Integrating and Interpreting Aerosol Observations and Models within the PARAGON Framework

Thomas P. Ackerman
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Amy J. Braverman
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David J. Diner
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Theodore L. Anderson
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Ralph A. Kahn
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John V. Martonchik
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Joyce E. Penner
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Philip J. Rasch
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Bruce A. Wielicki
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Bin Yu
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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.

Pacific Northwest National Laboratory, Richland, Washington

Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California

University of Washington, Seattle, Washington

University of Michigan, Ann Arbor, Michigan

National Center for Atmospheric Research, Boulder, Colorado

NASA Langley Research Center, Hampton, Virginia

University of California, Berkeley, Berkeley, California

CORRESPONDING AUTHOR: David J. Diner, JPL Mail Stop 169-237, 4800 Oak Grove Drive, Pasadena, CA 91 109, E-mail: djd@jord.jpl.nasa.gov

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.

Pacific Northwest National Laboratory, Richland, Washington

Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California

University of Washington, Seattle, Washington

University of Michigan, Ann Arbor, Michigan

National Center for Atmospheric Research, Boulder, Colorado

NASA Langley Research Center, Hampton, Virginia

University of California, Berkeley, Berkeley, California

CORRESPONDING AUTHOR: David J. Diner, JPL Mail Stop 169-237, 4800 Oak Grove Drive, Pasadena, CA 91 109, E-mail: djd@jord.jpl.nasa.gov
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