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Improving Warm Season QPF with Convection-allowing Models: Results from the 2011 NOAA Hazardous Weather Testbed Spring E

This study evaluates the effectiveness of convection-allowing models in improving warm season Quantitative Precipitation Forecasting (QPF). Experimental guidance, including ensemble forecasts and probabilistic products, were analyzed and compared to operational models. Results show improved QPF accuracy and confidence in using convection-allowing models for forecasting.

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Improving Warm Season QPF with Convection-allowing Models: Results from the 2011 NOAA Hazardous Weather Testbed Spring E

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  1. The Quantitative Precipitation Forecasting Component of the 2011 NOAA Hazardous Weather Testbed Spring Experiment David Novak1, Faye Barthold1,2, Mike Bodner1, Robert Oravec1, Andrew Orrison1, Bruce Sullivan1, Steve Weiss3, Andy Dean3, Israel Jirak3, Chris Melick3, Jack Kain4, Adam Clark4, Fanyou Kong5, Ming Xue5, Patrick Marsh5 , and Tara Jensen6 1NOAA/NWS/Hydrometeorological Prediction Center 2I.M. Systems Group, Inc. 3NOAA/NWS/Storm Prediction Center 4NOAA/National Severe Storms Laboratory 5University of Oklahoma 6Developmental Testbed Center

  2. Nashville: May 1, 2010 Atlanta: Sept. 21, 2009 Motivation Flooding is a leading cause of weather-related deaths Irene: Aug 28, 2011 "Improvements in QPF and mesoscale rainfall prediction need to be a top NWS research and training priority." 2009 SE US Flood Service Assessment 2

  3. QPF Improvement Gap Cool Season Warm Season 3

  4. 2011 Spring Experiment • 3 components (Severe, Initiation, QPF) • 5 week program (May 9 - June 10) • ~60 participants from research, academia, and operations HMT-HPC Leading QPF Component of Hazardous Weather Testbed Spring Experiment since 2010 Partners: SPC, OU, NSSL, DTC, GOES-R QPF Goal: Do convection-allowing models improve warm season QPF? 4

  5. Experimental Guidance

  6. Experimental Ensemble Products Probability matched mean—combines the spatial pattern of the ensemble mean QPF with the frequency distribution of the rainfall rates (Ebert 2001) Bias corrected mean—running 14 day bias correction applied to 6hr QPF Maximum—Maximum from any member Neighborhood probabilities—probability of an event occurring in the vicinity of a point Spaghetti plots—contours outlining selected precipitation amounts 6

  7. Daily QPF Activities • Use experimental guidance to produce 6 hr PQPF • .50” and 1” thresholds • Forecasts valid 18-00Z, 00-06Z, 06-12Z • Subjective verification of previous days forecast • Subjective evaluation of previous days experimental model guidance • Afternoon update of 00-06Z period 7

  8. Deterministic Example Forecast Valid 06Z 24 May 2011 6hr NSSLQ2 QPE valid 06Z 24 May 2011 12 km NAM 6 hr QPF (30 hr forecast) 8

  9. Deterministic Example Forecast Valid 06Z 24 May 2011 6hr NSSLQ2 QPE valid 06Z 24 May 2011 4 km NMMB 6 hr QPF (30 hr forecast) NMMB rated “Much Better” than operational NAM 9

  10. Deterministic Results Subjective Verification DTC Objective Verification 0.50” Threshold NCEP 4 km NMMB NSSL ARW NCEP NMM NCEP 12 km NAM NCEP 12 km NMMB 10

  11. Ensemble Example Forecast Valid 06Z 9 June 2011 6hr NSSLQ2 QPE valid 06Z 9 June 2011 SREF mean 6 hr QPF (30 hr forecast) 11

  12. Ensemble Example Forecast Valid 06Z 9 June 2011 6hr NSSLQ2 QPE valid 06Z 9 June 2011 SSEF mean 6 hr QPF (30 hr forecast) SSEF rated “Much Better” than operational SREF 12

  13. Ensemble Example Forecast Valid 06Z 9 June 2011 6hr NSSLQ2 QPE valid 06Z 9 June 2011 SSEO mean 6 hr QPF (30 hr forecast) SSEO rated “Much Better” than operational SREF 13

  14. Ensemble Results Subjective Verification DTC Objective Verification 0.50” Threshold SSEF SSEO SREF 14

  15. Ensemble Results Subjective Verification—Ensemble Size and Probability Evaluation 15 member ensemble mean not much different than 24 member mean.  But probabilities from small-membership SSEO less effective than full membership SSEF 15

  16. Ensemble Example Forecast Valid 00Z 12 May 2011 SSEF probability of exceeding 0.50”/6 hr (24 hr forecast) SSEO probability of exceeding 0.50”/6 hr (24 hr forecast) 16

  17. Post Processing Results (SSEF) 17

  18. Summary • Convection-allowing guidance can improve warm season QPF • SSEO performance demonstrates that a small membership “poor man’s” ensemble can provide useful QPF guidance The SSEO is now available to HPC forecasters. • Upcoming 4 km NMMB nest consistently produces reasonable precipitation amounts and realistic convective evolutionForecasters have confidence in using the NMMB nest • Raw probabilities and spaghetti plots were favored over more sophisticated visualizationsSpaghetti plots to be available from the SSEO • 2012 Experiment being planned Full 2011 detailed report at: http://www.hpc.ncep.noaa.gov/hmt/2011_SpringExperiment_summary.pdf 18

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