Bias characteristics of cloud diurnal variation in the FGOALS-f3-L model

Abstract

Cloud diurnal variation is crucial for regulating cloud radiative effects and atmospheric dynamics. However, it is often overlooked in the evaluation and development of climate models. Thus, this study aims to investigate the daily mean (CFR) and diurnal variation (CDV) of cloud fraction across high-, middle-, low-level, and total clouds in the FGOALS-f3-L general circulation model. The bias of total CDV is decomposed into the model biases in CFRs and CDVs of clouds at all three levels. Results indicate that the model generally underestimates low-level cloud fraction during the daytime and high-/middle-level cloud fraction at nighttime. The simulation biases of low clouds, especially their CDV biases, dominate the bias of total CDV. Compensation effects exist among the bias decompositions, where the negative contributions of underestimated daytime low-level cloud fraction are partially offset by the opposing contributions from biases in high-/middle-level clouds. Meanwhile, the bias contributions have notable land–ocean differences and region-dependent characteristics, consistent with the model biases in these variables. Additionally, the study estimates the influences of CFR and CDV biases on the bias of shortwave cloud radiative effects. It reveals that the impacts of CDV biases can reach half of those from CFR biases, highlighting the importance of accurate CDV representation in climate models.

摘要

云量日变化可以调节云辐射效应, 影响大气动力过程, 但在气候模式评估中常被忽视. 本研究评估了FGOALS-f3-L模式中高, 中, 低云及总云云量的日均值和日变化特征. 结果表明, 模式普遍低估白天低云云量和夜间中, 高云云量. 低云云量日变化误差主导总云云量日变化误差. 其中, 低云误差造成的负值贡献被中, 高云误差的正值贡献部分抵消. 误差贡献呈现显著的海陆和区域差异, 与相应云量的模式误差一致. 同时, 云量日变化误差对短波云辐射效应误差的影响可达日均云量影响的一半, 突显了在模式中准确表征云量日变化的重要性.