Observations of ClearAir Boundaries Made By the UMass “Tornado Radar” During the International H 2 O Project (IHOP) Data Summary and Collection Strategy Christopher Weiss & Howard Bluestein University of Oklahoma Norman, Oklahoma

Radar Spec Basics Boresighted camera on dish (calibrated) Operating frequency = 95 GHz ( =3 mm) Beamwidth = 0.18 degrees Three experimental modes for clear-air: ModeClear-1Clear-2Clear-3 Pulse Length110 ns228 ns528 ns Range Resolution15 m30 m75 m

Operations During IHOP_2002 June 9 (dryline) June 10 (dryline) June 3 (cold front) May 22 (dryline) Deployments: 4 rolling RHI 2 stationary RHI 2 VAD 1 vertical antenna X-sect Deployments: 1 stationary RHI Deployments: 2 rolling RHI 2 VAD Deployments: 3 rolling RHI 2 stationary RHI 2 VAD

Data Collection Strategies Mode #1 - VAD Synthesize vertical wind profile from elevated sector scan (~ 220 degrees in azimuth, at 45 degrees elevation) Six VADs performed during IHOP, three on each side of the dryline. 5/22/02 – moist side VAD W

Data Collection Strategies Mode #2 – Vertical Antenna Temporal/spatial profile of vertical velocity Performed on May 22 dryline

Data Collection Strategies Mode #3 – Stationary RHI Five such deployments during IHOP Drawback: No V r decomposition into u/w Vertical sectors perpendicular to feature of interest May 22 - Dryline retrogrades through truck June 9 – Dryline advances past truck

DZ VE W Dryline Retrogression 5/22/02 00:36 UTC (5/23)

DZ VE W Dryline Retrogression 5/22/02 00:37 UTC (5/23)

DZ VE W Dryline Retrogression 5/22/02 00:43 UTC (5/23)

Cold Front 6/3/02 DZ VE NW 19:49 UTC

DZ VE NW Cold Front 6/3/02 19:51 UTC

DZ VE NW Cold Front 6/3/02 19:56 UTC

Data Collection Strategies Mode #4 – Rolling RHI Nine rolling RHIs during IHOP (all across drylines) GPS data critical Use pseudo-dual Doppler principles for u/w decomposition in lobe but…more complicated than airborne technique.

Dryline 5/22/02 00:30 UTC (5/23) W DZ

Dryline 6/10/02 20:00 UTC DZ VE E (uncorrected)

Complications Subtraction of truck velocity is delicate. Accurate GPS position, velocity important Pitch of truck Uncertainty of GPS elevation data Translation and development of feature “Stationarity assumption” Uncertain boundary positions Sensitivity and range Irregular weave pattern (i.e., varying angle of intersection between two radar looks)