The GAMIL3: Model Description and Evaluation

The Grid-point Atmospheric Model of the IAP LASG version 3 (GAMIL3) has been developed by upgrading the horizontal resolution, methods of parallel computation, boundary layer scheme, aerosol parameterization, convective parameterization, stratocumulus cloud fraction scheme, land component, and coupler, as well as tuning some moist physical parameters with large uncertainties. Its performance is evaluated, and the results show significant improvements compared with the previous version, GAMIL2. The simulated performance of mean states is notably enhanced, including the energy budget terms at the top of the atmosphere (TOA) and surface, shortwave/longwave cloud radiative forcing (SWCF/LWCF), precipitation, zonal wind, low-level temperature, 500-hPa geopotential height, and snow cover fraction in the Northern Hemisphere. The characteristics of internal variability are captured well, such as the frequency band and active areas of quasi-biweekly (QBW) oscillation, spectral power of convectively coupled equatorial waves (CCEWs), Madden-Julian Oscillation (MJO) eastward propagation, and heat flux response to El Nino-Southern Oscillation (ENSO), and these variabilities are generally strengthened in GAMIL3. In addition, the anthropogenic aerosol climate effects are weakened when using the forcings recommended by CMIP6. Plain Language Summary The Coupled Model Intercomparison Project (CMIP) provides a multimodel platform for research in climate change originating from unforced variability or in response to changes in anthropogenic forcings. The Atmospheric Model Intercomparison Project (AMIP) experiment, which is part of the sixth phase of CMIP (CMIP6), is designed to evaluate the atmospheric component in the climate system. The GAMIL3 is the atmospheric component of Flexible Global-Ocean-Atmosphere-Land System Model Grid-point version 3 (FGOALS-g3), one of the CMIP6 models, and it has been developed from GAMIL2. This paper presents a description of the GAMIL3 model and its upgrades, the performance of the simulated mean state and internal variability, and the anthropogenic aerosol climate effects. This description is useful for understanding climate variability and change.