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主管单位 中华人民共和国
工业和信息化部
主办单位 哈尔滨工业大学 主编 冷劲松 国际刊号ISSN 0367-6234 国内刊号CN 23-1235/T

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引用本文:于瑛,贾晓宇,陈笑.基于气候突变年的太阳辐射模型统计时长选取方法[J].哈尔滨工业大学学报,2021,53(1):193.DOI:10.11918/201911110
YU Ying,JIA Xiaoyu,CHEN Xiao.Selection method of statistical duration in solar radiation model based on climate abrupt change year[J].Journal of Harbin Institute of Technology,2021,53(1):193.DOI:10.11918/201911110
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基于气候突变年的太阳辐射模型统计时长选取方法
于瑛,贾晓宇,陈笑
(西安建筑科技大学 机电工程学院,西安 710055)
摘要:
建立太阳辐射模型,通过气象参数估算太阳辐射是完善太阳辐射数据的重要途径. 建模数据统计时长的选取影响辐射模型系数,进而影响其估算误差. 为选择适当的数据统计时长,减小辐射模型估算误差,本文提出一种借助气候突变年选取建模数据统计时长的方法. 以我国90个台站超过25年的气象和辐射数据记录为例,选择与太阳辐射相关性较强的日照时数、温度和湿度3个气象要素分别进行突变检验,使用变差系数法确定气候突变年. 选取观测数据超过25年的统计时长和突变年之后的统计时长分别建立日总辐射模型和日散射辐射模型,比较使用不同统计时长建立的模型估算误差. 误差结果显示,以气候突变年为时间节点,选择其后的数据记录年份作为建模统计时长可以使辐射模型的均方根误差百分率降低2%以上,证明借助气候突变年选取辐射模型建模时长的方法可以有效降低模型估算误差. 该方法可为辐射模型统计时长的选取提供依据.
关键词:  太阳辐射模型  统计时长  气象要素  气候突变年  误差分析
DOI:10.11918/201911110
分类号:TU119+.2
文献标识码:A
基金项目:“十三五”国家科技支撑课题(2018YFC0704504)
Selection method of statistical duration in solar radiation model based on climate abrupt change year
YU Ying,JIA Xiaoyu,CHEN Xiao
(School of Mechanical and Electrical Engineering,Xi’an University of Architecture and Technology,Xi’an 710055,China)
Abstract:
Establishing a solar radiation model which employs pertinent meteorological parameters for the estimation of solar radiation is essential for enhancing solar radiation data. The statistical duration used by the radiation model influences the model’s coefficients and further affects its estimation errors. To select a proper statistics duration and minimize the radiation model estimation error, this paper proposes a kind of method that chooses an appropriate statistical duration based on the climate abrupt change year. By analyzing the meteorological and radiation data records of more than 25 years from 90 observatories and meteorological stations in China, three meteorological elements that are closely related to solar radiation, namely, sunshine duration, temperature and humidity, are used for abrupt change inspection. The coefficient of variation method is used to determine the climate abrupt change year. Daily global radiation model and daily diffuse radiation model are established respectively by choosing the statistics duration of observation data for over 25 years and the statistics duration after climate abrupt change year. The estimation errors of different models using different statistics duration are compared. According to the error results, the Root Mean Square Error percentage can be reduced by above 2% if data record years after the climate abrupt change year, which serves as the time node, are used as the modeling statistics duration. It demonstrates that the method of choosing radiation modeling duration using climate abrupt change year can reduce the modeling estimation error effectively. The method provides a reference to select the statistical duration in radiation models.
Key words:  solar radiation model  statistical duration  meteorological element  climate abrupt change year  error analysis

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