Where the Rubber Meets the Road:

1. Where the Rubber Meets the Road: Testbed Experiences of the Hydrometeorological Prediction Center David Novak1, Faye Barthold2, Mike Bodner1, and Ed Danaher1 1NOAA/NWS/HPC 2I.M. Systems Group

2. NCEP Test Beds • HPC – Hydrometeorological Test Bed • EMC – Developmental Test Bed • AWC – Aviation Weather Test Bed • SPC – Hazardous Weather Test Bed • NHC – Joint Hurricane Test Bed • CPC – Climate Test Bed • OPC – Ocean Test Bed • SPWC – Space Weather Test Bed

3. Success Criteria “Is data/technique feasible for operations?” • Benefit: expected improvement in operational forecast and/or analysis accuracy • Efficiency: adherence to forecaster time constraints and ease of use needs • Compatibility: IT compatibility with operational hardware, software, data, communications, etc. • Sustainability: availability of resources to operate, upgrade, and/or provide support

4. HMT – HPC Description A component of the NOAA HMT Goal: Transfer science and technology innovations into operations to improve and extend prediction of heavy precipitation Roles: • Identify and test new datasets to improve HPC forecasts • Develop forecaster-relevant tools/techniques • Provide training in new techniques to forecasters & researchers RESEARCH R2O O2R OPERATIONS NOAA HMT NOAA Labs Academics HPC RFCs WFOs HMT-HPC Testbed

5. Focus and Methods • Focus: Improve and extend prediction of heavy precipitation • Approach: • Improve understanding of heavy precipitation phenomena • Improve application of high-resolution and ensemble guidance Develop New Tools/Techniques Train Forecasters & Researchers Real-Time Collaborative Experiments Test New Datasets

6. Experiments • QPF Component of Spring Experiment • Focus:Warm-season convection • Datasets:Convection-allowing deterministic and ensemble guidance • Lead Time:0-36 hours Snow • Winter Weather Experiment • Focus:Assess & communicate uncertainty • Datasets:Convection-allowing deterministic and ensemble guidance • Lead Time:36-72 hours Sleet • Atmospheric Rivers Experiment (Fall 2012) • Focus: Precipitation amounts and timing • Datasets:High-res models and reforecasts • Lead Time:1-7 days

7. Experiment Format • Mix of operational forecasters and researchers • Challenged to make real-time forecasts with experimental data/techniques • Multiple week participation Forum for researcher –forecaster interaction & driving forecaster-relevant development

8. Recent Experiment Focuses How can the forecaster add value to probabilistic forecasts? How can convection-allowing model guidance be used with traditional guidance? How can ensemble guidance be more effectively used and visualized? What are effective means to communicate uncertainty?

9. Example Experiment Results Objective and subjective feedback provided directly to developers

10. Example Experiment Results

11. Example Experiment Results Forecast team’s confidence was qualitatively correlated to snowfall errors Transferring into operations MODEL DIAGNOSTIC DISCUSSION 225 AM EDT FRI OCT 28 2011 ...PREFERENCE: 00Z ECMWF/00Z GFS/00Z NAM/21Z SREF MEAN COMPROMISE WITH ABOVE AVERAGE CONFIDENCE

12. Operational Impacts • Warm Season QPF • Winter Weather • NWP • People

13. Operational Impacts Warm Season QPF • Convection-allowing guidance may be transformational for warm-season QPF • Demonstration that a small membership “poor man’s” ensemble can provide useful QPF guidance The SSEO is now available to HPC forecasters. • NAM Nest consistently produces reasonable precipitation amounts and realistic convective evolution • Forecasters have confidence in using the NAM Nest • Raw probabilities and spaghetti plots were favored over more sophisticated visualizationsSpaghetti plots to be available from the SSEO Full 2011 detailed report at: http://www.hpc.ncep.noaa.gov/hmt/2011_SpringExperiment_summary.pdf

14. Operational Impacts Winter Weather Use caution in applying convection-allowing guidance • Strengths: Depiction of topographic features and unique visualizations • Simulated reflectivity now available to forecasters • Weaknesses: Generally only NAM Nest snowfall amounts were as good as operational NAM amounts. • Increased confidence in using NAM Nest • Decreased confidence in High-Res Windows during cool season • There is a forecaster confidence – skill relationship • Include confidence information in HPC discussions Full 2011 detailed report at: http://www.hpc.ncep.noaa.gov/hmt/HMT_HPC_WWE_Summary_Final.pdf

15. Operational Impacts NWP Snow Sleet Demonstrating the value of convection-allowing guidance. Prototyping “poor man’s” operational approaches Motivating the development of improved NAM/GFS microphysics and LSMs Diagnosing model errors Fixed before implementation

16. Operational Impacts People • Create excitement by exposing forecasters & researchers to cutting-edge data • Staff view experiment participation as a reward (UCAR Review) • Fosters innovation • A “sandbox” to play in • Builds trust between researchers, developers, and forecasters • Catalyst for collaborative relationships

17. Summary • Operations sets a high bar. Candidate data must be: • Beneficial • Efficient • IT compatible • Sustainable • HMT-HPC Testbed established to improve and extend prediction of heavy precipitation. Embedded with HPC operations. • Spring, Winter, and Atmospheric River Experiments benefiting operations.