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A successful integrated convective warning system:

A successful integrated convective warning system:. Presented by Jim LaDue Warning Decision Training Branch Norman, Oklahoma. Workshop in Österreich – The integrated warning system 20-23 May 2003. Objective.

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A successful integrated convective warning system:

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  1. A successful integrated convective warning system: Presented by Jim LaDue Warning Decision Training Branch Norman, Oklahoma Workshop in Österreich – The integrated warning system 20-23 May 2003 Warning decision making – Austria 2003

  2. Objective To share our experiences with what makes an effective warning system Warning decision making – Austria 2003

  3. An integrated warning system • A research program for science, technology, human factors • Rapidly updating stream of information about storms and their environment from radar, satellite, point observations, model information, and spotters • An office with an effective warning operations plan to help forecasters maintain situational awareness • Knowledgeable forecasters in the science, technology and human factors recognize the threats and issue timely watches, warnings and updates • Multiple and redundant methods of communicating warnings to the media, emergency preparedness community and the general public • A public knowledgeable in using the watches and warnings to protect life and property • Post-mortem on events to review mistakes Warning decision making – Austria 2003

  4. Overview • Intro to the warning program • Pre-event products • Warnings and statements • The information flow • Radar, spotters, environment • Situational awareness • Warning Operations – maximizing SA • Office strategies • Individual storm assessment strategies • Maintaining proficiency • training • Learning from past mistakes Warning decision making – Austria 2003

  5. Pre-event awareness The Storm Prediction Center (SPC) issues outlooks from 1 to 3 days before the event The Norman Weather Forecast Office translates the SPC products to enhance public awareness of the risks Warning decision making – Austria 2003

  6. An example SPC outlook These outlooks are intended for forecasters -9 hr -6 hr -3 hr -0 hr +3hr Warning decision making – Austria 2003

  7. An example WFO hazardous weather outlook THUNDERSTORM OUTLOOK NATIONAL WEATHER SERVICE NORMAN OK 1230 PM CDT MON MAY 3 1999 THERE IS A MODERATE RISK OF SEVERE THUNDERSTORMS OVER THE WESTERN HALF OF OKLAHOMA AND WESTERN NORTH TEXAS LATER THIS AFTERNOON THROUGH TONIGHT. THE RISK AREA IS EAST OF A HOLLIS TO BUFFALO LINE AND WEST OF U.S.HIGHWAY 177. AREAS OF CENTRAL AND SOUTHEAST OKLAHOMA EAST OF HIGHWAY 177 ARE IN A SLIGHT RISK. DISCUSSION... (stuff deleted) WIND SHEAR IN THE ATMOSPHERE IS EXPECTED TO BE FAVORABLE FOR STORM ORGANIZATION AND SOME SUPERCELL THUNDERSTORMS ARE LIKELY. ALTHOUGH HAIL AND DAMAGING WINDS ARE THE MAIN SEVERE WEATHER THREATS...THE COMBINATION OF MODERATE INSTABILITY AND MODERATELY STRONG WIND FIELDS SUGGEST THAT ISOLATED TORNADOES ARE ALSO POSSIBLE INTO THE MID-EVENING. AS THE THUNDERSTORMS ORGANIZE INTO A SQUALL LINE LATER THIS EVENING...THE MAIN SEVERE THREATS WILL BE HAIL AND STRONG WINDS. EMERGENCY MANAGERS AND SPOTTER GROUPS ACROSS CENTRAL AND WESTERN OKLAHOMA AND WESTERN NORTH TEXAS SHOULD BE PREPARED FOR POSSIBLE ACTIVATION LATER THIS AFTERNOON AND THROUGH THE EVENING. Location of the moderate risk in Norman’s area Weather discussion Call to action Warning decision making – Austria 2003

  8. SPC watch – Threat imminent Issued before storms mature Valid for 6 hrs Local offices disseminate which counties are included in the watch Spotters are activated -9 hr -6 hr -3 hr -0 hr +3hr Warning decision making – Austria 2003

  9. -9 hr -6 hr -3 hr -0 hr +3hr Warning Operations • Severe Tstm • >2cm hail • >25 m/s • Valid 1 hr • Tornado • Radar/spotter indications • Valid <1hr • Flash flood • Life threatening flood • Spotter reports • Valid >2 hr Warning decision making – Austria 2003

  10. -9 hr -6 hr -3 hr -0 hr +3hr Warning Operations Warning decision making – Austria 2003

  11. Warning geometry • The warning is drafted with latitude/longitude vertices Warning decision making – Austria 2003

  12. Warning geometry BULLETIN - IMMEDIATE BROADCAST REQUESTED SEVERE THUNDERSTORM WARNING NATIONAL WEATHER SERVICE NORMAN OK 415 PM CDT MON MAY 3 1999 THE NATIONAL WEATHER SERVICE IN NORMAN HAS ISSUED A * SEVERE THUNDERSTORM WARNING FOR... COMANCHE COUNTY IN SOUTHWEST OKLAHOMA * UNTIL 500 PM CDT * AT 415 PM CDT...DOPPLER RADAR INDICATED A SEVERE THUNDERSTORM 3 MILES SOUTHWEST OF LAWTON...MOVING NORTHEAST AT 30 MPH. * LOCATIONS IN THE WARNING INCLUDE CACHE...ELGIN...FLETCHER…FORT ILL...GERONIMO...LAWTON...MEDICINE PARK...MEERS AND STERLING HAIL UP TO THE SIZE OF QUARTERS AND WIND GUSTS TO AT LEAST 60 MPH ARE LIKELY. LAT...LON 3454 9868 3447 9842 3454 9817 3485 9810 3483 9862 Warning decision making – Austria 2003

  13. Warning geometry • Most users refer to the political boundaries for which the warning has been issued • The body of the warning specify which towns are in the path • And expected wind and hail size • All warnings are tone alerted on weather radio Warning decision making – Austria 2003

  14. Warning geometry • The warning is followed by severe weather statements describing the progress of the warning SEVERE WEATHER STATEMENT NATIONAL WEATHER SERVICE NORMAN OK 421 PM CDT MON MAY 3 1999 AT 420 PM QUARTER SIZE HAIL WAS REPORTED IN LAWTON. A SEVERE THUNDERSTORM WARNING REMAINS IN EFFECT FOR COMANCHE COUNTY UNTIL 5 PM. LAT...LON 3454 9868 3447 9842 3454 9817 3485 9810 3483 9862 Warning decision making – Austria 2003

  15. Experimental warning products Significant weather advisory or pre-warning Warning decision making – Austria 2003

  16. Experimental Warning Products WARNING DECISION UPDATE NATIONAL WEATHER SERVICE NORMAN OK 345 PM CDT THU MAY 8 2003 THIS WARNING DECISION UPDATE CONCERNS SOUTHWEST AND CENTRAL OKLAHOMA. NORTHEAST COMANCHE COUNTY STORM IS STRENGTHENING AND POLARIMENTRIC RADAR DATA (ZDR) FROM NSSL SUGGESTS LIQUID WATER ABOVE FREEZING LEVEL INDICATIVE OF STRENGTHENING UPDRAFT. NOW LOOKING CAREFULLY FOR COLUMN OF HIGH Z (>50 DBZ) BETWEEN 15-30 KFT. THIS MAY BE AN INCIPIENT SUPERCELL. NOTE: THIS IS AN EXPERIMENTAL PRODUCT MEANT TO INCREASE INFORMATION EXCHANGE ON THE STORM SCALE. Warning decision making – Austria 2003

  17. Local Storm Reports • Required to relay all incoming storm reports immediately LOCAL STORM REPORT NATIONAL WEATHER SERVICE NORMAN OK 1025 AM CDT WED MAY 07 2003 TIME (CDT) .....CITY LOCATION.....STATE ...EVENT/REMARKS... ....COUNTY LOCATION.... 1040 PM 5 E STRINGTOWN OK .88 INCH HAIL 05/06/03 ATOKA PUBLIC REPORTED HAIL COVERED THE GROUND. Warning decision making – Austria 2003

  18. Other Warning operations tasks • Relay all warnings on the National Warning System (NAWAS) • All products are related out to spotters via amateur radio networks • Some offices also relay warnings out via pager services • Emergency managers in populated areas receive personal phone calls from NWS personel when warnings are issued • Some offices use instant messaging to describe their thought processes to selected customers Warning decision making – Austria 2003

  19. Data input Point soundings Surface data Yea Nay Lightning Radar Model ? Data ? Guidance ? (yours) Radar Data (others) Satellite Radar Data (others) Updated Probing Spotter Mesoscale Calls Reports Analysis Warning decision making – Austria 2003

  20. Radar data The most important input tool for short term warnings. Warning decision making – Austria 2003

  21. Influence of spotter reports on warnings • Warning frequency is strongly correlated to the number of reports • Therefore, spotters are the second most important input in warning decision making • Consider this example from St. Louis • Carroll et al. 2002 - Research Experiences for Undergraduates program at OU Warning decision making – Austria 2003

  22. St. Louis CWA Population Density People per km2 Warning decision making – Austria 2003

  23. Events per 1,000 km2 Events per 1,000 km2 Warning decision making – Austria 2003

  24. Warnings per 1,000 km2 Warnings per 1,000 km2 Warning decision making – Austria 2003 Carroll et al., 2002

  25. The Norman WFO amateur radio liaison network A ham radio operator at the NWS OUN office relays the latest warnings and storm updates out to one of three networks WX5OUN Dennis McCarthy – KC5EVH Warning decision making – Austria 2003

  26. The Norman WFO amateur radio liaison network Managers of repeater networks coordinate radio traffic between the NWS and local spotter networks, the media and emergency managers. SWIRA WX5OUN Example: The Southwest Independent Repeater Association (SWIRA) is managed by Terry Mahorney KB5LLI Warning decision making – Austria 2003

  27. The Norman WFO amateur radio liaison network Managers of repeater networks coordinate radio traffic between the NWS and local spotter networks, the media and emergency managers. SWIRA WX5OUN Example: The Southwest Independent Repeater Association (SWIRA) is managed by Terry Mahorney KB5LLI Warning decision making – Austria 2003

  28. The Norman WFO amateur radio liaison network SWIRA WX5OUN Chasers receive the NWS update, and may respond back with reports directly to the repeater or to a local spotter group The local spotter net controller relays spotter reports through the liaison network 146.79 Altus Warning decision making – Austria 2003

  29. The Norman WFO amateur radio liaison network Media stormchasers and helicopter pilots relay their observations back to their stations. These reports are fed back to the NWS via TV broadcasts, and by amateur radio. Other chasers/spotters listen in on these reports too. WX5OUN 146.79 Altus Warning decision making – Austria 2003

  30. The Norman WFO amateur radio liaison network Acknowledged contributors EM Rick Smith, WCM – NWS OUN Terry Mahorney KB5LLI SWIRA Andy Wallace, Lawton KC5GHH Ch 7 Lawton Charlie Byers SPS EM Robert Moose 'Moose' Ch4 OKC NBC Jay Kruckenberg, Woodward Mike Honigsburg, Garfield CO EM Putnam Ryder KC5GVD OK state EM office OKC Gayland Kitch, KC5MMU Moore EM Brent Myers, WA5NWS, Chillocothe, TX Police Herb Gunther, Seminole CO EM Dave Ewoldt EM EM EM EM EM EM Warning decision making – Austria 2003

  31. Where media assists the NWS Get to the video! Realtime chaser data from multiple stations Warning decision making – Austria 2003

  32. Environmental data input • Radar cannot adequately observe hail size, downbursts or tornadoes • Environmental data becomes important in the process Warning decision making – Austria 2003

  33. Pick the storm most likely to be tornadic 04 May 2001 04 June 2001 Warning decision making – Austria 2003

  34. 04 May 2001 Warning decision making – Austria 2003

  35. 04 June 2001 Warning decision making – Austria 2003

  36. Storm Types/Hazards Table Source: IC 5.7 Student Guide http://wdtb.noaa.gov/DLCourses/dlocFY03/ic57/ic57-0210-2-screen.pdf Warning decision making – Austria 2003

  37. Lightning data • Cloud to ground lightning sometimes is useful in severe thunderstorm detection • However, the most severe storms often elevate charging layers resulting in less LTGCG http://www.cira.colostate.edu/ramm/visit/ltgmet2.html Warning decision making – Austria 2003

  38. Satellite data • Supercells often exhibit a warm wake downstream of the updraft. • However, these wakes only occur with isothermal or inversion layers above the equilibrium level http://www.cira.colostate.edu/ramm/visit/ev.html http://www.nssl.noaa.gov/istpds/icu624/ Warning decision making – Austria 2003

  39. Overwhelming data input rate Point soundings Surface data Yea Nay Lightning Radar Model ? Data ? Guidance ? (yours) Radar Data (others) Satellite Radar Data (others) Updated Probing Spotter Mesoscale Calls Reports Analysis Warning decision making – Austria 2003

  40. And excessive workload • Can lead to lower performance Stress/Performance Curve Performance Stress Team Building Associates (1997) Warning decision making – Austria 2003

  41. A more robust look at events could yield valuable associations Percentage of Human Error Mishaps Associated with skill-based Errors (FY 91-99) • Skill – based Errors are: • Poor technique • Improper use of equipment • Omitting required procedures • Failure to observe critical data From analysis of Naval Safety Center accident database Shappell and Weigman, 2001 Warning decision making – Austria 2003

  42. 16 14 12 Human 10 8 Class A, B,& C Mishaps/100,000 Flight Hours 6 4 Mechanical 2 0 1979 1981 1987 1985 1983 1989 1991 1977 Year Aviation industry findings Mechanical errors decreased, human error did not Reason: Much emphasis on relatively easy to see mechanical problems… very little on human factors contribution. Shappell, S. and Wiegmann, D. (1996). U.S. Naval aviation mishaps 1977-1992 All NAVY/MARINE Class A, B, & C Mishaps Warning decision making – Austria 2003

  43. Organizational Factors Technology Science Human Factors It’s never just one thing • Latent Conditions • Training • Infrastructure, policy • Characteristics • Radar( RF, Dealiasing ,sampling) • Models • Stability of equipment • What we don’t know • NSE • Conceptual models • Active Conditions • Teamwork • Coordination • SA • Experience Failed or Absent Defenses • Unwarned event • Death and injury *Human Factors Analysis and Classification System (Shappell/Wiegman) Warning decision making – Austria 2003

  44. Situation Awareness -review The ability to maintain the big picture Only one of these guys has good SA. Warning decision making – Austria 2003

  45. Situation AwarenessOfficial definition • Perception of the elements in the environment within a volume of space and time (level I) • Comprehension of their meaning (level II) • Projection of their status in the near future (level III) Endsley 1988 Warning decision making – Austria 2003

  46. Situation Awareness • Perception of the elements in the environment within a volume of space and time (level I) Same time…different radar Is this what your decision is based on? Or did you see this as well? Warning decision making – Austria 2003

  47. Situation Awareness Perceive • Comprehension of their meaning (level II) Did you see this? Now that you’ve seen this, do you understand what this is? Hook echo with 65dBZ in the hook: debris Warning decision making – Austria 2003

  48. Situation Awareness Perceive • Projection of their status in the near future (level III) Project Comprehend Did you see this? Do you understand what this is? (Hook echo with 65dBZ in the hook: debris) Now do you realize what is likely to happen? And what you should do? …Tornado Emergency for the OKC Metro……... Warning decision making – Austria 2003

  49. Factors affecting your ability to get or maintain SA • Attention • Limited; affected by task priority • Working memory • Information stored but easily accessed • Use of conceptual models • Perception of meaningful patterns • Relationships between different pieces of information • Workload • As workload increases, SA decreases Warning decision making – Austria 2003

  50. SA and workload • Low SA, low workload • Don’t know anything, don’t want to know • Low SA, high workload • Don’t know anything, but am trying way too hard to find out • High SA, high workload • Do know plenty, but at great effort (can’t keep this up for long!) • High SA, low workload • Do know, and it comes easily • If you are not operating here….find out why and fix it! Warning decision making – Austria 2003

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