Cloud Radiative Feedbacks during the ENSO Cycle Simulated by CAMS-CSM

Springer Science and Business Media LLC - Tập 33 - Trang 666-677 - 2019
Lin Chen1,2,3, Lijuan Hua4, Xinyao Rong4, Jian Li4, Lu Wang1, Guo Zhang4, Ming Sun1, Zi’an Ge1
1Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environmental Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology (NUIST), Nanjing, China
2State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
3State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi’an, China
4State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, China Meteorological Administration, Beijing, China

Tóm tắt

This study evaluated the simulated cloud radiative feedbacks (CRF) during the El Nino-Southern Oscillation (ENSO) cycle in the latest version of the Chinese Academy of Meteorological Sciences climate system model (CAMS-CSM). We conducted two experimental model simulations: the Atmospheric Model Intercomparison Project (AMIP), forced by the observed sea surface temperature (SST); and the preindustrial control (PIcontrol), a coupled run without flux correction. We found that both the experiments generally reproduced the observed features of the shortwave and longwave cloud radiative forcing (SWCRF and LWCRF) feedbacks. The AMIP run exhibited better simulation performance in the magnitude and spatial distribution than the PIcontrol run. Furthermore, the simulation biases in SWCRF and LWCRF feedbacks were linked to the biases in the representation of the corresponding total cloud cover and precipitation feedbacks. It is interesting to further find that the simulation bias originating in the atmospheric component was amplified in the PIcontrol run, indicating that the coupling aggravated the simulation bias. Since the PIcontrol run exhibited an apparent mean SST cold bias over the cold tongue, the precipitation response to the SST anomaly (SSTA) changes during the ENSO cycle occurred towards the relatively warmer western equatorial Pacific. Thus, the corresponding cloud cover and CRF shifted westward and showed a weaker magnitude in the PI-control run versus observational data. In contrast, the AMIP run was forced by the observational SST, hence representing a more realistic CRF. Our results demonstrate the challenges of simulating CRF in coupled models. This study also underscores the necessity of realistically representing the climatological mean state when simulating CRF during the ENSO cycle.

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