1. Road Weather Information Systems September 28, 2011 Ray Murphy, US DOT - FHWA Office of Technical Support
2. Ray Murphy ray.murphy@dot.gov BSEE – IIT in Chicago FHWA +10 yrs - program support: Road Weather Management Emergency Transportation Operations Real – Time Data Management + 20 yrs Illinois Dept. of Transportation: Operations, Maintenance, & Construction ITS Project Manager CEC Officer/Seabees & Engineer Mentor 2
16. Definition: Road Weather Information System (RWIS) and its associated Environmental Sensor Stations (ESS) . The term RWIS has a number of diverse definitions ranging from sensing and processing devices in the field to a composite of all weather and pavement information resources available to highway operations and maintenance personnel. For our purposes, RWIS can be defined as the hardware, software programs, and communications interfaces necessary to collect and transfer field observations to a display device at the user’s location. While the original purpose of the RWIS was to address winter weather conditions, applications have been developed to detect and monitor a variety of road weather conditions impacting road operations and maintenance. 12
17. An ESS consists of one or more sensors measuring atmospheric, pavement, soil, and/or water level conditions. 13
21. Prioritized RWIS Observations Precipitation Type Surface Temperature Surface Status (dry/wet) Precipitation Rate/Intensity Visibility Precipitation Accumulation Chemical Percentage Dew point Air Temperature Ice Percentage Freezing Point Temperature Depth of Water Layer Wind Speed Relative Humidity Wind Direction Barometric Pressure Subsurface Temperature Wind Gusts 17
22. Environmental Sensor Station (ESS) Operational Applications Traffic Managers Maintenance Managers Emergency Managers Dynamic Message Signs & Other Roadside Devices Information Service Providers Public & Private Weather Service Providers Environmental Monitoring Networks ESS data provides many benefits, in addition to improving road safety, mobility, and productivity, by supplying information on roadway conditions essential for traffic operations, traveler information, road maintenance, and emergency response. 18
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24. National Weather Service (NWS), military(public) and private weather service providers use these data to develop weather products, short-range forecasts, and forecast verification, and as input to locally run weather forecast models.
25. State climatologists can use ESS data for long-term records and climatological analyses.
26. Local, state, or Federal disaster assessment and response agencies (e.g., Federal Emergency Management Agency and the Department of Homeland Security) may use these data to manage emergencies and related response actions.19
29. RWIS ESS data can also be leveraged to support rail, pipeline, and marine operations when such operations are adjacent to or reasonably near the ESS.
30. Government and university Mesonetscan include these data to support the development of weather and road weather forecast models.20
31. What is a Mesonet? In meteorology, a mesonet is a regional network of automated observing surface weather stations designed to observe mesoscale (intermediate size) meteorological phenomena (weather features and their associated processes). Due to the space and time scales associated with mesoscale phenomena, weather stations comprising a mesonet will be spaced closer together and report more frequently. The term mesonet refers to the collective group of these weather stations, and are typically owned and operated by a common entity. 21
32. Why Mesonets? Mesoscale phenomena can cause weather conditions in a localized area to be significantly different from that dictated by the ambient large-scale condition. As such, meteorologists need to understand these phenomena in order to improve forecast skill. Observations are critical to understanding the processes by which these phenomena form, evolve, and dissipate. The long-term observing networks (RWIS, ASOS, AWOS), however, are too sparse and report too infrequently for mesoscale research. RWIS, ASOS and AWOS stations are typically spaced 40 to 100 miles apart. "Mesoscale" weather phenomena occur on a spatial scale of hundreds of miles. Thus, an observing network with finer temporal and spatial scales is needed for mesoscale applications. This need led to the development of the mesonet. 22
33. Mesoscale phenomena can cause weather conditions in a localized area to be significantly different from that dictated by the ambient large-scale condition. 23
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35. Diverse Planning Team: The planning team should also include local DOT personnel, especially maintenance personnel. These individuals typically possess a vast knowledge of weather conditions along the road segment they maintain. The maintenance personnel can provide critical input about recurring weather problems such as the locations of frequent slippery pavements, low visibilities, or strong gusty winds that suggest the need for an ESS installation. Additionally, local DOT personnel can often identify areas where an ESS sensor might be vulnerable to large snow drifts, flooding, or pooling water from spring thaws. 25
36. An analysis of the operational requirements Planning the ESS network should include an analysis of the operational requirements for road weather information. This analysis will drive the environmental sensor requirements and lead to decisions regarding sensor selection and siting. Considerations to include: How will the road weather information be used? For example, will the information be used to monitor roadway conditions as input to winter maintenance decisions or road temperature modeling, or to support weather-responsive traffic management, traveler information systems (e.g., 511 systems) or road construction efforts? Will the ESS be used to measure a site-specific condition or to provide information that may represent conditions across a general area? For example, installing a sensor to monitor the visibility along a fog-prone road segment may result in completely different siting decisions than if the requirement is to collect wind and temperature information for input to a road weather model. . 26
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38. For example, if a pavement sensor is to be included in an installation, the DOT may also want to install air temperature, humidity, and precipitation sensors to complement the pavement sensor data.
39. The precipitation sensor can help identify whether pavement sensor readings are indicative of new or continuing precipitation, while the temperature and humidity sensors will indicate whether conditions support the formation of frost.
40. DOTs may want to create a prioritized list of the road weather elements and sites they need to fulfill their requirements. Such an approach may help in making tradeoffs when data collection needs exceed available funding or when a phased approach to meeting statewide requirements is desired.
41. DOTs should also consider other sources of weather and pavement data that may be available to meet road weather information requirements. Developing data-sharing partnerships with other agencies may help satisfy RWIS ESS installation requirements while improving the availability of data to all partners. 27
48. Communications Standards A common communications interface is used for RWIS and other ITS devices from multiple vendors to exchange information. Those NTCIP standards used in RWIS applications are referred to as ESS standards. 29
67. Metadata are used to document the characteristics of each sensor and its siting to provide users an understanding of what the sensor data really represent
68. Standards have been developed for some geospatial metadata, but not for RWIS ESS location and sensor metadata35
69. Version 2.0 Updates Discussion of bridge anti-icing systems Added a section on “How to use this guide” Updated information on ESS maintenance Information about the ClarusInitiative Included a discussion on archaeological constraints, soil conditions & clear zones Included a reference to the Storm water Guide for storm water management ESS sites 36
82. RWIS in Michigan’s Upper Peninsula Dawn Gustafson, P.E., Traffic and Safety Engineer Michigan Department of Transportation (906) 786-1830 ext. 316 gustafsond@michigan.gov October 13, 2009 40
84. NTCIP Compliant RWIS ESS Permanent Stations NTCIP compliant – V1 & V2 Can place in existing networks and poll with NTCIP-compliant software Hardware has no end-of-life Can easily replace existing stations Interfaces with many existing sensors from other vendors Compatible with existing towers & power supplies Lower replacement costs 42
85. Temporary or Seasonal Monitoring NTCIP-compliant Easy assembly and disassembly Any measurement can be made 43
92. Dam and Levee SafetySolar Power devices TxDOT Bridge Mount Weather & Stream Monitoring System SH35 at Brazos River Flooded Roadway Warning System with Automatic Barrier Gates W.W. White Rd, San Antonio, TX 44 44
97. Ability To Install an RWIS with minimal investment -- No RPU/Datalogger Needed Digital Interface Protocol Wind Sensor Pavement Sensor Small Compact RWIS with no RPU Modem Radio or Cellular Connection 46
105. Low Maintenance costs by firmwareInnovative principle:Microwaves–Doppler Radar Precipitation type (rain, snow, mixed rain, ice rain and hail) / Precipitation intensity (mm/h) Digital data communication with standard protocol and 2 digitale outputs 47
106. Road Weather Information Systems (RWIS) have evolved into complete ITS platforms capable of monitoring any weather or traffic condition. Flash Food Traffic Flow Air Quality Pavement sensors have moved out of the road surface to allow for safer, less expensive maintenance, while also adding surface friction. Non-intrusive Sensors 48
107. Weather on the Go To supplement fixed RWIS mobile weather sensors are becoming increasing popular. When tied to an AVL system you are able to extend your road weather network. Measures: Air temperature Pavement temperature Dew Point Relative Humidity 49
114. data dissemination system that can provide near real-time atmospheric and pavement observations from the collective states’ investments in environmental sensor stations (ESS). www.clarusinitiative.org
120. Participation Status for Clarus as of August 24, 2011 *1st time showing mobile data sources! * Canadian Participation Local Participation City of Indianapolis, IN McHenry County, IL City of Oklahoma City, OK Kansas Turnpike Authority Parks Canada Clarus Connection Status Connected (37 States, 5 Locals, 4 Provinces) Connected plus vehicles (1 state) Pending (4 States, 3 Locals, 1 Province) Considering (3 States, 1 Local) Sensor & Station Count 2,253 Sensor Stations (ESS) 52,471 Individual Sensors 81 Vehicles * 55
130. Quality Checking Algorithms Step Test Like Instrument Test Observation compared to the same observation types from the ESS Observation compared to previous observations over a configured time range to determine if the rate of change (plus or minus) was acceptable Example: Values: 10 C, 12 C, 15 C, 35 C Test did not pass 59
131. Quality Checking Algorithms Persistence Test Dewpoint Test Observation compared to previous observations to determine if the values had changed at all over a period of time Example: Values: 38.6%, 38.6%, 38.7% Test passed Determine the neighbors Calculate a dewpoint value based on the temperature & relative humidity Conduct a spatial test 60
132. Quality Checking Algorithms Barnes Spatial Test IQR Spatial Test Observation compared to neighboring ESS and ASOS/AWOS to determine if they are similar Neighboring ESS and ASOS/AWOS identified Eliminate the neighbors that are +-350 meters Eliminate the highest and lowest neighboring values Observation compared to remaining neighbors to determine if they are similar Requires 5 initial neighbors for the test to run 61
133. Quality Checking Algorithms Sea Level Pressure Test Precipitation Accumulation Calculate a sea level pressure from the station pressure and then conduct a spatial test Conversion based on current 700mb Rawinsonde observations or 30-year average gridded data Applies to: 3-hour 6-hour 12-hour 24-hour Uses Stage II & IV precipitation files to accumulate the precipitation for comparison 62
134. Mobile Observations Data Need Elevation Observations are on the map for one hour Used in quality checking 63
135. Clarus Survey Conducted by ITSA from 15 June - 15 July 2011 Intent was to increase understanding of how Clarus is used by system customers 28 Participants: 13 State DOTs 6 private sector companies 4 academic institutions 3 Federal agencies 1 weather service provider 1 transit agency
136. Clarus Data Uses Monitor near real-time weather observations 61% use multi-state view 54% use in-state view Weather model input: 39% Evaluating maintenance needs on RWIS: 36% Use in other systems (e.g. 511) and weather forecasting: 29%
147. Vehicle Data Translator (VDT) Ancillary: Radar, Satellite, RWIS, Etc. VDT 3.0 Stage I Stage III Stage II Mobile data ingesters Segment module Inference Module Ancillary data ingesters QC Module QC Module Output data handler Output data handler Output data handler QC Module Parsed mobile data Advanced road segment data Basic road segment data Apps and Other Data Environments
160. Broad Transportation Applications VDT-based data Winter Maintenance – Which roads have been treated? Route Specific Impact Warnings for… Tornado Warning! I70 Denver to Limon Delay Until 3:30pm School Buses EMS Truckers
161. Weather-related Applications Numerical Weather Modeling Traffic Modeling and Alerting Weather Modeling – complex terrain Other surface transportation users
162. Integrated Mobile Observing & Dynamic Decision Support State DOT & Private Vehicle Data Connected Vehicle Data Capture VDT (NCAR) Clarus Other Connected Vehicle Applications
163. FHWA Road Weather Mgmt. Team Paul Pisano, Team Leader Dale Thompson FHWA Office of Operations USDOT RITA, JPO 202-366-1301 202-366-4876 paul.pisano@dot.gov dale.thompson@dot.gov Roemer Alfelor C.Y. David Yang FHWA Office of Operations FHWA Off. of Operations R&D 202-366-9242 202-493-3284 roemer.alfelor@dot.gov david.yang@dot.gov Gabriel Guevara Ray Murphy FHWA Office of Operations FHWA Off. of Tech. Services 202-366-0754 708-283-3517 gabriel.guevara@dot.gov ray.murphy@dot.gov
Notes de l'éditeur
Adverse weather is our common enemy in road maintenance,traffi c, and emergency operations. Transportation agenciesare well aware of the operational and logistical challengesof such weather. Many agencies are fighting this age-oldbattle by implementing Road Weather Information Systems(RWIS). This requires that critical personnel be well-informedof the impacts and considerations of deploying RWIS. Thegoal of this course is to, not only discuss RWIS initiatives andconsiderations, but through workshops, exercises, and selfassessments,explore individual state and local deploymentchallenges which will leave participants with an action plantailored for their specifi c needs.
The Federal Highway Administration, the Aurora RWIS Pooled Fund Program, and the AASHTO Snow and Ice Cooperative Program partnered to produce this RWIS ESS Siting Guidelines. The guide lines provide a set of recommendations to support uniform siting of sensor stations that collect road weather observations for road weather information systems. The guidelines will also facilitate the development of a nationwide, integrated road weather observation network, which will aid in mitigating the effects of adverse weather on the highway system.
Campbell Scientific -Can place in existing networks: Because the stations are NTCIP-compliant, they will work in networks that are supported by NTCIP-compliant software.-Hardware has no end-of-life: As long as we can get replacement parts, we will continue to provide support for all of our hardware.-Can replace existing stations: Because our RPU can interface with many different sensor types, and because it can be mounted on an existing tower and use the existing power supply, the cost of such a replacement is low.-Free phone support: from Application Engineers at Campbell Scientific – directions, troubleshooting-Onsite support: Campbell Scientific is not a licensed contractor, so onsite support is limited by agreement with contractor – support for existing equipment, training, troubleshooting-Making your own changes: Adding or removing measurements requires programming changes which are done by the customer through Campbell Scientific programming software.-Perform maintenance: Maintain your own equipment on your own schedule and with no charge from Campbell Scientific.-No Contracts: No contracts related to hardware, data, or software from Campbell Scientific. (Depending on communications methods, you may have contracts with phone or internet companies.)
Campbell Scientific -Any measurement can be made: Our RPU can read RS-232, SDI-12, Modbus, Analog Voltage, Pulse, and Digital signals directly, and can read RS-485 and 4-20 mA signals through external devices.
1U NTCIP MiniRWIS Compact Remote Processing UnitSpecifically designed to integrate into existing infrastructure (ATC & DMS cabinets & signs)Full complement of atmospheric and road sensorsBuilt-in Surge SuppressorsSelected sensors drive dry contact output enabling optional local control of public safety devices (WRTMS)
The key to good software is having good data coming from the field. Many RWIS vendors today promise low cost solutions, but what are the long term costs of maintaining and repair? Vaisala has the most experienced road experts in the industry to be there to support the customer. Our non-intrusive pavement conditions and pavement temperature sensors are unmatched in the industry. The non-intrusive sensors are the future of RWIS! Reducing cost to maintain, and are safer to repair because there is nothing in the roadway. Customers can choose a solution of a video camera, a non-intrusive pavement sensor, and a non-intrusive condition sensor for less than many low cost RWIS solutions. All while maintaining the high quality and reliability.
Mobile weather data is the future of the industry. With the FHWA connected vehicle initiative more and more vehicles will be added to the mobile network. With the advent of AVL, data can now be passed back to a central location in near real-time. This gives the decision maker more information to make the best decision possible. Vaisala offers the most accurate, most reliable sensors in the industry. We can now monitor pavement temperature, air temperature, relative humidity, and dew point from these mobile sensors. Soon we will even be able to monitor surface condition from a moving vehicle.
The Federal Highway Administration’s (FHWA) Road Weather Management Program (RWMP) continues to support Intelligent Transportation Systems (ITS) applications that focus on roadway safety and mobility and at the same time promote technology deployments that help balance society’s need to protect the environment and maintain stable economic conditions. The program collaborates with NOAA, departments of transportation in each state, an important and vigorous private sector, the academic community, and professional societies such as the American Meteorological Society and other nongovernmental organizations, including the American Association of State Highways and Transportation Officials. This presentation will provide an overview of the Clarus system, including a review of recent enhancements, and an update on mobile observing of weather and road conditions – including the Connected Vehicle Technology Challenge and the VDT (Vehicle Data Translator).
QCh Algorithms under review:Sea Level Pressure TestClimate Range TestBarnes Spatial Analysis TestPersistence TestSensor Range TestLike Instrument TestStep TestDew Point Temperature TestPlus the Manual Set FlagThe Completion Flag
- Customers: who uses the data, how they use it, how they get it, how often they use it, etc- 28 sample size is not very big; doesn’t meet statisticalminimum of 30 especially for such a diverse community
May want to ask the audience first before showing results to get their involvement; but may be time limitedWx model surprising #2 use – would not have guessed so high - 11 respondents with so few orgs who can run wx models. May be a result of folks thinking MDSS is a wx model – ok.3rd bullet: this is not evaluating general maintenance needs
Respondents were asked what is their primary means of accessing the data. 48% of respondents use the map service.
- Labeled new data “preferences” because survey question did not ask for “needs” per se,but “what data sources would be useful to their organizations”.- Note each response is independent from each other so %’s do not equal 100%.- Mobile data high rating because potential of mobile data getting a lot of “marketing” lately with smart phones, CV program, etc.
- Org impact may be the result of some DOTs just deciding to be wx-wise or not.“Clear primary” means the majority or top results had significant margins from results at next level i.e. large difference in % from #1 and #2.
The Clarus Initiative, established in 2004, is a multi-year program to organize and make available more effective environmental and road condition observation capabilities in support of four primary motivations: Provide a North American resource to collect, quality check, and make available surface transportation weather and road condition observations. Surface transportation-based weather observations will enhance and extend the existing weather data sources that will support general purpose weather forecasting. Collection of real-time surface transportation-based weather observations will support real-time operational responses to weather. Combining Clarus data with existing observation data will permit broader support for the enhancement and creation of models to enhance forecasts in the atmospheric boundary layer and near the earth’s surface.
Clarus is one of the “ancillary” data source feeding into Stage II of the process; Clarus and other data are used to perform quality checks on the mobile data and possibly support/enhance the mobile data used to make the inferences/roadway hazard assessments in Stage III
Derive data and communicationsrequirements for weather, road condition, and vehicle status variables from mobile platforms (Using State DOT vehicles as the source)Enhance and expand post-processing algorithms to turn the data into useful observations that are tied to existing mesonets (e.g., Clarus)Explore the use of these and other observations in weather-related decision support systems.Clarus will be transitioning over the next few years to the NWS mesonet as part of a “National Next Gen Network”. Schedule is TBDOther observations may include input from other mesonets and networks or State DOT information