Assessment of NPP Sea Ice Products and Product Continuity for Regional and Global Studies

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 Assessment of NPP Sea Ice Products and Product
Continuity for Regional and Global Studies 

• Jim Maslanik
• University of Colorado
• Nov 4-6, 2003 

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EDR/CDR List

•      Target EDRs
• ice edge location (EDR 1.2.3.2.2.1)
• ice concentration (EDR 1.2.3.2.2.2)
• sea ice characterization (EDR 1.7.8)

•     Related EDRs
• sea surface temperature near and within the ice
  pack (EDR 1.2.4)
• sea ice albedo (EDR 1.5.2)
• snow cover/depth over sea ice (EDR 1.6.3)
• ice surface temperature (EDR 1.7.3)
• basic radiance imagery sea ice EDR 1.2.3)

•      Other EDRs (over sea ice-covered areas)
• Cloud parameters, neat heat flux

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Researcher Roles

• Principal Investigator Jim Maslanik
• - Algorithm and cal/val assessments,
  design/generation of proxy and synthetic data
  sets, other high-level research and reporting
  activities.
• Research Assistants Steve Hart, Charles Fowler
• - Assistance with data processing, organization
  of comparison data sets and other general
  analysis tasks.

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PI Background/Expertise

• Studies of local, regional and hemispheric
  climate variability using a range of data types,
  process models, and climate models.

• Algorithm development and product generation
  (AVHRR Polar Pathfinder, MODIS, SSM/I, SAR,
  AMSR-E).
• Algorithm refinement via R/T modeling,
  coefficient/tie point selection, synthetic data.

• Validation of satellite-derived sea ice and other
  products via collection and use of field,
  aircraft and satellite data (PI for field and
  modeling portion of the EOS AMSR-E sea ice
  product validation).

• User of operational sea ice / weather / ocean
  data sets.

     Consultant for CMIS ice EDR algorithms
(Ball Aerospace and Raytheon).
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Assessment Criteria

• How well do the proposed EDRs represent key
  climate parameters? Are the EDRs measuring the
  most important and/or sensitive sea ice
  conditions or processes?
• Are the EDRs able to extend existing long-term
  climate records? Level of reliance on sensor
  calibration vs. statistical matching?
•   How applicable are the EDRs to climate studies
  on a range of space and time scales, i.e., are
  they suitable for local and regional studies as
  well as hemispheric and global analyses.
• Applicability to modeling, assimilation?
• How well do the EDRs represent secondary sea
  ice parameters that may offer new climate change
  information?

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Assessment Criteria (cont.)

• How well do the EDRs perform under the full
  range of polar conditions? What capabilities
  (confidence flags, documentation, etc.) will be
  provided to indicate performance for users?
• How sensitive are the EDRs to sensor
  calibration, degradation of in-orbit sensor
  performance, and to changes in external
  environmental factors? How do the magnitudes of
  these sensitivities compare to the expected
  climate-change signal?

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Assessment Criteria (cont.)

• How well do the sea ice EDRs integrate with
  other EDRs relevant for ice-ocean-atmosphere
  studies, such as cloud, flux, and SST products?
• What types of metadata and documentation are
  included with the EDRs?
• What calibration/validation approaches have been
  considered for the EDRs? How realistic and
  feasible are the cal/val plans in terms of cost,
  logistics, risk? Sufficient to assess claimed
  performance?

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Approach

• Reviews ATBDs, algorithms, cal val plans,
  proxy and synthetic data sets
• Independent performance assessment using
  observations and imagery, proxy and synthetic
  data, sensitivity studies
• Performance assessment relative to heritage
  algorithms and advanced algorithms
• Document EDR performance relative to science
  user expectations
• Assess data packaging issues and
  polar-specific aspects

Within budget limits
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Resources Offered/Requested
Offered

• Validation/comparison data sets (satellite and
  aircraft imagery, atmospheric profiles, in-situ
  data).
• Synthetic data of typical and extreme polar
  surface and atmospheric conditions.

Requested

• Alternative/additional radiance models and
  other scene generation tools for comparison.

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Contributions to Deliverables

• Algorithm analysis report
• Cal/val planning logistics issues,
  coordination with other cal/val and field
  efforts, etc.
• Others (data documentation, user-accessible
  docs., QC flags, etc.)

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Questions?