The Quantitative Precipitation Forecasting Component of the 2011 NOAA Hazardous Weather Testbed Spring Experiment David Novak 1, Faye Barthold 1,2, Mike Bodner 1, Robert Oravec 1, Andrew Orrison 1, Bruce Sullivan 1, Steve Weiss 3, Andy Dean 3, Israel Jirak 3, Chris Melick 3, Jack Kain 4, Adam Clark 4, Fanyou Kong 5, Ming Xue 5, Patrick Marsh 5, and Tara Jensen 6 1 NOAA/NWS/Hydrometeorological Prediction Center 2 I.M. Systems Group, Inc. 3 NOAA/NWS/Storm Prediction Center 4 NOAA/National Severe Storms Laboratory 5 University of Oklahoma 6 Developmental Testbed Center

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

3 QPF Improvement Gap Cool Season Warm Season

Spring Experiment 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? 3 components (Severe, Initiation, QPF) 5 week program (May 9 - June 10) ~60 participants from research, academia, and operations

Experimental Guidance ProviderModelDelta XNotesLabel CAPS WRF/ARPS 24 member ensemble 4 km Multi-model, multi-physics, multi-IC ensemble system with radar assimilation SSEF SPC WRF/NMMB 7 member ensemble 4 km Combination of available high resolution deterministic runs SSEO EMCNMMB 4 km and 12 km Pre-implementation version of the NAMNMMB NSSLWRF-ARW4 kmNAM initial and boundary conditions NSSL WRF-ARW EMCWRF-NMM4 kmNAM initial and boundary conditions NCEP HRW-NMM EMCWRF-ARW5.1 kmNAM initial and boundary conditions NCEP HRW-ARW GSDHRRR3 kmHourly updating with radar assimilationHRRR MDLHRMOS4 kmGFS-based statistical regressionHRMOS

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

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 Daily QPF Activities 7

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

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

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

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

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

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

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

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

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 Ensemble Example

Post Processing Results (SSEF) 17

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 evolution Forecasters have confidence in using the NMMB nest Raw probabilities and spaghetti plots were favored over more sophisticated visualizations Spaghetti plots to be available from the SSEO 2012 Experiment being planned Full 2011 detailed report at: 18