclical factors and the heating state above the surface between sea and atmosphere in the year, concentrating on whether the El nino/la Nina actually happened, that had to be taken into account.
(6) In 2010, the natural precipitation in this region could basically meet the water demands of actual productive and domestic uses in summer drought season. Therefore, it did not need to take artificial precipitation operation in Yiwu city this year.
引文
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