noaa/nws twin cities northern plains winter storm conference saint cloud state university, saint...
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Initial Results and Future Plans for a Winter Impact Index (WII)
NOAA/NWS Twin Cities
Northern Plains Winter Storm ConferenceSaint Cloud State University, Saint Cloud, MN16 November 2010Tom Hultquist & Lisa Schmit
Outline
Motivation Winter Weather Impacts on the
Transportation Industry Past Research Methodology Event Analysis from Past Two Winter
Seasons Future Plans Final Thoughts
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.
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).
Winter Weather Impacts on the Transportation Industry
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.
Cause of Delays in National Airspace System
November 2008 – April 2010
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
Winter Weather Impacts on the Transportation Industry /
MNDOT StatsMNDOT 2009-10 Winter Severity Index
Change from Winter 2008-09
Some Past Research
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).
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.
Uncertainty and Impact
Public Response
Meteorology Road Conditions
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
NWA Annual Meeting – Norfolk, VA (Patterson, Graham et al.)
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
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
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.
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.
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
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.
Winter 2008-2010 Events
Events from 2008-2010 Winter Seasons
Weather-related Accidents 0
500
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Metro Area Accidents by Day of the Week
SaturdaySundayMondayTuesdayWednesdayThursdayFriday
3 Events
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35 Events
Events from 2008-2010 Winter Seasons
No Head-line40% Advisory
34%
Warning26%
By Headline Type
No Headline Advisory Warning
Case Examples
14th December 2008 - Advisory 20th December 2008 - Advisory 8th & 9th December 2009 - Warning 7th January 2010 – No Headline
12/1
4/08
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nt
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-9/0
9 Ev
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1/7/
10 E
vent
0200400600800
10001200140016001800
123 157426
221287
661
1,196752
Comparison of Event Accidents with Fair Weather Conditions
Event Accidents
14th December 2008Advisory Event
500 hPaAnalyses12 UTC 12/13/08 – 12 UTC 12/15/08
14th December 2008Advisory Event
SurfaceAnalyses12 UTC 12/13/08 – 12 UTC 12/15/08
14th December 2008
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Accidents Correlated with Weather Conditions
Precip (mm)Linear (Precip (mm))Accidents/HourVisibilityTemperatureWind Speed (knots)Fair Wx Accidents
Rain Snow
Advisory Event Total Accidents: 287Total Snowfall: 2.4”Other Factors: Sunday
14th December 2008Advisory Event
14th December 2008Advisory Event
14th December 2008Advisory Event
20th December 2008Advisory Event
500 hPaAnalyses00 UTC 12/19/08 – 00 UTC 12/22/08
20th December 2008Advisory Event
850 hPaAnalyses00 UTC 12/19/08 – 00 UTC 12/22/08
20th December 2008Advisory Event
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Accidents Correlated with Weather Conditions
Precip (mm)Accidents/HourVisibilityTemperatureWind Speed (knots)Fair Wx Day Accidents
Snow
Total Accidents: 661Total Snowfall: 3.6”Other Factors: Sat.-Shopping
20th December 2008Advisory Event
20th December 2008Advisory Event
20th December 2008Advisory Event
8th-9th December 2009Warning Event
500 hPaAnalyses12 UTC 12/08/09 – 12 UTC 12/10/09
8th-9th December 2009Warning Event
SurfaceAnalyses00 UTC 12/08/09 – 12 UTC 12/10/09
8th-9th December 2009Warning Event
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Accidents Correlated with Weather Conditions
Precip (mm)Accidents/HourVisibilityTemperatureWind Speed (knots)Fair Wx Day Accidents
Snow
Total Accidents: 1,196Total Snowfall: 7.4”Other Factors: Mid-week
8th-9th December 2009Warning Event
7th January 2010No Headline
500 hPaAnalyses00 UTC 01/06/10 – 12 UTC 01/08/10
7th January 2010No Headline
SurfaceAnalyses00 UTC 01/06/10 – 12 UTC 01/08/10
7th January 2010Sub-Advisory
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Accidents Correlated with Weather Conditions
Precip (mm)Accidents/HourVisibilityTemperatureWind Speed (knots)Fair Wx Day Accidents
Snow
Total Accidents: 752Total Snowfall: 2.2”Other Factors: Thursday
7th January 2010Sub-Advisory
Event
7th January 2010Sub-Advisory
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7th January 2010Sub-Advisory
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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)
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.
Winter Impact Index (WII)
for travel
Low ModerateExtreme
0 5
Graphical Forecast Editor
Webpage Graphic
Acknowledgements Brad Estochen, Nathan Drews, Brian
Kary (MN DOT)
Questions?