Effects of model resolution and parameterizations on the simulations of clouds, precipitation, and their interactions with aerosols

Abstract

<p><strong>Abstract.</strong> This study investigates the effects of model resolution and microphysics parameterizations on the uncertainties or errors in the simulations of clouds, precipitation, and their interactions with aerosols using the Global Forecast System (GFS) model as one of the representative numerical weather prediction (NWP) models. For this investigation, we used the GFS model results and compare them with those from the cloud-system resolving model (CSRM) simulations as benchmark simulations that adopt high resolutions and full-fledged microphysical processes. These simulations were evaluated against observations and this evaluation demonstrated that the CSRM simulations can function as benchmark simulations. Substantially lower updrafts and associated cloud variables (e.g., cloud mass and condensation) were simulated by the GFS model compared to those simulated by the CSRM. This is mainly due to the coarse resolutions in the GFS model. This indicates that the parameterizations that represent sub-grid processes in the GFS model do not work well and thus need to be improved. Results here also indicate that the use of the coarse resolution in the GFS model lowers the sensitivity of updrafts and cloud variables to increasing aerosol concentrations compared to the CSRM simulations. The parameterization of the saturation process plays an important role in the sensitivity of cloud variables to aerosol concentrations while the parameterization of the sedimentation process has a substantial impact on how cloud variables are distributed vertically. The variation in cloud variables with resolution is much greater and contributes to the discrepancy between the GFS and CSRM simulations to a much greater degree than what happens with varying microphysics parameterizations.</p>

Comparison of Anthropogenic Aerosol Climate Effects among Three Climate Models with Reduced Complexity

“…Using these climate models, aerosol optical and cloud-interaction properties can be calculated and used to estimate aerosol climate effects. This approach proved to be challenging because important aerosol processes and aerosol-cloud interactions remain poorly understood [14][15][16], and even well-understood processes are difficult to simulate consistently in large-scale climate models [17][18][19]. As a result, individual climate and precursor emissions are applied to derive the CAM model.…”