Difference between revisions of "Summer 2007 Session: Air quality interoperability experiments"

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A variety of air quality web services and other service oriented architecture components have been established recently. The objective of this session is to demonstrate interoperable connections among service and discuss future interoperability development and connections among air quality services.
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A variety of air quality web services and other service oriented architecture components have been established recently. The objective of this session is to demonstrate interoperable connections among services and discuss future interoperability development and connections among air quality services.  
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'''This session will be held as part of the poster session Wednesday evening (July 18). Participation is open. If you would like to include an interoperability demonstration or poster, please add it to the following list.'''
  
  
*Data Comparison and Reconciliation (Stefan Falke, Washington University and Northrop Grumman IT)
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*[[Data Comparison and Reconciliation]] (Stefan Falke, Washington University and Northrop Grumman IT)
 
**Numerous datasets spanning surface monitoring, satellite imagery, and model output are available through web interfaces. Each provides a unique view to particular aspects of air quality. In many cases, researchers and decision-makers are interested in comparing these datasets. Before meaningful comparisons can be calculated, differences in the spatial and temporal properties of the datasets must first be resolved. Methods for reconciliation include conversion of point data to grid formats or temporal aggregation from one resolution (e.g., daily) to another (e.g., monthly).
 
**Numerous datasets spanning surface monitoring, satellite imagery, and model output are available through web interfaces. Each provides a unique view to particular aspects of air quality. In many cases, researchers and decision-makers are interested in comparing these datasets. Before meaningful comparisons can be calculated, differences in the spatial and temporal properties of the datasets must first be resolved. Methods for reconciliation include conversion of point data to grid formats or temporal aggregation from one resolution (e.g., daily) to another (e.g., monthly).
 
**Web services are developed for conducting spatial and temporal reconciliation. The demonstration scenario will involve air emissions data, ambient concentration data, satellite imagery and model output that are accessed through Open Geospatial Consortium (OGC) Services, primarily the Web Coverage Service. Comparison services are provided for gridded and tabular data. Rendering services are invoked to created displays in maps, time series and tables.
 
**Web services are developed for conducting spatial and temporal reconciliation. The demonstration scenario will involve air emissions data, ambient concentration data, satellite imagery and model output that are accessed through Open Geospatial Consortium (OGC) Services, primarily the Web Coverage Service. Comparison services are provided for gridded and tabular data. Rendering services are invoked to created displays in maps, time series and tables.
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**A particularly promising application of the OMI data is for air quality management. The high resolution (25km) spatial coverage and the daily repetition augments the current surface-based monitoring in a substantial way. The ability to use the OMI data for air quality applications can be enhanced by information infrastructure that can deliver these data in a timely manner to the users in convenient interfaces. The key purpose of this pilot project is to establish a data flow and processing environment for the transfer of the OMI data from the providers at NASA and ESA (KNML) and air quality analysts {EPA and elsewhere).  
 
**A particularly promising application of the OMI data is for air quality management. The high resolution (25km) spatial coverage and the daily repetition augments the current surface-based monitoring in a substantial way. The ability to use the OMI data for air quality applications can be enhanced by information infrastructure that can deliver these data in a timely manner to the users in convenient interfaces. The key purpose of this pilot project is to establish a data flow and processing environment for the transfer of the OMI data from the providers at NASA and ESA (KNML) and air quality analysts {EPA and elsewhere).  
  
*TEXAQS (Brad Pierce, NOAA NESDIS)
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*TEXAQS and [http://idea.ssec.wisc.edu IDEA] (Brad Pierce, NOAA NESDIS, Tony Wimmers, CIMSS/SSEC University of Wisconsin - Madison)
**Real-time aerosol/ozone assimilation/forecasting and Lagrangian analysis of regional influences on Houston/Dallas AQ. Demonstration of satellite/surface/airborne/modeling synthesis.
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**Real-time aerosol/ozone assimilation/forecasting and Lagrangian analysis of regional influences on Houston/Dallas AQ. Illustration of satellite/surface/airborne/modeling synthesis.
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**[http://idea.ssec.wisc.edu Infusing Satellite Data into Environmental Applications (IDEA)]
  
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*[http://giovanni.gsfc.nasa.gov Giovanni] and other interoperability services from the GES DISC(Stephen Berrick, NASA GSFC)
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*[http://eie.cos.gmu.edu Earth Information Exchange & Air Quality Portlet], and [http://esg.gsfc.nasa.gov/ Earth Science Gateway] (Phil Yang, NASA Geosciences Interoperability Office (GIO) /George Mason Univ., John Evans NASA GIO / GST)
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*3D-AQS and [http://alg.umbc.edu/usaq/ Smog Blog] (Jill Engel-Cox, Battelle Memorial Institute)
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*[http://www.airnow.gov AIRNow] (Phil Dickerson, EPA OAQPS)
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'''Interested?  Add your name below.'''
 
'''Interested?  Add your name below.'''
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*Brad Pierce
 
*Brad Pierce
 
*Erin Robinson
 
*Erin Robinson
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*Phil Yang
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[[Category:Interoperability]]

Latest revision as of 13:00, November 28, 2008

A variety of air quality web services and other service oriented architecture components have been established recently. The objective of this session is to demonstrate interoperable connections among services and discuss future interoperability development and connections among air quality services. This session will be held as part of the poster session Wednesday evening (July 18). Participation is open. If you would like to include an interoperability demonstration or poster, please add it to the following list.


  • Data Comparison and Reconciliation (Stefan Falke, Washington University and Northrop Grumman IT)
    • Numerous datasets spanning surface monitoring, satellite imagery, and model output are available through web interfaces. Each provides a unique view to particular aspects of air quality. In many cases, researchers and decision-makers are interested in comparing these datasets. Before meaningful comparisons can be calculated, differences in the spatial and temporal properties of the datasets must first be resolved. Methods for reconciliation include conversion of point data to grid formats or temporal aggregation from one resolution (e.g., daily) to another (e.g., monthly).
    • Web services are developed for conducting spatial and temporal reconciliation. The demonstration scenario will involve air emissions data, ambient concentration data, satellite imagery and model output that are accessed through Open Geospatial Consortium (OGC) Services, primarily the Web Coverage Service. Comparison services are provided for gridded and tabular data. Rendering services are invoked to created displays in maps, time series and tables.
  • Distributed Access and Analysis OMI NO2 (Rudy Husar and Erin Robison, Washington University)
    • The OMI sensor on the AURA platform has opened up a new era of atmospheric composition characterization and monitoring. The sensor provides global daily coverage of columnar concentration of ozone, NO2, and formaldehyde. It also delivers absorbing aerosol index and other parameters that characterize atmospheric composition. The near-real-time delivery of these products are, in effect, described the "chemical weather", in a similar manner as meteorological satellites characterize the physical weather. These products of atmospheric composition are also available for assimilation into chemical models which in turn can improve the chemical forecasts.
    • A particularly promising application of the OMI data is for air quality management. The high resolution (25km) spatial coverage and the daily repetition augments the current surface-based monitoring in a substantial way. The ability to use the OMI data for air quality applications can be enhanced by information infrastructure that can deliver these data in a timely manner to the users in convenient interfaces. The key purpose of this pilot project is to establish a data flow and processing environment for the transfer of the OMI data from the providers at NASA and ESA (KNML) and air quality analysts {EPA and elsewhere).
  • TEXAQS and IDEA (Brad Pierce, NOAA NESDIS, Tony Wimmers, CIMSS/SSEC University of Wisconsin - Madison)
  • Giovanni and other interoperability services from the GES DISC(Stephen Berrick, NASA GSFC)
  • 3D-AQS and Smog Blog (Jill Engel-Cox, Battelle Memorial Institute)
  • AIRNow (Phil Dickerson, EPA OAQPS)



Interested? Add your name below. Contacts: Rudy Husar, rhusar@me.wustl.edu or Stefan Falke, stefan.falke@wustl.edu

  • Rudy Husar
  • Stefan Falke
  • Brad Pierce
  • Erin Robinson
  • Phil Yang