In Finland, the international ICAO (Internetional Civill Aviation Organization) standard is used for raporting runway weather conditions.The rapport includes e.g. runway weather conditions and snow/slush layer thickness. There has been no automatic system for measuring layer thickness and numbers are only based on sensory estimations and spot checks with measuring ruler. The layer thickness estimation is difficult, because the general picture from even 18 hectares (0,11 square miles) area must be produced quickly.
In Finland, both Vaisala Oyj (DSP310) and Teconer Ltd (RCM411) have developed an optical road weather sensor, which reports e.g. the road weather condition type and layer thickness (figure 1). In this study, the ability of DSP310 and RCM411 to measure layer thickness, road weather class and friction in runways has been tested.
The layer thicknesses founf from the runway are typically very low. Slush and wet snow layers can be few millimetres at maximum, dry snow 2-3 centimeters at maximum. Very thick layers can be demanding for optical sensors, because of the technical limitations. According to the tests, the road weather sensors estimated over 10 mm layers either too low or unrecognizable.
The optical road weather sensors express the layer thickness as “water equivalent”, in other words as a number, which describes the water layer height after the snow, slush or ice layer has been melted. In this study, the water equivalents of sensors has been compared to the equivalents measured by weighting the snow, slush or ice.
When the highest layer thicknesses are outside the examination, we could estimate, that the road weather sensors expressed the layer thickness as indicative. If these sensors are used as a support for layer thickness estimations, the user should have broad experience of sensor behaviour in various conditions. According these tests, it cannot be recommended, that sensor information would be the only source of information, when estimating layer thickness.
On the other hand, sensors seem to be quite reliable when assessing runway weather classification. If the runway weather type is irregular, these sensors could give fairly reliable picture of runway weather distributions.We have already observed in our earlier studies, that sensor’s ability to classify the condition into bare or winter type condition is very accurate.
In this study, the friction measuring ability of these sensors has been compared to the BV-11 friction meter, a meter widely used in airports. The correlation between sensor friction and BV-11 friction wasn’t as good as the correlation between sensor friction and braking friction meters on roads in earlier studies.