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    Tests of Monte Carlo Independent Column Approximation in the ECHAM5 Atmospheric GCM

    Source: Journal of Climate:;2007:;volume( 020 ):;issue: 019::page 4995
    Author:
    Räisänen, P.
    ,
    Järvenoja, S.
    ,
    Järvinen, H.
    ,
    Giorgetta, M.
    ,
    Roeckner, E.
    ,
    Jylhä, K.
    ,
    Ruosteenoja, K.
    DOI: 10.1175/JCLI4290.1
    Publisher: American Meteorological Society
    Abstract: The Monte Carlo Independent Column Approximation (McICA) method for computing domain-average radiative fluxes allows a flexible treatment of unresolved cloud structure, and it is unbiased with respect to the full ICA, but its flux estimates contain conditional random noise. Here, tests of McICA in the ECHAM5 atmospheric GCM are reported. ECHAM5 provides an interesting test bed for McICA because it carries prognostic variables for the subgrid-scale probability distribution of total water content, which allows us to determine subgrid-scale cloud variability directly from the resolved-scale model variables. Three experiments with differing levels of radiative noise, each consisting of ten 6-yr runs, are performed to estimate the impact of McICA noise on simulated climate. In an experiment that attempted to deliberately maximize McICA noise, a systematic reduction in low cloud fraction occurred. For a more reasonable implementation of McICA, the impact of noise is very small, although statistically discernible. In terms of the impacts of noise, McICA appears to be a viable approach for use in ECHAM5. However, to improve the simulation of cloud radiative effects, realistic representation of both unresolved and resolved cloud structures is needed, which remains a challenging problem. Comparison of ECHAM5 data with a global cloud system?resolving model dataset and with International Satellite Cloud Climatology Project data suggested two problems related to unresolved cloud structures. First, ECHAM5 appears to underestimate subgrid-scale cloud variability. This problem seems partly related to the use of the beta distribution scheme for total water content in ECHAM5: in its current form, the scheme is unable to generate highly inhomogeneous clouds (relative standard deviation of condensate amount >1). Second, it appears that in ECHAM5, overcast cloud layers occur too frequently and partially cloudy layers too rarely. This problem is not unique to the beta distribution scheme; in fact, it is more pronounced when using an alternative, relative humidity?based cloud fraction scheme.
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      Tests of Monte Carlo Independent Column Approximation in the ECHAM5 Atmospheric GCM

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    contributor authorRäisänen, P.
    contributor authorJärvenoja, S.
    contributor authorJärvinen, H.
    contributor authorGiorgetta, M.
    contributor authorRoeckner, E.
    contributor authorJylhä, K.
    contributor authorRuosteenoja, K.
    date accessioned2017-06-09T17:03:38Z
    date available2017-06-09T17:03:38Z
    date copyright2007/10/01
    date issued2007
    identifier issn0894-8755
    identifier otherams-78750.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4221453
    description abstractThe Monte Carlo Independent Column Approximation (McICA) method for computing domain-average radiative fluxes allows a flexible treatment of unresolved cloud structure, and it is unbiased with respect to the full ICA, but its flux estimates contain conditional random noise. Here, tests of McICA in the ECHAM5 atmospheric GCM are reported. ECHAM5 provides an interesting test bed for McICA because it carries prognostic variables for the subgrid-scale probability distribution of total water content, which allows us to determine subgrid-scale cloud variability directly from the resolved-scale model variables. Three experiments with differing levels of radiative noise, each consisting of ten 6-yr runs, are performed to estimate the impact of McICA noise on simulated climate. In an experiment that attempted to deliberately maximize McICA noise, a systematic reduction in low cloud fraction occurred. For a more reasonable implementation of McICA, the impact of noise is very small, although statistically discernible. In terms of the impacts of noise, McICA appears to be a viable approach for use in ECHAM5. However, to improve the simulation of cloud radiative effects, realistic representation of both unresolved and resolved cloud structures is needed, which remains a challenging problem. Comparison of ECHAM5 data with a global cloud system?resolving model dataset and with International Satellite Cloud Climatology Project data suggested two problems related to unresolved cloud structures. First, ECHAM5 appears to underestimate subgrid-scale cloud variability. This problem seems partly related to the use of the beta distribution scheme for total water content in ECHAM5: in its current form, the scheme is unable to generate highly inhomogeneous clouds (relative standard deviation of condensate amount >1). Second, it appears that in ECHAM5, overcast cloud layers occur too frequently and partially cloudy layers too rarely. This problem is not unique to the beta distribution scheme; in fact, it is more pronounced when using an alternative, relative humidity?based cloud fraction scheme.
    publisherAmerican Meteorological Society
    titleTests of Monte Carlo Independent Column Approximation in the ECHAM5 Atmospheric GCM
    typeJournal Paper
    journal volume20
    journal issue19
    journal titleJournal of Climate
    identifier doi10.1175/JCLI4290.1
    journal fristpage4995
    journal lastpage5011
    treeJournal of Climate:;2007:;volume( 020 ):;issue: 019
    contenttypeFulltext
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