Evaluation of the CAM6 Climate Model Using Cloud Observations at McMurdo Station, Antarctica

Abstract

Simulating clouds is an intricate challenge for global climate models (GCMs). In pursuit of improving the fidelity of future climate prediction, a better understanding of cloud radiative effects and the environmental conditions for cloud formation is needed. To estimate cloud radiative effects, models must accurately represent physical processes occurring during cloud formation and evolution, in order to capture cloud microphysical properties (e.g., mass and number concentrations of cloud hydrometeors) and macrophysical properties (e.g., vertical and horizontal extent, cloud fraction) (Liou, 1992;Liou & Wittman, 1979). Therefore, systematic identification of these physical processes is one Abstract A comparative analysis between observational data from McMurdo Station, Antarctica and the Community Atmosphere Model version 6 (CAM6) simulation is performed focusing on cloud characteristics and their thermodynamic conditions. Ka-band Zenith Radar (KAZR) and High Spectral Resolution Lidar (HSRL) retrievals are used as the basis of cloud fraction and cloud phase identifications. Radiosondes released at 12-h increments provide atmospheric profiles for evaluating the simulated thermodynamic conditions. Our findings show that the CAM6 simulation consistently overestimates (underestimates) cloud fraction above (below) 3 km in four seasons of a year. Normalized by total in-cloud samples, ice and mixed phase occurrence frequencies are underestimated and liquid phase frequency is overestimated by the model at cloud fractions above 0.6, while at cloud fractions below 0.6 ice phase frequency is overestimated and liquid-containing phase frequency is underestimated by the model. The cloud fraction biases are closely associated with concurrent biases in relative humidity (RH), that is, high (low) RH biases above (below) 2 km. Frequencies of correctly simulating ice and liquid-containing phase increase when the absolute biases of RH decrease. Cloud fraction biases also show a positive correlation with RH biases. Water vapor mixing ratio biases are the primary contributor to RH biases, and hence, likely a key factor controlling the cloud biases. This diagnosis of the evident shortfalls of representations of cloud characteristics in CAM6 simulation at McMurdo Station brings new insight in improving the governing model physics therein.Plain Language Summary Global climate models (GCMs) historically struggle to accurately estimate the amounts and types of clouds over the polar regions. Cloud cover and thermodynamic phase directly influence Earth's radiation budget and the accuracy of future climate prediction. Particularly, Antarctic ice sheet is vulnerable to a changing climate through interactions with atmosphere and ocean, and the impacts of clouds are still not well understood. In this study, shortcomings of cloud representations in the CAM6 model were diagnosed by comparing with observational data (ground-based remote sensing and radiosondes), which encompassed a year of measurements at McMurdo Station, Antarctica. Cloud fraction...

Ship‐Based Observations and Climate Model Simulations of Cloud Phase Over the Southern Ocean

“…The E3SM in-cloud frequency shows a sudden increase below −20°C in the 60°-70°S latitudinal bin which is not seen in the observations. This is consistent with a recent study which showed that the Community Atmosphere Model version 6 (CAM6) climate model (i.e., a model with similar cloud microphysics parameterizations to E3SM version 1) tends to overestimate cloud fraction and cloud height at higher latitudes (Yip et al, 2021).…”

“…Tuning the model parameterization to allow more SLW has been found to reduce the shortwave bias (Kay, Bourdages, et al., 2016; Kay, Wall, et al., 2016). Observations have confirmed that cloud top SLW layers are common over the SO and Antarctica (Yip et al., 2021; D. Zhang et al., 2010; D. Zhang et al., 2019; Y. Zhang et al., 2019). Analysis of satellite data further shows that cloud top phase varies with latitudes (Mace, Protat, & Benson, 2021).…”

“…An interesting feature is observed at the higher latitudes (Figure 10p), that is, liquid phase frequency slightly increases at temperatures between −10°C and −30°C compared with lower latitudes (Figures 10f and 10k). This is likely due to the presence of SLW layers commonly observed near cloud tops at higher latitudes (Alexander et al, 2021;Huang et al, 2012;Mace, Protat, & Benson, 2021;Yip et al, 2021) which occur at lower temperatures compared with liquid layers found near surface. This phenomenon is represented as higher mixed-phase frequencies in M1 (Figure 10q) and higher liquid-phase frequencies in M2 (Figure 10r) due to reasons discussed in Figures 8 and 9.…”

Predicting Frigid Mixed‐Phase Clouds for Pristine Coastal Antarctica

“…The newer CAM6 has enhancements to cloud ice nucleation and simulates increased supercooled liquid (Gettelman et al, 2020). Yip et al (2021) found that in contrast to the CAM5 results, CAM6 frequently overstimulates liquid water at McMurdo. While this may appear to be a contrarian result, it may emphasize the need for improved modeling of cases with enhanced ice particle amounts.…”

“…Yip et al. (2021) found that in contrast to the CAM5 results, CAM6 frequently overstimulates liquid water at McMurdo. While this may appear to be a contrarian result, it may emphasize the need for improved modeling of cases with enhanced ice particle amounts.…”