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NEXRAD Dual-Polarization Product Review
Kevin ScharfenbergOU-CIMMS and NOAA-NSSL2nd Workshop on NWS
Severe Weather Warning Technology -- 10 July 2007 -- Norman, OK
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Dual-pol product field evaluationConducted Autumn 2006
8 WFOs (Duluth, Melbourne, Norman, Pittsburgh, Sacramento, St.
Louis, Sterling, Tucson)
Several other agencies (RFC-Tulsa, Lincoln Labs, DoD, etc.)
Online training modules provided by WDTB
Used WDSS-II software to interrogate data
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Dual-pol product field evaluationSeven cases from KOUN prototype
dual-pol WSR-88D
14 May 2003: Widespread hail, heavy rain, considerable
non-precipitation echoes 10 Jun 2003: Squall line, heavy rain 29
May 2004: Tornadic high-precipitation supercell 22 Dec 2004:
Light-moderate snow 5 Jan 2005: Rain and freezing rain, some sleet
28 Jan 2005: Heavy snow & light drizzle/mix 2 May 2005: Light
rain, low 0C level
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Dual-pol product field evaluationOnline worksheets and
questionnaires
Evaluation of how the products might be used in the offices
operations
Base products and algorithms
Also considered user factors (e.g., data displays, cursor
readouts, etc.)
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Dual-pol product field evaluation
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Dual-pol product field evaluation
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Dual-pol product field evaluation
Norman working group experienced with KOUN data and technology
transfer to operations concurrently evaluated products and analyzed
field feedback
Wrote basic findings & recommendations for final report
Formed needs assessment and determined priorities
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Base ProductsZDRrhvKDP
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Hydrometeor Classification AlgorithmNo echoLight/moderate
rainHeavy rainRain/hailBig dropsBiologicalsAP/ground
clutterUnknownDry snowWet snowCrystalsGraupel
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Other productsRainfall algorithms Undergoing major revisions
during field evaluation phase so could only be generic
Melting layer algorithm no stand-alone output yet to evaluate,
but critical to understanding hydrometeor classification algorithm
(and later, rainfall algorithms)
Filtered reflectivity product uses hydrometeor classification to
filter out non-precip echoes from reflectivity product
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ResultsUse of base products to form a 4D conceptual model
Base products at highest-possible resolution, data precision
Broad-based training will be critical for success
Flexible, innovative display concepts needed
The black box algorithm problem
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Results, continuedHydrometeor classification melting layer
rainfall algorithms intertwined, still in developmental stages
Need to keep users in the loop as algorithms are refined
Product color schemes need to be unique for quick
identification
Product toggles, cursor readouts, etc. should be reexamined
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Results, continuedWide variety of end-users
Numerous software considerations (FFMP, clutter canceling, etc.)
some unknowns
Primary focus should be on highest-quality base data for users,
software, algorithms, etc
Downstream users can do the slicing & dicing
What about user-adaptable parameters and other NEXRAD
initiatives (super-resolution, new VCPs, etc.)?
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Setting an aggressive agenda for changeIn my opinion,
hydrometeor classification, rainfall accumulation, and other
algorithms will be much more successful by incorporating multiple
radars and other data sources
Must also coordinate operations concept with ongoing transition
to warn-on-forecast models, gridded warnings, etc.
Also must keep in mind new technologies like FSI, AWIPS2, other
radar upgrades, new radars, etc.
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Setting an aggressive agenda for changeDiscussion
Push toward incorporation of multi-radar, multi-sensor products
into routine NWS operations so we are prepared to take advantage of
dual-pol capabilities
Think outside the box on visualization for complex data
interrogation
Strive for the best possible training
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