NOAA/NWS Twin Cities Northern Plains Winter Storm Conference Saint Cloud State University, Saint...

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.


Amount of data is overwhelming I-395/100 Interchange

42 sensors on the Rt. 100 portion of the interchange alone


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

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Metro Area Accidents by Day of the Week

SaturdaySundayMondayTuesdayWednesdayThursdayFriday

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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

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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


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


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Precip (mm)Accidents/HourVisibilityTemperatureWind Speed (knots)Fair Wx Day Accidents

Snow

Total Accidents: 661Total Snowfall: 3.6”Other Factors: Sat.-Shopping

8th-9th December 2009Warning Event



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Snow

Total Accidents: 1,196Total Snowfall: 7.4”Other Factors: Mid-week

7th January 2010No Headline


7th January 2010Sub-Advisory

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Snow

Total Accidents: 752Total Snowfall: 2.2”Other Factors: Thursday

7th January 2010Sub-Advisory

Event

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?

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