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

    Source: Journal of Climate:;2019:;volume 032:;issue 014::page 4145
    Author:
    Berry, Elizabeth
    ,
    Mace, Gerald G.
    ,
    Gettelman, Andrew
    DOI: 10.1175/JCLI-D-18-0693.1
    Publisher: American Meteorological Society
    Abstract: AbstractThe 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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      Using A-Train Observations to Evaluate Cloud Occurrence and Radiative Effects in the Community Atmosphere Model during the Southeast Asia Summer Monsoon

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4263195
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    contributor authorBerry, Elizabeth
    contributor authorMace, Gerald G.
    contributor authorGettelman, Andrew
    date accessioned2019-10-05T06:42:59Z
    date available2019-10-05T06:42:59Z
    date copyright4/16/2019 12:00:00 AM
    date issued2019
    identifier otherJCLI-D-18-0693.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4263195
    description abstractAbstractThe 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.
    publisherAmerican Meteorological Society
    titleUsing A-Train Observations to Evaluate Cloud Occurrence and Radiative Effects in the Community Atmosphere Model during the Southeast Asia Summer Monsoon
    typeJournal Paper
    journal volume32
    journal issue14
    journal titleJournal of Climate
    identifier doi10.1175/JCLI-D-18-0693.1
    journal fristpage4145
    journal lastpage4165
    treeJournal of Climate:;2019:;volume 032:;issue 014
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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