Similar in concept to JDOP, except with the goal to operationally demonstrate the value of the polarimetric upgrade of the 88D.

Multi-seasonal to study both cold and warm season precipitation, with an Intense Observing Period planned for the spring of 2003.

Dense ground-based and airborne data collection to support verification. Significant hydrological component is planned.

Operational focus to polarimetric rainfall and hydrometeor identification algorithm tests.

Goals: -collect data and information that will allow cost/benefit analysis to be performed -demonstrate the utility and feasibility of a polarimetric 88D

• The overarching operational goals of JPOLE are to test the engineering design and determine the data quality of a polarimetric WSR-88D radar, demonstrate the utility and feasibility of the radar, and collect data and information that will allow a cost/benefit analysis to be performed.

• Plans call for an experiment that will consists of two phases: a multi-seasonal test and evaluation period (to begin in the spring of 2002), and an intense observation period (to begin in the spring of 2003).

JPOLE will include the first operational test of a polarimetric WSR-88D weather radar. It will also provide an opportunity to investigate many complementary hydrological and meteorological scientific objectives.

The open systems development and polarimetric upgrade to the KOUN WSR-88D radar has been a tri-agency effort supported by the NWS, FAA, AFWA. As such the operational objectives of JPOLE are designed to meet the needs of three agencies.

• Evaluating the engineering design and data quality of a polarimetric WSR-88D radar

• Examining the benefits of polarimetric radar data to operational meteorologists, hydrologists, and aviation users.

Objectives:The JPOLE Operational Demonstration Objectives and requirements can be broken down into two broad categories

•Demonstrate the accuracy of KOUN reflectivity, velocity, and spectrum width through detailed comparisons with conventional WSR-88D radar data

•Demonstrate the accuracy of KOUN polarimetric measurements through comparisons with high-quality research polarimetric radar data

•Demonstrate that polarimetric precipitation estimation and hydrometeor classification products can be collected with acceptable rotation rates (all previous research results were obtained with relatively slow scan strategies).

•Perform tests to assure minimal degradation in VCP times, and no degradation in ground clutter filtering, anomalous propagation filtering, and velocity dealiasing.

•Evaluate the value of alternate HV and LDR scans (and limits to any of the variables).

The Operational Demonstration will provide an opportunity to evaluate critical engineering and data quality issues, for example:

• Improve Quantitative Precipitation Estimation (QPE)• Use QPE to improve operational hydrologic forecasts (especially for

flash flood events)• Discriminate hail from rain and gauge hail size• Identify precipitation type in winter storms (dry/wet snow, sleet, rain)• Identify biological scatterers (and their effect on wind measurements)• Identify the presence of chaff (and it effect on precipitation measurements)• Identify areas of ground clutter and anomalous propagation• Provide initial conditions and constraints to numerical models for

short term forecasts• Investigate the feasibility of identifying aircraft icing conditions

Demonstrate to the hydrological, meteorological, and aviation communities a polarimetric radar’s ability to:

• Train operational hydrologists and meteorologists on the use of polarimetric radar data and products (spring of 2001).

• Field Phase I: Collect data sets that will allow a detailed analysis of present (non-polarimetric) and future (polarimetric) WSR-88D rainfall and hydrometeor products (to begin in the spring of 2002).

• Field Phase II: Collect additional verification data sets using improved infrastructure provided by the addition of community-wide facilities (to begin in the spring of 2003).

JPOLE will be similar in concept to JDOP, except with the goal to operationally demonstrate the value of the polarimetric upgrade to the WSR-88D radar.

• Cold-season: (February-March of 2003)• Focus on hydrometeor identification in winter precipitation and non-

precipitating clouds• S-band radar• Ka-band radar• aircraft

• Warm-season: (April-June of 2003)• Focus on hydrometeor identification, rain measurements, and

hydrologic forecasting for springtime precipitation events• S-band radar• X-band radar• aircraft• surface verification data sets (mesonet, ARS, PicoNet, disdrometer, hail)

Phase II:The proposed JPOLE Intense Observation Period (IOP) will include both cold-season and warm-season observations.

• Verify and compare radar rainfall estimates and improve radar rainfall estimators

• Investigate DSD variability• Measure streamflow and runoff• Conduct hydrologic modeling

• Improve physical understanding of polarimetric signatures• Verify and improve hydrometeor classification schemes• Develop and verify hydrometeor quantification schemes• Investigate the use of polarimetric hydrometeor information in

cloud resolving models

Hydrological:

Meteorological:

• Improve physical understanding of polarimetric signatures.• Conduct verification and comparison studies of radar rainfall products. Compare conventional and

polarimetric radar rainfall estimates.• Collect data that can be used to evaluate the accuracy of operational precipitation and hydrometeor

identification algorithms. • Investigate the effect of natural drop size distribution variability on conventional and polarimetric

rainfall estimators.• Investigate the effect of drop oscillations and canting angles on conventional and polarimetric rainfall

estimators.• Examine the accuracy of hydrometeor classification schemes through detailed comparisons with

verification data sets.• Use verification data sets to develop hydrometeor quantification schemes.• Investigate how microphysical information derived from polarimetric radar measurements can be

used in cloud resolving models.• Examine the microphysical basis for drop size distribution variability in both cold and warm season

precipitation events.• Investigate source of typical overestimation of extreme “cold-process” rain and underestimation of

extreme “warm-process” rain.• Investigate how improved precipitation estimates from polarimetric rainfall measurements can be

used to initialize hydrologic models.• Measure streamflow and runoff and conduct hydrologic modeling studies. Investigate how input

data uncertainties influence flood prediction, the maximum time/space scales required to accurately simulate a flash flood, and the basin characteristics that are most important in transforming rainfall into runoff.

• Conduct polarimetric S-band radar intercomparison studies with polarimetric Ka- and X-band radars.• Assess how Ka-band (hydrometeor identification) and X-band (precipitation) measurements can be

used to improve interpretation of polarimetric S-band radar data.

JPOLE Scientific Objectives

KTLXKOUN

CIM

KINX

KFDR

KVNX

CIM-KOUN Dual-Doppler

KOUN 100 km range ring

3D lightning mapping network

ARS rain gauge network

Dry Creek watershed

Polarimetric radars

WSR-88D radars

405 MHz profiler

HKL

LMN

PRC

VCI

Blue River basin

Small red dots indicate location of Oklahoma mesonet sites

• Research polarimetric radar that can be strategically placed in central Oklahoma to provide both a source of high-quality data that can be used for a comparison with the KOUN radar data (as well as provide input for hydrological distributed modeling studies)

• Ka-band and X-band polarimetric radars that can be used for radar comparison studies

• Research aircraft to provide in situ microphysical data

• Additional rain gauges and disdrometers

• Streamflow measurements

• Hail chase vehicles

• Coordinate product development with operational meteorologists, hydrologists, and aviation, whose insight and feedback will be of vital importance to the evaluation of the polarimetric WSR-88D products

• Introduce polarimetric precipitation accumulation products and modify the HCA to include winter precipitation products (fall of 2001)

• Replace NSSL Cimarron polarimetric radar data with that from the KOUN WSR-88D radar (spring of 2002) and begin multi-seasonal data collection

• Continue planning for the JPOLE Intense Observational Period (spring of 2003)

• Conduct a detailed analysis of non-polarimetric and polarimetric radar products to examine the utility of an operational polarimetric radar

• Coordinate a presentation to the PMC

• Develop a short list of evaluation items for FY 2002

• Develop procedures for meteorological and hydrologic forecasters to evaluate polarimetric products

• Develop process for information flow from NWS Headquarters to Region to the local Forecast Office (to coordinate NWS interaction with operational demonstration)

• Develop plans for passing hydrologic (Digital Precipitation Array) information to the River Forecast Center.

October 2, 2001 NSSL/NWS Operational Demonstration Meeting

NSSL Polarimetric Radar Algorithms

Operational benefits of polarimetric radar: Hydrometeor Classification Precipitation Estimation

NSSL currently has three versions of the classification algorithm: 1) RHI - 11 classes (meteorological only) 2) PPI_1 - 5 classes (meteorological only) 3) PPI_2 - 7 classes (meteorological, ground clutter, AP, biological)

PPI_2 has been developed to run in real time on NSSL Cimarron polarimetric radar data. After some additional testing, it was delivered to the NWS in late May of 2001.

The real-time HCA was delivered to the Norman, OK NWS office in May of 2001. It has 7 classes (meteorological, ground clutter, AP, biological) and is currently running on data from the NSSL Cimarron polarimetric radar.

Hail

Moderate Rain

Heavy Rain

Light Rain

Big Drops

AP

Birds/Insects

May 6, 2001

Hydrometeor Classification - PPI_1 Algorithm

Specific Differential Phase (deg/km) Classification

Differential Reflectivity (dB)Reflectivity (dBZ)

Rain/Hail

Heavy Rain

Moderate Rain

Light Rain

Large Drops

Hydrometeor Classification - PPI_2 Algorithm

Identification and Removal of AP and Biological Scatterers

An extensive region of AP and biological scatterers (birds) was identified and removed.

Meteorological data were then classified and put into five categories: Rain/Hail, Heavy Rain, Moderate Rain, Light Rain, and Large Drops.

Hydrometeor Classification - RHI Algorithm

Light Rain

Wet Snow

Heavy Rain

Large Drops

Moderate Rain

Vertical Ice

Horizontal Ice

Dry Snow

Hail

Graupel/Small Hail

Rain/Hail

Hydrometeor ClassificationRHI Algorithm

Radar Reflectivity

Hydrometeor Classification