1 / 17

Probabilistic Hazard Information for Severe Weather Threats

Probabilistic Hazard Information for Severe Weather Threats. Advanced WAS*IS Workshop Beyond Storm Warnings: A collaboration between stakeholders, the National Weather Service, and the Hazardous Weather Testbed September 15-17, 2008. 2 of 5.

jgallo
Download Presentation

Probabilistic Hazard Information for Severe Weather Threats

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Probabilistic Hazard Information for Severe Weather Threats Advanced WAS*IS Workshop Beyond Storm Warnings: A collaboration between stakeholders, the National Weather Service, and the Hazardous Weather Testbed September 15-17, 2008

  2. 2 of 5 Warn on Forecast in 2020: What might it look like? Radar and Initial Forecast at 2100 CST Radar at 2130 CST: Accurate Forecast Probabilistic tornado warning: Forecast looks on track, storm circulation (hook echo) is tracking along centerline of highest tornadic probabilities An ensemble of storm-scale NWP models predict the path of a potentially tornadic supercell during the next 1 hour. The ensemble is used to create a probabilistic tornado warning. Most Likely Tornado Path Most Likely Tornado Path Developing thunderstorm 30% 30% 50% 50% 70% 70% T=2200 CST T=2200 CST T=2150 T=2150 T=2140 T=2140 T=2130 T=2130 T=2120 CST T=2120 CST Courtesy Lou Wicker, NSSL NSSL Warn on Forecast Briefing March 5, 2007

  3. The Vision: The future evolution of warning decision-making science “Warn on detection” (deterministic) Forecaster-based uncertainty NWP “Warn on forecast” Blended statistics NWP WRF storm typing Statistics-based uncertainty Storm-scale NWP EnKF analysis / storm typing Present 2010 (± 2 yr) 2017 (± 5 yr) 2025 (± 10 yr) WSR-88D Dual-Polarization Radar CASA Phased Array Radar Existing storms Newly initiated convection Forecast convection (doesn’t yet exist)

  4. The Vision: The future evolution of warning decision-making science Statistics / storm-scale analysis / threat identification Data assimilation / NWP “Warn on detection” (deterministic) Forecaster-based uncertainty NWP “Warn on forecast” Blended statistics NWP WRF storm typing Statistics-based uncertainty Storm-scale NWP EnKF analysis / storm typing Present 2010 (± 2 yr) 2017 (± 5 yr) 2025 (± 10 yr) WSR-88D Dual-Pol / CASA Phased Array Radar Existing storms Newly initiated convection Forecast convection (doesn’t yet exist)

  5. Initial State

  6. Probabilistic Warning Information

  7. Additional Probabilistic Information

  8. Initial threat area 30 min. threat probability 1 hr threat swath (accum) Est. time of arrival Probabilistic Warning Guidance • Bridge to Warn On Forecast • High resolution in space and time • Goal: Improve decision support for high impact weather hazards. • Initially convective hazards

  9. Two ways to improve storm lead time • Continuously updating warning grids (~ 5 minute updates – same scale as weather obervations) • Probabilistic information  longer lead times, but great uncertainty

  10. “Point Warnings” for everyone • “Advecting warning grid” moves with the threat • Greater lead time for most users • Goal: compare lead times with actual NWS warnings • Probabilities provide uncertainty information • Even greater lead time for advanced users • Information supplied before threat becomes severe. • NWS Next-Generation Warning Tool

  11. Current storm-based warning system A B Person “A” gets 45 minutes lead time… A B …while person “B” gets only 5 minutes

  12. Automatically translating warnings Warning automatically translates downstream based on storm motion until adjusted or cancelled A B Both “A” and “B” get roughly the same lead time

  13. Probabilistic output at a point • For each grid point in the warning, the intersection of the threat area over time provides time of arrival and time of departure information, and probabilities of the event. 1 Warn? 0 A B Time 

  14. Sociology of Probabilistic Warnings Risk = Hazard * Exposure * Response Time • The NWS cannot anticipate everyone’s exposure and response time • The NWS can make hazard warnings more adaptable to those that do know their own exposure and response time • Adaptive warnings allow users to set their threshold criteria • Any high resolution grid (space and time) can be aggregated into simpler and simpler formats across all levels of sophistication e.g., Tornado, wind, hail, hazardous materials How to account for this?

  15. “Advecting Warning Grid” • Provides additional downstream lead time versus “storm based” / “polygon” warning • Removes warning from area where threat has passed. Area where threat no longer exists Downstream points with additional lead time NWS Warning Strong Mesocyclone

  16. Output probabilities: other information • Threat area at T = + 15 minutes (other times are available) • Projected “Time of Arrival” for points in the warning

More Related