Summary of EPA STAR Grants related to Climate and Air Quality

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Summary of EPA STAR Grants related to Climate
and Air Quality

• Slide provided by Darrell Winner
• U.S. EPA, Office of Research and Development,
• National Center of Environmental Research,
  Washington, DC

On assignment from NOAA Air Resources Laboratory
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Specific collaborations ongoing with Dr. Daniel
Jacob (Harvard) and Dr. Peter Adams (Carnegie
Mellon) and USEPA ORD (to be discussed in next
slides)
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Overview of the Climate Impact on Regional Air
Quality (CIRAQ) Project

• Ellen J. Cooter, Alice Gilliland, William
  Benjey,
• Robert Gilliam and Jenise Swall
• U.S. EPA, Office of Research and Development,
• National Exposure Research Laboratory,
  Atmospheric Modeling Division,
• Research Triangle Park, NC
• 2004 Models-3 Conference
• October 18-20, 2004

On assignment from NOAA Air Resources Laboratory
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Climate Impacts on Regional Air Quality (CIRAQ)

• Objective Examine potential climate change
  impacts on O3 and PM using the regional scale
  Community Multiscale Air Quality (CMAQ) model
  linked with global scale climate and chemical
  transport models
• Supports U.S. Climate Change Science Program
  (CCSP) research goals and synthesis products
• AMD PIs include
• Ellen Cooter Project management
• Climate assessment, landscape/vegetation
  change
• Alice Gilliland CMAQ modeling and linkages with
  global CTMs
• Bill Benjey Air quality emissions, future
  emission scenarios
• Robert Gilliam Regional climate model evaluation
• Collaborators include
• Ruby Leung Pacific Northwest National Laboratory
  (MM5 RCM)
• Dan Loughlin EPA NRMRL (future emission
  scenarios)
• Daniel Jacob Harvard University (GISS, GEOS-CHEM)
• Loretta Mickley
• Peter Adams Carnegie Mellon University (global
  CTM)

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CIRAQ Information Flow and Responsibilities
Agency Key
EPA / NOAA(ASMD)
GCM and GCTM (Harvard, Carnegie Mellon via STAR)
EPA /NRMRL
EPA / NCEA
DOE / PNNL
USDA /FS
MM5/RCM Meteorology (GCM Downscaling)
Anthropogenic Emissions
CCSP Synthesis Report 4.5 Air Quality Scenarios
CCSP Synthesis Report 4.6 Socioeconomic Impacts
of Climate Variability
CCSP Base Program 3. Atmospheric Composition
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CIRAQ Project Timeline

• FY03-05
• Understanding the global to regional climate
  linkage to
• support regional scale air quality
  simulations
• FY04-07
• Understanding the impact of climate change on
  regional
• air quality (CIRAQ Phase 1)
• Develop 5-yr current and future (fixed technology
  and landuse) emissions scenarios
• Perform 5-yr current and future (2050) CMAQ
  simulations
• FY06-09
• Understanding the impact of climate and
  emissions
• changes on regional air quality
  (CIRAQ Phase 2)

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Downscaled Meteorology(linking global and
regional scale climate)

• GCM (Harvard University)
• GISS version II
• 6hrly output saved for 10 present-day and 10
  future years.
• Used as boundary and initial conditions to MM5
• Downscaling with MM5 (DOE/PNNL)
• MM5 run in regional climate mode
• 23 layers, MRF planetary boundary layer
  parameterization, Grell cumulus cloud
  parameterization, RRTM radiation scheme and mixed
  phase microphysics
• 36km x36km horizontal resolution spanning
  continental US, northern Mexico and southern
  Canada

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RCM Evaluation/Analysis

• The Goal
• To understand climatological biases that could
  impact CMAQ model performance
• The Challenge
• RCM scenarios characterize time periods under
  representative climatological conditions and will
  not necessarily reproduce day-to-day and exact
  year-to-year observations.
• The Solution
• Base evaluation on distributions of model output
  means, extremes and variability on both spatial
  and temporal scales.

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MM5/RCM
Obs
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MM5/RCM/MCIP EvaluationTime Series Analysis
(Leads, Gilliland and Swall)

• Meteorological conditions include annual,
  diurnal, and interannual cycles
• Use time series analysis techniques (e.g.,
  filtering techniques, Fourier analysis, etc.) to
  separate these time scale variations in the data
• Amplitude of these cycles and the extent of
  variability can be compared for observational
  data and model output
• Understanding these cyclical patterns allows for
  better detection of climate change signals and
  investigation of these changes

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MM5/RCM/MCIP EvaluationSpatial Analysis(Lead,
Cooter)

• Goal Develop methods to compare spatial
  patterns of gridded
• meteorological (or other) means and
  extremes across datasets.
• Method
• Cluster analysis
• Wards (means)
• Average linkage and k-means (extremes)
• Analysis
• Visual difference mappings
• Quantitative frequency analysis
• Developed and tested using 10 years of NCEP and
  NCEP/AMIP reanalysis data

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Question
Do average summer season 700mb transport patterns
look similar?
NCEP Reanalysis R-1 (black arrows)
NCEP/AMIP Reanalysis R-2 (red arrows)
(R2 R1)
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CMAQ Air Quality Simulations(Lead, Gilliland)

• Plan
• O3, PM2.5, PM10, sulfate and nitrate deposition,
  
• U.S. continental domain, 36 km horizontal
  resolution
• Linkages to global scale chemical transport
  simulations through boundary conditions
• Two global CTMs (Harvard and Carnegie-Mellon
  EPA STAR program)
• Both driven by GISS II GCM
• Challenge
• Global CTM chemical mechanism matched to SAPRC
  (AMD, Univ. of Houston)
• Temporal and spatial scale issues (Univ. of
  Houston)
• CMAQ simulations are expected to
  begin during FY05

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Analysis of Air Quality Simulations EOF Analysis

• Another link to the EPA STAR program
• Harvard and CIRAQ collaborations include an
  empirical orthogonal function (EOF) analysis of
  spatial variability in ozone and PM2.5
  predictions
• Refers back to the climatological evaluation
  approach needed
• Both global CTM and CMAQ results will be included
  in the analysis

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Summary

• Several arms to the ORD study of climate impact
  on air quality
• STAR program is very extensive (albeit briefly
  described here)
• NERL CIRAQ project fosters broad collaborations,
  including several STAR (e.g., Hogrefe, Jacob,
  Adams, Fu) recipients and ICAP investigators
  (e.g., Jang, Byun, Jacob, Fu)
• Through these partnerships, a broader study of
  climate and air quality interactions can be
  attained
• Future goals include even more integrated project
  goals between ORD and OAQPS (discussions ongoing)
• Satellite data for intercontinental transport
• Integration of aerosol feedbacks into photolysis
  rates
• More

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Disclaimer

• Portions of the research presented here were
  performed under the Memorandum of Understanding
  between the U.S. Environmental Protection Agency
  (EPA) and the U.S. Department of Commerces
  National Oceanic and Atmospheric Administration
  (NOAA) and under agreement number DW13921548.
• Although this work was reviewed by EPA and NOAA
  and approved for publication, it may not
  necessarily reflect official Agency policy.