Using A-Train Observations to Evaluate Cloud Occurrence and Radiative Effects in the Community Atmosphere Model during the Southeast Asia Summer Monsoon

The distribution of clouds and their radiative effects in the Community Atmosphere Model, version 5 (CAM5), are compared to A-Train satellite data in Southeast Asia during the summer monsoon. Cloud radiative kernels are created based on populations of observed and modeled clouds separately in order to compare the sensitivity of the TOA radiation to changes in cloud fraction. There is generally good agreement between the observation- and model-derived cloud radiative kernels for most cloud types, meaning that the clouds in the model are heating and cooling like clouds in nature. Cloud radiative effects are assessed by multiplying the cloud radiative kernel by the cloud fraction histogram. For ice clouds in particular, there is good agreement between the model and observations, with optically thin cirrus producing a moderate warming effect and cirrostratus producing a slight cooling effect, on average. Consistent with observations, the model also shows that the median value of the ice water path (IWP) distribution, rather than the mean, is a more representative measure of the ice clouds that are responsible for heating. In addition, in both observations and the model, it is cirrus clouds with an IWP of 20 g m(-2) that have the largest warming effect in this region, given their radiative heating and frequency of occurrence.

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Author Berry, Elizabeth
Mace, Gerald G.
Gettelman, Andrew
Publisher UCAR/NCAR - Library
Publication Date 2019-07-01T00:00:00
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Topic Category geoscientificInformation
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Metadata Date 2023-08-18T19:20:29.577595
Metadata Record Identifier edu.ucar.opensky::articles:22600
Metadata Language eng; USA
Suggested Citation Berry, Elizabeth, Mace, Gerald G., Gettelman, Andrew. (2019). Using A-Train Observations to Evaluate Cloud Occurrence and Radiative Effects in the Community Atmosphere Model during the Southeast Asia Summer Monsoon. UCAR/NCAR - Library. http://n2t.net/ark:/85065/d7bv7k3w. Accessed 20 June 2025.

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