Evaluation of NASA GISS Post-CMIP5 Single Column Model Simulated Clouds and Precipitation Using ARM Southern Great Plains Observations

The planetary boundary layer turbulence and moist convection parameterizations have been modified recently in the NASA Goddard Institute for Space Studies （GISS） Model E2 atmospheric general circulation model （GCM; post-CMIP5, hereafter P5）. In this study, single column model （SCM_P5） simulated cloud fractions （CFs）, cloud liquid water paths （LWPs） and precipitation were compared with Atmospheric Radiation Measurement （ARM） Southern Great Plains （SGP） groundbased observations made during the period 2002-08. CMIP5 SCM simulations and GCM outputs over the ARM SGP region were also used in the comparison to identify whether the causes of cloud and precipitation biases resulted from either the physical parameterization or the dynamic scheme. The comparison showed that the CMIP5 SCM has difficulties in simulating the vertical structure and seasonal variation of low-level clouds. The new scheme implemented in the turbulence parameterization led to significantly improved cloud simulations in P5. It was found that the SCM is sensitive to the relaxation time scale. When the relaxation time increased from 3 to 24 h, SCM_P5-simulated CFs and LWPs showed a moderate increase （10%-20%） but precipitation increased significantly （56%）, which agreed better with observations despite the less accurate atmospheric state. Annual averages among the GCM and SCM simulations were almost the same, but their respective seasonal variations were out of phase. This suggests that the same physical cloud parameterization can generate similar statistical results over a long time period, but different dynamics drive the differences in seasonal variations. This study can potentially provide guidance for the further development of the GISS model.

A Sensitivity Study of Single Column Model

A single column model (SCM) is constructed by extracting the physical subroutines from the NCAR Community Climate Model version 1 (CCM1).Simulated data are generated by CCM1 and used to validate the SCM and to study the sensitivity of the SCM to errors in its input data.It is found that the SCM temperature predictions are moderately sensitive to errors in the input horizontal temperature flux convergence and moisture flux convergence.Two types of error are concerned in this study,random errors due to insufficient data resolution,and errors due to insufficient data area coverage.While the first type of error can be reduced by filtering and/or increasing the data resolution,it is shown that the second type of error can be reduced by enlarging the data area coverage and using a suitable method to compute the input flux convergence terms.

The Construction of SCM in GRAPES and Its Applications in Two Field Experiment Simulations

A Single Column Model(SCM) for Global and Regional Atmospheric Prediction Enhanced System (GRAPES) is constructed for the purpose of evaluating physical process parameterizations.Two observational datasets including Wangara and the third Global Energy and Water Cycle Experiment Atmospheric Boundary Layer Study(GABLS-3) SCM field observations have been applied to evaluate this SCM.By these two numerical experiments,the GRAPESSCM is verified to be correctly constructed.Furthermore, the interaction between the land surface process and atmospheric boundary layer(ABL) is discussed through the second experiment.It is found that CASE3(CoLM land surface scheme coupled with ABL scheme) simulates less sensible heat fluxes and smaller surface temperature which corresponds with its lower potential temperature at the bottom of the ABL.Moreover,CASE3 simulates turbulence that is weaker during the daytime and stronger during nighttime,corresponding with its wind speed at 200 m which is bigger during daytime and smaller during nighttime.However,they are generally opposite in CASE2(SLAB coupled with ABL).The initial profile of the water vapor mixing ratio is artificially increased by the experiment setup which results in the simulated water vapor mixing becoming wetter than actually observed.CASE1 (observed surface temperature taken as lower thermal forcing) and CASE2 have no soil moisture prediction and simulate a similar water vapor mixing ratio,while CASE3 has a soil moisture prediction and simulates wetter.It is also shown that the time step may affect the stabilization of the ABL when the vertical levels of the SCM are fixed.