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    Integrating and Interpreting Aerosol Observations and Models within the PARAGON Framework

    Source: Bulletin of the American Meteorological Society:;2004:;volume( 085 ):;issue: 010::page 1523
    Author:
    Ackerman, Thomas P.
    ,
    Braverman, Amy J.
    ,
    Diner, David J.
    ,
    Anderson, Theodore L.
    ,
    Kahn, Ralph A.
    ,
    Martonchik, John V.
    ,
    Penner, Joyce E.
    ,
    Rasch, Philip J.
    ,
    Wielicki, Bruce A.
    ,
    Yu, Bin
    DOI: 10.1175/BAMS-85-10-1523
    Publisher: American Meteorological Society
    Abstract: Given the breadth and complexity of available data, constructing a measurement-based description of global tropospheric aerosols that will effectively confront and constrain global three-dimensional models is a daunting task. Because data are obtained from multiple sources and acquired with nonuniform spatial and temporal sampling, scales, and coverage, protocols need to be established that will organize this vast body of knowledge. Currently, there is no capability to assemble the existing aerosol data into a unified, interoperable whole. Technology advancements now being pursued in high-performance distributed computing initiatives can accomplish this objective. Once the data are organized, there are many approaches that can be brought to bear upon the problem of integrating data from different sources. These include data-driven approaches, such as geospatial statistics formulations, and model-driven approaches, such as assimilation or chemical transport modeling. Establishing a data interoperability framework will stimulate algorithm development and model validation and will facilitate the exploration of synergies between different data types. Data summarization and mining techniques can be used to make statistical inferences about climate system relationships and interpret patterns of aerosol-induced change. Generating descriptions of complex, nonlinear relationships among multiple parameters is critical to climate model improvement and validation. Finally, determining the role of aerosols in past and future climate change ultimately requires the use of fully coupled climate and chemistry models, and the evaluation of these models is required in order to trust their results. The set of recommendations presented here address one component of the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) initiative. Implementing them will produce the most accurate four-dimensional representation of global aerosols, which can then be used for testing, constraining, and validating models. These activities are critical components of a sustained program to quantify aerosol effects on global climate.
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      Integrating and Interpreting Aerosol Observations and Models within the PARAGON Framework

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    • Bulletin of the American Meteorological Society

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    contributor authorAckerman, Thomas P.
    contributor authorBraverman, Amy J.
    contributor authorDiner, David J.
    contributor authorAnderson, Theodore L.
    contributor authorKahn, Ralph A.
    contributor authorMartonchik, John V.
    contributor authorPenner, Joyce E.
    contributor authorRasch, Philip J.
    contributor authorWielicki, Bruce A.
    contributor authorYu, Bin
    date accessioned2017-06-09T16:42:23Z
    date available2017-06-09T16:42:23Z
    date copyright2004/10/01
    date issued2004
    identifier issn0003-0007
    identifier otherams-72639.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4214664
    description abstractGiven the breadth and complexity of available data, constructing a measurement-based description of global tropospheric aerosols that will effectively confront and constrain global three-dimensional models is a daunting task. Because data are obtained from multiple sources and acquired with nonuniform spatial and temporal sampling, scales, and coverage, protocols need to be established that will organize this vast body of knowledge. Currently, there is no capability to assemble the existing aerosol data into a unified, interoperable whole. Technology advancements now being pursued in high-performance distributed computing initiatives can accomplish this objective. Once the data are organized, there are many approaches that can be brought to bear upon the problem of integrating data from different sources. These include data-driven approaches, such as geospatial statistics formulations, and model-driven approaches, such as assimilation or chemical transport modeling. Establishing a data interoperability framework will stimulate algorithm development and model validation and will facilitate the exploration of synergies between different data types. Data summarization and mining techniques can be used to make statistical inferences about climate system relationships and interpret patterns of aerosol-induced change. Generating descriptions of complex, nonlinear relationships among multiple parameters is critical to climate model improvement and validation. Finally, determining the role of aerosols in past and future climate change ultimately requires the use of fully coupled climate and chemistry models, and the evaluation of these models is required in order to trust their results. The set of recommendations presented here address one component of the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) initiative. Implementing them will produce the most accurate four-dimensional representation of global aerosols, which can then be used for testing, constraining, and validating models. These activities are critical components of a sustained program to quantify aerosol effects on global climate.
    publisherAmerican Meteorological Society
    titleIntegrating and Interpreting Aerosol Observations and Models within the PARAGON Framework
    typeJournal Paper
    journal volume85
    journal issue10
    journal titleBulletin of the American Meteorological Society
    identifier doi10.1175/BAMS-85-10-1523
    journal fristpage1523
    journal lastpage1533
    treeBulletin of the American Meteorological Society:;2004:;volume( 085 ):;issue: 010
    contenttypeFulltext
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