Differences Evaluation among Three Global Remote Sensing SDL Products

• Published in: Remote Sensing
• Main Authors: Laibo Yu, Guoxiang Liu, Rui Zhang
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2023
• Subjects: surface downwelling longwave radiation; CERES-SYN; ECMWF-SRB; GEWEX-SRB; Science; Q; Antarctic; Arctic; Greenland; The Antarctic; Antarc*
• Online Access: https://doi.org/10.3390/rs15174244; https://doaj.org/article/9e44fa229e864395901ba7c99c921d6c

At present, a variety of global remote sensing surface downwelling longwave radiation (SDL) products are used for atmospheric science research; however, there are few studies on the quantitative evaluation of differences among different SDL products. In order to evaluate the differences among different SDL products quantitatively, we have selected three commonly used SDL products—Clouds and the Earth’s Radiant Energy System-Synoptic Radiative Fluxes and Clouds (CERES-SYN), the European Centre for Medium Range Weather Forecasts-Surface Radiation Budget (ECMWF-SRB) and the Global Energy and Water Exchanges Project-Surface Radiation Budget (GEWEX-SRB)—to comprehensively study in this paper. The results show that there are significant differences among the three SDL products in some areas, such as in the Arctic, the Antarctic, the Sahara, the Tibet Plateau, and Greenland. The maximum absolute root mean square error (RMSE ab ) in these areas is greater than 20 Wm −2 , the maximum relative root mean square error (RMSE re ) is greater than 20%, the maximum and minimum absolute mean bias error (MBE ab ) are about 20 Wm −2 and −20 Wm −2 , respectively, and the maximum and minimum relative mean bias error (MBE re ) are about 10% and −10%, respectively. Among the three SDL products, the difference between the ECMWF-SRB and GEWEX-SRB is the most significant. In addition, this paper also analyzed the differences among different SDL products based on three aspects. Firstly, the differences among the three SDL products show that there is significant seasonality, and the differences among different months may vary greatly. However, the differences are not sensitive to years. Secondly, there are some differences in cloud-forcing radiative fluxes (CFRFs) of different SDL products, which is also an important factor affecting the difference between different SDL products. Finally, in the process of converting high temporal resolution SDL products into monthly SDL products, data processing also affects the difference between ...