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    Characterizing and Understanding Cloud Ice and Radiation Budget Biases in Global Climate Models and Reanalysis

    Source: Meteorological Monographs:;2016:;Volume( 56 )::page 13.1
    Author:
    Li, J.-L. F.
    ,
    Waliser, D. E.
    ,
    Stephens, G.
    ,
    Lee, Seungwon
    DOI: 10.1175/AMSMONOGRAPHS-D-15-0007.1
    Publisher: American Meteorological Society
    Abstract: he authors present an observationally based evaluation of the vertically resolved cloud ice water content (CIWC) and vertically integrated cloud ice water path (CIWP) as well as radiative shortwave flux downward at the surface (RSDS), reflected shortwave (RSUT), and radiative longwave flux upward at top of atmosphere (RLUT) of present-day global climate models (GCMs), notably twentieth-century simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), and compare these results to those of the third phase of the Coupled Model Intercomparison Project (CMIP3) and two recent reanalyses. Three different CloudSat and/or Cloud?Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) combined ice water products and two methods are used to remove the contribution from the convective core ice mass and/or precipitating cloud hydrometeors with variable sizes and falling speeds so that a robust observational estimate can be obtained for model evaluations.The results show that, for annual mean CIWC and CIWP, there are factors of 2?10 (either over- or underestimate) in the differences between observations and models for a majority of the GCMs and for a number of regions. Most of the GCMs in CMIP3 and CMIP5 significantly underestimate the total ice water mass because models only consider suspended cloud mass, ignoring falling and convective core cloud mass. For the annual means of RSDS, RLUT, and RSUT, a majority of the models have significant regional biases ranging from ?30 to 30 W m?2. Based on these biases in the annual means, there is virtually no progress in the simulation fidelity of RSDS, RLUT, and RSUT fluxes from CMIP3 to CMIP5, even though there is about a 50% bias reduction improvement of global annual mean CIWP from CMIP3 to CMIP5. It is concluded that at least a part of these persistent biases stem from the common GCM practice of ignoring the effects of precipitating and/or convective core ice and liquid in their radiation calculations.
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      Characterizing and Understanding Cloud Ice and Radiation Budget Biases in Global Climate Models and Reanalysis

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    contributor authorLi, J.-L. F.
    contributor authorWaliser, D. E.
    contributor authorStephens, G.
    contributor authorLee, Seungwon
    date accessioned2017-06-09T16:41:47Z
    date available2017-06-09T16:41:47Z
    date copyright2016/04/01
    date issued2016
    identifier issn0065-9401
    identifier otherams-72408.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4214408
    description abstracthe authors present an observationally based evaluation of the vertically resolved cloud ice water content (CIWC) and vertically integrated cloud ice water path (CIWP) as well as radiative shortwave flux downward at the surface (RSDS), reflected shortwave (RSUT), and radiative longwave flux upward at top of atmosphere (RLUT) of present-day global climate models (GCMs), notably twentieth-century simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), and compare these results to those of the third phase of the Coupled Model Intercomparison Project (CMIP3) and two recent reanalyses. Three different CloudSat and/or Cloud?Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) combined ice water products and two methods are used to remove the contribution from the convective core ice mass and/or precipitating cloud hydrometeors with variable sizes and falling speeds so that a robust observational estimate can be obtained for model evaluations.The results show that, for annual mean CIWC and CIWP, there are factors of 2?10 (either over- or underestimate) in the differences between observations and models for a majority of the GCMs and for a number of regions. Most of the GCMs in CMIP3 and CMIP5 significantly underestimate the total ice water mass because models only consider suspended cloud mass, ignoring falling and convective core cloud mass. For the annual means of RSDS, RLUT, and RSUT, a majority of the models have significant regional biases ranging from ?30 to 30 W m?2. Based on these biases in the annual means, there is virtually no progress in the simulation fidelity of RSDS, RLUT, and RSUT fluxes from CMIP3 to CMIP5, even though there is about a 50% bias reduction improvement of global annual mean CIWP from CMIP3 to CMIP5. It is concluded that at least a part of these persistent biases stem from the common GCM practice of ignoring the effects of precipitating and/or convective core ice and liquid in their radiation calculations.
    publisherAmerican Meteorological Society
    titleCharacterizing and Understanding Cloud Ice and Radiation Budget Biases in Global Climate Models and Reanalysis
    typeJournal Paper
    journal volume56
    journal titleMeteorological Monographs
    identifier doi10.1175/AMSMONOGRAPHS-D-15-0007.1
    journal fristpage13.1
    journal lastpage13.20
    treeMeteorological Monographs:;2016:;Volume( 56 )
    contenttypeFulltext
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