Probing the spuriousness of observed downwelling radiative fluxes over the global Tropical Oceans

Abstract. A statistical evaluation of daily downwelling radiation data from the Global Tropical Moored Buoy Array (GTMBA), collocated with Clouds and Earth's Radiant Energy Systems (CERES) satellite data, was conducted from 2000 to 2023. This study addressed systematic biases and spurious data downwelling shortwave (Qs) and longwave (Q_L) radiation, which are crucial for understanding the ocean's energy budget and climate system. Two filtering methods were applied: a fixed threshold (Qs > 350 Wm^-2, Q_L > 450 Wm^-2) and a dynamic threshold (mean + 2 standard deviations per station) to check the spuriousness. For Qs, both methods had a negligible effect or resulted in a slight increase in bias, with no significant improvement in root mean squared error (RMSE) or correlation across regions. However, for Q_L showing large discrepancies in buoy observations in peaks (420–440 Wm^-2) compared to satellite (400–410 Wm^-2), both fixed and dynamic threshold filtering consistently improved correlation, bias, and RMSE. This greater effectiveness for Q_L is attributed to its strong influence by atmospheric temperature and humidity profiles, creating systematic biases that filtering effectively addresses. Overall, threshold filtering proved more effective for Q_L than for Qs, with fixed methods delivering consistently positive results for Q_L. The study highlights the need for customised threshold strategies to validate in situ data and advocates for further advancements in satellite retrieval algorithms and data assimilation to enhance the accuracy of radiative flux products and mitigate existing biases.