Experimental service for high-resolution slipperiness risk forecasts in Finland
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1 ID: 11 C O N S U L T I N G Experimental service for high-resolution slipperiness risk forecasts in Finland Pirkko Saarikivi 1 and Mikko Malmivuo 2 1 Foreca Consulting Ltd Tammasaarenkatu 5, FI Helsinki, Finland pirkko.saarikivi@forecaconsulting.com 2 VTT Technical Research Centre of Finland, mikko.malmivuo@vtt.fi
2 Background Weather forecasting models have improved considerably, and now it is possible to develop forecasts and warnings for road stretches with 10 km spatial resolution. Finnish Road Administration and Foreca Ltd developed a road condition pilot service in February-April 2007 for Main road 8 between Turku and Pori 140 km long road was divided into 11 stretches Road is coastal and known to have rapid changes in road conditions
3 User interface Users were very fond of the service made with Flash/xml-techniques. Lots of information but shown in a clear way.
4 Road condition warnings Rain freezing on cold road surface Slipperiness due to snow fall Wet road surface is freezing Risk for hoar frost Colour codes tell if a warning is issued for a certain 2 hour period
5 Weather during the pilot Lämpötila helmikuu maaliskuu huhtikuu Temperature in Turku and Pori during the pilot Pori lämpötila Turku lämpötila End of winter 2007 was mostly mild with two periods of cold weather in February
6 Forecast statistics Road stretch from south to north Av. air temp Av. road temp Hoar frost Snow fall Road freezing Freezing rain Hoar frost Snow fall Road freezing Freezing rain o C o C kpl kpl kpl kpl % % % % 1 Turku-Raisio -0,54 0, ,08 % 7,52 % 3,34 % 0,05 % 2 Raisio-Masku -0,54 0, ,10 % 7,74 % 3,24 % 0,00 % 3 Masku-Kaitarainen -0,53 0, ,72 % 7,67 % 2,85 % 0,00 % 4 Kaitarainen-Mynämäki -0,49 0, ,27 % 7,91 % 3,07 % 0,00 % 5 Mynämäki-Nästi -0,53 0, ,72 % 8,66 % 4,88 % 0,15 % 6 Nästi-Laitila -0,67 0, ,05 % 7,83 % 3,91 % 0,03 % 7 Laitila-Ihode -0,75 1, ,52 % 7,40 % 3,18 % 0,00 % 8 Ihode-Rauma -0,78 1, ,47 % 6,11 % 3,24 % 0,00 % 9 Rauma-Eurajoki -0,94 1, ,62 % 6,50 % 3,35 % 0,00 % 10 Eurajoki-Luvia -1,06 0, ,93 % 7,33 % 4,73 % 0,00 % 11 Luvia-Pori -1,16 0, ,33 % 7,42 % 5,69 % 0,00 % Total -0,73 0, ,07 % 7,46 % 3,77 % 0,02 % Statistics show that there is variability between road stretches About 7% of warnings were generated due to hoar frost of snow fall Freezing road or rain were very unfrequent
7 Mean temperature Mean temperature of air and road surface 1,50 1,00 0,50 0,00-0,50-1,00-1, S road stretch N Keskim. ilman lt Keskim. tienp. lt Mean air temperature Mean road surface temp Mean temperature gets logically colder towards North Road surfaces are warmest along the road stretch Laitila-Ihode
8 Road condition warnings Relatve amount of risk warnings 12,00 % 10,00 % 8,00 % 6,00 % 4,00 % 2,00 % 0,00 % Kuura Lumisade Märkä tie jäätyy Sade jäätyy tienpintaan Hoar frost Snow fall Wet road freezing Rain freezing on road ro ad s tre tc h Warnings for hoar frost increase towards Pori (north) Lots of warnings also along Mynämäki-Nästi stretch
9 Frozen road or rain Case 17th February, Red area: Service predicted well area of freezing rain Cases with freezing rain are rare. Fortunately, as they are most dangerous to road transport. Model predicted well the two cases during pilot tests
10 Conventional web service Six-hourly road weather forecast on FinnRA s web service. The main roads are coloured green, yellow or read depending on the risk level due to road conditions
11 Comparing the risk warnings Pilot and conventional warnings compared. Red columns on the left show all Pilot warnings combined. Columns on the right show the conventional road condition warning with three severity levels.
12 Conclusions Road condition pilot functioned technically well Users liked the looks and the user interface of the service Model resolution was good enough for 10 km road stretches Warnings were justified in most cases, but sometimes the variability from one hour to next was disturbing Warning generation limits should be developed to avoid unnecessary warnings when risk for slipperiness is low Warnings should include measure of the intensity of risks
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