LessRad OLR：用于气候监测的高分辨率（0.05°，每小时）MODIS出射长波辐射数据集

出射长波辐射 (Outgoing Longwave Radition, OLR) 是地球能量收支的关键组成部分，也是天气预报、气候和其他耦合模型所需的关键边界条件。卫星遥感通过快速获取大规模观测数据，为获取全球 OLR 提供了一种可行且经济有效的方法。在现有的卫星 OLR 产品中，云和地球辐射能量系统 (Clouds and the Earth’s Radiant Energy System, CERES) 能量平衡与填充 (Energy Balanced and Filled, EBAF) OLR 因其准确性和长期数据记录而广受认可。然而，其粗糙的空间分辨率（1°）限制了其在高分辨率耦合模型和区域气候研究中的适用性。为了解决这一限制，我们开发了一个统一的 OLR 推导算法框架，利用日益普及的中高分辨率卫星数据。该算法框架计算效率高，只需极少的输入数据（波段辐射度和观测角度），为利用极轨卫星红外传感器生成高分辨率 OLR 估计提供了一种实用方法。将该框架应用于20多年的MODIS数据（从2000年3月到2024年5月），我们开发了长期地球系统时空无缝辐射收支数据集（LessRad OLR）的全球OLR产品。该产品具有高空间分辨率（0.05°）和精度（均方根误差，RMSE ~ 2.4 W m-2）。与其他产品相比，LessRad OLR与CERES EBAF OLR表现出高度的空间和时间一致性，即使在沙漠和深对流等极端条件下也表现良好。LessRad OLR数据集已公开发布，网址为https://doi.org/10.11888/Atmos.tpdc.301403。该数据集为各种应用提供了宝贵的资源，例如分析地球能量收支的精细时空变化、陆气相互作用以及评估耦合模型，从而支持对地球气候系统和动力学的理解。

Outgoing Longwave Radiation (OLR) is a critical component of the Earth’s energy budget and a key boundary condition required for weather forecasting, climate and other coupled models. Satellite remote sensing provides a feasible and cost-effective approach to acquiring global OLR by rapidly obtaining large-scale observational data. Among existing satellite OLR products, the Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) OLR is widely recognized for its accuracy and long-term data record. However, its coarse spatial resolution (1°) limits its applicability in high-resolution coupled models and regional climate studies. To address this limitation, we developed a unified OLR derivation algorithm framework that leverages the increasingly popular medium- and high-resolution satellite data. This algorithm framework features high computational efficiency and requires only minimal input data (band radiance and observation angles), providing a practical method for generating high-resolution OLR estimates using polar-orbiting satellite infrared sensors. By applying this framework to more than 20 years of MODIS data (from March 2000 to May 2024), we developed the global OLR product of the long-term spatiotemporally seamless radiation budget dataset for the Earth system, termed LessRad OLR. This product boasts high spatial resolution (0.05°) and accuracy (root mean square error, RMSE ~ 2.4 W m⁻²). Compared with other products, LessRad OLR exhibits high spatial and temporal consistency with CERES EBAF OLR, and performs well even under extreme conditions such as deserts and deep convection. The LessRad OLR dataset has been publicly released at https://doi.org/10.11888/Atmos.tpdc.301403. This dataset serves as a valuable resource for various applications, such as analyzing fine spatiotemporal variations of the Earth’s energy budget, land-atmosphere interactions, and evaluating coupled models, thereby supporting the understanding of the Earth’s climate system and its dynamics.