It is of great importance for climate change studies to construct a worldwide, long-term surface downward longwave radiation (L_d, 4–100 μm) dataset. Although a number of global L_d datasets are available, their low accuracies and coarse spatial resolutions limit their applications. This study generated a daily L_d dataset with a 5-km spatial resolution over the global land surface from 2000 to 2018 using atmospheric parameters, which include 2-m air temperature (Ta), relative humidity (RH) at 1000 hPa, total column water vapor (TCWV), surface downward shortwave radiation (S_d), and elevation, based on the gradient boosting regression tree (GBRT) method. The generated L_d dataset was evaluated using ground measurements collected from AmeriFlux, AsiaFlux, baseline surface radiation network (BSRN), surface radiation budget network (SURFRAD), and FLUXNET networks. The validation results showed that the root mean square error (RMSE), mean bias error (MBE), and correlation coefficient (R) values of the generated daily L_d dataset were 17.78 W m⁻², 0.99 W m⁻², and 0.96 (p < 0.01). Comparisons with other global land surface radiation products indicated that the generated L_d dataset performed better than the clouds and earth’s radiant energy system synoptic (CERES-SYN) edition 4.1 dataset and ERA5 reanalysis product at the selected sites. In addition, the analysis of the spatiotemporal characteristics for the generated L_d dataset showed an increasing trend of 1.8 W m⁻² per decade (p < 0.01) from 2003 to 2018, which was closely related to Ta and water vapor pressure. In general, the generated L_d dataset has a higher spatial resolution and accuracy, which can contribute to perfect the existing radiation products.

中文翻译：

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2000年至2018年全球陆地长期地面下行长波辐射估计

构建全球范围的长期地表向下长波辐射（L _d，4–100μm）数据集对气候变化研究非常重要。尽管可以使用许多全局L _d数据集，但它们的低准确性和粗糙的空间分辨率限制了它们的应用。这项研究使用大气参数（包括2-m气温（Ta），1000 hPa的相对湿度（RH），总柱）从2000年到2018年生成了全球陆地表面具有5 km空间分辨率的每日L _d数据集水蒸气（TCWV），向下表面的短波辐射（S _d）和海拔，基于梯度增强回归树（GBRT）方法。生成的L_d数据集是使用从AmeriFlux，AsiaFlux，基线表面辐射网络（BSRN），表面辐射预算网络（SURFRAD）和FLUXNET网络收集的地面测量数据进行评估的。验证结果表明，根均方误差（RMSE），平均偏移误差（MBE），和相关系数（R）产生的日常值大号_d数据集分别为17.78脉冲W M ^-2，0.99女男^-2，和0.96 （ p <0.01）。与其他全球陆地表面辐射产品的比较表明，产生的L _d数据集在选定地点的性能优于云层和地球的辐射能系统概要（CERES-SYN）版本4.1数据集和ERA5重新分析产品。此外，对生成的L _d数据集的时空特征的分析显示，从2003年到2018年，每十年增加1.8 W m ^-2（p <0.01）的趋势，这与Ta和水蒸气压密切相关。通常，生成的L _d数据集具有较高的空间分辨率和精度，可以有助于完善现有的辐射产品。