1. DUAL-POLARIZATION OF WSR-88D NETWORK
Edward Fenelon, National Weather Service, Chicago, IL
Emergency Management Meeting

2. Dual-Polarization Radar: Coming Soon!
Impacts entire WSR-88D network
Several new products available
Training content still evolving
Doppler Radars

3. Dual-Polarization Radar Technology: Current Schedule for Upgrade
KLOT will be part of the Beta Test period
February 28 – March 13, 2011
Beginning in Fall 2010, NWS will upgrade WSR-88D radars to collect dual-polarization data. This will provide several new and vastly different products in addition to what is currently disseminated. It should take approximately 3 years to upgrade all of the existing WSR-88D radars.

4. Impacts of the New Technology
Dual Pol is the biggest radar system upgrade since the WSR-88D was fielded
No data for almost 2 weeks – have to use surrounding radars
Steep learning curve to use new data and master the new system – not unlike when it was first installed.
Benefits will surely outweigh these short terms imapcts!!!

5. What is Dual-Polarization?

6. What is Dual-Polarization?
A radio wave is a series of oscillating electromagnetic fields. If we could see them, they would look like this:
All weather radars, including NEXRAD, measure horizontal reflectivity. That is, they measure the reflected power returned from the radar's horizontal pulses. Polarimetric radars, on the other hand, measure the reflected power returned from both horizontal and vertical pulses.
. These waves can have different orientation (or polarization). From a graphical standpoint you can imagine two different orientations of these electromagnetic fields:
Polarization currently used by WSR-88D’s

7. What is Dual-Polarization & How Is It Different from Conventional Doppler Radar??
Most radars (WSR-88D included) transmit and receive radio waves with a single, horizontal polarization
Polarimetric radars transmit and receive both horizontal and vertical polarizations
This is most commonly done by alternating between horizontal and vertical polarizations with each successive pulse
Get a better pictures of the targets that reflect energy back to the radar
Extra data provides information about size and shape information of the targets in the air – up to now have to make guesses about targets based on knowledge of environment

8. Polarimetric Radar:
Polarimetric radars measure both the horizontal and vertical dimensions of cloud and precipitation particles – can determine SIZE and SHAPE
By transmitting both horizontally and vertically polarized signals, increased information will be available including information about the shape of the hydrometeors with dual polarization radar.

9. Why are two poles better than one?
By comparing these reflected power returns of the two phases in different ways (ratios, correlations, etc.), we are able to obtain information on the size, shape, and ice density of cloud and precipitation particles, as well as better identify non-weather echoes.

10. Benefits of Dual-Polarization:
Detect when hail is present in a thunderstorm
Detect areas of heavy rain better (Improved precipitation estimation via determining droplet distributions (rainfall rates))
Differentiate rain, snow, melting snow
Identify non-weather echoes more easily
Detect debris lofted by significant tornadoes
Will take a few years for benefits to fully materialize

11. Using Shape and Variety Info to Differentiate Rain, Snow, and Melting Snow
Common problem with mixed precipitation events – have to rely upon surface data and environmental information to infer precip type.

12. Using Shape and Variety Info to Differentiate Rain, Snow, and Melting Snow
Surface obs and spotter reports still provide a critical piece of information!

13. Using Shape and Variety Info to Differentiate Rain, Snow, and Melting Snow
Correlation Coefficient (CC)
0.96<CC<1 – Small hydrometeor diversity*
0.85 <CC<0.96 – Large hydrometeor diversity*
CC < 0.85 – Non-hydrometeors present
* refers to sizes, shapes, orientations, etc.

14. High CC indicates all one precip type Low CC indicates mix (melting)
Using Shape and Variety Info to Differentiate Rain, Snow, and Melting Snow
Reflectivity:
Correlation Coefficient:
High CC indicates all one precip type Low CC indicates mix (melting)

15. Specific Benefit Example: Melting Layer Detection Algorithm
MLDA – computer algorithm output that identifies layer where falling precipitation starts melting – I.e. where the radar beam intersects the level of the atmosphere where frozen precipitation starts melting.
Most directly benefits aviation interests, but also useful to note trends.
Product is generated on each elevation angle that the radar scans.

16. Using Shape and Variety Info to Better Detect Hail
Identifying hail in thunderstorms – currently radar, computer models, and upper air observation s to identify storms that may have hail. Dual pol allows us to differentiate directly from the radar data.
Show have better recognition of storms with hail
Reports of hail size, hail damage, and accumulation of hail still critical to have via spotters

17. Using Shape and Variety Info to Better Detect Hail
Z on right: note high reflectivity core in purple
ZDR on left: note minima of near zero where highest Z co-located. This indicates hail core!
ZDR is a measurement related to the returned energy difference between the vertical and horizontal radar pulses. Large positive values indicated targets that are generally much larger horizontally than vertically. Values near zero indicate the targets are generally spherical. Negative values indicate targets are larger in the vertical than in the horizontal.

18. ZDR > 0:
Positive ZDR indicates a mean power return profile wider than it is tall
Larger positive ZDR usually indicates the presence of larger liquid drops
Falling rain drops flatten into “hamburger bun” shape (generally range from 0.5 to 5.0 dB)

19. ZDR ~ 0:
ZDR values around zero indicate a spherical mean profile power return
Tumbling hail stones result in nearly spherical return

20. Rain/Sleet Changing to Snow:
Left: High ZDR indicates liquid covered sleet/snow
Right: 2 hours later, precip changing to snow. Note decrease in ZDR
ZDR also will be very useful for winter applications, here note the decrease in ZDR associated with winter precip event indicating transition from liquid to snow.

21. Heavy Rain Detection Should Improve with Dual Pol Upgrade
High reflectivity on left – heavy rain, hail, or even non wx echos – can you tell which is what area has heavier rainfall from the other?
Dual pol products help – in this case Specific differential phase – data on the right helps identify area of locally heavier rain.
Specific Diff Phase (KDP) is a measurement of difference between the horizontal and vertical pulses phase changes as they travel through the atmosphere.
Specific Diff Phase values are largest when going through areas dominated by large rain drops. In some cases, regions with high KDP values may also contain melting hail.

22. Dual Pol Radars Can Detect Debris From Significant Tornadoes
Hook echo region of supercell can sometimes be characterized by area of enhanced reflectivity with low ZDR values and low CC values.
Beneficial when tornado obscured:
At Night
Rain Wrapped
A radar signature commonly referred as “Tornado Debris Signature” (TDS) can be identified with dual-pol radar.

23. Potential Derived Products: Hydrometeor Classification Algorithm
Assigns hydrometeor classification to each range bin (11 types). Uses base output, MLDA output and “fuzzy logic”
Hydrometeor: any particle that can be a cloud – raindrop, snowflake, hailstone, sleet
HCA: predominate hydrometeor in the radar beam – includes biological and other non-weather targets. Displays which of the predefined categories most likely was the cause of the radar echo at that location.
Available for each elevation angle the radar scans. Lowest 4 available externally.

24. Estimation of Rainfall Amounts
Old:
OHP, THP, STP
New: (based on dual pol data)
OHA, STA, DPR
1 hour and storm total are analogous to previous rainfall analysis system. Will keep old and also have new, and improvements will be added incrementally – so will have 2 sets to compare. Will have 2 sets of data to use. Best set to use will vary by event, and won’t know which is best going into any particular event. Have additional information to compare, and a good idea to compare both sets of data to observed rainfall amounts.
Rate product did not exist before – gives the rainfall rate in inches per hour. Benefit: don't have to wait for accumulations to occur before thinking of actions to take. High rainfall rates, 2-4 inches per hour or greater, even for short durations, can give the possibility of the onset of flash flooding, especially in urban areas. In this example, rate product indicated rates of 4-6 inches per hour rates, several hours before final rainfall accumulations were calculated.

25. Estimation of Rainfall Amounts
Areas either side of hail shaft – similar values of Z, but area NW has much lower values of ZDR – much higher concentration of smaller drops

26. Want to Learn More Details about Dual Polarization Radar?
Dual-Polarization Radar Training for NWS Partners
Meteorologists
Non-Meteorologists who use the data
Technology Overview
Hydrometeor Classification Product
Estimated Rainfall Amount Products

27. Summary Dual-Polarization will arrive KLOT March 1, 2011
New base products and new derived products, but nothing gone from what you’re currently using
Improved precipitation estimates, identification of freezing/frozen/liquid precipitation types, location of hail cores, updrafts, etc.
Identification of non-meteorological returns, and better filtering from processed data

28. Thank You!

30. What does a polarimetric radar measure?
All of the “legacy” products will be available that are currently being created:
Reflectivity for Horizontal Polarization (Z)
- Base Velocity (V)
- Spectrum Width (SW)
New products that will be available:
- Differential Reflectivity (ZDR)
- Correlation Coefficient (CC)
- Differential Phase (DP)
We will examine these more closely in a bit.

31. Differential Reflectivity (ZDR)
Ratio of reflected horizontal and vertical power returns
Depends on the median shape and size of scatterers
Good indicator of drop shape
the shape is a good estimate of average drop size
ZDR proportional to: Horizontal Power Returned Vertical Power Returned

32. Differential Reflectivity (ZDR):
ZDR > 0: positive ZDR means horizontally oriented mean profile
ZDR < 0: negative ZDR indicates vertically oriented mean profile
ZDR ~ 0: Spherical mean profile

33. ZDR Differential Reflectivity Summary
Values of ZDR help identify hydrometer type
+ZDR (up to 1.5): liquid drops greater than 1-2 mm
++ZDR (> 3): large liquid drops, perhaps with ice cores
0 ZDR: spherical or effectively spherical, most likely hail if coincident with higher Z
Used to identify hail shafts, convective updrafts, regions of liquid vs. frozen hydrometeors
Make inferences on hydrometer type

34. Correlation Coefficient (CC):
Correlation between the horizontal and vertical backscattered power from the scatterers within a sample volume (zero to 1)
Think “Spectrum Width” for hydrometeors
Large spread of hydrometeor sizes and shapes results in lower correlation
The correlation coefficient is a correlation between the reflected horizontal and vertical power returns. It is a good indicator of regions where there is a mixture of precipitation types, such as rain and snow.

35. CC: What is it good for? Reflectivity: Correlation Coefficient:
Absolutely Something! Say it Again!
Reflectivity:
Correlation Coefficient:
Note area on left of each image: Low CC identifies this as non-meteorological returns.

36. CC in Winter Precipitation:
Reflectivity:
Correlation Coefficient:
High CC indicates all one precip type Low CC indicates mix (melting)

37. CC Summary CC -> Infer a side distribution of hydrometers
Values > 0.95 indicate consistent size, shape, orientation, and/or phase of hydrometeors
Values < 0.95 indicate a mixture of size, shape, orientation, and/or phase of hydrometeors
Very low (0.80 or less) means non-meteorological scatterers, sometimes very large hail

38. Potential Derived Products:
Quantitative Precipitation Estimation (QPE) – including 8-bit instantaneous intensity