Evaluation and Attribution of Shortwave Feedbacks to ENSO in CMIP6 Models

The shortwave (SW) feedback to El Niño–Southern Oscillation (ENSO) is one of the largest biases in climate models, as the feedback includes atmosphere–ocean interactions and cloud processes. In this study, the performance of SW feedbackover tropical Pacific in 19 models from the 6th Coupled Model Intercomparison Project (CMIP6) is evaluated against observations or reanalysis datasets, and the biases are attributed using the historical and Atmospheric Model Intercomparison Project (AMIP) runs and two coupled assimilation experiments. The results demonstrate that while superior to CMIP5 counterparts, most CMIP6 models still underestimate the strength of SW feedback to different degree. The underestimates of SW feedback arise mainly from the biased feedbacks to El Niño in the four models with relatively better skills, while from both underestimated negative feedbacks to El Niño and overestimated positive feedbacks to La Niña in other models, which reproduce better seasonal variations than corresponding CMIP5 models. Furthermore, the SW feedback bias is connected to weak convective/stratiform rainfall feedback, which is sensitive/insensitive to sea surface temperature (SST) biases during El Niño/La Niña. The total rainfall feedbacks and dynamical feedbacks are underestimated in the historical runs, more than in CMIP5, and shows close relationship with each other. Finally, several data assimilation experiments are conducted using FGOALS-g3, one of models in CMIP6 model ensemble, and the Dimension-Reduced Projection Four-Dimensional Variational (DRP-4DVar) data assimilation system to verify the causes and relationships between feedbacks and mean states, further conclusiona are made.