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25 th IIPS 15.5

WSR-88D Dual Polarization Initial Operational Capabilities

25th AMS Conference on International Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology

15 January 2009 Michael J. Istok NOAA/NWS/Office of Science and Technology

Systems Engineering Center, Silver Spring, MD

[email protected]

WSR-88D Dual Polarization

Initial Operational Capabilities

• • • • • • •

Coauthors: Mark Fresch, NOAA/NWS/Office of Hydrologic Development Zack Jing, Steven Smith, Richard Murnan, NOAA/NWS/OOS/Radar Operations Center Alexander Ryzhkov, John Krause, and Michael Jain, NOAA/OAR/National Severe Storms Laboratory Paul Schlatter (Training Division), John Ferree (Meteorological Services Division), NOAA/NWS/OCWWS Brian R. Klein, Daniel Stein III, Wyle Information Systems Gregory Cate, NOAA/NWS/Office of Science and Technology/Programs and Plans Division Robert E. Saffle, Noblis, Inc.

• • •

Acknowledgments: Ning Shen, Yukuan Song, Zihou Wang, James Ward, Jihong Lui, Zhan J Zhang, Wyle Information Systems Cham Pham, NOAA/NWS/Office of Hydrologic Development Jim Ramer, Joanne Edwards, Xiangbao Jing, NOAA/OAR/ESRL/Global Systems Division

Slide 2 2009 AMS: 25th IIPS (15.5) WSR-88D DUAL POLARIZATION INITIAL OPERATIONAL CAPABILITIES

Introduction

• •

Mission benefits by adding dual polarization capability to the WSR-88D

– – – – Improved hail detection for severe thunderstorm warnings, Improved rainfall estimation for flood and flash flood warnings, Rain/snow discrimination for winter weather warnings and advisories, Data retrieval from areas of partial beam blockage to improve services in mountainous terrain, and – Removal of non-weather artifacts such as birds and ground clutter to improve overall data quality for algorithms and numerical model input.

Dual Polarization program lead by NWS OST

– Contract awarded September 2007 to develop and deploy changes to the RDA.

– Begin System and Beta test in October 2009 and June 2010 – 2-year deployment starts in October 2010 – RPG and AWIPS changes implemented through NOAA collaboration – RPG Build 12: NWS OST, OHD, ROC, OCWWS, and OAR NSSL. – Test and deploy with RDA upgrade – AWIPS OB 8.3 & 9: NWS OST, OHD, OCWWS, and OAR ESRL GSD.

– Deploy in early 2009 to support WSR-88D testing and AWIPS-2 program.

– NWS OCWWS involved in product requirements & WDTB has begun training development 2009 AMS: 25th IIPS (15.5) WSR-88D DUAL POLARIZATION INITIAL OPERATIONAL CAPABILITIES Slide 3

WSR-88D RDA

• Simultaneous transmission of horizontal and vertically polarized pulses to acquire dual polarization data. – Minimizes dwell time, therefore will not lengthen volume scans – Splitting the power results in a return signal with reduced sensitivity – Scientific analysis and WFO usage reports indicated no significant operational impact – Hardware design and signal processing techniques should recover some of the reduced sensitivity • Differential Reflectivity (Zdr), Correlation Coefficient (CC), and Differential Phase (Phi) will be added to the base data fields – At range resolution of 250 m, up to maximum range of 300 km – On low elevation split cuts, radials will be provided at 0.5 deg azimuth. – The other two data enhancements introduced in WSR-88D Build 10 will be extended to all the remaining elevations of all VCP’s – 250 m range resolution for reflectivity data – 300 km maximum range for Doppler moments Slide 4 2009 AMS: 25th IIPS (15.5) WSR-88D DUAL POLARIZATION INITIAL OPERATIONAL CAPABILITIES

WSR-88D RPG: Algorithms

Recombination Algorithm

– Creates 1 degree azimuth data from 0.5 degree data on split cuts •

Dual Polarization Preprocessing Algorithm

– Inputs recombined base data (1 degree by 250m) – Unwrap PHI – Estimate specific differential phase (Kdp) – Correct reflectivity and differential reflectivity with differential phase – Calculate signal-to-noise ratio and the spatial variability (the texture) of both the reflectivity and the differential phase – Smooth dual polarization fields and base moments along the radial to reduce the variances from noise and ground clutter contamination – Output to the dual polarization initial operational capability (IOC) algorithms and products Slide 5 2009 AMS: 25th IIPS (15.5) WSR-88D DUAL POLARIZATION INITIAL OPERATIONAL CAPABILITIES

WSR-88D RPG: Algorithms - continued

Hydrometeor Classification (HC) Algorithms

– Quality Index Algorithm (QIA) – Calculate quality index for six of HCAs input data fields – Estimate of the impact from the following five factors: – Attenuation, non-uniform beam filling effects, magnitude of the correlation coefficient, signal-to-noise ratio and partial beam blockage. – Data with a quality index value less than 1.0 indicates the data is degraded by one or more of the five factors. – HC Algorithm (HCA) – – – – Fuzzy logic to classify each sample bin to one of 12 categories Proximity to Melting Layer constrains classification possibilities Weighting factors control influence of data variables on classification Hard Rules (e.g., HA > 30 dBZ, BI < 0.97 CC) – Computes aggregate score for each allowable hydrometeor classification – Melting Layer Detection Algorithm (MLDA) – – – HCA output is used to eliminate bins of GC, BI, UK, ND Reflectivity and CC of remaining bins are used to search for ML signatures – Elevation angles 4.5 to 10 degrees; Altitude below 6km; SNR > 5 dB If data is sparse, uses 0 deg C altitude from RUC model or manually entered Slide 6 2009 AMS: 25th IIPS (15.5) WSR-88D DUAL POLARIZATION INITIAL OPERATIONAL CAPABILITIES

WSR-88D RPG: Algorithms - continued

• • • • • • • • • • • •

HCA Categories GC

Ground clutter / anomalous propagation

BI DS WS IC

Biological Dry snow Wet snow Ice crystals

BD RA HR GR HA UK ND

Big drops Rain (light and moderate) Heavy rain Graupel Hail (mixed with rain) Unknown No data (less than threshold) • • • • •

Melting Layer Constrains HCA Completely below:

– GC, BI, BD, RA, HR, HA, UK, ND

Partly below:

– GC, BI, WS, BD, RA, GR, HR, HA, UK, ND

Mostly within:

– GC, BI, DS, WS, BD, GR, HA, UK, ND

Partly above:

– GC, BI, DS, WS, IC, BD, GR, HA, UK, ND

Completely above:

– DS, IC, GR, HA, UK, ND Slide 7 2009 AMS: 25th IIPS (15.5) WSR-88D DUAL POLARIZATION INITIAL OPERATIONAL CAPABILITIES

WSR-88D RPG: Algorithms - Continued

Quantitative Precipitation Estimation (QPE) Algorithm

– Constructs hybrid scan of precipitation rate based on terrain data, hydrometeor classes, MLDA, and Dual Polarization data fields – Smoothes elevations of HCA data with 9 point Mode Filter – – – Reject GC or UK bins and look to next elevation Rate of zero is assigned to BI or ND bins Reject data if CC < 0.85, or blocked by 70%, and look to next elevation – Compute rate based on hydrometeor class & height relative to melting layer – 0 [mm hr-1] nonmeteorological echo (BI, ND) – R(Z, ZDR) Light/Moderate Rain (RA) – R(Z, ZDR) Heavy Rain or Big Drops (HR, BD) – R(KDP) – 0.6 * R(Z) – 0.8 * R(Z) – 0.8 * R(Z) – R(Z) – 2.8 * R(Z) – 2.8 * R(Z) Hail, mixed with rain (HA) below the top of the melting layer Wet Snow (WS) Graupel (GR) Hail, mixed with rain above the top of the melting layer Dry Snow (DS) below the top of the melting layer Dry Snow (DS) above the top of the melting layer Ice Crystals (IC) – Begins and ends storm total accumulation based on rate and area thresholds Slide 8 2009 AMS: 25th IIPS (15.5) WSR-88D DUAL POLARIZATION INITIAL OPERATIONAL CAPABILITIES

WSR-88D RPG: Algorithms - Concluded

The QPE algorithm should improve precipitation estimation in the following situations:

– Where the radar beam is partially blocked – For nearly all hydrometeor classes – By greatly reducing contamination from non-precipitation echoes – By identifying the bright-band (melting layer) – By discriminating between rain and snow – By identifying hail and mitigating hail contamination Slide 9 2009 AMS: 25th IIPS (15.5) WSR-88D DUAL POLARIZATION INITIAL OPERATIONAL CAPABILITIES

WSR-88D RPG: Products

• •

Elevation Based Products

– Base Products (Zdr, CC, Kdp) – Built from output of preprocessor algorithm – Hydrometeor Classification – Melting Layer

Precipitation

– Hybrid Scan Hydrometeor Classification – Precipitation Rate – One-Hour Accumulation – Storm-Total Accumulation – User Selectable Accumulation Period – Specify (hh:mm) end time and span within previous 24 hour period – Difference Products: Dual Pol QPE minus Legacy PPS – One-Hour Difference – Storm-Total Difference 2009 AMS: 25th IIPS (15.5) WSR-88D DUAL POLARIZATION INITIAL OPERATIONAL CAPABILITIES Slide 10

WSR-88D Dual Polarization Product Suite

Dual Polarization Base Products HCA Quantitative Precip Est(QPE) Technical Requirements for the WSR-88D Dual Polarization Products rev14 3jun2008-mji Product Mnemonic and Message Code (#) RPG ICD Packet Code Number of Data Levels Azimuth Resolution Range Resolution Compression Method RPG # AWIPS deg m DZD ZDR 159 ZDR 158 16 256 1 250 af1f 16 1 1000 BZ2 rle DCC 161 16 256 1 250 BZ2 CC CC 160 af1f 16 1 1000 rle DKD KDP 163 KDP 162 16 256 1 250 af1f 16 1 1000 BZ2 rle DHC HC ML 165 16 HC 164 166 ML af1f e03,802 256 1 250 16 1 1000 4 1 250 BZ2 rle HHC 177 HHC 16 16 1 250 BZ2 DPR 176 DPR 28 65536 1 250 BZ2 OHA DAA 169 170 OHA DAA af1f 16 16 1 2000 256 1 250 rle BZ2 STA DSA 171 STA 172 af1f 16 1 2000 rle 16 256 1 250 BZ2 DUA 173 DUA 16 256 1 250 BZ2 DOD DSD 174 175 DOD DSD 16 16 256 1 250 256 1 250 BZ2 BZ2 Maximum Range Generation Frequency Minimum, Maximum Data Values & (precision) Uncompressed Product Storage Size (Kilo bytes) Product Transmission Size (Kilo bytes) during Widespread Svr Wx km E/V min max avg min max avg 300 Elev 230 -7.9,7.9 (.0625) -4,6 (.25-3) 0.2,1.05 0.2,1.05 -2,I0 (.00333) (.01-.25) (.05) 93 337 236 33 103 80 same as xmit 27 29 28 300 93 337 236 28 86 66 Elev 230 same as xmit 25 27 26 300 Elev 230 93 337 236 11 51 33 -2,7 (.25-3) same as xmit 17 20 18 300 230 Elev n/a 93 337 236 8 23 17 n/a same as xmit 12 13 12 230 Elev 0.1

6 5 5 5 230 Vol n/a 0.1

331 331 8.9

11 9.8

230 230 230 230 Vol 0.0,65.535 (0.001) like PPS OHP 0.1

663 663 140 151.4

144.7

Vol 0.1

21 Vol 1* 0.1

331 Vol like PPS STP 0.1

28 21 11.4

331 28 11 10.9

12.0 165.5 10.9

132 10.9

230 Vol 1* 0.1

339 339 62.7

62.8

62.8

230 Vol, otr 1* 0.1

331 331 55.6

64.7

61.8

230 Vol 2* 0.1

331 331 51.9

58.2

54.8

230 Vol 2* 0.1

331 331 52.9

53.0

53 (1) an adjusting range of data and precision, based on the maximum data value. (2) adjusting range of data and precision, based on the maximum absolute value of the data and with equal precision and data range for both positive and negative values.

2009 AMS: 25th IIPS (15.5) WSR-88D DUAL POLARIZATION INITIAL OPERATIONAL CAPABILITIES Slide 11

Marginally Severe Supercell

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Marginally Severe Supercell

Precip Insects

2009 AMS: 25th IIPS (15.5) WSR-88D DUAL POLARIZATION INITIAL OPERATIONAL CAPABILITIES

What about the rest?

All > 0.97

Slide 13

Marginally Severe Supercell

2009 AMS: 25th IIPS (15.5) WSR-88D DUAL POLARIZATION INITIAL OPERATIONAL CAPABILITIES Slide 14

SOO-DOH Images\kcri_0.5_HC_20080408_0638.png

20000 ft MSL 2009 AMS: 25th IIPS (15.5) WSR-88D DUAL POLARIZATION INITIAL OPERATIONAL CAPABILITIES Slide 15

ML Product in AWIPS

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Dual- Polarization QPE Products

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AWIPS Enhancements

• • • • •

Reorganized radar menus Four-Panel display operations

– All-Tilts – Panel/Combo Rotate – All-Panel Sample

Four Dimensional Storm Cell Investigator State scale mosaics Volume Browser CAPPI’s of radar products

– Height above radar level – Height above mean sea level – At a temperature level 2009 AMS: 25th IIPS (15.5) WSR-88D DUAL POLARIZATION INITIAL OPERATIONAL CAPABILITIES Slide 18

AWIPS Radar Menu Redesign

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AWIPS All Panel Sample

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AWIPS Dual Pol Display via FSI

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AWIPS Volume Browser CAPPI Displays

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Future Development

• • • • • • • •

Optimize HCA for transitional and winter weather Adjust MLDA for cold season storms when melting level is low Add classes by splitting Hail/Rain Mixture into small hail, large hail and adding freezing rain.

Improving accuracy of precipitation at longer distances and in the presence of partial beam blockage Quantitative estimate of snow Identifying location of convective cells in projecting areas with higher melting layers and different hydrometeor characteristics Rain gage bias correction Improve data quality and automatically identify & assess features

– Include dual polarization data in AP and clutter mitigation schemes – Bird-specific data and/or data with bird returns removed – Liquid water equivalent and In-flight icing – Tornado debris cloud Slide 33 2009 AMS: 25th IIPS (15.5) WSR-88D DUAL POLARIZATION INITIAL OPERATIONAL CAPABILITIES

For Additional Information

Michael Istok

– National Weather Service Office of Science and Technology Systems Engineering Center, Silver Spring, MD – 301-713-0763 x103 – [email protected]

2009 AMS: 25th IIPS (15.5) WSR-88D DUAL POLARIZATION INITIAL OPERATIONAL CAPABILITIES Slide 34

Data and Product Distribution and Archive

• •

Level II Data (Top Tier Sites, NCDC)

– Message 31 introduced for super-res, also supports dual-pol data – Changes to Metadata include VCP, Alarms, P/M data messages – Currently, 10 to 180 kbps per radar, depending on VCP & weather, and resulting in a network max hourly load near 7 mbps – Worst case dual pol increase by factor of 2.1 (per radar & network) – Version numbers will be expanded for new data characteristics – Resource constraints cause a mixture of Level II data versions – Full resolution, recombined, and dual pol removed – Exploring options to overcome constraints to provide additional data

Level III Products (RPCCDS, NOAAPORT, NCDC)

– Currently, 3 to 21 kbps per radar, depending on VCP & weather, and resulting in network max hourly load near 1.6 mbps.

– Dual pol product types, elevations, and resolution will drive increase – Requirements formulation in progress – Dual pol to increase product load by at least a factor of 2 Slide 35 2009 AMS: 25th IIPS (15.5) WSR-88D DUAL POLARIZATION INITIAL OPERATIONAL CAPABILITIES

Elevation Based Dual Polarization Products

2009 AMS: 25th IIPS (15.5) WSR-88D DUAL POLARIZATION INITIAL OPERATIONAL CAPABILITIES Slide 36