1. WindShear-1 JYNC 1/24/2008 MIT Lincoln Laboratory Comparative Analysis of Terminal Wind-Shear Detection Systems John Y. N. Cho, Robert G. Hallowell, and Mark E. Weber 24 January 2008

2. MIT Lincoln Laboratory WindShear-2 JYNC 8/6/2007 Terminal Wind-Shear Hazards Wet microburst Dry microburst Gust front 1985 Crash in Dallas

3. MIT Lincoln Laboratory WindShear-3 JYNC 8/6/2007 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 FAA Ground-Based Wind-Shear Detection Systems Wind Shear Accidents EA66 JFK PA759 MSY DL191 DFW US1016 CLT Development Deployment SLEP Development Deployment TDWR ASR-9 WSP Higher performance Stand-alone system: higher cost Lower performance Piggyback system: lower cost SLEP NEXRAD Deployment Development SLEP SLEP: service life extension program Shared with NWS, DoD Not sited at airports LLWAS Dev. Deployment SLEP In situ: local coverage only Multiple towers per airport 1994 Wind Shear Systems Cost-Benefit Study Report Update study now

4. MIT Lincoln Laboratory WindShear-4 JYNC 8/6/2007 Cost-Benefit Analysis P Ground Probability that a ground-based system will detect wind shear with sufficient advance warning for the A/C to avoid a wind shear P Visual Probability that a pilot will visually recognize and avoid an area of wind shear P Airborne Probability that an airborne radar will detect wind shear with sufficient advance warning for the A/C to avoid a wind shear P Recovery Probability that a given A/C type will recover from a wind shear Benefit vs. Cost Safety benefit + Delay reduction benefit Safety benefit Accident cost  P Accident Operations Wind-shear exposure factor X X X = P Accident = 1 - P Ground 1 - P Visual 1 - P Airborne 1 - P Recovery XXX

5. MIT Lincoln Laboratory WindShear-5 JYNC 8/6/2007 Outline Scope –Sensors –Sites –Wind-shear type and coverage Methodology –Radar –Lidar –Combinations Selected results Summary

6. MIT Lincoln Laboratory WindShear-6 JYNC 8/6/2007 Sensor Sites 154 NEXRADs* TDWRs 46 TDWR Airports 40 LLWAS-RSs ASR-9s 135 ASR-9s 35 WSPs 46 TDWR airports + 35 WSP airports + 40 LLWAS-RS airports = 121 total airports studied *Only some are close enough to airports to be useful

7. MIT Lincoln Laboratory WindShear-7 JYNC 8/6/2007 New Products to be Considered ParameterLidarRadar* Wavelength 1.6  m 3.3 cm Range Resolution 30 – 50 m100 m Peak PowerN/A200 kW Average Power2 W180 W Beam WidthCollimated1.4° Antenna GainN/A43 dB Clutter Suppression N/A< 50 dB Lockheed Martin Coherent Technologies “WindTracer ® Terminal Doppler Solution” TDWR-11 NEXRAD-10 ASR-97 LMCT X band -3 Min. Detectable dBZ @ 50 km (No precipitation attenuation) *Proposed product

8. MIT Lincoln Laboratory WindShear-8 JYNC 8/6/2007 Wind-Shear Types and Coverage Terrain blockage Gust front domain: 18-km radius around airport (corresponds to 20 minutes @ 15 m/s) Microburst domain: Union of ARENAs Radar Microburst Gust front ARENAs = Areas Noted for Attention Runway + 3 miles final arrival + 2 miles departure

9. MIT Lincoln Laboratory WindShear-9 JYNC 8/6/2007 Outline Scope –Sensors –Sites –Wind-shear type and coverage Methodology –Radar –Lidar –Combinations Selected results Summary

10. MIT Lincoln Laboratory WindShear-10 JYNC 8/6/2007 Radar Wind-Shear P d Estimation Model Wind-shear reflectivity probability distribution function (PDF) Wind-shear thickness PDF Digital Terrain Elevation Data Digital Feature Analysis Data Range-fold contamination effects included Precipitation attenuation included (X band) Beam-filling loss, PRI & CPI effects included Site-specific false alarm factors such as bat roosts not included Range-fold contamination effects included Precipitation attenuation included (X band) Beam-filling loss, PRI & CPI effects included Site-specific false alarm factors such as bat roosts not included 1994 study: Results given for 5 climatic regions This study: Results are airport specific

11. MIT Lincoln Laboratory WindShear-11 JYNC 8/6/2007 Radar P d Estimation Engine Radar AA  A = r  r r → A To get “visibility” for each “pixel” in area of interest –Compute minimum and maximum detectable reflectivity –Sum over wind-shear reflectivity PDF between these limits –Sum over area of interest Multiply visibility by “inherent” detection probability of microburst or gust-front detection algorithm To get “visibility” for each “pixel” in area of interest –Compute minimum and maximum detectable reflectivity –Sum over wind-shear reflectivity PDF between these limits –Sum over area of interest Multiply visibility by “inherent” detection probability of microburst or gust-front detection algorithm Microburst Reflectivity PDF Probability dBZ Min. Max. Fraction of visible microbursts

12. MIT Lincoln Laboratory WindShear-12 JYNC 8/6/2007 Lidar Wind-Shear P d Estimation Model Assume siting at center of ARENAs (X-band radar also) Assume ground clutter does not interfere with collimated beam Assume dBZ along observation vector is same as wind-shear dBZ Detection likelihood vs. wind-shear dBZ is inverse of radar case: Detection range decreases with increasing dBZ Assume siting at center of ARENAs (X-band radar also) Assume ground clutter does not interfere with collimated beam Assume dBZ along observation vector is same as wind-shear dBZ Detection likelihood vs. wind-shear dBZ is inverse of radar case: Detection range decreases with increasing dBZ

13. MIT Lincoln Laboratory WindShear-13 JYNC 8/6/2007 Sensor Combinations Radar + Radar and Radar(s) + Lidar –Assume combined detection algorithm performs integration at “interest field” level (okay for line-of-sights to be different) –Compute optimum combined visibility pixel by pixel and sum over interest region Radar(s) + LLWAS –LLWAS coverage for existing systems are known –For new LLWAS, use average of LLWAS-RS sites –Detection phenomenologies (radar vs. LLWAS) are independent –P d (combined) = 1 – [1 – P d (radar)][1 – P d (LLWAS)] –Likewise, P fa also combines to increase—normalize to P fa = 10% assuming IID Gaussian distributions

14. MIT Lincoln Laboratory WindShear-14 JYNC 8/6/2007 Outline Scope –Sensors –Sites –Wind-shear type and coverage Methodology –Radar –Lidar –Combinations Selected results Summary

15. MIT Lincoln Laboratory WindShear-15 JYNC 8/6/2007 Microburst P d Examples TDWRWSPNEXRAD*X bandLidarLLWAS Single Sensor96%82%79%87%34%49%** Lidar +97%96%98%93% LLWAS +96%83%80% NEXRAD +87% NEXRAD + WSP +98%87% ModelMeasurement 90%92% Washington (DCA) FAA requirement Microburst P d = 90% @ P fa = 10% These results assume post-upgrade radar performance *Assumes implementation of rapid (~1 min) terminal wind-shear scan mode **No LLWAS at these sites: Use average value for LLWAS-RS system DCA legacy TDWR microburst P d @ P fa = 10% Example 1 TDWRWSPNEXRAD*X bandLidarLLWAS Single Sensor87%73%0%64%49%49%** Lidar +96%97%49%81% LLWAS +87%76%49% NEXRAD +73% NEXRAD + WSP +97%76% Las Vegas (LAS) Example 2 Sanity check

16. MIT Lincoln Laboratory WindShear-16 JYNC 8/6/2007 Gust-Front P d Examples TDWRWSPNEXRADX bandLidar Single Sensor87%59%50%87%16% Lidar +89%65%56%91% NEXRAD +76% NEXRAD + WSP +79% New Orleans (MSY) Example 1 No P d requirement specified for gust front detection TDWRWSPNEXRADX bandLidar Single Sensor92%67%90%91%16% Lidar +93%71%91%92% NEXRAD +93% NEXRAD + WSP +93% Dallas-Ft. Worth (DFW) Example 2 LLWAS coverage close to nil (~2%) for gust-front study region (18-km radius around airport)

17. MIT Lincoln Laboratory WindShear-17 JYNC 8/6/2007 Summary Developed objective wind-shear detection probability estimation model for radar and lidar –Incorporates sensor performance specs, terrain blockage, site-specific ground clutter (including roads), wind-shear thickness distributions, and site-dependent microburst reflectivity distributions TDWR is still the best single-sensor solution –ASR-9 WSP cannot provide microburst P d ≥ 90% at most airports even after planned upgrade –NEXRAD is too far away at majority of airports to provide adequate coverage Typical LLWAS-RS ARENAs coverage is low (~50%) –Incremental benefit to already existing TDWR/WSP is small Lidar is ideal complement to radar for ARENAs coverage –Affected minimally by ground clutter –Performs best under low dBZ conditions