Search Results
You are looking at 1 - 4 of 4 items for :
- Author or Editor: Philip J. Rasch x
- Bulletin of the American Meteorological Society x
- Refine by Access: All Content x
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.
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.
A comprehensive and cohesive aerosol measurement record with consistent, well-understood uncertainties is a prerequisite to understanding aerosol impacts on long-term climate and environmental variability. Objectives to attaining such an understanding include improving upon the current state-of-the-art sensor calibration and developing systematic validation methods for remotely sensed microphysical properties. While advances in active and passive remote sensors will lead to needed improvements in retrieval accuracies and capabilities, ongoing validation is essential so that the changing sensor characteristics do not mask atmospheric trends. Surface-based radiometer, chemical, and lidar networks have critical roles within an integrated observing system, yet they currently undersample key geographic regions, have limitations in certain measurement capabilities, and lack stable funding. In situ aircraft observations of size-resolved aerosol chemical composition are necessary to provide important linkages between active and passive remote sensing. A planned, systematic approach toward a global aerosol observing network, involving multiple sponsoring agencies and surface-based, suborbital, and spaceborne sensors, is required to prioritize trade-offs regarding capabilities and costs. This strategy is a key ingredient of the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) framework. A set of recommendations is presented.
A comprehensive and cohesive aerosol measurement record with consistent, well-understood uncertainties is a prerequisite to understanding aerosol impacts on long-term climate and environmental variability. Objectives to attaining such an understanding include improving upon the current state-of-the-art sensor calibration and developing systematic validation methods for remotely sensed microphysical properties. While advances in active and passive remote sensors will lead to needed improvements in retrieval accuracies and capabilities, ongoing validation is essential so that the changing sensor characteristics do not mask atmospheric trends. Surface-based radiometer, chemical, and lidar networks have critical roles within an integrated observing system, yet they currently undersample key geographic regions, have limitations in certain measurement capabilities, and lack stable funding. In situ aircraft observations of size-resolved aerosol chemical composition are necessary to provide important linkages between active and passive remote sensing. A planned, systematic approach toward a global aerosol observing network, involving multiple sponsoring agencies and surface-based, suborbital, and spaceborne sensors, is required to prioritize trade-offs regarding capabilities and costs. This strategy is a key ingredient of the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) framework. A set of recommendations is presented.
Aerosols exert myriad influences on the earth's environment and climate, and on human health. The complexity of aerosol-related processes requires that information gathered to improve our understanding of climate change must originate from multiple sources, and that effective strategies for data integration need to be established. While a vast array of observed and modeled data are becoming available, the aerosol research community currently lacks the necessary tools and infrastructure to reap maximum scientific benefit from these data. Spatial and temporal sampling differences among a diverse set of sensors, nonuniform data qualities, aerosol mesoscale variabilities, and difficulties in separating cloud effects are some of the challenges that need to be addressed. Maximizing the longterm benefit from these data also requires maintaining consistently well-understood accuracies as measurement approaches evolve and improve. Achieving a comprehensive understanding of how aerosol physical, chemical, and radiative processes impact the earth system can be achieved only through a multidisciplinary, interagency, and international initiative capable of dealing with these issues. A systematic approach, capitalizing on modern measurement and modeling techniques, geospatial statistics methodologies, and high-performance information technologies, can provide the necessary machinery to support this objective. We outline a framework for integrating and interpreting observations and models, and establishing an accurate, consistent, and cohesive long-term record, following a strategy whereby information and tools of progressively greater sophistication are incorporated as problems of increasing complexity are tackled. This concept is named the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON). To encompass the breadth of the effort required, we present a set of recommendations dealing with data interoperability; measurement and model integration; multisensor synergy; data summarization and mining; model evaluation; calibration and validation; augmentation of surface and in situ measurements; advances in passive and active remote sensing; and design of satellite missions. Without an initiative of this nature, the scientific and policy communities will continue to struggle with understanding the quantitative impact of complex aerosol processes on regional and global climate change and air quality.
Aerosols exert myriad influences on the earth's environment and climate, and on human health. The complexity of aerosol-related processes requires that information gathered to improve our understanding of climate change must originate from multiple sources, and that effective strategies for data integration need to be established. While a vast array of observed and modeled data are becoming available, the aerosol research community currently lacks the necessary tools and infrastructure to reap maximum scientific benefit from these data. Spatial and temporal sampling differences among a diverse set of sensors, nonuniform data qualities, aerosol mesoscale variabilities, and difficulties in separating cloud effects are some of the challenges that need to be addressed. Maximizing the longterm benefit from these data also requires maintaining consistently well-understood accuracies as measurement approaches evolve and improve. Achieving a comprehensive understanding of how aerosol physical, chemical, and radiative processes impact the earth system can be achieved only through a multidisciplinary, interagency, and international initiative capable of dealing with these issues. A systematic approach, capitalizing on modern measurement and modeling techniques, geospatial statistics methodologies, and high-performance information technologies, can provide the necessary machinery to support this objective. We outline a framework for integrating and interpreting observations and models, and establishing an accurate, consistent, and cohesive long-term record, following a strategy whereby information and tools of progressively greater sophistication are incorporated as problems of increasing complexity are tackled. This concept is named the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON). To encompass the breadth of the effort required, we present a set of recommendations dealing with data interoperability; measurement and model integration; multisensor synergy; data summarization and mining; model evaluation; calibration and validation; augmentation of surface and in situ measurements; advances in passive and active remote sensing; and design of satellite missions. Without an initiative of this nature, the scientific and policy communities will continue to struggle with understanding the quantitative impact of complex aerosol processes on regional and global climate change and air quality.