Severe Weather Warning Decision Making Research & Development Improvements

1. Severe Weather Warning Decision Making Research & Development Improvements Gregory J. Stumpf CIMMS / University of Oklahoma NWS Meteorological Development Laboratory Decision Assistance Branch Location: National Severe Storms Laboratory, Norman, OK

2. National Severe Storms Laboratory (NSSL)Mission • To enhance the National Oceanic and Atmospheric Administration’s (NOAA) capabilities to provide accurate and timely forecasts and warnings of hazardous weather events. NSSL accomplishes this mission, in partnership with the National Weather Service (NWS), through • a balanced program of research to advance the understanding of weather processes • research to improve forecasting and warning techniques • development of operational applications • and transfer of understanding, techniques, and applications to the NWS. • NSSL is the sole NOAA agency responsible for the R&D of new applications and technology to improve NWS severe weather warning decision making.

3. NWS/MDL in Norman • My former NSSL position was as group manager responsible for the development of severe weather warning decision making applications and algorithms. • In April 2004, I transferred to the NWS Meteorological Development Laboratory Decision Assistance Branch. • My location remained at NSSL in Norman • Act as a liaison to transfer severe weather research and application development at NSSL into NWS operations • Develop experimental warning decision making testbed for new remote-sensing technologies and new multiple-sensor warning applications

4. History • NSSL developed initial suite of single-radar algorithms for the WSR-88D Doppler Radar: • Detection, Diagnosis, and Tracking of storm cells, hail, mesocyclones, tornado vortex signatures.

5. WDSS Sites Legacy WDSS • NSSL designed its legacy Warning Decision Support System (WDSS) in the early 1990s. • Tested throughout the 1990s at various NWS offices nationwide.

6. One hour trend of storm parameters Detects storms and vortices and forecasts their movement. Legacy Warning Decision Support System (WDSS) Probability of tornado and damaging winds from neural network Table ranking the most severe storms Pop-up table alerting of rapidly growing storms Time-height trend information from 130 million data points

7. Legacy WDSS • Early in the project, employed some human factors engineers to help design the DSS. • Funding for the human factors component was cut early in the project.

8. WDSS Proof-of-ConceptTest Objectives • To evaluate the operational utility of new severe weather algorithms and the decision support system display. • To expose NSSL developers and scientists to NWS operations to better understand user requirements. • Feedback surveys designed by the meteorologists (no other disciplines involved) were used to refine the applications.

9. WDSS Implementation • Eventual operational implementation in NWS systems. • The radar algorithms were implemented into the WSR-88D system. • The WDSS concept was implemented as the NWS System for Convective Analysis and Nowcasting (SCAN).

10. NWS Decision Assistance Branch • Mission: • Develop and implement a comprehensive suite of advanced tools covering the full scope of hydro-meteorological phenomena, other hazardous events, and NWS forecaster responsibilities • Along with SCAN: • Flash Flood Monitoring and Prediction (FFMP) • System on AWIPS for Forecasting and Evaluation of Seas and Lakes (SAFESEAS) • Fog Monitor • System for Nowcasting Winter Weather (SNOW) • Fire Weather Monitor and Nowcasting (FIREMAN)

11. But what happened with SCAN? • Although the NSSL WDSS proof-of-concept tests were very favorable, SCAN has become a thorn in the side of the NWS warning program. • SCAN User Feedback indicated that the users preferred not to use the algorithms, but rather base data analysis.

12. Back to NSSL • NSSL addressing many of the limitations of the current algorithm and display design.

13. Warning Decision Support System – Integrated Information (WDSS-II) • Support multiple-radar and multi-sensor data integration • Including multi-office/national CONUS applications. • Develop innovative 4D display tool • Support for algorithm/application developers in the form of an Application Programming Interface (API) • Easy to add new products and concepts • Seamless path from data ingest, processing, and output using standard formats • To improve the pace of science and technology infusion

14. New Severe Weather Algorithm Requirements • Objectives for new warning application development: • Integrate multiple-radar and multiple-sensor information • No longer single-radar specific • Must input highest resolution data in native format • More accuracy in detection and diagnosis (oversampling - more “eyes” looking at storms). • Must have rapid-update capability • Uses virtual volume scan concept • Better lead time (no more waiting until end of volume scan for guidance). • Must be scientifically sound

15. Multiple-Radar 3D Reflectivity Mosaic • Filling the cones-of-silence • Single Radar

16. Multiple-Radar 3D Reflectivity Mosaic • Filling the cones-of-silence • Multiple radars

17. Multiple Sensor Applications Reflectivity @ -20C

18. NSSL Google Earth Products • http://wdssii.nssl.noaa.gov/geotiff/ • Multi-radar reflectivity products (1 km, 5-minute updates) • Multi-radar Doppler velocity products (0.5 km, 2-minute update) • Severe storm analysis products derived from 3D reflectivity fields and environmental data • Products on the web site are either Continental U.S. (CONUS) or broken up by region.

19. Hail Swaths March 12-13 2006 Outbreak Kansas Missouri Illinois Indiana Multiple-Radar Hail Swaths from Google Earth Note “Six-State Supercell”! “Is there a business I can call to verify my warning?” “Where was the greatest likelihood of the largest hail?”

20. “Rotation Tracks” “Where should we send damage survey teams?” “Where do the first responders need to focus on?” “Did it affect Aunt Joan’s house?”

21. The Lemon Technique Four-DimensionalStormcell Investigator (FSI) • Can update X-Section line by dragging reference points • 2D and 3D pictures are linked • Other representations update on-the-fly

22. New Forecast Techniques and Observational Tools • Radar: • Dual-Polarization Radar • Phased-Array Radar • Gap-Filling Radar (mobile and stationary) • Satellite Technology Improvements • 3D Lightning Detection • Multi-Sensor Precipitation Estimation • Warn on Forecast • Instead of Warn On Detection • Uses storm-scale numerical models

23. So, what are we doing with all of this? • And how does this relate to WAS*IS?

24. So, what are we doing with all of this? • NSSL R&D has outpaced NWS technology. • Working to help define new NWS hardware and software to support new applications, products, and concepts of operations. • But new hardware and software costs MONEY, and must be justified in the context of improvements in service and benefit to society. • The NWS is “poor”. • There are challenges dealing with NWS Headquarters culture.

25. So, what are we doing with all of this? • Working to posture ourselves for potential new NWS Concepts of Operations (ConOps). • User feedback workshops: • NWS meteorologists • Users of NWS products (disaster planning exercise) • Testing new applications, products, and services in an national experimental “proving ground”.

26. Future NWSConcept of Operations Enable and Communicate forecaster expertise

27. Enabling Forecaster Expertise • Improve Situational Awareness • Non traditional information • TV, Webcams, Electrical Grid status, road conditions • Gatekeeper or coordinator • Situational Awareness Displays

28. Enabling Forecaster Expertise • Improve Data Integration • Multi-sensor algorithms • Better data visualization • Geographic Information System (GIS)

29. Communicating Forecaster Expertise • Exploit Digital Media • The Internet, cell phone, PDAs, vehicle “On-Star”, etc. • Improve collaboration tools • With other NWS and private sector meteorologists • With “community gatekeepers” • Geo-reference Information and Expertise • Enable users’ decision making • Improvements to severe weather warning products • Improved threat ID and tracking • Smaller time and space scales • Expressing forecaster uncertainty (probabilities)

30. Probabilistic Threat Information

31. >50% >25% >10% >0% Probabilistic Threat Information SEVERE THUNDERSTORM WARNING These data are digital!

32. “Warn On Forecast” • Advances and research and technology are fostering probabilistic forecasts across the spectrum of time and space scales. • Now: Warnings based on detection • Future: Warnings based on forecast

33. Will the public understand probabilistic warnings? • How do we define “the public” (or publics)? • What about the “community gatekeepers”? • Any high-resolution grid can be aggregated to simpler and simpler formats… • …but not the other way around! • A perfect opportunity for societal impact studies! • As well as user workload studies.

34. 1st Severe Tech Workshop • 12–14 July 2005, NWS Headquarters, Silver Spring, MD • Sponsors: MDL/Decision Assistance Branch; Warning Decision Training Branch • Google “MDL severe workshop” • Attendees • Primary User Audience: WFO meteorologists • Scientists and developers (NSSL, MDL, NCAR, NESDIS, NASA, GSD) • NWS and Region Headquarters management and requirements group representatives • Objectives • To review the “state of the science and technology” of NWS severe weather warning assistance tools. • To identify gaps in the present methodologies and technologies • To gain expert feedback from the field (including “stories” from the front lines) • To discuss the near-term and long-term future trends in R&D • For field forecasters and R&D scientists to help pave the direction for new technological advances. • To improve severe weather warning services to users.

35. Workshop Survey Results • Areas of Desired improvements: • Higher resolution observational data on temporal and spatial scale of severe convection • More dedicated time, resources, and infrastructure for improved training • Improvements in base data displays that allow more effective navigation in both space (2D and 3D) and time (4D) • Faster and more dependable software and hardware • Improved algorithm guidance information • Better decision support tools • Improved software interface design • New tools to monitor situation awareness • New product formats that allow for better conveying uncertainty in warning decisions • More effective warning communication • Better measures of public service and verification improvements • Improved leadership skills and workload management • More research into forecast problems and better guidance • Better capabilities to merge geographic information into operations • Faster implementation of technological improvement

36. 2nd Severe Tech Workshop • Fall 2006 (tentative) • Attendees • In addition to the type at workshop #1 • Users from various sectors (private, EM, etc)?

37. National Weather Center (NWC) Hazardous Weather Testbed (HWT)Research Transition to Operations (RTO)

38. Experimental Warning Program (EWP) • Traditionally has been an NSSL-Storm Prediction Center (SPC) activity (the SPC “Spring Program”) • Spinning up a National warning-scale component this year, to be known as the “Experimental Warning Program” (EWP) at Norman, OK – National Weather Center (NWC) • NSSL • Norman Weather Forecast Office (WFO) • SPC • MDL • Warning Decision Training Branch (WDTB) • Visiting forecasters, scientists, etc. • Collaboration with other disciplines, emergency management, private industry, etc.

39. Norman is unique • Sensor-rich. A few unique ones: • Phased Array Radar • Polarimetric radar • Gap-filling radars • 3D Lightning Mapping Array • Mesonet • National-scale applications run locally (models, WDSSII) • Large community of researchers, operational meteorologists, students, industry • Meteorology also intersects with other disciplines • Lots of visiting meteorologists (WDTB, visiting scientists, etc.)

40. Some Initial Objectives • Capability to emulate the warning operations for any location in the Continental U.S. (CONUS). • Evaluation of new warning guidance applications and displays that integrate data from multiple sensors (both operational and experimental) and numerical models (including “warn-on-forecast”) • Development and evaluation of new warning dissemination techniques (e.g., probabilistic warning grids) • Development of methods to significantly improve warning verification tasks and improve the climate record of hazardous weather events • Create advanced Geographic Information System information for utilization in emergency management response to disasters (WxGIS) • Testing the operational utility of new meteorological sensors.

41. Primary Goalsand Challenges • Collaboration between researchers and operational forecasters • 0-2 hour forecasts/warnings • Post-event response • Forecasters benefit from the latest research tools • Researchers gain valuable insight into operational forecasters’ needs • The EWP is mostly unfunded! • Looking for collaborations for socio/econ wx projects that benefit NWS and society.

42. Questions? Email: Greg.Stumpf@noaa.gov NWS Meteorological Development Laboratory Decision Assistance Branch http://www.nws.noaa.gov/mdl/dab/decisionassistbr.htm