Overview on RWIS, Clarus with CT DOT on Sept. 28, 2011 Ray Murphy

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

3. Agenda Wednesday, September 28, 2011 09:30-09:40Welcome 09:40-10:30RWIS 10:30-10:45BREAK 10:45-11:20Clarus 11:20-11:30Wrap-up 3

4. Self-Introductions Name Position/Role Any specific area of interest with Road Weather Management? 4

7. December - 10.4 inches

8. January - 12.3 inches

12. Environmental Sensor Stations 2,253 Sensor Stations (ESS) 52,471 Individual Sensors 8

14. 10

15. Gaps – data/operational Gaps – data/operational The Clarus System (screen shot) 11

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

18. Examples of ESS Sensors 14

20. ESS Location Relative to Roadway 16

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

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

28. Forensic meteorologists can use ESS data to better understand and reconstruct roadway crashes.

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

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

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

43. Added maintenance responsibilities

44. Utilizing the data

45. Communications

46. Varied Users

47. Liability28

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

51. Increase efficiency

52. Increase effectiveness

53. Provide the highest level of service possible30

54. Road Weather Information System Environmental Sensor Station Siting Guidelines 31

57. Maximize investments in ESS

59. Encourage compiling & maintaining metadata33

61. Update with new technology & metadata information

62. Three State DOT’s were interviewed for their evaluation of the Guidelines:

63. Michigan DOT

64. Idaho Transportation Department

65. New Hampshire DOT34

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

71. Better defines thermal characteristics

72. Help identify similar areas

73. Optimize the number of ESS to be installed

74. Portable sensor systems help identify:

75. potential permanent ESS sites

76. the use of non-intrusive sensors (not requiring implanting in/below pavement)37

78. Siting recommendations are designed to satisfy as many road weather monitoring, detecting and predicting requirements as possible.

79. Siting decisions are best made by a team of transportation operations, road maintenance, and weather experts.

80. Siting recommendations encourage uniformity in siting, application and participation in the greater community.38

81. New Hampshire input 39

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

83. Non-Intrusive Detection/Applications Disclaimer: FHWA does not endorse any 3rd party vendor products and/or services 41

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

87. Wet & Icy Warnings

88. High Wind Warnings

90. Rain & Stream Gauging

91. Weather Stations

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

94. Flat Plate window & lens guard simplifies lens cleaning.

95. Wi-Fi access simplifies set-up and calibration from ground level

96. One-Click Automatic calibration45

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

99. Measurement of water film height

100. Measurement of ice percentage in water and determination of freeze temperature

101. Measurement of friction

102. Fully integrated surface temperature measurement (pyrometer)

103. Electric Isolation

104. Easy to mount

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

108. 15 minute Break 50

109. Clarus and the Connected Vehicle Ray Murphy Federal Highway Administration September 28, 2011 Meeting with Connecticut DOT

111. To do so, FHWA created a robust

112. data assimilation,

113. quality checking, and

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

116. One database removes borders

117. Provides advanced quality checking for both atmospheric & pavement data

118. Includes extensive metadata

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

121. Clarus System Observations

123. government agencies (federal, state, local)

124. academic institutions

125. weather providers

126. TV stations

127. private sector firms

128. unknown sources (Internet providers, etc.)

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%

137. ClarusAccess Methods Map: 48% On-demand request: 26% Subscription: 22% Other: 4%

138. New Data Preferences Mobile Data: 81% Air Quality: 50% ASOS/AWOS: 46% Other: 20% Response Frequency 67

140. Main use of data is monitoring current weather

141. Map is the main access method

143. Connected Vehicle Scenarios 70

144. Connected Vehicle “Anytime, Anywhere Road Weather Data” 71

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

149. Transportation-specific applications

151. Fill in the gaps between fixed stations

153. What are the current roads conditions?

154. Accurate pavement temperature modeling

155. Manage Maintenance Actions

156. End of Shift Reports

158. Alerts from other vehicles

159. Re-routing*Simulated screen – designed to not distract the driver

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