Estimation of the distribution of the total net radiative flux from satellite and automatic weather station data in the Upper Blue Nile basin, Ethiopia

环境科学 短波辐射 短波 中分辨率成像光谱仪 克里金 遥感 蒸散量 卫星 均方误差 气象学 辐射传输 辐射 地质学 地理 计算机科学 数学 物理 生物 机器学习 统计 天文 量子力学 生态学
作者
Eyale Bayable Tegegne,Yaoming Ma,Xuelong Chen,Weiqiang Ma,Bingbing Wang,Zhangwei Ding,Zhikun Zhu
出处
期刊:Theoretical and Applied Climatology [Springer Science+Business Media]
卷期号:143 (1-2): 587-602 被引量:10
标识
DOI:10.1007/s00704-020-03397-9
摘要

Abstract Net radiation is an important factor in studies of land–atmosphere processes, water resource management, and global climate change. This is particularly true for the Upper Blue Nile (UBN) basin, where significant parts of the basin are dry and evapotranspiration ( ET ) is a major mechanism for water loss. However, net radiation has not yet been appropriately parameterized in the basin. In this study, we estimated the instantaneous distribution of the net radiation flux in the basin using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Terra satellite and Automatic Weather Station (AWS) data. Downward shortwave radiation and air temperature usually vary with topography, so we applied residual kriging spatial interpolation techniques to convert AWS data for point locations into gridded surface data. Simulated net radiation outputs were validated through comparison with independent field measurements. Validation results show that our method successfully reproduced the downward shortwave, upward shortwave, and net radiation fluxes. Using AWS data and residual kriging spatial interpolation techniques makes our results robust and comparable to previous works that used satellite data at a finer spatial resolution than MODIS. The estimated net shortwave, longwave, and total radiation fluxes were in close agreement with ground truth measurements, with mean bias (MB) values of − 14.84, 5.7, and 20.53 W m −2 and root mean square error (RMSE) values 83.43, 32.54, and 78.07 W m −2 , respectively. The method presented here has potential applications in research focused on energy balance, ET estimation, and weather prediction for regions with similar physiographic features to those of the Nile basin.
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