Paul Joe 1 , Tom Keenan 2 , Jian Jie Wang 3 , George Isaac 1* and Dmitri Kiktiv 4

1. Future Nowcasting Systems: Lessons from the WWRP Olympic Nowcasting ProjectsAdvancing nowcasting through research Paul Joe1, Tom Keenan2 , Jian Jie Wang3, George Isaac1* and Dmitri Kiktiv4 Environment Canada1, Centre for Climate and Australian Weather Research (retired) 2, China Meteorological Administration3, Environment Canada (retired) 1, Roshydromet4

2. Outline • Background • The WWRP/WGNR • Nowcastingdefined • The Olympic projects • Lessons Learned • Implications for the development of future nowcasting systems

3. Working Group on Nowcasting Research + experts Paul Joe George Isaac Kazuo Saito Alan Seed Matthias Steiner Brian Golding Yong Wang Slobodan Nickovic Jim Wilson Peter Li* Jeanette Onvlee Estelle de coning Marianne Koenig Augusto Pereira Jian Jie Wang Jenny Sun Rita Roberts Who is wwrp/wgnr?

4. We work with many Partners The Mandate of WWRP Working Groups are… • Advance the science of high impact weather • Promote science and understanding • Capacity Build / Technology Transfer • Strategy documents • White Papers • Specialty Workshops • Symposium Themes • Demonstration / Development Project • Training workshops

5. What is severe weather nowcasting?

6. Nowcasting and Mesoscale Weather Forecasting Research Nowcasting (0-2) and Very Short Range Forecasting (0-12) • Nowcasting are prediction that are precise in time and space (seconds, minutes; meters, kilometers) and weather elements (tornadoes, downbursts) over the 0 to 6 hour time frame. Such systems outperform numerical weather prediction in the first several hours of a forecast. Mesoscale Weather Forecasting/Short Range Forecasting (0-72) • Mesoscale Weather Forecasting Research are at fine resolution over a limited domain on the meso-gamma resolution (~500m – 3km), covering time scales from 0 ~ 48h. Mesoscale prediction systems are driven toward this high resolution because the largest impacts on society tend to be regional or even local in nature. HIWeather Project • THORPEX Legacy, in formulation

7. Nowcast (Anal) >Warning VSRF (Anal+NWP) >Caution SRF(NWP) >Outlook Action for disaster prevention Action for recovery Evacuation Preparation Keep in mind Recovery Stand by Ready to take action Cancel warning Nowcasts are “calls to action” Met. Information Aviation (Convection Avoidance) Local Government / Industry Citizen 1-2 days before 3-6 hours before 1 hour before Is the skill of our forecast fulfilling their needs? High impact weather Event Precip. Intensity Courtesy, Shingo Yamada JMA

8. Pushing the boundaries Why the Olympics?

9. Olympics have futuristic nowcast challengesLeads to “advancements” • Safety of lots of people in specific spaces • Safety of athlete • Fairness of event Impact

10. The Olympic Forecasting RequirementsInternational Olympic Committee Nowcasting Weather is the #1 agenda item in the daily planning meetings!

11. Olympics have specific/quantifiable weather element requirements 2 turns/gates Chris Doyle Summer: heavy rain, wind, hail and lightning

12. x x x x x x Olympics require spatial precision Broad area (40 km), in 6 hour time steps, 1-7days Precise in space (km), time (minutes- hours), wx element Data Models Nowcasting 24 to 96 hours 0 to 6 hours (HIW) Lower Mainland Top of downhill run High/Low of +3/-5 snow will start at 10:20am 60% chance of moderate snow intensity will be 10 cm/h

13. Upslope Diurnal Transition On Sunny Days Drainage Bottom Top Nowcasting is precision in Time, Space and Wx Element Ski Jump up/down slope wind 2 hour of 1 second data Ruping Mo Andrew Teakles

14. Promoting and Advancing Nowcasting Science Forecast Demonstration projectsvsResearch Development Projects

15. Evolution of the Nowcast Science Sydney Beijing Sochi Vancouver Lake Victoria Basin • Sydney 2000 FDP • Demonstrate state of the art and benefits of nowcast systems • Automatic detection of thunderstorm features • Summer Convection • Beijing 2008 FDP+RDP • Focus on blending and extending the temporal range (FDP) • Probabilistic Nowcasting • Real-time Verification • Ensemble mesoscale prediction (RDP) • SNOW-V10 (Vancouver 2010) RDP (FDP) • Winter nowcasting, complex terrain • Multiple Weather Elements (Temperature, Humidity, Visibility) – not just precipitation • FROST14 (Sochi 2014) FDP-RDP • Winter nowcasting, Technology Transfer • High resolution models (1 km and less) • Low res ensembles vs high res deterministic

16. S2K Focus on automated summer convective weather radar processing systems.

17. Cell View to access to data/products Echo Top hail gradient VIL CAPPI’s Time history Automated XSECT

18. Sydney 2000 • The answer is not enough! • Automation is a tool but it is not enough! • The Early Warning Dilemma • Trade-off between lead time vs high Prob of Detection vs low False Alarm Rate! • Need to have diagnostic products to support “answers”.

19. Need a high skill level for “call to action” decision-making! Need to be here for tactical decisions Decay Growth Holy Grail: Focus of nowcasting research Message from Beijing 2008

20. B08 S2K “know the user/know the impact”

21. Probability ProductsConveying uncertainty • Automatic product combined strike probability from TITAN, SWIRLS, CARDS • Tracks used different reflectivity thresholds • Manual product had choice of TITAN thresholds (35, 40, 45dB) and could include tracks based on NIWOT & VDRAS advice How does one validate probability products for severe weather? Statistics vs rare event!

22. Real-time StatisticsQuartile-Quartile Plots manual automatic Ebert/Bally

23. Real-time Verification! Which system is performing the best? Factors: Z-R; Tracking

24. Nowcasting Relative Humidity, etc Site Dependent Mean Absolute Error Nowcast systems outperform NWP out > 6 hours Isaac, Huang Figure Courtesy of Laura Huang and George Isaac

25. Isaac, Huang Mean Absolute Error for different sites and variables / 0.53 Figure Courtesy of Laura Huang and George Isaac / 0.72 / 0.58 INTW – green, LAM 1k – red, LAM 2.5k – dark yellow, REG - blue

26. INTW Nowcasting System is best Legacy: Adopt in operational systems Isaac, Huang INTW – green, LAM 1k – red, LAM 2.5k – dark yellow, REG - blue Figure Courtesy of Laura Huang and George Isaac

27. Deterministic Models (3 best models are shown in red) Tsyrunikov

28. Ensemble Models Tsyrunikov

29. Nowcast Systems Tsyrunikov

30. Visualization is critical for impactful use for Forecasters and End-Users “Very good but with some drop-offs (precip trapped in the mountains). Surprisingly, informative graphics.”

31. Summary

32. Observation gap! Technology gap! 1 minute data Web cams vs Visibility Sensors Clear Air Echoes S2K V10

33. Motherhood: Need to close the skill-predictability gap! • Prediction Improvements • Prediction of impact variables – forecaster, NWP, uMOS, Post-Processing, … • Improvements in boundary layer needed! • Not good enough yet for nowcasting decision requirements!

34. The answer is not enough! Need diagnostic and uncertainty products with for Forecasters and End-Users (Expertise/Trust)

35. Closer engagement with end-users Warnings on diff SWs by BMB Closer engagement with end-users by: • Ingesting user’s needs into the product generation procedure, and shaping the forecast products relevant to special needs • Making action plans together with end users • Establishing the response mechanisms in practice ERO of BJ city BMB example Offices, Bureaus of BJ gov. Same data – Different Users

36. A mile wide/an inch deep vs An inch wide/a mile deep Role of capacity building, training Create a learning environment. Prime with experience. Build Trustwith users for impact.

37. Forecast System of the Future Warning vs non-warning nowcast service? Who delivers?

38. Thank You