TY - JOUR
T1 - Evaluation of the CAM6 Climate Model Using Cloud Observations at McMurdo Station, Antarctica
AU - Yip, Jackson
AU - Diao, Minghui
AU - Barone, Tyler
AU - Silber, Israel
AU - Gettelman, Andrew
N1 - Funding Information:
J. P. Yip, T. Barone and M. Diao would like to acknowledge the funding grants for this research provided by the U.S. National Science Foundation Office of Polar Programs (OPP grant #1744965) and Division of Atmospheric and Geospace Science (AGS grant #1642291). M. Diao also acknowledges the support from the Department of Energy (DOE) Atmospheric System Research (ASR) grant DE-SC0021211. I. Silber was supported by the National Science Foundation grant PLR-1443495 and the DOE grant DE-SC0017981. A. Gettelman acknowledges funding from NSF OPP grant #1744946. The National Center for Atmospheric Research is supported by the U.S. National Science Foundation. We thank all the hard work from the AWARE campaign science team.
Funding Information:
J. P. Yip, T. Barone and M. Diao would like to acknowledge the funding grants for this research provided by the U.S. National Science Foundation Office of Polar Programs (OPP grant #1744965) and Division of Atmospheric and Geospace Science (AGS grant #1642291). M. Diao also acknowledges the support from the Department of Energy (DOE) Atmospheric System Research (ASR) grant DE‐SC0021211. I. Silber was supported by the National Science Foundation grant PLR‐1443495 and the DOE grant DE‐SC0017981. A. Gettelman acknowledges funding from NSF OPP grant #1744946. The National Center for Atmospheric Research is supported by the U.S. National Science Foundation. We thank all the hard work from the AWARE campaign science team.
Publisher Copyright:
© 2021. American Geophysical Union. All Rights Reserved.
PY - 2021/8
Y1 - 2021/8
N2 - 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.
AB - 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.
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U2 - 10.1029/2021JD034653
DO - 10.1029/2021JD034653
M3 - Article
AN - SCOPUS:85113425954
SN - 2169-897X
VL - 126
JO - Journal of Geophysical Research: Atmospheres
JF - Journal of Geophysical Research: Atmospheres
IS - 16
M1 - e2021JD034653
ER -