2010 phased-array radar innovative sensing experiment

2010 Phased-Array Radar Innovative 2010 Phased-Array Radar Innovative Sensing ExperimentSensing Experiment

Sebastian TorresNSSL and CIMMS

Photo by Adam Smith

Daphne LaDueOU/CAPS

Pam HeinselmanNSSL

Photo by James Murnan

Heather Lazrus SSWIM

2010 PARISE April 2010 Norman, OK

Acknowledgements

National Weather Center Contributions– Signal processing techniques and software

development• Ric Adams, Chris Curtis, Eddie Forren, Igor Ivic, Dave

Priegnitz, John Thomson, David Warde (NSSL/CIMMS)

– WARNGEN for WDSS-II• Charles Kerr & Kurt Hondl (NSSL/CIMMS)• David Andra and other fcsters at Norman WFO

– WES cases• Mark Sessing, Darrel Kingfield, & Ben Baranowski

(WDTB)

– Playback Simulations• Kevin Manross (NSSL/CIMMS)

– Experimental Warning Program Logistics• Greg Stumpf and Travis Smith (NSSL/CIMMS and MDL)


What’s Unique to PAR?Parabolic Antenna– Single radiation

element• Single transmitter• Single receiver

– Non-conformal– Fixed beam pattern– Mechanical steering

Phased Array Antenna

– Multiple radiation elements

• Multiple transmitters• Multiple receivers

– Conformal– Variable beam pattern– Electronic steering

Unique Capabilities


PAR Electronic Beam Steering

Adapted from Jeff Herd, MIT LL

Beam Perpendicular to the Array

Scan To 30 deg

Want fields to interfere constructively in desired directions, and interfere destructively in the remaining space


Why a PAR at NSSL?

The WSR-88D (NEXRAD) is ~20 years old

– End of life around the year 2020– Investigating replacement technology

• Affordability of new technology vs. operating costs for obsolete technology

• Improved weather surveillance capabilities– e.g., faster updates

• Combine weather and aircraft surveillance networks

– Reduce number of radars– Reduce maintenance costsThe MPAR Concept

+


Multi-function PAR Concept

Long-Range Surveillance

Severe Weather Non-Cooperative Targets Weather Fronts

Terminal Surveillance

WMD Cloud


What is the NWRT PAR?

SPY-1A Antenna

U.S. Navy

Partnership+

GovernmentAcademia

Private Industry

National Weather Radar Testbed Phased-Array

Radar

=

NWRT PAR

Photo by A. Zahrai


Purpose of the NWRT PARWhich type of scanning

improvement do forecasters consider most

important?

62%

Stakeholders’ needs:Faster Updates

Why are faster updates needed?

1) Tornado cyclone and mesocyclone evolution can occur in 10s of seconds

2) Significant storm evolution and transition between storm types can occur between WSR-88D scans

3) Mid and upper-level signatures indicative of downbursts are not reliably detected

Source: Radar Operations Center Source: LaDue et al. 2010, in press (BAMS)

Determine how to best capitalize on PAR capabilities to address 21st century forecast and warning needs

Determine how to best capitalize on PAR capabilities to address 21st century forecast and warning needs


Future PAR Design?

Ultimate GoalWhat we have now


NWRT PAR Characteristics

90

1.5

2.1 2.1

Characteristics Similar to WSR-88D

Wavelength: PAR = 9.4 cm / WSR-88D = ~10 cm (S-band)

Range Resolution: PAR = 240 km / WSR-88D = 250 km

Sector Scans Polarization

90

Beam Width

1.5

2.1 2.1

10 km

Characteristics Different from WSR-88D


Signal Processing Upgrades

– Data Quality: brings performance closer to that of operational radars

• Artifact removal– Ground clutter, interference, DC bias, point targets

• Range and velocity ambiguity mitigation• Calibration

– Evolutionary: demonstrates PAR technology for weather applications

• Faster updates– Range oversampling– Adaptive scanning


Interference FiltersFilters OFF Filters ON

NWRT1 May 200800:25 UTC


CLEAN-APCLutter Environment ANalysis Using Adaptive Processing

CLEAN-AP is OFFAre these storms?

NWRT10 Feb 09 16:19

CLEAN-AP is ONAP contamination was removed!

NWRT10 Feb 09 16:19

KTLX ReflectivityAll-bins filtering


Range Unfolding

14


Dynamic PRT Adjustmentvia the Radar Control Interface

PRT Change

PRT Change


Want Faster Updates?There’s no such thing as a free lunch

Full ScanFull Scan Full ScanFull ScanShort Obs. Short Obs.

Time Time

Partial ScanPartial Scan

Less coverage

Less accuracy

Faster updates

Faster updates

Adaptive Adaptive ScanningScanning

Range Range OversamplingOversampling


Range OversamplingA Signal Processing Solution

• Range oversampling (RO) adds more information without increasing the observation time

– RO leads to overlapping radar volumes

– RO results in more accurate estimates and/or faster updates

c/2

c/2L

c/2

Traditional Sampling Oversampling

These are These are cleverly cleverly combined combined

for for improved improved accuracyaccuracy


Range OversamplingPerformance Demonstration

Data collected using same observation

time

Standard Processing Range Oversampling Processing

A smoother field is an indication of more accurate data


Adaptive scanning

Areas of interest onlyArbitrary

Adaptive scanning

Areas of interest onlyArbitrary

Conventional scanning

EverywhereSequential

Conventional scanning

EverywhereSequential

Electronic Adaptive Scanning

Courtesy of Chris Curtis

Goal: Faster UpdatesGoal: Faster Updates


What is ADAPTS?• Adaptive DSP Algorithm for PAR Timely

Scans– Beam positions are classified as active or

inactive• Only active beam positions are scanned

– Active beam positions are updated after every scan– Full surveillance volume scans are scheduled periodically

AZ

EL

Radar scans full surveillance volume

ADAPTS determines

active beam

positions

ADAPTS redetermines active

beam positions

time

SURV ADAPTS ADAPTS ADAPTS ADAPTS SURV ADAPTS

tn

AZ

EL

Radar scans active beam positions

tn+1

AZ

EL


tn+2

AZ

EL


tn+3

AZ

EL


AZ

EL


Surveillance update time

Scanning strategy schedule:

tn tn+1 tn+2 tn+3


1st Criterion1st Criterion 2nd Criterion2nd Criterion 3rd Criterion3rd Criterion

How does ADAPTS work?• Active beam positions

meet one or more criteria• Elevation angle• Continuity and coverage• Neighborhood

Zth

continuity

Always scan at the lower elevations

Range

Z

Determine significant weather

signals

coverage

Real-time display of active beam positions

Look around to respond to storm

evolution

EL

AZleft right

up

dow

n


ADAPTS PerformanceQualitative Evaluation

ADAPTS is OFF

ADAPTS is ON

09 AUG 2008 – Reflectivity - 8.7 deg

09 AUG 2008 – Reflectivity - 8.7 deg


ADAPTS PerformanceQuantitative Evaluation

0040:59 0104:35 0129:24 0154:27 0217:27Time (UTC)

Te

mp

ora

l R

es

olu

tio

n (

min

)

0.9

1.0

1.1

1.2

1.3

1.4

a)

0040:59 0129:24 0217:27b)

200 km 150 km 100 km 200 km 150 km 100 km 200 km 150 km 100 km

1 May 2009 Nominal Update Time

ADAPTS Update Times


PARISE: MotivationNWRT PAR has unique capabilities

Research Questions:1) How can technology be used to produced more focused, efficient, and effective weather surveillance?

2) Can improved understanding of storm processes be attained from high-temporal resolution data?

3) What are potential operational impacts of higher temporal resolution data on the warning decision process?

4) What additional warning lead time might be gained? Photos by James

Murnan


NWRT PAR: More focused, efficient, effective weather surveillance?

1) Oversampled VCP2) Weather-driven ADAPTIVE scanning

Automated and Manual


What is an Oversampled VCP?

Dense Vertical Sampling

Most dense sampling near the ground

Tilts chosen to sample storm extending to 18 km AGL w/in 20 km of the PAR

Optimized when the max height uncertainty (%) is ~same at all ranges and heights of storm features (Brown et al. 2000)

Overlapped Azimuthal Sampling

50% overlapped azimuthal sampling at all tilts to improve the apparent resolution of azimuthal signatures

Data Quality

Number of pulses for reflectivity and velocity estimates meet or exceed VCP 12 standards


Oversampled VCP

22 tilts; max height uncertainty 18%

Update Time: 2 min

Red lines = VCP 12


Weather-driven Adaptive Scanning

Are storms located only w/in 120 km of NWRT PAR?

Yes No

Choose uniform-PRT version of Oversampled VCP and run ADAPTS

Max Update Time: 1.4 min

Choose split-cut-PRT version of Oversampled VCP and run ADAPTS

Max Update Time: 2 min



Are storms located only w/in 120 km of NWRT PAR?

Are storms potentially tornadic?

Yes No

Are storms located within 120 km of PAR?

Choose 2-tilt, split-cut VCPUpdate Time: 22 s

Composite Update Time: 2.7 min

Yes No

Continue to sample as assessed above

If only located w/in 120 km: Choose 4-tilt, uniform PRT VCP

Update Time: 18 sComposite Update Time: 2.3 min

Else: Choose 4-tilt, split-cut PRT VCP

Update Time: 38 sComposite Update Time: 3.3 min



VCP # Tilts Waveform Update Time (s)

Oversampled VCP (OVCP) 22 Split cut < 6 120

OVCP_within_120km 22 Uniform 82

Storm Surveillance 11 Uniform 55

Tornadic_outside_120km 2 Split cut 22

Composite_outside_120 2 + 22 Split cut 164

Tornadic_SplitCut 4 Split cut 38

Composite_SplitCut 4 + 22 Split cut 196

Tornadic_within_120km 4 Uniform 18

Composite_within_120km 4 + 22 Uniform 138


PARISE: MotivationNWRT PAR has unique capabilities

Research Questions:1) How can technology be used to produced more focused, efficient, and effective weather surveillance?

2) Can improved understanding of storm processes be attained from high-temporal resolution data?

3) What are potential operational impacts of higher temporal resolution data on the warning decision process?

4) What additional warning lead time might be gained? Photos by James

Murnan


1) How might higher temporal resolution data impact the warning decision process?

2) Will faster data updates increase warning lead time?

How will we answer these questions?

Tuesday Evening and WednesdayFor a variety of playback and real-time (hopefully!) cases, interrogate PAR data and issue warnings as you would in your office.

After each event, discuss your experience in making warning decisions (or not)

Thursday: Impact of Temporal Resolution ExperimentDirectly compare how forecasters (you!) issue warnings based on data provided at current radar update rates, with warnings issued based on faster data updates provided by Phased Array Radar (PAR).

James Murnan

Impacts on warning decision process?


Become comfortable using WDSS-II to interrogate storms and issue warnings

Issue warnings for 5 playback and/or real-time events

Participate in discussions on warning decision experience

Photos by James Murnan

Your Goals!


Impact of Temporal Resolution

Experiment PurposeDetermine potential operational impact of temporal resolution on warning decision process and warning lead time

34

MethodControl and experiment groups• Control: PAR data degraded to WSR-88D update time • Experiment: PAR data with full-temporal resolution

Matched groups: You help us determine which pairings results in equivalent radar-interpretation skills


What you will do during experiment

• Form two teams• Work through two cases– Gain situational awareness (WES)– Write an Area Forecast Discussion– Work through the case in displaced real time– Issue warning products as needed– Discuss your experience within your team– Contrast experiences with other team

• Break for lunch / work through 2nd case / final debrief to end the day

35


Consent• Read through consent forms

• Participation– Provides first rigorous test of impact of temporal

resolution on warning decision process– Lasts one 8-hr workday– Provides opportunity to learn from each other– Is not completely confidential – Is not reimbursed above normal compensation– Is voluntary

• Indicate your preference on quotation and recording

36


2:45 Gain experience using Warning Decision Support System – Integrated Information (WDSS-II)

4:00 Tour National Weather Center

5:00 Group Dinner (wx dependent)

6:30 First playback or real-time event

9:00 End of day!

Photos by James Murnan

Today’s Schedule

2010 phased-array radar innovative sensing experiment

Documents

mdl2010 parise

now2010 parise

zahrai2010 parise

utc2010 parise

wsr88d2010 parise

par technology

press bams2010 parise

remaining space2010