Tornadogenesis In the beginning, there was well, uh, that depends

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 SchmitLS1OutlineMotivationWinter Weather Impacts on the Transportation IndustryPast ResearchMethodologyEvent Analysis from Past Two Winter SeasonsFuture PlansFinal ThoughtsLS2MotivationThe 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.LS3Winter Weather Impacts on the Transportation IndustryWinter weather extends travel time, and also places travelers in a potentially dangerous position.The National Research Council estimatesDrivers endure over 500 million hours of delay annually on the nations highways due to winter weather.1.5 million vehicular crashes occur each year due to winter weather800,000 injuries7,000 fatalitiesEconomic 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).TH4Winter Weather Impacts on the Transportation IndustryWinter-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 SystemNovember 2008 April 2010TH5Winter Weather Impacts on the Transportation Industry / MNDOT Stats

Combination of # of snow events, # of freezing rain events, total snow amount, and total storm durationTH6Winter Weather Impacts on the Transportation Industry / MNDOT Stats

MNDOT 2009-10 Winter Severity IndexChange from Winter 2008-09

TH7Some Past Research

TH: Danger Degree Project (Amanda Graning): Quick Project overview so as I break it down you know where I am going.First we

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 eventTheory: Higher the Danger Degree, Greater Potential Impact.

8Past ResearchGraning 2009Danger Degree ProjectDeveloped 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 eventTheory: Higher the Danger Degree, Greater Potential Impact.Shea 2008Traffic Accident StudyReviewed traffic accidents in LaCrosse are in comparison with winter weather events (and specifically the amount of snowfall received and corresponding temperatures).TH9Past ResearchPatterson et al. 2009Winter Storm Related Congestion in Salt Lake ValleyStudied 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. 2006Snowstorm Event-based Crash AnalysisComprehensive 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.TH10Uncertainty and ImpactPublic ResponseMeteorologyRoad ConditionsImpactThis 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.)11TH: UncertaintyMeteorological Impact on the RoadsHuman behavior

Focus on societal impactsBetter understanding could lead to improved service

Spend time looking at meteorological uncertaintyConsider road impact in largely a superficial fashionDo not understand human behavior or response to messages from weather enterprise

Can we improve the forecast?Focus more on timing, snowfall rates etc

Better understanding of road impacts?Road temperaturesMitigation strategies

MethodologySelected event dates from the 2008-2010 winter seasons based on KMSP reports of:Snowfall 1 inchSnowfall less than one inch if combined with report of freezing precipitationCoordinated with MN DOT to get the daily accident report data from 2008-2010 7 county metro areaLat/lons, Time, Severity, Weather, Road Surface ConditionsLooked at the accident data for the selected event datesCompared the accident numbers with non-wx daysLS12MethodologyFor the event dates, looked at numerous factors:Weather Conditions (KMSP)Precipitation, temperature, visibility, windNon-weather FactorsDay of week, time of day, headline statusSelected a few event dates to look at todayTypical Definition of NWS HeadlinesWinter Storm Warning: 6 in 12 hrs, 8 in 24 hrsWinter Weather Advisory: 3-5 in 12 hrs

LS13MethodologyTraffic Flow/Congestion AssessmentMNDOT 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.

TH14MethodologyTraffic Flow/Congestion AssessmentFor 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.

TH15MethodologyTraffic Flow/Congestion AssessmentAmount of data is overwhelmingI-395/100 Interchange42 sensors on the Rt. 100 portion of the interchange alone

TH16MethodologyTraffic Flow/Congestion AssessmentExtracted 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. 100Retrieved 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.TH17Winter 2008-2010 EventsLS18Events from 2008-2010 Winter Seasons35 EventsLS19Events from 2008-2010 Winter SeasonsLS20

LS21

TH22Case Examples14th December 2008 - Advisory20th December 2008 - Advisory8th & 9th December 2009 - Warning7th January 2010 No Headline

LS23LS2414th December 2008Advisory Event

500 hPaAnalyses12 UTC 12/13/08 12 UTC 12/15/08TH2514th December 2008Advisory Event

SurfaceAnalyses12 UTC 12/13/08 12 UTC 12/15/08TH2614th December 2008RainSnowAdvisory EventTotal Accidents: 287Total Snowfall: 2.4Other Factors: SundayLS: *Had our first notable increase in accidents when the precipitation started and the visibility started to drop. There was also an increase in wind speed noted at this time. *Temperature hovered right above freezing for the first half of the event, and we noticed a second peak in the accidents when the temperature dropped below freezing and the precipitation changed over to snow. A sharp increase in the winds was also noted, along with another decrease in visibilities. *Note we do see a rather suspect increase in the fair weather accidents, which reminds us that we need to get a larger data set for the fair weather accident days to get a more accurate representation.2714th December 2008Advisory Event

TH2814th December 2008Advisory Event

2914th December 2008Advisory Event

TH3020th December 2008Advisory Event

500 hPaAnalyses00 UTC 12/19/08 00 UTC 12/22/08TH3120th December 2008Advisory Event

850 hPaAnalyses00 UTC 12/19/08 00 UTC 12/22/08TH3220th December 2008Advisory EventSnowTotal Accidents: 661Total Snowfall: 3.6Other Factors: Sat.-ShoppingLS: *The precipitation in this event was in the form of snow for the duration. A substantial increase in the accident count is observed simultaneous with the onset of snow. Although there was only a little over an inch more of snow in this advisory event than the previous one, one reason that there may have been significantly more accidents was due to the fact that it was the Saturday before Christmas, and the roads were busy with holiday shoppers in the metro area.3320th December 2008Advisory Event

TH3420th December 2008Advisory Event

TH3520th December 2008Advisory Event

TH368th-9th December 2009Warning Event

500 hPaAnalyses12 UTC 12/08/09 12 UTC 12/10/09TH378th-9th December 2009Warning Event

SurfaceAnalyses00 UTC 12/08/09 12 UTC 12/10/09TH388th-9th December 2009Warning EventSnowTotal Accidents: 1,196Total Snowfall: 7.4Other Factors: Mid-weekLS: *This event also had a sharp increase in the accident counts attendant with the onset of the snow. Although you would normally see an increase correlated with the afternoon rush hour, the snow induced this rise several hours earlier. *Although a notable increase occurs again on the second morning, it seems to occur more gradually than on a normal day, which may be in part to late starts and commuters who went into work later.*The accident count in the afternoon actually decreases when it would normally increase, which infers that less people may have been out on the roads at this point.398th-9th December 2009Warning Event

TH: *Had our first notable increase in accidents when the precipitation started and the visibility started to drop. There was also an increase in wind speed noted at this time. *Temperature hovered right above freezing for the first half of the event, and we noticed a second peak in the accidents when the temperature dropped below freezing and the precipitation changed over to snow. A sharp increase in the winds was also noted, along with another decrease in visibilities. *Note we do see a rather suspect increase in the fair weather accidents, which reminds us that we need to get a larger data set for the fair weather accident days to get a more accurate representation.407th January 2010No Headline

500 hPaAnalyses00 UTC 01/06/10 12 UTC 01/08/10TH417th January 2010No Headline

SurfaceAnalyses00 UTC 01/06/10 12 UTC 01/08/10TH:427th January 2010Sub-Advisory EventSnowTotal Accidents: 752Total Snowfall: 2.2Other Factors: Thursday*Although just over 2 inches of snow fell in this event, the fact that the snow began overnight and coated the roads prior to the morning rush hour caused a significant increase in the accident count for the morning hours. 437th January 2010Sub-Advisory Event

TH447th January 2010Sub-Advisory Event

*Had our first notable increase in accidents when the precipitation started and the visibility started to drop. There was also an increase in wind speed noted at this time. *Temperature hovered right above freezing for the first half of the event, and we noticed a second peak in the accidents when the temperature dropped below freezing and the precipitation changed over to snow. A sharp increase in the winds was also noted, along with another decrease in visibilities. *Note we do see a rather suspect increase in the fair weather accidents, which reminds us that we need to get a larger data set for the fair weather accident days to get a more accurate representation.457th January 2010Sub-Advisory Event

TH46Future PlansContinue 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)TH47Winter Impact Index (WII)for travelWould be derived out of the Gridded Forecast Editor (GFE)Placed on the NWS web pageDecision support tool that would hopefully be helpful even in sub-advisory eventsWould 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. LS48Winter Impact Index (WII)for travel05

Graphical Forecast EditorWebpage GraphicLS49AcknowledgementsBrad Estochen, Nathan Drews, Brian Kary (MN DOT)Questions?LS50