The Cloud Feedback Model Intercomparisons Project (CFMIP) Observation Simulator Package (COSP) is adopted in the Grid-point Atmospheric Model of IAP LASG (GAMIL2) during CFMIP at Phase II to evaluate the model cloud fractions in a consistent way with satellite observations. The cloud simulation results embedded in the Atmospheric Model Intercomparison Project (AMIP) control experiment are presented using three satellite simulators: International Satellite Cloud Climatology Project (ISCCP), Moderate Resolution Imaging Spectroradiometer (MODIS), and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) lidar onboard the Cloud- Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). Overall, GAMIL2 can produce horizontal distributions of the low cloud fraction that are similar to the satellite observations, and its similarities to the observations on different levels are shown in Taylor diagrams. The discrepancies among satellite observations are also shown, which should be considered during evaluation.
This study mainly introduces the development of the Flexible Global Ocean-Atmosphere-Land System Model： Grid-point Version 2 （FGOALS-g2） and the preliminary evaluations of its performances based on re- sults from the pre-industrial control run and four members of historical runs according to the fifth phase of the Coupled Model Intercomparison Project （CMIP5） experiment design. The results suggest that many obvi- ous improvements have been achieved by the FGOALS-g2 compared with the previous version, FGOALS-gl, including its climatological mean states, climate variability, and 20th century surface temperature evolution. For example, FGOALS-g2 better simulates the frequency of tropical land precipitation, East Asian Monsoon precipitation and its seasonal cycle, MJO and ENSO, which are closely related to the updated cumulus parameterization scheme, as well as the alleviation of uncertainties in some key parameters in shallow and deep convection schemes, cloud fraction, cloud macro/microphysical processes and the boundary layer scheme in its atmospheric model. The annual cycle of sea surface temperature along the equator in the Pacific is significantly improved in the new version. The sea ice salinity simulation is one of the unique characteristics of FGOALS-g2, although it is somehow inconsistent with empirical observations in the Antarctic.
GAMIL2.0 is the newly released version of the Grid-point Atmospheric Model of IAP LASG(GAMIL),in which the major modifications from GAMIL1.0 include an updated deep convection scheme and the incorporation of a two-moment bulk stratiform cloud microphysics scheme.This study evaluates the performances of both versions on Madden Julian Oscillation(MJO) simulations.The results show that GAMIL2.0 obtains an enhanced MJO eastward and northward propagation,which is weak in GAMIL1.0,and it reproduces a more reasonable MJO major structure coupling upper level wind,lower level wind,and outgoing long wave radiation.The contributions of each scheme and factor to the improvement of GAMIL2.0 simulations need further study.
The Grid-point Atmospheric Model of IAP LASG version 2 （GAMIL2） has been developed through upgrading the deep convection parameterization, cumulus cloud fraction and two-moment cloud microphys- ical scheme, as well as changing some of the large uncertain parameters. In this paper, its performance is evaluated, and the results suggest that there are some significant improvements in GAMIL2 compared to the previous version GAMIL1, for example, the components of the energy budget at the top of atmosphere （TOA） and surface; the geographic distribution of shortwave cloud radiative forcing （SWCF）; the ratio of stratiform versus total rainfall; the response of atmospheric circulation to the tropical ocean; and the east- ward propagation and spatiotemporal structures of the Madden Julian Oscillation （MJO）. Furthermore, the indirect aerosols effect （IAE） is -0.94 W m-2, within the range of 0 to -2 W m-2 given by the IPCC 4th Assessment Report （2007）. The influence of uncertain parameters on the MJO and radiation fluxes is also discussed.
The variability of Atlantic Meridional Overturning Circulation （AMOC） in the pre-industrial control experiment of the Flexible Global Ocean-Atmosphere-Land System model, Grid-point Version 2 （FGOALS-g2） was investigated using the model outputs with the most stable state in a 512-yr time window from the total 1500-yr period of the experiment. The period of AMOC in FGOALS-g2 is double peaked at 20 and 32 years according to the power spectrum, and 22 years according to an auto-correlation analysis, which shows very obvious decadal variability. Like many other coupled climate models, the decadal variability of AMOC in FGOALS-g2 is closely related to the convection that occurs in the Labrador Sea region. Deep convection in the Labrador Sea in FGOALS-g2 leads the AMOC maximum by 3-4 years. The contributions of thermal and haline effects to the variability of the convection in three different regions [the Labrador, Irminger and Greenland-Iceland- Norwegian （GIN） Seas] were analyzed for FGOALS-g2. The variability of convection in the Labrador and Irminger Seas is thermally dominant, while that in the colder GIN Seas can be mainly attributed to salinity changes due to the lower thermal expansion. By comparing the simulation results from FGOALS-g2 and 11 other models, it was found that AMOC variability can be attributed to salinity changes for longer periods （longer than 35 years） and to temperature changes for shorter periods.
CAPT and Atmospheric （Climate Change Prediction Radiation Measurement Program Program （CCPP-ARM） Parameterization Testbed） has been a valu- able tool to assess climate models in recent years, and the Tropical Warm Pool-International Cloud Experiment （TWP-ICE） has collected comprehensive measurements to verify its physical parameterizations. The present study evaluates the performances of the two GAMIL （grid-point atmospheric model of lAP LASG） versions during TWP-ICE using CAPT. The results indicate that GAMIL2.0 reproduced better shifts of clouds and rainfall during three distinct monsoon phases than GAMIL1.0, although both of them simulated the large-scale dynamical states well, which are mainly attributable to the different convective parameterizations.
