Evaluation of VIIRS Cloud EDRs

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 Evaluation of VIIRS Cloud EDRs 

• Qingyuan HanUniversity of Alabama in Huntsville
• Nov 4-6, 2003 

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EDR/CDR List

•      VIIRS Cloud EDR
• Cloud Optical thickness
• Effective Particle Size
• Water Cloud
• Ice Cloud
• Cloud Base Height
•      CrIS Atmospheric Profiles
• Temperature
• Humidity
•      ATMS Cloud Water

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Roles of PI and Co-I's

•      PI Qingyuan Han
• Expertise
• Developed algorithms for global cloud property
  retrieval
• Worked on validating global cloud products
• Radiative transfer calculations
• Role
• Full responsibility for management of the project
  
• Acquire necessary data and code
• Submit analysis results
• Prepare project reports
• Contribution to deliverables of the NPP Science
  Team

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Approach (EDR)

•      Systematic test of algorithm performance
• Check the fidelity of retrieval algorithms
• Simulated radiances
• Retrieval algorithms
• Evaluating the effect of vertical variations in
  particle sizes
• Vertical distributions of particle sizes
• Results from different channels (3.7, 2.2, 1.6
  mm)
• Results from different viewing angles
• Evaluating the effect of broken clouds
• Results from different spatial resolutions
• Evaluating the effects of size distributions
• Single scattering properties and reflectances for
  30 different size distributions
• Using VIIRS algorithm to test the uncertainties
• Evaluating the effect of multiple solutions
• Method used for reporting multiple solutions
• Estimate the impact of the artifact

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Approach (CDR)

• Out Standing Issues that need immediate action
  
• Evaluating the effects of ice crystal shapes (May
  cause 10 bias in TOA flux between tropics and
  midlatitude)
• Developing an alternative algorithm for MODIS
  (NRA-03-OES-02 proposal pending)
• Determining distribution of crystal shapes using
  CERES biaxial data (NRA-03-OES-02 proposal
  pending)
• Retrieval of cloud properties using one month of
  MODIS data
• Comparison of results from different particle
  shape assumptions
• Evaluating the uncertainties of cloud base height
  (99 IR downward flux from layers below 700 hpa)
• Vertical profiles of T and humidity (CrIs)
• Cloud water content from ATMS
• In situ measurements from Central America (Costa
  Rica)
• Examining the assumption of cloud liquid water
  content

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Validation strategy (I)

• Scientific reasoning and comparisons can point
  out problems

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Validation strategy (II)

• Validation results need careful examination

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Validation strategy (III)

• Algorithm accuracy must be checked to solve
  problems

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Resources Offered/Requested

•      Access to codes and data (Requesting)
• For intercomparison of different RT codes
• Simulated data
• Radiative transfer model from NPP1
• Retrieval algorithm
• Verify the fidelity of forward-retrieval process
  under a wide variety of conditions (t, re, qo, q,
  f, T)
• MODIS radiance and cloud product
• To compare with results from VIIRS algorithms

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Contribution to Deliverables

•      Algorithm analysis report
• Cloud optical thickness
• Particle size
• Cloud base height
•   Cal/Val plan
• Validation strategy
• Validation is a never ending process (e.g., FIRE
  I, II)
• Ground observations and in situ measurements are
  valuable but have limitations (e.g., ARM,
  AERONET)
• Validation by scientific reasoning and comparison
  can point out problems but may significantly
  delay production
• Rigorous test of algorithm is an important step