Difference between revisions of "Air quality interoperability challenges"

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This is a workspace for outlining gaps in interoperability among air quality projects and initiatives and for defining steps in addressing them. This is an '''open page''' and you are encouraged to '''comment on existing entries or add new entries'''.
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This will serve as one of the base documents for the air quality sessions during the 2007 Summer ESIP meeting but the intent is that they will remain active after the meeting and continue to be refined.
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==Interoperability of Existing Tools==  
 
==Interoperability of Existing Tools==  
''contributed by EPA/OAR, Terry Keating and Glynis Lough''
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''contributed by Terry Keating and Glynis Lough, EPA/OAR''
  
 
DataFed, NEISGEI, RSIG (and the KML Viewer), BlueSky RAINS, AirQuest, Giovanni, AIRNow and AIRNowTech, NOAA’s Forecasting Site, 3-D AQS (IDEA)…
 
DataFed, NEISGEI, RSIG (and the KML Viewer), BlueSky RAINS, AirQuest, Giovanni, AIRNow and AIRNowTech, NOAA’s Forecasting Site, 3-D AQS (IDEA)…
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==The TF HTAP Challenge==
 
==The TF HTAP Challenge==
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''contributed by Terry Keating and Glynis Lough, EPA/OAR''
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The Task Force on Hemispheric Transport of Air Pollutants seeks to create an infrastructure and the methodologies to enable access to and comparative analysis of:
 
The Task Force on Hemispheric Transport of Air Pollutants seeks to create an infrastructure and the methodologies to enable access to and comparative analysis of:
 
*Observational data from surface networks, aircraft campaigns, and satellites
 
*Observational data from surface networks, aircraft campaigns, and satellites
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==The Air Quality ReAnalysis Challenge (AMI)==
 
==The Air Quality ReAnalysis Challenge (AMI)==
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''contributed by Terry Keating and Glynis Lough, EPA/OAR''
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Create the best representation (best spatial and temporal resolution, most comprehensive characterization) of the state of the atmosphere over the continental U.S. for 2000-present by integrating:
 
Create the best representation (best spatial and temporal resolution, most comprehensive characterization) of the state of the atmosphere over the continental U.S. for 2000-present by integrating:
 
*Surface, sonde, aircraft, satellite, and ground-based remote sensing observations
 
*Surface, sonde, aircraft, satellite, and ground-based remote sensing observations
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*Add modeling and analysis tools to do source attribution
 
*Add modeling and analysis tools to do source attribution
 
*Make such reanalysis possible on an operational basis
 
*Make such reanalysis possible on an operational basis
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[[Category:Interoperability]]

Latest revision as of 13:01, November 28, 2008

This is a workspace for outlining gaps in interoperability among air quality projects and initiatives and for defining steps in addressing them. This is an open page and you are encouraged to comment on existing entries or add new entries.

This will serve as one of the base documents for the air quality sessions during the 2007 Summer ESIP meeting but the intent is that they will remain active after the meeting and continue to be refined.

Interoperability of Existing Tools

contributed by Terry Keating and Glynis Lough, EPA/OAR

DataFed, NEISGEI, RSIG (and the KML Viewer), BlueSky RAINS, AirQuest, Giovanni, AIRNow and AIRNowTech, NOAA’s Forecasting Site, 3-D AQS (IDEA)…

Issues and First Steps:

  • What roles do each of these play? What are their niches? Strengths and weaknesses?
  • What steps can be taken to maximize the strengths of each, and allow each to benefit from the strengths of others?
  • What steps can be taken to improve their interoperability, especially very-short term?


The TF HTAP Challenge

contributed by Terry Keating and Glynis Lough, EPA/OAR

The Task Force on Hemispheric Transport of Air Pollutants seeks to create an infrastructure and the methodologies to enable access to and comparative analysis of:

  • Observational data from surface networks, aircraft campaigns, and satellites
  • Emissions inventories and projections for various domains and time periods
  • Modeling outputs from global and regional models

The challenge includes, in the short term, enabling participants in the Task Force to compare their (EIs, obs. data, models) directly with a central database or with other participants’ (EIs, obs. data, models). In the longer term, it would be flexible to allow outside researchers to access the information and perform comparative analysis, and possibly add their results to the system. This could be the underpinnings of a system to expand in the future, or an example of how to build such a system.

Steps already taken:

  • Some steps have been taken to address parts of the challenge, but not the challenge as a whole (ie, selected modeling outputs for TF participants have been gathered in one database for use with the JRC HemiTAP tool)

Possible Building blocks / existing tools:

  • DataFed, NEISGEI, HTAP Server, Giovanni and NASA DAACs, NARSTO archive, JRC’s HemiTap Tool, EPA’s RSIG, NILU database, ESIP portals, WMO portals, GAW databases, …and others…

Issues and First Steps:

  • What are the roles of the various elements (“building blocks”) described above?
  • What are the major challenges or obstacles to creating such a system, including infrastructure and methods?
  • What are the gaps to be crossed in information, communication, and technology?
  • What can be done with existing resources or small grants (less than $50K)?
  • What future funding is needed?


The Air Quality ReAnalysis Challenge (AMI)

contributed by Terry Keating and Glynis Lough, EPA/OAR

Create the best representation (best spatial and temporal resolution, most comprehensive characterization) of the state of the atmosphere over the continental U.S. for 2000-present by integrating:

  • Surface, sonde, aircraft, satellite, and ground-based remote sensing observations
  • Model estimates (with assimilated/fused observational data)

Steps already taken:

  • Achievements of the EPA AMI and PHASE projects

Goals/Added value:

  • Translate information into meaningful health and ecosystem indicators
  • Add modeling and analysis tools to do source attribution
  • Make such reanalysis possible on an operational basis