Abstract This study aims to ascertain the uncertainties related to the spatiotemporal estimation of net radiation, and its components, using remote sensing data. Geographical focus is an irrigated agricultural hotspot of the Brazilian semiarid region, for which we also investigate the impact that contrasting land-cover types have on the upwelling radiation balance components, and hence on net radiation. Instantaneous (Rn) and daily (Rn,24) values of net radiation were estimated based on OLI/TIRS-Landsat-8 images and key weather variables. In addition, we evaluated two models for downwelling shortwave (Rsw), ten models for downwelling longwave radiation (Rlw), and two models for derivation of Rn,24. The accuracy of each model was evaluated with radiation measurements obtained from research quality sensors installed in micrometeorological towers. The best performances were found for the Allen model, Duarte model, and De Bruin model for Rsw, Rlw, and Rn,24, respectively. The contrasting land-use types exhibited substantial differences in the biophysical variables and radiative properties that affect Rn. The albedo for the irrigated crops has average absolute values that are 0.01–0.03 greater than those found for the pristine caatinga, whereas the land surface temperature, LST, is 3–5 degrees smaller. However, Rn for these two distinctly different surface types was similar, as a result of a considerably lower surface emissivity in the caatinga. For rangeland, the albedo, LST, and hence the upwelling radiation had greater values than those found for the caatinga, which caused reduced values of Rn. The urban areas exhibited the lowest values of Rn, mainly as a consequence of their high albedo values. We show that when in-situ net radiation data are not available, remote sensing data combined with more readily available in-situ weather data can be used to derive spatiotemporal estimates of Rn. This facilitates the identification of anthropogenic impacts on the radiation at the land-surface and ultimately the energy balance, including the short-term seasonal and long-term effects.

中文翻译：

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使用遥感可靠估计净辐射及其组成部分：对比巴西半干旱地区农业热点土地覆盖的案例研究

摘要 本研究旨在利用遥感数据确定与净辐射及其分量的时空估计相关的不确定性。地理焦点是巴西半干旱地区的灌溉农业热点，为此我们还调查了对比土地覆盖类型对上升流辐射平衡分量的影响，从而对净辐射产生影响。根据 OLI/TIRS-Landsat-8 图像和关键天气变量估计净辐射的瞬时 (Rn) 和每日 (Rn,24) 值。此外，我们评估了下涌短波 (Rsw) 的两个模型、下涌长波辐射 (Rlw) 的十个模型和两个推导 Rn 的模型24。每个模型的准确性通过从安装在微气象塔中的研究质量传感器获得的辐射测量值进行评估。对于 Rsw、Rlw 和 Rn，分别发现 Allen 模型、Duarte 模型和 De Bruin 模型的最佳性能，24。对比鲜明的土地利用类型在影响 Rn 的生物物理变量和辐射特性方面表现出显着差异。灌溉作物的反照率的平均绝对值比原始 caatinga 的平均绝对值高 0.01-0.03，而地表温度 LST 小 3-5 度。然而，这两种截然不同的表面类型的 Rn 是相似的，因为卡廷加的表面发射率相当低。对于牧场，反照率、LST 以及上升流辐射的值比发现的卡廷加辐射值更大，这导致 Rn 值降低。城市地区表现出最低的 Rn 值，主要是因为它们的高反照率值。我们表明，当现场净辐射数据不可用时，遥感数据与更容易获得的现场天气数据相结合，可用于推导出 Rn 的时空估计。这有助于确定人为对地表辐射和最终能量平衡的影响，包括短期季节性和长期影响。