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    A Comparison of MERRA and NARR Reanalyses with the DOE ARM SGP Data

    Source: Journal of Climate:;2011:;volume( 024 ):;issue: 017::page 4541
    Author:
    Kennedy, Aaron D.
    ,
    Dong, Xiquan
    ,
    Xi, Baike
    ,
    Xie, Shaocheng
    ,
    Zhang, Yunyan
    ,
    Chen, Junye
    DOI: 10.1175/2011JCLI3978.1
    Publisher: American Meteorological Society
    Abstract: tmospheric states from the Modern-Era Retrospective analysis for Research and Applications (MERRA) and the North American Regional Reanalysis (NARR) are compared with data from the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site, including the ARM continuous forcing product and Cloud Modeling Best Estimate (CMBE) soundings, during the period 1999?2001 to understand their validity for single-column model (SCM) and cloud-resolving model (CRM) forcing datasets. Cloud fraction, precipitation, and radiation information are also compared to determine what errors exist within these reanalyses. For the atmospheric state, ARM continuous forcing and the reanalyses have good agreement with the CMBE sounding information, with biases generally within 0.5 K for temperature, 0.5 m s?1 for wind, and 5% for relative humidity. Larger disagreements occur in the upper troposphere (p < 300 hPa) for temperature, humidity, and zonal wind, and in the boundary layer (p > 800 hPa) for meridional wind and humidity. In these regions, larger errors may exist in derived forcing products. Significant differences exist for vertical pressure velocity, with the largest biases occurring during the spring upwelling and summer downwelling periods. Although NARR and MERRA share many resemblances to each other, ARM outperforms these reanalyses in terms of correlation with cloud fraction. Because the ARM forcing is constrained by observed precipitation that gives the adequate mass, heat, and moisture budgets, much of the precipitation (specifically during the late spring/early summer) is caused by smaller-scale forcing that is not captured by the reanalyses. While reanalysis-based forcing appears to be feasible for the majority of the year at this location, it may have limited usage during the late spring and early summer, when convection is common at the ARM SGP site. Both NARR and MERRA capture the seasonal variation of cloud fractions (CFs) observed by ARM radar?lidar and Geostationary Operational Environmental Satellite (GOES) with high correlations (0.92?0.78) but with negative biases of 14% and 3%, respectively. Compared to the ARM observations, MERRA shows better agreement for both shortwave (SW) and longwave (LW) fluxes except for LW-down (due to a negative bias in water vapor): NARR has significant positive bias for SW-down and negative bias for LW-down under clear-sky and all-sky conditions. The NARR biases result from a combination of too few clouds and a lack of sufficient extinction by aerosols and water vapor in the atmospheric column. The results presented here represent only one location for a limited period, and more comparisons at different locations and longer periods are needed.
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      A Comparison of MERRA and NARR Reanalyses with the DOE ARM SGP Data

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4213782
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    contributor authorKennedy, Aaron D.
    contributor authorDong, Xiquan
    contributor authorXi, Baike
    contributor authorXie, Shaocheng
    contributor authorZhang, Yunyan
    contributor authorChen, Junye
    date accessioned2017-06-09T16:39:59Z
    date available2017-06-09T16:39:59Z
    date copyright2011/09/01
    date issued2011
    identifier issn0894-8755
    identifier otherams-71845.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4213782
    description abstracttmospheric states from the Modern-Era Retrospective analysis for Research and Applications (MERRA) and the North American Regional Reanalysis (NARR) are compared with data from the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site, including the ARM continuous forcing product and Cloud Modeling Best Estimate (CMBE) soundings, during the period 1999?2001 to understand their validity for single-column model (SCM) and cloud-resolving model (CRM) forcing datasets. Cloud fraction, precipitation, and radiation information are also compared to determine what errors exist within these reanalyses. For the atmospheric state, ARM continuous forcing and the reanalyses have good agreement with the CMBE sounding information, with biases generally within 0.5 K for temperature, 0.5 m s?1 for wind, and 5% for relative humidity. Larger disagreements occur in the upper troposphere (p < 300 hPa) for temperature, humidity, and zonal wind, and in the boundary layer (p > 800 hPa) for meridional wind and humidity. In these regions, larger errors may exist in derived forcing products. Significant differences exist for vertical pressure velocity, with the largest biases occurring during the spring upwelling and summer downwelling periods. Although NARR and MERRA share many resemblances to each other, ARM outperforms these reanalyses in terms of correlation with cloud fraction. Because the ARM forcing is constrained by observed precipitation that gives the adequate mass, heat, and moisture budgets, much of the precipitation (specifically during the late spring/early summer) is caused by smaller-scale forcing that is not captured by the reanalyses. While reanalysis-based forcing appears to be feasible for the majority of the year at this location, it may have limited usage during the late spring and early summer, when convection is common at the ARM SGP site. Both NARR and MERRA capture the seasonal variation of cloud fractions (CFs) observed by ARM radar?lidar and Geostationary Operational Environmental Satellite (GOES) with high correlations (0.92?0.78) but with negative biases of 14% and 3%, respectively. Compared to the ARM observations, MERRA shows better agreement for both shortwave (SW) and longwave (LW) fluxes except for LW-down (due to a negative bias in water vapor): NARR has significant positive bias for SW-down and negative bias for LW-down under clear-sky and all-sky conditions. The NARR biases result from a combination of too few clouds and a lack of sufficient extinction by aerosols and water vapor in the atmospheric column. The results presented here represent only one location for a limited period, and more comparisons at different locations and longer periods are needed.
    publisherAmerican Meteorological Society
    titleA Comparison of MERRA and NARR Reanalyses with the DOE ARM SGP Data
    typeJournal Paper
    journal volume24
    journal issue17
    journal titleJournal of Climate
    identifier doi10.1175/2011JCLI3978.1
    journal fristpage4541
    journal lastpage4557
    treeJournal of Climate:;2011:;volume( 024 ):;issue: 017
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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