中国综合农业分区下的Ångström-Prescott公式系数逐月校正与优选

doi:10.11821/dlxb202104008

Abstract

Abstract:

?ngstr?m-Prescott equation is the recommended algorithm for calculating the radiation coefficients for the Penman-Monteith formula, which is the standard method for reference crop evapotranspiration recommended by the Food and Agriculture Organization (FAO) of the United Nations. The calibration and optimization of a_s and b_s coefficients in the equation is the key to accurately calculate the surface solar radiation. This study aims at obtaining the ?ngstr?m-Prescott equation coefficients a_s and b_s, which are optimized for China's comprehensive agricultural areas. The monthly average solar radiation (R_s) (from Dataset of Monthly Values of Radiation Data from Chinese Surface Stations) and srelative sunshine duration data (from Dataset of Monthly Values of Climate Data from Chinese Surface Stations) at 121 stations during 1957-2016 were collected. Using the data from 1957 to 2010, we calculated the monthly a_s and b_s coefficients for each area through the least squares regression. Then, taking the observation values of R_s from 2011 to 2016 as the true values, we estimated and compared the relative accuracy of R_s calculated by regression values of coefficients a_s and b_s and that calculated by FAO suggested coefficients a_s and b_s. The results showed that the monthly average coefficients a_s and b_s of each area are significantly different from the FAO recommended coefficients both temporally and spatially. There are some differences between regions and within regions, and the relative value of a_s and b_s shows the opposite state. The relative error range (0-54%) of solar radiation calculated by the regression a_s and b_s coefficients is small, while the relative error range (0-77%) of solar radiation calculated by the FAO recommended value is large. So, overall, the relative accuracy of R_s calculated by regression values of a_s and b_s coefficients is better than that calculated by the FAO suggested coefficients. The relative error was reduced by 1% to 6%, and the relative error decreases more in winter and spring than in summer and autumn. However, regression values of a_s and b_s coefficients perform worse in some months and some agricultural areas for verification in application. It is said that the regression values of a_s and b_s are not entirely reliable. For each month and each agricultural area, the best scheme is to combine the regression values of a_s and b_s coefficients with the FAO recommended values. Therefore, we chose the a_s and b_s coefficients with the minimum R_s estimation error as the final coefficients and made a coefficient recommendation table for 38 agricultural production and management areas in the Chinese mainland. This study further illustrates the necessity of localization modification of ?ngstr?m-Prescott equation coefficients in application, and enriches the case study of coefficient calibration of ?ngstr?m-Prescott equation in China, which is helpful for improving the accuracy of calculation of surface solar radiation and reference crop evapotranspiration based on existing data.

Key words: solar radiation, coefficient calibration, ?ngstr?m-Prescott equation, China

XIA Xingsheng, PAN Yaozhong, ZHU Xiufang, ZHANG Jinshui. Monthly calibration and optimization of Ångström-Prescott equation coefficients for agricultural comprehensive area in China[J].Acta Geographica Sinica, 2021, 76(4): 888-902.

Figures/Tables 10

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Monthly calibration and optimization of Ångström-Prescott equation coefficients for agricultural comprehensive area in China

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