Infrared Temperature and Water Vapor Sounding

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Infrared Temperature and Water Vapor Sounding

• Presented by
• Chris Barnet

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Requirement, Science, and Benefit

• Requirement/Objective
• Weather Water
• Increase lead time and accuracy for weather and
  water warnings and forecasts.
• Increase development, application, and transition
  of advanced science and technology to operations
  and services
• Climate
• Reduce uncertainty in climate projections through
  timely information on the forcing and feedbacks
  contributing to changes in the Earths climate.
• Increase number and use of climate products and
  services to enhance public and private sector
  decision making.
• Science
• How can hyper-spectral information be exploited
  to improve accuracy and reduce uncertainty in
  satellite-derived temperature, moisture and trace
  gases?
• Benefit
• National Weather Service forecasters and their
  customers
• Fully exploit temperature and moisture
  information content from hyper-spectral
  instruments.
• Increase utilization of hyper-spectral
  information in difficult sounding domains (e.g.,
  cloudy scenes)
• Climate applications
• Long-term temperature and moisture trends and
  their interaction (water vapor feedback)
• Long-term monitoring of greenhouse gases (carbon
  dioxide, methane, carbon monoxide).

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Challenges and Path Forward

• Science challenges
• First principles algorithm still has regional
  and time dependent biases as result of null
  space errors between temperature, water vapor,
  and carbon dioxide.
• Next steps
• Migration of the AIRS/IASI algorithm to the CrIS
  instrument on NPP
• Mitigation of biases through algorithm
  improvements.
• Collaboration with modeling centers to develop
  efficient communication of retrieval vertical
  correlation (averaging functions) and error
  covariance.
• Transition Path
• For IASI the transition path is through SPSRB and
  products available via OSDPD.
• For AIRS the transition path is through the NASA
  AIRS Science team and products are available at
  the NASA data archive.

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Satellite Hyper-spectralInfrared Sounding
Research

• Research description
• Hyper-spectral instruments have 1000s of
  channels covering the near and far IR
• State-of-the-art forward models used to compute
  instrument radiances.
• Cloud clearing approach removes cloud effects.
• Simultaneous solution of trace gases improves
  temperature and moisture products
• Geophysical products derived from cloud cleared
  radiances capture more of the relevant weather
  information and significantly reduces data volume
  .
• Recent science accomplishments
• NOAA develops algorithms as part of the
  Atmospheric Infrared Sounder (AIRS) Science Team
  and delivers these to NASA for implementation.
• AIRS algorithm has been migrated to the
  operational Infrared Atmospheric Sounding
  Interferometer (IASI) processing system.
• Common algorithm and spectroscopy provides
  consistent products in the am and pm orbits.

IASI spectrum above comprised of 8460 channels
that sample molecular absorption from carbon
dioxide, water, ozone, trace gases. Sounding
algorithms use specific (i.e., select best)
channels to retrieve temperature and other
products.
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NESDIS OperationalHyper-spectral products

• STAR led the development and implementation of
  new and improved geophysical products from
  hyper-spectral instruments.
• Led development of cloud clearing approaches.
• Led development of deriving surface emissivity.
• Knowledge of trace gases improves temperature and
  moisture accuracy in difficult sounding regions.
• ozone absorption affects the temperature
  retrieval.
• Trace gas products are useful in air-quality and
  climate applications
• carbon monoxide is a precursor to tropospheric
  ozone which is both pollutant and greenhouse
  gas.
• Detection of sulfur dioxide from volcanic events
  has enabled hazard condition alerts for air
  travel.
• Atmospheric carbon products (carbon dioxide,
  methane, and carbon monoxide) are valuable for
  monitoring and understanding the carbon cycle and
  climate.

Product AIRS IASI
Temperature NASA DAAC NCDC/ CLASS
Water vapor NASA DAAC NCDC/ CLASS
Ozone NASA DAAC NCDC/ CLASS
Carbon monoxide NASA DAAC NCDC/ CLASS
Methane NASA DAAC NCDC/ CLASS
Carbon dioxide NOAA NESDIS (experimental) NCDC/ CLASS
Volcanic Sulfur Dioxide Real time flag From NOAA/NESDIS Real time flag From NOAA/NESDIS
Nitric Acid NOAA NESDIS (experimental) NCDC/ CLASS
Nitrous Oxide NOAA NESDIS (experimental) NCDC/ CLASS
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Recent experiments show potentialvalue of
geophysical products

• STAR has participated in experiments to
  demonstrating impact of using sounding products
  in operational forecast.
• Joint Center for Satellite Data Assimilation
  experiments show that cloud cleared radiances
  have positive impact on the global forecast.
• Use of cloud clear radiances (red) improves 6 day
  forecast by 4 hours relative to assimilation
  with AIRS clear scenes (blue).
• Univ. Maryland, College Park has used
  experimental temperature and moisture products
  (w/ covariance) in their Kalman Ensemble model
• AIRS T(p) and q(p) profiles improve zonal and
  meridional winds (blue regions)
• NASA/Global Modeling and Assimilation Office has
  evaluated AIRS operational products.
• Use of AIRS T(p) and q(p) profiles with QC
  improves forecast (red vs. black lines) more so
  than assimilating radiances (green)

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Challenges and Path Forward

• Science challenges
• First principles algorithm still has regional
  and time dependent biases as result of null
  space errors between temperature, water vapor,
  and carbon dioxide.
• Next steps
• Migration of the AIRS/IASI algorithm to the CrIS
  instrument on NPP
• Mitigation of biases through algorithm
  improvements.
• Collaboration with modeling centers to develop
  efficient communication of retrieval vertical
  correlation (averaging functions) and error
  covariance.
• Transition Path
• For IASI the transition path is through SPSRB and
  products available via OSDPD.
• For AIRS the transition path is through the NASA
  AIRS Science team and products are available at
  the NASA data archive.