复杂地形区晴空太阳辐射模型构建与应用
CONSTRUCTION AND APPLICATION OF CLEARSKY SOLAR RADIATION MODEL OVER COMPLEX TERRAIN
丁雪倩 1张淑花 1金存银1
作者信息
- 1. 西安科技大学测绘科学与技术学院,西安 710054
- 折叠
摘要
以昆仑山提孜那甫河流域为研究区,利用中分辨率成像光谱仪(MODIS)提供的大气数据基于Iqbal Model C模型估算晴空大气透射率空间分布,并引入地形开阔度(SVF)和遥感地表反照率数据分别用于估算散射辐射地形阻挡以及反射辐射反照率系数空间分布,最后结合Kumar模型的直接辐射地形阻挡模拟过程,实现对Kumar模型的改进,改进后模型综合考虑了大气以及地形对太阳辐射的影响.利用改进后模型对研究区地表太阳辐射时空分布进行模拟和分析,基于地面气象站点观测数据对模拟结果进行验证.结果表明:模型估算值与站点观测值存在很好的一致性,相关系数R2为0.96,平均绝对误差(MAE)为1.47 MJ/m2,平均绝对相对误差(MARE)为12.26%.春季、夏季以及秋季模型的模拟精度较高,冬季模型的模拟精度较低,可能的原因为冬季MODIS大气数据有所低估.
Abstract
With the Tizinafu River Basin of Western China as the study area,the MODIS atmospheric data is used to estimate the spatial distribution of clear-sky atmospheric transmittance based on the Iqbal Model C,and the sky view factor(SVF)and remote sensing surface albedo data are introduced to calculate the topographic obstruction of scattered radiation and the spatial distribution of albedo coefficients of reflected radiation,respectively.Finally,combined with the direct radiation terrain shading effect of the Kumar model to improve the Kumar model.The improved model comprehensively considers the influence of the atmosphere and terrain on solar radiation.The spatial and temporal distribution of surface solar radiation in the study area is simulated and analyzed by the improved model,and the simulation results are verified based on the observation data from ground-based meteorological stations.The results show that the estimated values of the model and the observed values of the sites are in good agreement,with a correlation coefficient R2of 0.96,a mean absolute error(MAE)of 1.47 MJ/m2,and a mean absolute relative error(MARE)of 12.26%.The simulation accuracy of the model is higher n spring,summer and autumn but lower in winter,which may be due to the underestimation of MODIS atmospheric data in winter.
关键词
太阳辐射/遥感/地形/MODIS大气数据/大气透射率Key words
solar radiation/remote sensing/topography/MODIS atmospheric data/atmospheric transmittance引用本文复制引用
基金项目
陕西省教育厅一般专项科研计划(21JK0770)
新疆综合科学考察项目子课题(第三次)(2022xjkk010103)
国家自然科学基金(41701442)
国家自然科学基金(41977059)
出版年
2024
NETL
NSTL
万方数据