Abstract. Land Surface Temperature (LST) and Surface Net Radiation (SNR) are vital inputs for many land surface and hydrological models. However, current remote sensing datasets of these variables come mostly at coarse resolutions. Although high-resolution LST and SNR retrievals are available, they have large gaps due to cloud-cover that hinder their use as input in models. Here, we present a downscaled and continuous daily LST and SNR product across Europe for 2018–2019. The LST product is based on all-sky LST retrievals from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard the geostationary Meteosat Second Generation (MSG) satellite, and clear-sky LST retrievals from the Sea and Land Surface Temperature Radiometer (SLSTR) onboard the polar-orbiting Sentinel 3 satellites. The product combines the medium spatial (approx. 5–7 km) but high temporal (30 minute) resolution, gap-free data from MSG, with the low temporal (2–3 days) but high spatial (1 km) resolution of the Sentinel 3 LST retrievals. The resulting 1 km and daily LST dataset is based on an hourly merging of both datasets through bias-correction and Kalman Filter assimilation. Longwave outgoing radiation is computed from the merged LST product in combination with MSG-based emissivity data. Shortwave outgoing radiation is computed from the incoming shortwave radiation from MSG and downscaled albedos using 1 km PROBA-V data. MSG incoming shortwave and longwave radiation and the outgoing radiation components at 1 km spatial resolution are used together to compute the final daily SNR dataset in a consistent manner. Validation results indicate an improvement of the root mean squared error by ca. 8 % with a substantial increase in spatial detail compared to the original MSG product. The resulting pan-European LST and SNR dataset can be used for hydrological modelling and as input to models dedicated to estimating evaporation and surface turbulent heat fluxes and will be regularly updated in the future.

中文翻译：

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欧洲上空的高分辨率全天空地表温度和净辐射

摘要。地表温度 (LST) 和地表净辐射 (SNR) 是许多地表和水文模型的重要输入。然而，这些变量的当前遥感数据集大多是粗分辨率的。尽管可以使用高分辨率 LST 和 SNR 检索，但由于云层覆盖阻碍了它们在模型中用作输入，它们之间存在很大差距。在这里，我们展示了 2018-2019 年整个欧洲的缩减且连续的每日 LST 和 SNR 产品。LST 产品基于来自地球静止气象卫星第二代 (MSG) 卫星上的旋转增强可见光和红外成像仪 (SEVIRI) 的全天空 LST 反演，以及来自海陆表面温度辐射计 (SLSTR) 的晴空 LST 反演在极轨哨兵 3 号卫星上。该产品结合了中等空间（约。5-7 公里）但高时间（30 分钟）分辨率，来自 MSG 的无间隙数据，具有 Sentinel 3 LST 检索的低时间（2-3 天）但高空间（1 公里）分辨率。生成的 1 公里和每日 LST 数据集基于通过偏差校正和卡尔曼滤波器同化每小时合并两个数据集。长波出射辐射是根据合并的 LST 产品结合基于 MSG 的发射率数据计算得出的。短波出射辐射是根据来自 MSG 的入射短波辐射和使用 1 公里 PROBA-V 数据的缩小反照率计算的。MSG 入射短波和长波辐射以及 1 km 空间分辨率的出射辐射分量一起用于以一致的方式计算最终的每日 SNR 数据集。验证结果表明均方根误差提高了 ca。与原始 MSG 产品相比，空间细节大幅增加 8%。由此产生的泛欧 LST 和 SNR 数据集可用于水文建模，并作为专用于估计蒸发和表面湍流热通量的模型的输入，并将在未来定期更新。