1. Evaluation of the CAM6 Climate Model Using Cloud Observations at McMurdo Station, Antarctica.
- Author
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Yip, Jackson, Diao, Minghui, Barone, Tyler, Silber, Israel, and Gettelman, Andrew
- Subjects
LIDAR ,CLOUDS ,THERMODYNAMICS ,ANTARCTIC climate ,ANTARCTIC environmental conditions - 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 and phase as well as thermodynamic variables were examined to identify model biases. The model overestimates cloud cover above 3 km and underestimates it below that altitude. In cases where cloud cover is greater than 60%, the model also produces excessively large percentages of liquid clouds. These model biases are well correlated with biases in relative humidity, which is further dominated by biases in water vapor concentrations. Thus, these findings indicate that improving representations of water vapor concentrations in the model is a key step toward improving the simulations of cloud characteristics in Antarctica. Key Points: CAM6 shows higher (lower) cloud fraction above (below) 3 km than observations at McMurdo Station, AntarcticaCAM6 underestimates (overestimates) ice phase proportion among all cloud samples at cloud fraction ≥0.6 (<0.6)Model RH biases are dominated by water vapor biases instead of temperature biases, and correlate with cloud fraction and cloud phase biases [ABSTRACT FROM AUTHOR]
- Published
- 2021
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