1. 1 Where the Rubber Meets the Road: Testbed Experiences of the Hydrometeorological Prediction Center David Novak 1, Faye Barthold 2, Mike Bodner 1, and Ed Danaher 1 1 NOAA/NWS/HPC 2 I.M. Systems Group

2. 2 NCEP Test Beds HPC – Hydrometeorological Test BedHPC – Hydrometeorological Test Bed EMC – Developmental Test BedEMC – Developmental Test Bed AWC – Aviation Weather Test BedAWC – Aviation Weather Test Bed SPC – Hazardous Weather Test BedSPC – Hazardous Weather Test Bed NHC – Joint Hurricane Test BedNHC – Joint Hurricane Test Bed CPC – Climate Test BedCPC – Climate Test Bed OPC – Ocean Test BedOPC – Ocean Test Bed SPWC – Space Weather Test BedSPWC – Space Weather Test Bed

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

4. HMT – HPC 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 Description A component of the NOAA HMT NOAA HMT NOAA Labs Academics HPC RFCs WFOs HMT-HPC Testbed RESEARCHOPERATIONS R2O O2R

5. Real-Time Collaborative Experiments 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 Test New Datasets

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

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

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

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

10. Example Experiment Results

11. Forecast team’s confidence was qualitatively correlated to snowfall errors Example Experiment Results Transferring into operations

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

13. 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 visualizations Spaghetti plots to be available from the SSEO Full 2011 detailed report at: http://www.hpc.ncep.noaa.gov/hmt/2011_SpringExperiment_summary.pdf Operational Impacts Warm Season QPF

14. 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 Operational Impacts Winter Weather Use caution in applying convection-allowing guidance Full 2011 detailed report at: http://www.hpc.ncep.noaa.gov/hmt/HMT_HPC_WWE_Summary_Final.pdf

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

16. 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 Operational Impacts People

17. 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. Summary