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SCOS97-NARSTO Upper-Air Meteorological Data Wind / RASS Profiler Processing / Objective QC PowerPoint Presentation
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SCOS97-NARSTO Upper-Air Meteorological Data Wind / RASS Profiler Processing / Objective QC

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SCOS97-NARSTO Upper-Air Meteorological Data Wind / RASS Profiler Processing / Objective QC

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  1. SCOS97-NARSTOUpper-Air Meteorological DataWind / RASS ProfilerProcessing / Objective QC Bob WeberNOAA/ETLBoulder, Colorado Rip Off of Robert Baxter

  2. Wind / RASS ProfilerData CollectionJune - October 1997 • 26 Sites ARB VCAPCD SCAQM SDAPCD USAF STI NOAA • SOP Real-Time Meteorological Products Quality Control Radar Doppler Spectral Moments Post Processing / Quality Control Radar Doppler Spectra Post Processing / Quality Control

  3. On-Line Real-TimeMeteorological Products • First Look Winds and Temperatures • Radar Diagnostics • Incomplete Processing • Inadequate Quality Control • Unreliable for Critical Applications • Requires Post Analysis

  4. Wind / RASS ProfilerOperations /Data Collection Radar Spectral Moments • Multiple Antenna Beams (3 - 5) • Time Sampling ~ 1 Minute • Spatial Sampling ~ 50-100 Meters • Doppler Velocity Spectral Signal Strength Spectral Signal Doppler Broadening

  5. Wind / RASS ProfilerPost Processing /Quality Control Hourly / Daily • Contamination Rejection Noise, RFI, birds, ground clutter ... • Objective Quality Control Time-Height Consistency  Hourly-Averaged Radar Spectral Moments  Meteorological Products

  6. Site Locations

  7. Time-Height Consistency Objective Analysis Compare Data with Interpolated Value using neighbors in time and in height Quality Control  Recognize Patterns of Continuous Data over time and over height (hourly, daily)

  8. “Met 0” hourly QC > hourly average > daily QC > Correct Vertical Motion > Met Products “Met 1” * Correct Vertical Motion > hourly QC > hourly average > daily QC > Met Products  Meteorological Noise, Radar Signal Contamination ? - choose higher objective QC value - choose neither - use other subjective criteria Objective / Subjective

  9. Small-Scale Motion Precipitation, Convection, Waves, Fronts, … Complex Terrain Land-Sea, Mountains, Land Use, … Adverse Effects on Performance Wind/RASS Profiler Models Meteorological Noise

  10. Pacific Standard Time Correction for Antenna Orientation Merged High and Low modes QC Codes Final Data Set

  11. QC = 0 valid = 5 missing = 6 erroneous ( > 1 m/s or 10%, 1 Deg C ) = 7 suspect ( Objective QC ) = 8 invalid ( Objective QC ) = 9 no data QC Codes

  12. 1:00 Jim Pederson (ARB) Characterization of Upper Air Meteorology Conditions on IOP Days 1:15 Clinton MacDonald (STI) STI Analysis of 1997 Upper Air Met Data in SoCAB 1:30 Bob Weber (NOAA) Interpreting Data from a RWP/RASS Network 1:15 Bob Baxter (Parsons) Quality Assurance of Upper Air Met Data 2:20 to 2:30 Refreshment break for ten minutes 2:30 Clinton MacDonald (STI) Spatial and Temporal Observations of the Planetary Boundary Layer During Ozone Episodes in Southern California 2:50 Robert Bornstein (SJSU) The 4-7 August SCOS97 Ozone Episode: Comparisons between Observations and MM5 Simulations 3:15 to 3:20 Refreshment Break 3:20 Clinton MacDonald (STI) Moderator-Roundtable on Use of Aloft Meteorological Data: Lidar, Radar Wind Profiler Radio Acoustic Sounding Networks, Sodar Networks (60M) 4:20 Session III Concludes SCOS97-NARSTOData Analysis Conference13 February, 2001 Day 1-1:00 to 4:20 pmSession III: Upper Air & Other Meteorological Data

  13. Measure Winds ???? 1.3-1.7 m/s Clear Air co-located wind profilers (Strauch et al., 1987) 2-4 m/s Precipitation co-located wind profilers (Wuertz et al., 1988) 2.5 m/s 2 years wind profiler / rawinsonde (Weber & Wuertz, 1989) 3.1 m/s co-located rawinsondes (Hoehne, 1980)