Vaisala Visualization. November 2010 Petteri Leppänen

Transcription

1 Vaisala Visualization November 2010 Petteri Leppänen

2 Roads Web visualization offering sales price Road Weather Advisor Road Weather Observer Road Weather Navigator 2.0 RWDSS customer value Page 2 / date / name / Internal use / Vaisala

3 Road Weather Advisor Includes easy to set alarms Page 3 / date / name / Internal use / Vaisala

4 Road Weather Observer Page 4 / date / name / Internal use / Vaisala

5 Archiving for Navigator Page 5 / date / name / Internal use / Vaisala

6 Differences between the products Single station view (camera image, main parameters, configurable graph) Outcomes based messages Simple alert management Supports more than five stations Map view (station status, parameters) Thermal map Station summary list, Camera wall Forecast texts from service providers Timer slider (controls map, list and wall) Animated playback of map layers Historical data available Single-click PDF reports and data exports Advanced alert management Advisor Observer Navigator Page 6 / date / name / Internal use / Vaisala

7 Single site view with observed data Page 7 / date / name / Internal use / Vaisala

8 Forecaster generated texts show up in drop down boxes Page 8 / date / name / Internal use / Vaisala

9 Vaisala Solution (Icebreak) Icebreak is a mathematical model capable of simulating the changes in pavement temperature and state using information about the forecast location and forecasted atmospheric conditions. Icebreak s 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. Page 9 / date / name / Internal use / Vaisala

10 Vaisala Solution (Icebreak) 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. Vaisala s Icebreak model and RWIS serve as a foundation for accurate, timely road weather predictions Icebreak setup techniques help ensure that forecast accuracy is maximized. Additional products, such as Thermal Mapping, can be used augment and support pavement forecasting. Page 10 / date / name / Internal use / Vaisala

11 Icebreak Input Requirements Initial Road Weather Conditions Client Site Metadata Forecast Data Icebreak Navigator Display Page 11 / date / name / Internal use / Vaisala

12 Icebreak Client Site Data Location of forecast site (latitude, longitude) Elevation As-built properties of the pavement Road versus bridge Asphalt versus concrete Subsurface layer properties (type and thickness) Number and depth of sensors Surface roughness length A height which aids in understanding the impact of roughness elements such as trees or buildings on the wind. Sky view factor Used to gauge the obstructions on the forecast site. Obstructions impact the amount of radiation received at the site location. Each of these factors is essential in predicting the evolution of pavement conditions; however, a number of road weather providers don t attempt to account for all of these parameters. Page 12 / date / name / Internal use / Vaisala

13 Icebreak Initial Condition Inputs Properly assessing the initial atmospheric and road conditions is extremely important for forecast accuracy. Weather and road condition information can be used to initialize both NWP models* and Icebreak For Icebreak, the main source of initial conditions comes from RWIS Icebreak input data for initial conditions Weather Air temperature Dew point temperature Wind speed Precipitation status/intensity Road Pavement temperature Subsurface temperature(s) Pavement condition (i.e., dry, wet, icy, etc.) * NWP models rely mainly on weather and soil condition parameters Page 13 / date / name / Internal use / Vaisala

14 Icebreak Weather Forecast Inputs Atmospheric forecast data is used to help drive Icebreak Icebreak input forecast data Air temperature Dew point temperature Wind speed Precipitation status/intensity Cloud cover Page 14 / date / name / Internal use / Vaisala

15 Icebreak Output Pavement temperature Pavement condition Subsurface temperatures Air temperature Dew point temperature Wind speed Precipitation status friction in close future Page 15 / date / name / Internal use / Vaisala

16 IceNet Delivery Icebreak forecast (pavement temp) Observed Pavement Temperature Page 16 / date / name / Internal use / Vaisala

17 Coupling Icebreak Predictions and Thermal Mapping Icebreak will provide forecasts at point locations (typically RWIS sites) In cases where roads have been thermally mapped, Icebreak forecasts can be extrapolated to other sections of the roadway to provide an understanding of what is occurring between stations or forecast points* Extrapolated Forecast Forecast point Extrapolated Forecast *This can be done in none-precipitation situations during nighttime hours Page 17 / date / name / Internal use / Vaisala

18 Summary Icebreak is capable of supporting year-round maintenance activities by providing prognostic information regarding pavement temperature and conditions. Icebreak can support tactical and/or strategic decision making process. Data from RWIS are leveraged by Icebreak for effective pavement predictions. Site specific characteristics are used to enhance Icebreak forecasts Icebreak can be driven by Vaisala or third party supplied weather forecasts. Page 18 / date / name / Internal use / Vaisala

19 Time slider function allows you to browse into the future all data shown is then forecast values, color codes etc Page 19 / date / name / Internal use / Vaisala

20 Single site view when forecasts are available Now Page 20 / date / name / Internal use / Vaisala

21 Comparing critical values of your choice Page 21 / date / name / Internal use / Vaisala

22 Road surface nearly dry with some chemical present Road surface now wet with chemical present (melted snow) Snow overwhelmed treatment and settles on road Snow melted again back to wet roads with chemical present Page 22 / date / name / Internal use / Vaisala

23 Road surface wet with active chemical present note embedded sensor gives freezing temperature below RST Freezing temperature now above sub zero RST hence ICE forms on the road New treatment restores wet roads with sufficient chemical to lower freezing temperature Page 23 / date / name / Internal use / Vaisala

24 Introduction to Thermal Mapping Page 24 / date / name / Internal use / Vaisala

25 Depth Temperature Sky View Rural Proximity to water Wind Road Surface Cloud Temperature Traffic Volume Road construction Humidity Altitude Tunnels Urban Page 25 / date / name / Internal use / Vaisala Road surface Bridges Air temperature

26 Factors affecting Road Surface Temperature Static Sky View Urban environment Rural environment Proximity to water/sea Bridges Tunnels/Underpasses Road construction Road surfaces Altitude Road Surface Temperature Variable Cloud Humidity / Dew Point Wind speeds Depth temperature Air Temperature Traffic volumes Page 26 / date / name / Internal use / Vaisala

27 Factors affecting Road Surface Temperature No one factor has complete control Sky View 70% of the variability However construction has massive impact Page 27 / date / name / Internal use / Vaisala

28 Variable factors can have different affects Clear skies Day Allow sunshine on the road giving it extra heat Night allows heat to escape fast dropping temperatures quickly Wind Calm Cold air sinks next to surface creating cold layer, heat is drawn out of the road more quickly. Windy warmer air aloft bought down to the surface warms the road/stops heat loss. Traffic Rush hour traffic makes location a warm site lots of extra heat Sunday morning can mean location suddenly becomes colder than usual. Page 28 / date / name / Internal use / Vaisala

29 Modelling Road Surface Temperature (RST) RST is the final product No one factor dictates what it is or will become Static Factors are always the same so drop out of the equation once a site is known (Thermal Mapping shows this for a whole network). Variable Factors need more care and attention Models are written to take into account heat balance equations Page 29 / date / name / Internal use / Vaisala

30 What forecasters do Site specific forecasts verified by observed data RST model run by specifying key weather variables Air Temperature Dew Point Cloud Cover Wind Speed Precipitation Each has a significant effect on the RST at the site Final output is an estimation of RST at that site throughout 24 hr period Page 30 / date / name / Internal use / Vaisala

31 What Vaisala do Thermally Map the road to identify how fixed variable effect the RST on average conditions Damped Cloudy/windy/rainy Extreme Clear/still/dry Intermediate somewhere in between the two Output is a repeatable temperature variation measurement across the whole network based upon all fixed factors. Weather variables are held fixed by choosing similar characteristic nights to survey on. Results different by category, cold spots tend to stay the same but not always. Temperature variations most noticeable under Extreme conditions Page 31 / date / name / Internal use / Vaisala

32 Put them together Forecasters cover the variable factors Vaisala cover the Fixed factors By combining the two you can get a representation of all factors in one Time Step Thermal Maps How does it work? Page 32 / date / name / Internal use / Vaisala

33 Using Thermal Fingerprints Warmer location Average Network Temperature Colder location Page 33 / date / name / Internal use / Vaisala

34 Using Thermal Fingerprints, how repreentative is one point measurement only? Page 34 / date / name / Internal use / Vaisala

35 Forecast Thermal Maps can also be animated Page 35 / date / name / Internal use / Vaisala

36 Animated radar on same screen Page 36 / date / name / Internal use / Vaisala

37 Other forecast relevant map layers available on demand Air Temperature GLD360 Lightning Data Page 37 / date / name / Internal use / Vaisala

38 Traffic Counting Page 38 / date / name / Internal use / Vaisala

39 Alert Function for visibility Page 39 / date / name / Internal use / Vaisala

40 Alert Setting for Slippery Conditions Page 40 / date / name / Internal use / Vaisala

41 Alert Setting for High Winds Page 41 / date / name / Internal use / Vaisala

42 Your total solution for weather management Technology Services End-user applications Measurement instrumentation Communication solutions System design User interface Product services Observation services 24/7 customer commitment Data quality monitoring Customer Training Road weather prediction Ice and snow warning Wind warning Fog warning Route Optimization Rain warning Thermal Mapping Page 42 / date / name / Internal use / Vaisala

43 We are ready are you? Page 43 / date / name / Internal use / Vaisala

44 Page 44 / date / name / Internal use / Vaisala Thank you