Abstract
Cloud-radiative forcing (CRF) at the top of the atmosphere (TOA) over the western Pacific warm pool (WP) shows unique characteristics in response to El Niño events. In this region, the responses of CRF to El Niño events have been a useful metric for evaluating climate models. Satellite data are used to analyze the CRF anomalies to El Niño events simulated by the new and old versions of the Climate System Model of the Chinese Academy of Meteorological Sciences (CAMS-CSM), which has participated in the Atmospheric Model Intercomparison Project (AMIP). Here, simulations for super El Niño years, El Niño years, and normal years are compared with observations. The results show that the mean values of both longwave CRF (LWCRF) and shortwave CRF (SWCRF) in CAMS-CSM are weaker than the observations for each category of El Niño events. Compared with the old version of CAMS-CSM, the decrease in LWCRF during El Niño events is well simulated by the new version of CAMS-CSM. However, both new and old models cannot reproduce the anomalous SWCRF in El Niño events. The biases in the CRF response to El Niño events are attributed to the biases in the cloud vertical structure because of a weaker crash of the Walker circulation in CAMS-CSM. Due to the modification of the conversion rate from cloud droplets to raindrops in the cumulus convection scheme, the new version of CAMS-CSM has better CRF skills in normal years, but biases in El Niño events still exist in the new version. Improving the response of the Walker circulation to El Niño events is key to higher skills in simulating the cloud radiative responses.
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We thank the Chinese Academy of Meteorological Sciences for providing the CAMS-CSM model data.
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Supported by the Ministry of Science and Technology of China (2017YFA0604004) and National Natural Science Foundation of China (41775102, 41420104006, and 41661144009).
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Zhang, B., Guo, Z., Chen, X. et al. Responses of Cloud-Radiative Forcing to Strong El Niño Events over the Western Pacific Warm Pool as Simulated by CAMS-CSM. J Meteorol Res 34, 499–514 (2020). https://doi.org/10.1007/s13351-020-9161-3
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DOI: https://doi.org/10.1007/s13351-020-9161-3