Assessments of the Climate System Model (CAS-ESM-C) Using IAP AGCM4 as Its Atmospheric Component
IAP第四代大气环流模式的气候系统模式模拟性能评估

This paper assesses the performance of a new climate system model, namely CAS-ESM-C (Chinese Academy of Sciences-Earth System Model-Climate system component), which employs the recently improved version of IAP AGCM, namely IAP AGCM4, as its atmospheric component. This paper first describes the development and framework of the model briefly, and then evaluates the performances of the model in simulating the climate mean states of the atmosphere, land surface, ocean, and sea ice. Some aspects of the seasonal cycle and interannual variability are also analyzed. The results indicate that the CAS-ESM-C succeeds in controlling the long-term climate drift and has acceptable performances in realistically reproducing the climate mean states of the atmosphere, ocean, land surface and sea ice. The CAS-ESM-C also successfully reproduces the seasonal cycle of SST over the tropical Pacific and the seasonal cycle of the sea ice cover in the Arctic. The seasonal migration of monsoon rain band is well reproduced in the model, indicating the acceptable performance of the East Asian monsoon simulation. Except for the slight underestimation of the ENSO period and overestimation of the average amplitude, other characteristics of interannual variability over the tropical Pacific are well reproduced in the CAS-ESM-C. It is particularly important that, benefiting from the realistic simulation of the seasonal cycle of SST over the tropical Pacific, a "phase-locked" phenomenon appears in the simulated ENSO, which is hardly reproduced in other coupled models. The main deficiency of the CAS-ESM-C is the tropic bias, which is common in other coupled models. Some analyses are made to reveal the possible reason behind these simulation biases especially the tropical bias. The results suggest that the biases in the atmosphere which are amplified by the ocean-atmosphere feedback are the key reasons of the tropic bias in the coupled system. According to the analyses of the biases, future improvements of the CAS-ESM-C should focus on the treatment of physical processes of cloud and precipitation in the AGCM. From this point, updating or improving the low-level cloud scheme and the convective parameterization of the atmosphere model may be the first step for the future development of the CAS-ESM-C.