mitigating the impacts of weather on surface...

Mitigating the Impacts of Weather on Surface TransportationKevin R. Petty, Ph.D.Head of Technology Research

/ 21 September 2010 / Kevin R. Petty / ©Vaisala

Basic Element of Weather

The sun is the driving force behind the weather we receive Creates unequal heating of the

Earth’s surface Circulations are generated in an

attempt to distribute or equalize heating


Air Masses Air Masses

Air masses are parcels of air that bring distinctive weather features to the country A large body of air with similar

TEMPERATURE and/or HUMIDITY properties throughout Air masses acquire the properties of the

terrain over which they move They are classified according to their

TEMPERATURE and MOISTURE content

Maritime Polar (cool, moist)Continental Polar (cold, dry)Maritime Tropical (warm, moist)Continental Tropical (hot, dry)

cPmP

mTcT

mP

mT


Frontal Boundaries

LH

Occurrence of a weather front Boundary between air masses of

markedly different properties Marked change in weather with

the passage of a front Cold Fronts Warm Fronts Stationary Fronts Occluded Fronts


Cold Fronts

Where a cold air mass is replacing a warmer air mass Cold air is undercutting the warm air causing it to rise Hazards: Thunder activity, strong winds, heavy rain and

sometimes snow

Rising Warm AirAdvancing Cold Air

Cold Front


Warm Fronts

Warm air advancing and rising over a wedge of colder air When air rises it cools and the water vapor within it

condenses to produce clouds and precipitation Hazards: Snow and freezing rain

Cold AirRising Warm Air

Warm Front


Precipitation Type

Vertical atmospheric temperature profiles and associated precipitation type

Surface

10,000 Feet

0oC/32oF

After Ahrens 1994 – Meteorology Today

0oC/32oF 0oC/32oF 0oC/32oFwarmercolder warmercolder warmercolder warmercolder

Snow Sleet Freezing Rain Rain


Localized Influences

Proximity to bodies of water Lakes Rivers and Streams Oceans

Orographic Features HillsMountains

ElevationUrban Development


Road Surface Heat Balance Factors


Diagnostic Solutions

Assessing current conditions Atmospheric conditions

– Road Weather Information Systems (RWIS)

– Satellite data– Radar data– Cameras– Mobile observations

Pavement conditions– RWIS observations

– In-pavement sensors– Non-invasive sensors

– Thermal mapping– Cameras– Mobile observations


Lost Trail Pass, Idaho : Guess the driving conditions on the following days? Images courtesy of Idaho Transportation Department


How well did you do!

Air Temp: 25ºF

Road Temp: 30ºF

Road State: Slush

Grip: Good

Air Temp: 20ºF

Road Temp: 28ºF

Road State: Ice

Grip: Poor

Air Temp: 36ºF

Road Temp: 39ºF

Road State: Dry

Grip: Excellent

Air Temp: 25ºF

Road Temp: 50ºF

Road State: Dry

Grip: Excellent

Air Temp: 23ºF

Road Temp: 43ºF

Road State: wet

Grip: Good

Air Temp: 23ºF

Road Temp: 28ºF

Road State: Ice

Grip: Poor

Air Temp: 28ºF

Road Temp: 43ºF

Road State: Wet

Grip: Good

Air Temp: 24ºF

Road Temp: 28ºF

Road State: Ice

Grip: Very poor

Air Temp: 14ºF

Road Temp: 21ºF

Road State: Dry

Grip: Excellent

Salt Residue

Salt Residue

Images courtesy of Idaho Transportation Department


Prognostic Solutions Predicting future conditions

Atmospheric– Persistence –

– simplistic method based on the assumption that conditions are not going to change.

– Not a good method to use in environments subject to rapid or dramatic changes.– Analog

– based on past, similar events– Difficult to use, as no two systems are exactly alike

– Statistical – Derive trends from medium to large datasets– In terms of road weather, can be very effective for short range forecasting, but

breaks down at longer lead times (i.e., >6 hours)– Numerical Weather Prediction (NWP)

– Computational simulations based on fluid dynamics and physics– Attempt to capture may of the topics previously mentioned – Although not perfect, generally regarded as the best solution for road weather

applications


Energy and Mass Balance Pavement Model

Pavement prediction based on numerical modeling is currently the best solution for forecasting changes in pavement conditions (i.e., pavement model). Typically a one dimensional energy and mass balance model is used

A mathematical model capable of simulating the changes in pavement temperature and state using information about the forecast location and predicted atmospheric conditions

The capacity to provide tactical and strategic information (i.e. nowcasts and forecasts) about the ever changing road weather conditions supports the planning and execution of maintenance activities


Energy and Mass Balance Pavement Modeling

A fundamental element of good weather and road condition forecasts is accurate assessment of the environment and pavement at the beginning of the forecast period

Good pavement models and RWIS serve as a foundation for accurate, timely road weather predictions Not all models are created equal Setup and execution techniques help ensure that forecast

accuracy is maximized Additional products (e.g., thermal mapping) can be used augment

and support pavement forecasting


Diagnostic and Prognostic Display


Supplemental Support (Consultation)

Provides an added level of support (human interface opportunity) Forecast clarification Ascertain forecast confidence System monitoring

Consultants should Be trained in weather and experienced Be familiar with the region (e.g.,

microclimates) Understand/speak winter maintenance

operations Understand specific end user

perspective Be available 24 hours/day, 7 days per

week


Point of Contact Information

Kevin R. Petty, Ph.D.VaisalaHead of Technology ResearchOffice (303)262-4093Email: [email protected]

mailto:[email protected]�

Mitigating the Impacts of Weather on Surface Transportation

Leon F. Osborne, Jr.

President

Meridian Environmental Technology, Inc.

TRB Webinar 21 September 2010

”“The combination of weather and

road conditions in a given area.

2

Road Weather

Mobility Safety

Productivity Environment

Types of Road Weather Impacts

3

7,130

167

573

47

41

18

170

117

62

44

74

00 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000

Annual Weather-related Fatalities(1995 - 2008)

Road

Speed reductions on signalized arterial routes

can range from:

10-25% on wet pavement and

30-40% on snowy or slushy pavement.

“Weather Impacts on Arterial Traffic Flow”, Mitretek Systems, Inc., December 2002

5

On freeways, 23% of non-recurrent

delays are due to snow, ice, and fog.

“Temporary Losses of Highway Capacity and Impacts on Performance”, Oak Ridge National Laboratory, May 2002.

6

Vehicle Performance

Travel Speed

Roadway Capacity

Travel Time

Road Closures

& Detours

Operating Costs

7

Each year weather-related highway crashes

account for more than 7,130 people are killed

and over 673,000 people are injured.

8

Reduced Visibility

Reduced Pavement Friction

Increased Accident Risk

Loss of Life and Injury

Property Damage

9

More than $2 billion is spent

each year by state and local agencies

on snow and ice control operations.

Highway Statistics 1999, FHWA Office of Highway Policy Information, October 2000

10

Approximately 20% of state

DOT maintenance budgets annually.

Shutting down a statewide highway network for

one day results in $15 to $76 millionin lost time, productivity, and wages.

Standards and Poor’s DRI Study, 199911

”“Chemical anti-icing and deicing account

for roughly 1/3 of expenditures for snow

and ice control.

~ Environment CanadaPSL2 Road Salts Draft Assessment ReportAugust, 2000

12

Strategies and tools designed to implement these strategies to mitigate the impact of weather on surface transportation activities.

Advisory:

Notification of weather impacts and mitigation measures

Control:

Implementation of measures to alter transportation system

use due to weather events

Treatment:

Action to reduce the impact of weather on roadways

13

Modern Tools to Mitigate the Impacts of Weather on Surface Transportation Operations

• Improved Road Weather Data Resources

• Tailored Surface Transportation Weather

Condition Forecasting

• Maintenance Decision Support Systems

Combined effort of U.S. DOT RITA &

FHWA Road Weather Management Program

To develop and demonstrate an integrated transportation

weather observations data management system

Promote effective quality checking of ESS data

15

http://www.clarus-system.com

16

Applications of CLARUS ESS Data

Benefits:

“Road view” of atmospheric conditions

Source of in situ pavement condition monitoring

Useful for monitoring current conditions and

initialization of road weather forecasts

17

Quality checking information for filtering “undesired” data

Cross jurisdictional availability of ESS data

Use of Road Weather Data Provides…

Road weather forecasts

supporting transportation

agency decision making

Critical current observations

for transportation operations

18

Road Weather Forecasts are Tailored Forecasts

• Contain forecasted weather and pavement conditions

• Highlight specific forecasted conditions that affect

user operations

• Updated each hour or less to support user-specific

decision processes

• Done for zones, road segments, or specific points

19

Pavement Condition Forecasts

• Tailored forecast of road surface conditions

(dynamic layer)

• Generated from weather forecasts inputted into a

pavement condition model

• Created using computer assisted decision logic

• Requires greater understanding of material

physics, radiation, and chemistry

20

Maintenance Decision Support Systems (MDSS)

Benefits of using MDSS:

Cost savings for use of labor,

materials, and equipment

Maintaining a consistent,

higher level of service on

roads

Providing training for new

DOT personnel

Reviewing maintenance actions

from past storms

21

Maintenance Decision Support System Process

Maintenance Actions

Modifications to Standard Practices

Results Expected from Proposed

Treatment

Road Condition Observations /

Analyses

Propose Alternative Treatment

‘Optimal’

Treatment & Expected Results

Maintenance Practices and

Activities Databases

MDSSProcessing& IntegrationSystem

RWIS

Yellow: Forecast / Theoretical RED: Real-Time / Actual BLACK: Applies to Both

SOLID: Automatic or Semi-Automatic Process DASHED: User-Driven Process

ResourcesUsed /

Available

Road ConditionAnalysis &

Forecast System(RCAF)

High ResolutionGridded Weather

Forecast Database

High ResolutionGridded Weather

Observations Database

Observed & Analyzed

Roadway State Databases

Available ResourcesDatabase

Roadway & Environment

Characterization Database

http://images.google.com/imgres?imgurl=www.orbital.com/images/snowplow.jpg&imgrefurl=http://www.orbital.com/TMS/RoadMaintenance/&h=150&w=150&sz=8&tbnid=eQ0E8qSiN4YJ:&tbnh=90&tbnw=90&start=1&prev=/images%3Fq%3Dsnowplow%26hl%3Den%26lr%3D%26ie%3DUTF-8%26safe%3Doff%26sa%3DN

Maintenance Decision Support Methods

• Synthesis of observed road and weather conditions

• Geospatial awareness of:– Current & projected

weather conditions / alerts

– Projected roadway conditions

– Maintenance action recommendations

• Use of selectable display features

Maintenance Decision Support Methods

• Route-based display of past, present, and future road & weather conditions

• Treatment recommendations– Determined from

physics-based rules driven by changing road & weather conditions

– Alternative treatments defined by user defined requirements / scenarios („What If‟)

Deploying MDSS

Source: “Maintenance Decision Support System - Deployment Guide”

FHWA Road Weather Management ProgramFHWA-JPO-08-059 (EDL #14439) - July 2008http://ops.fhwa.dot.gov/weather/mitigating_impacts

For More Information:

Contact . . .

Leon OsborneMeridian Environmental Technology, Inc.

701-792-1800

[email protected]

http://mdss.meridian-enviro.com

MDSS – Mitigating Winter’s Effects on the Highway

Anthony K. McClellan P.E.

Senior Transportation Engineer

September 21, 2010

Did you know?

• In Indiana One load of salt is approximately $500 - $1000 in materials.

• How would saving one load per truck per season affect your budget?

• MDSS is Green - One trip saved could result in significant reductions in salt.

MDSS

Maintenance Decision Support System

•Dynamic•Situation

•Road•Condition

•Material•Applications

•Plowing•Operations

•Current Status

•Materials•Inventory

•Crew•Schedules

•Equipment•Availability

•Static Resources

•Facilities

•Policies

•Practices

•Maintenance Information• RWIS• Road Reporting• Maintenance Activity• Tracking

•MDSS Processing Model – Maintenance Input

MDSS Overview

• Provides Managers and Foremen one location for snow and ice information

• Provides recommendations to Managers and Foremen

Graphical User Interface (GUI)• Provides:

– MDSS Routes and condition

– Forecast with hourly update

– Radar/Satellite

– RWIS data

– Multiple views: Table, Graph, Map

– Alerts

GUI Map View

GUI Graph View

GUI Table View

Data Collection from the Road

• Data from operators can be radioed in to switchboard or foreman and then entered into the system.

• Data entered into the system includes; Temperature, Material Used, Application Rate and Weather Conditions

INDOT’s FY 09 MDSS Mitigating the Costs of Winter Weather

Observed Hours of Snow/Fz Rain

3 Year Ave. FY 08 FY 09 Variation from 3 yr ave to 09

Variation from 08 to 09

Crawfordsville 304 390 334 9.9% -14.4%

Fort Wayne 420 501 496 18.1% -1.0%

Greenfield 304 390 334 9.9% -14.4%

LaPorte 263 329 396 50.6% 20.4%

Seymour 119 162 128 7.6% -21.0%

Vincennes 78 121 69 -11.5% -43.0%

All Districts 1,488 1,893 1,757 18.1% -7.2%

Observed Hours of Snow/Fz Rain (Nov - Apr)

Crawfordsville

020406080

100120

FY 06 FY 07 FY 08 FY 09

(Lbs per Lane Mile) perSN/FZRN Hour

La Porte

0

50

100

150

200

FY 06 FY 07 FY 08 FY 09


Seymour

0

100

200

300

400

FY 06 FY 07 FY 08 FY 09

(Lbs per Lane Mile) per SN/FZRNHour

Vincennes

0

50

100

150

200

250

FY 06 FY 07 FY 08 FY 09

(Lbs per Lane Mile) per SN/FZRNHour

Fort Wayne

0

20

40

60

80

100

FY 06 FY 07 FY 08 FY 09


Greenfield

0

50

100

150

FY 06 FY 07 FY 08 FY 09


•Lbs per lane mile /Observed Hours of Snow and Fz Rain

The Bottom Line

FY 08 Through February

FY 09 Through February

1,324 1,359

$27,100,384 $17,350,292

Observed SN/FZRN HoursTons of Salt Used

Dollars of Salt511,328 327,364

Salt Usage – All Districts

ALL DISTRICTS - STATEWIDE SALT USAGE

0

100,000

200,000

300,000

400,000

500,000

600,000

NOV DEC JAN FEB MAR APR

Months

Tons

5 Year Ave.FY 200870% of FY 2008FY 2009

Salt Usage

3 Year Ave. 5 Year Ave. 10 Year Ave. FY 08 FY 09 Variation 3 yr ave to 09

Variation 10 yr ave to 09

Variation from 08 to 09

Crawfordsville 58,313 58,324 51,484 95,318 41,402 -29.0% -19.6% -56.6%

Fort Wayne 70,389 71,946 66,993 100,762 71,674 1.8% 7.0% -28.9%

Greenfield 74,067 74,886 78,863 110,670 60,686 -18.1% -23.0% -45.2%

LaPorte 86,387 98,830 103,021 132,039 89,546 3.7% -13.1% -32.2%

Seymour 62,212 53,174 45,398 66,726 40,250 -35.3% -11.3% -39.7%

Vincennes 35,355 32,997 29,059 52,759 26,246 -25.8% -9.7% -50.3%

All Districts 386,723 390,157 374,818 558,274 329,804 -14.7% -12.0% -40.9%

Salt Usage (Nov - Apr)

Overtime Hours – Snow & Ice

FY 08 FY 09 Variation from 08 to 09

Crawfordsville 38,240 17,971 -53.0%

Fort Wayne 44,896 35,603 -20.7%

Greenfield 36,614 32,074 -12.4%

LaPorte 50,961 51,743 1.5%

Seymour 33,240 19,027 -42.8%

Vincennes 22,533 11,792 -47.7%

All Districts 226,484 168,210 -25.7%

OVT Hours - Snow and Ice (Nov - Apr)

Tons of Salt per Snow/Fz Rain Hour

Tons/Sn Hour 3 Year Ave

Tons/Sn Hour 08

Ton/SnHr 09

Diff from 3 Yr Ave Diff from 08

Crawfordsville 192 244 124 -35.4% -49.3%

Fort Wayne 168 201 145 -13.8% -28.2%

Greenfield 244 284 182 -25.4% -36.0%

LaPorte 328 401 226 -31.2% -43.7%

Seymour 523 412 314 -39.9% -23.7%

Vincennes 453 436 380 -16.1% -12.8%

All Districts 260 295 188 -27.8% -36.4%

The Bottom Line

$AVING$ - Overtime

FY 08 (Reduced by 7.2%) FY 09 Difference (Hours) Savings @

$23.33/hour

All Districts 210,177 168,210 41,967 $979,136

Overtime Hours

$AVING$ - Salt Usage

FY 08 (Reduced by 7.2%) FY 09 Difference (Tons) Savings @

$53/Ton

All Districts 518,078 329,804 188,274 $9,978,536

Salt Usage (Tons)

So, Why isn’t MDSS Used Everywhere?

• MDSS involves Organizational Change

• “We already know how to fight snow”

• “We can save the salt without MDSS”

• It’s too expensive

But we already know how to fight snow!

How many people know how to change a tire?

•What movie is this shot from?

• Where was the Movie Setting?

“There are two basic rules of life: Change is inevitable and everybody resists change”

– Author Roger Von Oech

“Attitude Reflects Leadership”

- Can You Name the Movie?

How is our work affected by change?

We’re Interested In MDSS – Where Do We Go form Here?

•The Pooled Fund Study for MDSS, TRB and FHWA and even the Internet are all good sources for information on how to get MDSS in your organization.

•Training Plan will be needed

•Account and plan for “Organizational Change”

•Create Experts by using past saved storms for training and support

•Account for the resistance to change and be prepared for it.

Maintenance Decision Support System (MDSS):

Indiana Department of Transportation (INDOT)

Statewide Implementation

Prepared by:

Tony McClellan, P.E., Project Manager

Paul Boone, P.E.

Melody A. Coleman

Link for Report: www.in.gov/indot/files/MDSSReportWinter08-09.pdf

Questions?Anthony K. McClellan, P.E.

Sr. Transportation Engineer

Meridian Environmental Technology

[email protected]

mailto:[email protected]�

mitigating the impacts of weather on surface...

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