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Outline• Challenges in radar precipitation estimation• New techniques in automated QPE• QPE SUMS technique description• QPE SUMS case results• Algorithm evaluation efforts• Latest improvements and diagnostic products
Quantitative PrecipitationEstimation (QPE) by Radar• Reflectivity to Rainfall Conversion Problems Drop size distributions Mass flux• Sampling Problems Anomalous propagation Ground clutter Beam overshooting Mixed-phase sampling Hail contamination Bright band contamination
Page 1: Towards Improvements in QPEfor Flas
Page 5 and 6: “Mass Flux” Impactsfrom Dotzek
Page 7 and 8: Ground Clutter• Results from rada
Page 9 and 10: Beam Overshooting/Mixed-Phase Sampl
Page 11 and 12: And the Result is…• Overestimat
Page 13 and 14: 5. Multisensor QPEA little history
Page 15 and 16: Modules in Polar Coordinates• Rad
Page 17 and 18: AP and GC removal(Phoenix, AZ)befor
Page 19 and 20: Conv/Strat Segregation• dBZ > 50
Page 21 and 22: Bright Band Identification(BBID)•
Page 23 and 24: Comparisons of BBID withVertically-
Page 25 and 26: Radar Sampling ofPrecipitation Type
Page 27 and 28: Generate Polar Products(Text, Nids,
Page 29 and 30: CartesianModules in CartesianCoordi
Page 31 and 32: Determination of PrecipitationPhase
Page 33 and 34: Generating Multisensor FieldRegress
Page 35 and 36: QPE SUMS Product Generation• 3 di
Page 37: Evaluation Efforts• Case study ap
Page 42 and 43: CentennialWashPhoenix RadarYuma Rad
Page 44 and 45: QPESUMS Radar Only -Storm Total Pre
Page 46 and 47: Gauge Comparison:Storm Total Statis
Page 48 and 49: 6-Month Statistics in OKDomain: Bia
Page 50 and 51: MultisensorRadar-OnlyRMS Error
Page 52 and 53:
Latest Improvements andDiagnostic P
Page 54 and 55:
Radar Calibration Differences
Page 56 and 57:
KIWA Hybrid ScanAfterBefore
Page 58:
Questions???gourley@ou.edu
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