31 October 2015 A statistical forecast model for road surface friction Marjo Hippi Ilkka Juga Pertti Nurmi Finnish.

Slides:



Advertisements
Similar presentations
RT6 Plenary Prague GA Examples of FMIs work Ari Venäläinen, Kirsti Jylhä Ilmatieteen laitos.
Advertisements

Wisconsin DOTs MDSS RFP Experience March, 2005 Tom Martinelli Winter Operations Engineer.
PHYSICALLY BASED MODELING OF EXTREME FLOOD GENERATION AND ASSESSMENT OF FLOOD RISK L. S. Kuchment, A. N. Gelfan and V. N. Demidov Water Problems Institute.
Extension and application of an AMSR global land parameter data record for ecosystem studies Jinyang Du, John S. Kimball, Lucas A. Jones, Youngwook Kim,
Snow Pack Analyser, May Snow Pack Analyser SPA.
Fighting the Great Challenges in Large-scale Environmental Modelling I. Dimov n Great challenges in environmental modelling n Impact of climatic changes.
Open data based RWIS for mobile devices Mikael Holmström, Intrinsic Oy.
IRWIN IRWIN Improved winter index for maintenance and climate scenarios Torbjörn Gustavsson Pirkko Saarikivi, Dave Rayner, Jörgen Bogren, Caroline Tengroth.
Development of high spatial resolution Forest Fire Index for boreal conditions Applications to Helsinki Testbed area - Preliminary results- Andrea Vajda,
Welcome to Weather Science Jeopardy GeneralKnowledge Weather Factors I Weather Factors II ForecastingTools Final Jeopardy.
/ RM. EJ Research on climate changes and its consequences NordFoU Workshop January 29th, 2007.
ENVIRONMENTAL AGENCY OF THE REPUBLIC OF SLOVENIA/National Weather Service Structure of national warning system MET. Forecasts Department Civil.
Climate & Transportation R&D program conducted by the Norwegian Public Roads Administration , cca 2,5 mill € Update design, construction, operation.
Predicting the Weather. Weather Forecasting Meteorologists are scientists who study the causes of weather and try to predict it. –They analyze data and.
Mobile friction observations and thermal mapping in Testbed area Helsinki Testbed mesoscale course Toni Hellinen and Marjo Hippi.
1 Winter Operations Program Presented by Ken Greene October 10, 2011.
MDSS Challenges, Research, and Managing User Expectations - Weather Issues - Bill Mahoney & Kevin Petty National Center for Atmospheric Research (NCAR)
Lecture 10 (11/11) Numerical Models. Numerical Weather Prediction Numerical Weather Prediction (NWP) uses the power of computers and equations to make.
Detection of Soil Freeze/Thaw Processes using SMOS and ELBARA-II Finnish Meteorological Institute (FMI) K. Rautiainen, J. Lemmetyinen, J. Pulliainen, A.
© Crown copyright Met Office Operational OpenRoad verification Presented by Robert Coulson.
1 The Evolution of METRo in a Roadway DSS Seth K. Linden Sheldon D. Drobot National Center for Atmospheric Research (NCAR) SIRWEC 15 th International Road.
4-1 Lesson 4 Technology: Resources and Implementation.
NWS Situational Awareness Update: Winter Weather Impacts National Weather Service Forecast Office – Fort Worth/Dallas 230 PM Thursday February 6, 2014.
Zhang Mingwei 1, Deng Hui 2,3, Ren Jianqiang 2,3, Fan Jinlong 1, Li Guicai 1, Chen Zhongxin 2,3 1. National satellite Meteorological Center, Beijing, China.
Modelling of Acid deposition in South Asia Magnuz Engardt Swedish Meteorological and Hydrological Institute (SMHI) Introduction to Acid deposition.
Civil Engineering Research Institute for Cold Region, PWRI, JAPAN Method for Calculating the Amount of Accumulated Snow Transported.
REGIONAL DECISION SUPPORT SYSTEM T. Bazlova, N. Bocharnikov, V. Olenev, and A. Solonin Institute of Radar Meteorology St. – Petersburg, Russia 2010.
Buckinghamshire County Council 1 Winter Service Presentation to Members November 4 th
15th International Road Weather Conference February 5th - 7th, 2010 in Québec City, Canada By Naoto Takahashi*, Roberto Tokunaga* & Naoki Nishiyama **
P. Ñurmi / WWRP QPF Verification - Prague 1 Operational QPF Verification of End Products and NWP Pertti Nurmi Finnish Meteorological Institute.
Evaluation of climate change impact on soil and snow processes in small watersheds of European part of Russia using various scenarios of climate Lebedeva.
Best Practices on Monitoring Deployment Road Weather Monitoring Conclusions Yrjö Pilli-Sihvola Finnish Road Administration.
SIRWEC 2010: 15th International Road Weather Conference Quebec City Convention Center, 5-7 February 2010, ROADIDEA Session (Topic R) The Effects.
Suitability of the new paradigm for winter observation of road condition Mr. Rok Kršmanc, Ms. Alenka Šajn Slak, Mr. Samo Čarman CGS plus d.o.o., Slovenia,
LAPS __________________________________________ Analysis and nowcasting system for Finland/Scandinavia Finnish Meteorological Institute Erik Gregow.
END-USER FOCUSED VERIFICATION OF PRECIPITATION NOWCASTS DURING THE SOCHI 2014 WINTER OLYMPICS Larisa Nikitina 1, Suleiman Mostmandy 2, Pertti Nurmi (presenter)
INSTYTUT METEOROLOGII I GOSPODARKI WODNEJ INSTITUTE OF METEOROLOGY AND WATER MANAGEMENT TITLE : IMPLEMENTATION OF MOSAIC APPROACH IN COSMO AT IMWM AUTHORS:
Meteorological Data Analysis Urban, Regional Modeling and Analysis Section Division of Air Resources New York State Department of Environmental Conservation.
Refinement and evaluation of the suspension emission model Mari Kauhaniemi Research Scientist Finnish meteorological Institute, Air Quality, Dispersion.
National Oceanic & Atmospheric Administration Real-Time Transportation Infrastructure Information Systems: Applications.
René Kelpin German Aerospace Centre, Institute for Transport Research ROADIDEA Data Collection 15th International Road Weather Conference, Quebec City.
An air quality information system for cities with complex terrain based on high resolution NWP Viel Ødegaard, r&d department.
A Decision Support Tool for Highway Maintenance: A First Principle Thermal Mapping Model & Edward E. Adams WTI / MSU Bozeman, MT Allen R. Curran ThermoAnalytics.
Climate Change: Past, Present, and Future Dr. Cameron Wake Climate Change Research Center Institute for the Study of Earth, Oceans, and Space (EOS) University.
Weather The amount that air presses on the earth is called… Air pressure.
Winter Weather Homeroom Read. Warm Up: Define WINTER WEATHER ADVISORIES WINTER STORM WATCH WINTER STORM WARNING FROST/FREEZE WARNING.
OMI Science Team 2014, Anders Lindfors / FMI OMI cloud optical depth contributes to the observed positive bias in surface UV Anders V. Lindfors, T. Mielonen,
Planning, development and implementation of a Mobile Winter Maintenance Centre Authors: Bent Juhl Pedersen, M.Sc.EE, Danish Road Directorate Kim Niels.
Briefing by: Roque Vinicio Céspedes Finally Here! The MOST awaited briefing ever! February 16, 2011.
Estimation of Stone-loss on network condition surveys by use of multiple texture lasers Thomas Wahlman, Peter Ekdahl,
Snow Pack Analyser, March Snow Pack Analyser SPA.
Working together to advance Road Weather Information Systems (RWIS) technology.
1 Initial Investigation Red River of the North Floods March, April 2009 OHD Mike Smith, Victor Koren, Ziya Zhang, Naoki Mizukami, Brian Cosgrove, Zhengtao.
COSMO General Meeting Zurich, 2005 Institute of Meteorology and Water Management Warsaw, Poland- 1 - Simple Kalman filter – a “smoking gun” of shortages.
Snow modelling using Surfex with the Crocus snow scheme for Norway Dagrun Vikhamar-Schuler 1 and Karsten Müller 2 1 MET.NO, 2 NVE.
Formation of pancake ice in a wave field Hayley Shen, Stephen Ackley Clarkson University and Mark Hopkins USACRREL NSF/McMurdo Ground Station Science.
Evaluation of cloudy convective boundary layer forecast by ARPEGE and IFS Comparisons with observations from Cabauw, Chilbolton, and Palaiseau  Comparisons.
CONTROL OF BIRDS AND OTHER WILDLIFE AT AIRPORTS Aga M3-13 Bird migration enroute…. Photo Tapani Kuoksa AIP ENR
1 The Use of METRo (Model of the Environment and Temperature of the Roads) in Roadway Operation Decision Support Systems The Use of METRo (Model of the.
Development and evaluation of the suspension emission model Mari Kauhaniemi Research Scientist Finnish meteorological Institute, Air Quality, Dispersion.
Snow modelling using the Surfex-Crocus snow scheme Dagrun Vikhamar-Schuler and Karsten Müller 1 1 Norwegian Water Ressources and Energy Directorate (NVE)
Tayba Buddha Tamang Meteorology/Hydromet Services Division Department of Energy Ministry of Economic Affairs South Asian Climate Outlook Forum (SASCOF-1)‏
Road Weather Information Network Systems
Meteorology and Weather Forecasting
ANALYSIS OF TEMPERATURE INFLUENCE ON SKID RESULTS
Method and techniques of NMA forecasts
Looking for universality...
Road Weather Information Systems (RWIS)
Runway Weather Information Systems & Grip
The FMI Road Weather Model, Applications and Projects
Presentation transcript:

31 October 2015 A statistical forecast model for road surface friction Marjo Hippi Ilkka Juga Pertti Nurmi Finnish Meteorological Institute

31 October 2015SIRWEC 15th International Road Weather Conference, 5th - 7th February 2010, Quebec, Canada2 Winter in Finland Snow and ice may exists on roads almost 6 months per year in Finland In north roads are covered by snow and ice most of the winter whereas in south roads are tried to keep clear of ice and snow always when possible Ice and snow reduce friction In case of low friction values risk of traffic incidents rise

31 October 2015SIRWEC 15th International Road Weather Conference, 5th - 7th February 2010, Quebec, Canada3 Friction model :: Background Friction means the grip between tires and road surface The amount of water/ice/snow on the surface as well as an estimation of friction can be measured by Vaisala DSC111 sensor FMI has developed a statistical friction model based on observations made by DSC111 sensor The model is running for points installed with DSC111 sensor The friction model was developed to help road maintenance personnel and meteorologists Also, product for drivers in ROADIDEA pilot Vaisala DSC111 sensor Vaisala DSC111 sensors in Finland

31 October 2015SIRWEC 15th International Road Weather Conference, 5th - 7th February 2010, Quebec, Canada4 Road weather classification Classification by Finnish Road Administration

31 October 2015SIRWEC 15th International Road Weather Conference, 5th - 7th February 2010, Quebec, Canada5 Observed friction vs. snow+ice and water on the surface a)b) Anjala’s observations winter Observed friction with ice and/or snow on the surface (water content in mm) Observed friction with water on the surface.

31 October 2015SIRWEC 15th International Road Weather Conference, 5th - 7th February 2010, Quebec, Canada6 Developed friction model Own formulas for snowy/icy, wet/damp and dry situations Friction is a function of depth of snow/ice/water on the surface Small temperature dependency in case of snow/ice on the surface A - E are coefficients Minimum value for friction 0.10 and maximum 0.82 Used formulas were developed using Utti’s data observed in winter Same formulas in use for all computation points

31 October 2015SIRWEC 15th International Road Weather Conference, 5th - 7th February 2010, Quebec, Canada7 How does the friction model work? All input data available on FMI’s road weather model  Friction formulas included into FMI’s road weather model Model takes into account weather parameters, precipitation, melting/freezing, evaporation/condensation, traffic wear, traffic heat, turbulence, … Initialization is done by running the model with observations (48 hours) Forecasted values up to 48 hours Input data Depth of ice/snow/water Road surface temperature Output data Friction Simulation

31 October 2015SIRWEC 15th International Road Weather Conference, 5th - 7th February 2010, Quebec, Canada8 Simulated results :: modeled vs. observed Observed (OBS) and modeled friction (FC) in case of icy and/or snowy roads. Correlation a)b) Simulations for Anjala’s point using independent data Observed (OBS) and modeled friction (FC) in case of water on the road. Correlation 0.97.

31 October 2015SIRWEC 15th International Road Weather Conference, 5th - 7th February 2010, Quebec, Canada9 Implementation Google.maps application presents 3 hour forecast of expected road weather Temperature Friction Road condition Produced in collaboration with FMI, Destia and Demis Also, a mobile phone application available Information of road weather (including friction), road weather pictures, warnings given by other users Produced in collaboration with FMI, Destia and Logica

31 October 2015SIRWEC 15th International Road Weather Conference, 5th - 7th February 2010, Quebec, Canada10 Results Model simulates cases of poor friction very well, but… Friction model produces often too low values for friction too long time FMI’s road weather model has too big storages for ice The lack of road maintenance action More discussion on validation in next presentation by P. Nurmi / FMI

31 October 2015SIRWEC 15th International Road Weather Conference, 5th - 7th February 2010, Quebec, Canada11 Problems Finnish road weather model has usually too much ice (and frost) on the surface  too low values for friction Need to develop the wearing of ice in the model Need to improve influence of traffic Common problem in road weather forecasts: no information about road maintenance actions available Modeling presents situation if no maintenance actions have been done

31 October 2015SIRWEC 15th International Road Weather Conference, 5th - 7th February 2010, Quebec, Canada12 Conclusions and future Friction model is a new and innovative product Results are not as good as expected, but the problems are known Testing, evaluating and developing is an ongoing process Define station specific correlations at all computation points