This study derives radiatively-active hydrometeors frequencies (HFs) from CloudSat-CALIPSO satellite data to evaluate cloud fraction in present-day simulations by CMIP5 models. Most CMIP5 models do not consider precipitating and/or convective hydrometeors but CESM1-CAM5 in CMIP5 has diagnostic snow and CESM2-CAM6 in CMIP6 has prognostic precipitating ice (snow) included. However, the models do not have snow fraction available for evaluation. Since the satellite-retrieved hydrometeors include the mixtures of floating, precipitating and convective ice and liquid particles, a filtering method is applied to produce estimates of cloud-only HF (or NPCHF) from the total radiatively-active HF (THF), which is the sum of NPCHF, precipitating ice HF and convective HF. The reference HF data for model evaluation include estimates of liquid-phase NPCHF from CloudSat radar-only data (2B-CWC) and ice-phase THF from CloudSat-CALIPSO 2C-ICE combined radar/lidar data. The model evaluation results show that cloud fraction from CMIP5 multi-model mean (MMM) is significantly underestimated (up to 30 %) against the total HF estimates, mainly below the mid-troposphere over the extratropics and in the upper-troposphere over the midlatitude lands and a few tropical convective regions. The CMIP5 cloud fraction biases are reduced dramatically when compared to the cloud-only HF estimates, but the area of overestimates expands from the tropical convective regions to mid-latitudes in the lower and upper troposphere. There is no CMIP5 standard output snow fraction available for comparison against CloudSat-CALIPSO estimate. The implications of these results show that hydrometeors frequency estimates from CloudSat-CALIPSO provide a reference for GCM’s cloud fraction from stratiform and convective form.

Sub-grid topographic heterogeneity has large impacts on surface energy balance and land-atmosphere interactions. However, the impacts of representing sub-grid topographic effects in land surface models (LSMs) on surface energy balance and boundary conditions remain unclear. This study analyzed and evaluated the impacts of sub-grid topographic representations on surface energy balance, turbulent heat flux and scalar (co-)variances in the Energy Exascale Earth System Model (E3SM) land model (ELM). Three sub-grid topographic representations in ELM were compared: (1) the default sub-grid structure (D), (2) the recently developed sub-grid topographic structure (T), and (3) high spatial resolution (1KM). Additionally, two different solar radiation schemes in ELM were compared: (1) the default plane-parallel radiative transfer scheme (PP) and (2) the parameterization scheme (TOP) that accounts for sub-grid topographic effects on solar radiation. A series of simulations with the three grid structures (D, T and 1KM) and two treatments of solar radiation (TOP and PP) were carried out in the Sierra Nevada, California. There are significant differences between TOP and PP in the 1-km simulated surface energy balance, but the differences in the mean values and standard deviations become small when aggregated to the grid-scale (i.e., 0.5°). The T configuration better mimics the 1KM simulations than the D configuration, and better captures the sub-grid topographic effects on surface energy balance as well as surface boundary conditions. These results underline the importance of representing sub-grid topographic heterogeneities in LSMs and motivate future research to understand the sub-grid topographic effects on land-atmosphere interactions over mountain areas.