Establishes a high-resolution OLR dataset, improving climate monitoring and model validation.
Current global Outgoing Longwave Radiation (OLR) products often face a trade-off between spatial resolution and temporal frequency, constraining their utility in monitoring rapid weather dynamics and fine-scale climate processes. To bridge this gap, this study presents a generation and comprehensive validation of the global Long-term Earth System spatiotemporally Seamless Radiation budget OLR dataset (LessRad OLR, https://doi.org/10.11888/Atmos.tpdc.301403). Derived from over two decades of MODIS observations (March 2000–May 2024), the dataset was generated using an optimized framework that integrates scene-dependent instantaneous retrievals with physically constrained temporal upscaling. The resulting product provides global coverage at an unprecedentedly high resolution (0.05°/h). Comprehensive validation against the CERES Energy Balanced and Filled (EBAF) product confirms robust climatological consistency, with a global monthly Root Mean Square Error (RMSE) of approximately 2.4 W m−2. Crucially, high-frequency evaluations reveal robust performance at hourly (RMSE ~5.65 W m−2) and daily (RMSE ~4.33 W m−2) scales. Furthermore, the 0.05° resolution effectively resolves the fine-scale structures of extreme weather events, which are typically obscured in coarser datasets. This multi-decadal, high-resolution climate data record serves as a valuable resource for investigating diurnal land-atmosphere interactions and validating high-resolution climate models in the era of Big Earth Data.
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Li et al. (2026) studied this question.
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