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Modelling both water and ice clouds: how goes the worthy effort?

02 Nov 2022 | Science Notes

From the CO2Science archive: In this intriguing study, Kay et al. (2016) used space-borne lidar observations from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite to evaluate cloud amount and phase in the Community Atmosphere Model version 5 (CAM5), which is the atmospheric component of a widely-used state-of-the-art global coupled climate model dubbed the Community Earth System Model, wherein they embedded a lidar simulator. And what did they learn from this exercise?

Paper reviewed: Kay, J.E., Bourdages, L., Miller, N.B., Morrison, A., Yettelia, V., Chepfer, H. and Eaton, B. 2016. Evaluating and improving cloud phase in the Community Atmosphere Model version 5 using spaceborne lidar observations. Journal of Geophysical Research: Atmospheres 121: 4162-4176.

The seven scientists – hailing from Canada, France and the United States – report that (1) “CAM5 has insufficient liquid cloud” and (2) “excessive ice cloud,” compared to CALIPSO observations, and that (3) “over the ice-covered Arctic Ocean, CAM5 has insufficient liquid cloud in all seasons.” On top of these problems, they further note that (4) “a liquid cloud deficit contributes to a cold bias of 2-3°C for summer daily maximum near-surface air temperature at Summit, Greenland.” Also, over mid-latitude storm tracks, CAM5 is reported by them to have (5) “excessive ice cloud” and (6) “insufficient liquid cloud.” And over the Southern Ocean, they report there are also (7) “larger-than-observed seasonal variations in cloud phase” in CAM5.

As for their take-home message, Kay et al. say their results “demonstrate the importance and value of simulator-enabled comparisons of cloud phase in models used for future climate projection.” But their report on their research indicates there are still model shortcomings that need to be resolved.

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