Initial Results and Future Plans for a Winter Impact Index (WII)

1. NOAA/NWS Twin Cities Northern Plains Winter Storm Conference Saint Cloud State University, Saint Cloud, MN 16 November 2010 Tom Hultquist & Lisa Schmit Initial Results and Future Plans for a Winter Impact Index (WII)

2. Outline • Motivation • Winter Weather Impacts on the Transportation Industry • Past Research • Methodology • Event Analysis from Past Two Winter Seasons • Future Plans • Final Thoughts

3. Motivation • The NWS guidelines/criteria for winter weather advisories/warnings are not impact focused. • Fixed snowfall amounts in fixed time periods do not account for the myriad of ingredients which lead to significant vs. non-significant impacts. • It would be difficult to identify and quantify every possible variable and its contribution to various user impacts, but there are some for which reliable data exist and can be leveraged. • Focusing on impacts to transportation, in terms of accidents, delays, level of service provided by the system, etc, provides a valuable and reasonably objective measure of the overall impact to various aspects of the user community.

4. Winter Weather Impacts on the Transportation Industry • Winter weather extends travel time, and also places travelers in a potentially dangerous position. • The National Research Council estimates • Drivers endure over 500 million hours of delay annually on the nation’s highways due to winter weather. • 1.5 million vehicular crashes occur each year due to winter weather • 800,000 injuries • 7,000 fatalities • Economic impact from weather-related crashes cost an average of $42 billion in the U.S. each year (due to injuries, loss of lives, & property damage).

5. Winter Weather Impacts on the Transportation Industry Cause of Delays in National Airspace System November 2008 – April 2010 • Winter-related flight delays cost the U.S. economy more than $30 billion annually ($41 billion in 2007). • Weather remains the #1 cause (60-70%) of delays within the NAS each year.

6. Winter Weather Impacts on the Transportation Industry / MNDOT Stats Combination of # of snow events, # of freezing rain events, total snow amount, and total storm duration

7. Winter Weather Impacts on the Transportation Industry / MNDOT Stats MNDOT 2009-10 Winter Severity Index Change from Winter 2008-09

8. Some Past Research

9. Past Research • Graning 2009 • Danger Degree Project • Developed a "checklist" of meteorological and societal factors • Each factor is assigned a weighted value • These values are added up to result in a quantitative "score" or Danger Degree for each event • Theory: Higher the Danger Degree, Greater Potential Impact. • Shea 2008 • Traffic Accident Study • Reviewed traffic accidents in LaCrosse are in comparison with winter weather events (and specifically the amount of snowfall received and corresponding temperatures).

10. Past Research • Patterson et al. 2009 • Winter Storm Related Congestion in Salt Lake Valley • Studied the impact of weather conditions on the highway system in the Salt Lake City area, particular its impact on traffic flow, congestion, and overall level of service provided by the system during a variety of events. • Qin et al. 2006 • Snowstorm Event-based Crash Analysis • Comprehensive study of winter weather-related crashes in Wisconsin, focusing on 2000-02. Looked at timing of crashes in relation to events, and made extensive comparison of weather conditions and DOT mitigation efforts.

11. Meteorology Road Conditions Public Response Uncertainty and Impact “This is also an encouraging finding because it suggests that the highest overall delay may be predictable (but perhaps not avoidable) with accurate weather forecasts.” – UDOT 2007 Congestion Report Impact NWA Annual Meeting – Norfolk, VA (Patterson, Graham et al.)

12. Methodology • Selected event dates from the 2008-2010 winter seasons based on KMSP reports of: • Snowfall ≥ 1 inch • Snowfall less than one inch if combined with report of freezing precipitation • Coordinated with MN DOT to get the daily accident report data from 2008-2010 • 7 county metro area • Lat/lons, Time, Severity, Weather, Road Surface Conditions • Looked at the accident data for the selected event dates • Compared the accident numbers with non-wx days

13. Methodology • For the event dates, looked at numerous factors: • Weather Conditions (KMSP) • Precipitation, temperature, visibility, wind • Non-weather Factors • Day of week, time of day, headline status • Selected a few event dates to look at today • Typical Definition of NWS Headlines • Winter Storm Warning: 6” in 12 hrs, 8” in 24 hrs • Winter Weather Advisory: 3-5” in 12 hrs

14. Methodology • Traffic Flow/Congestion Assessment • MNDOT has thousands of sensors embedded in the major roadways in the Twin Cities Metro Area. Data from these sensors is used by MNDOT to calculate vehicle volume, speed, spacing, and other variables. • Data is available for download from every sensor dating back to 1994. The sheer volume of data makes analysis difficult.

15. Methodology • Traffic Flow/Congestion Assessment • For initial study, data was extracted for specific points of interest to get a “flavor” of how traffic is impacted during winter weather events. • May incorporate additional sensors as we move forward with the project, and attempt to more closely correlate impacts at specific locations with observed conditions (rather than looking at only system-wide impacts). Also working to assess inbound vs. outbound congestion, which further complicates data selection and analysis.

16. Methodology • Traffic Flow/Congestion Assessment • Amount of data is overwhelming • I-395/100 Interchange • 42 sensors on the Rt. 100 portion of the interchange alone

17. Methodology • Traffic Flow/Congestion Assessment • Extracted traffic flow information from specific points of interest along major arteries in the metro area. • I-94, I-394, I-494, I-694, I-35W, I-35E, US-169, Rt. 100 • Retrieved traffic flow/volume, speed, vehicle spacing, and other information for specific “cases” of interest and their corresponding “good weather” analogs. • Attempt to extract “impact” information from these variables, and particularly how they vary in comparison to “good weather” days. Will need to incorporate more complete dataset before thorough statistical analysis is performed.

18. Winter 2008-2010 Events

19. Events from 2008-2010 Winter Seasons 35 Events

20. Events from 2008-2010 Winter Seasons

23. Case Examples • 14th December 2008 - Advisory • 20th December 2008 - Advisory • 8th & 9th December 2009 - Warning • 7th January 2010 – No Headline

25. Advisory Event 14th December 2008 500 hPa Analyses 12 UTC 12/13/08 – 12 UTC 12/15/08

26. Advisory Event 14th December 2008 Surface Analyses 12 UTC 12/13/08 – 12 UTC 12/15/08

27. 14th December 2008 Advisory Event Total Accidents: 287 Total Snowfall: 2.4” Other Factors: Sunday Rain Snow

28. 14th December 2008 Advisory Event

29. 14th December 2008 Advisory Event

30. 14th December 2008 Advisory Event

31. Advisory Event 20th December 2008 500 hPa Analyses 00 UTC 12/19/08 – 00 UTC 12/22/08

32. Advisory Event 20th December 2008 850 hPa Analyses 00 UTC 12/19/08 – 00 UTC 12/22/08

33. 20th December 2008 Advisory Event Total Accidents: 661 Total Snowfall: 3.6” Other Factors: Sat.-Shopping Snow

34. 20th December 2008 Advisory Event

35. 20th December 2008 Advisory Event

36. 20th December 2008 Advisory Event

37. Warning Event 8th-9th December 2009 500 hPa Analyses 12 UTC 12/08/09 – 12 UTC 12/10/09

38. Warning Event 8th-9th December 2009 Surface Analyses 00 UTC 12/08/09 – 12 UTC 12/10/09

39. 8th-9th December 2009 Warning Event Total Accidents: 1,196 Total Snowfall: 7.4” Other Factors: Mid-week Snow

40. 8th-9th December 2009 Warning Event

41. 7th January 2010 No Headline 500 hPa Analyses 00 UTC 01/06/10 – 12 UTC 01/08/10

42. 7th January 2010 No Headline Surface Analyses 00 UTC 01/06/10 – 12 UTC 01/08/10

43. 7th January 2010 Sub-Advisory Event Total Accidents: 752 Total Snowfall: 2.2” Other Factors: Thursday Snow

44. 7th January 2010 • Sub-Advisory Event

45. 7th January 2010 • Sub-Advisory Event

46. 7th January 2010 • Sub-Advisory Event

47. Future Plans • Continue to work toward the goal of providing impact-based, customer-driven information to help drive decisions which save time, money, and lives. • Need to perform comprehensive statistical analysis of the copious amount of information available so that scientifically valid conclusions can be drawn from the past. • Gives us the ability to provide meaningful decision assistance tools and information in the future. • Development of a Winter Impact Index, focused on weather disruptions to travel. • Would complement existing winter weather products, and be essentially automated based on gridded forecast elements and their correlation with statistical analysis of past data (crashes, traffic congestion, aviation disruptions, etc). • Could lead to changes in “legacy” products down the road, but that may be difficult given differences in impact due to local factors, etc. • Index would be tied to expected impacts given forecast conditions and societal factors. • Possible by-products could include things such as a commute disruption estimate (125% of normal, 200% of normal, etc)

48. Winter Impact Index (WII)for travel • Would be derived out of the Gridded Forecast Editor (GFE) • Placed on the NWS web page • Decision support tool that would hopefully be helpful even in sub-advisory events • Would be geared toward the Twin Cities metro area, particularly since it will be derived from metro area data. • However, conditions which lead to travel disruptions in the metro area likely produce them elsewhere, albeit with less amplitude but possibly with equal relative impact.

49. Winter Impact Index (WII)for travel Graphical Forecast Editor Webpage Graphic 0 5

50. Acknowledgements • Brad Estochen, Nathan Drews, Brian Kary (MN DOT) Questions?