# Presentation: 436156

## Kevin Scharfenberg

- NEXRAD Dual-Polarization Product Review
- OU-CIMMS and NOAA-NSSL

- 2nd Workshop on NWS Severe Weather Warning Technology -- 10 July 2007 -- Norman, OK

## Dual-pol product field evaluation

- Conducted 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

## Dual-pol product field evaluation

- Seven 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 0oC level

## Dual-pol product field evaluation

- Online worksheets and questionnaires
- Evaluation of how the products might be used in the office’s operations
- Base products and algorithms
- Also considered user factors (e.g., data displays, cursor readouts, etc.)

## Dual-pol product field evaluation

## Dual-pol product field evaluation

## 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

## Base Products

- ZDR

- hv

- KDP

## Hydrometeor Classification Algorithm

- No echo
- Light/moderate rain
- Heavy rain

- Rain/hail
- “Big drops”
- Biologicals

- AP/ground clutter
- Unknown
- Dry snow

- Wet snow
- Crystals
- Graupel

## Other products

- Rainfall 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

## Results

- Use 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

## Results, continued

- Hydrometeor 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

## Results, continued

- Wide 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.)?

## Setting an aggressive agenda for change

*In 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.

## Setting an aggressive agenda for change

- Discussion...
-  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
- Kevin.Scharfenberg@noaa.gov