## 1 Introduction
This explains why, in recent years, the interest on road ice formation has increased in many countries and networks of sensors have been placed for monitoring the state of the asphalt together with some weather stations for gauging atmospheric conditions. These sensors are capable of measuring the presence of water, ice or snow, surface humidity and temperature, while weather stations measure standard atmospheric variables like air temperature and humidity, wind, and precipitation. Although the knowledge of real time road conditions plays a relevant interest, the prediction of the same quantities may be crucial for the activation of road winter maintenance service and safety. Therefore, operational weather warning services are needed to mitigate the effects of adverse weather conditions on roads [8]. This requires enough observations and skilful models to predict their conditions. Since different methods of forecasting the ice risk have been developed, various strategies can be followed focusing the attention on different aspects also depending on the context and on the geographical area. However, two main approaches can be defined for the development of a forecast model: the physically based approach, considering the energy balance equation on the surface for the prediction of the Land Surface Temperature (LST) and the empirical/statistical one. Both the approaches address the same final goal: an accurate prediction of road surface temperature and state (dry, wet, frost, or ice) which may be a valuable information for authorities and organizations that can decide where and when the interventions have to be put in place [9]. Models based on physical equations of hydro-meteorological processes at road surface have been introduced by several authors in the past [10; 11; 12; 13]. For instance, the Deutscher Wetterdienst (DWD) introduced SWIS (Starsenzustands und Wetterinformationssystem) as a nationwide road weather information system, in order to forecast road conditions and surface temperature over a time period of 27 h by an energy balance model [14], while the Finnish Meteorological Institute developed RoadSurf, a modelling system for predicting road weather and surface conditions [15]. Other operational examples exist in many countries as the Model of the Environment and Temperature of Roads (METRo) developed by Environment Canada to predict road conditions and temperatures [16], the road condition model implemented by the Danish Meteorological Institute (DMI) with external forcing by their operational limited area model [17] to produce road weather forecasts for pre-defined sites, which are equipped with observing devices, and the model developed by MeteoS consult in the Netherlands, which has made progress in producing road condition and temperature forecasts for the road network by using the output from an energy balance road model, with high resolution weather forecasts and data concerning sky and sun view factors on the routes [18]. Therefore, it is clear how a reliable system for forecasting the LST and, consequently, the presence of ice is definitely one of the best tools to make the winter road maintenance service effective and efficient, in order to reduce both the frequency of accidents and the waste of salt. In this paper, we proposed a study of an algorithm developed by the Meteo Expert Centre (MEC) based on land surface temperature (LST) forecasts and, afterwards, applied for predicting ice risk. As described above, several methods have been developed to forecast the LST value, based on the energy balance equations that provide precise results, but involve a large amount of data [19; 20]. The MEC algorithm, instead, has the advantage of being fast and operationally easy to apply as it is based on a joint distribution of those variables which influence the road temperature and ice formation. The developed algorithm calculates the expected LST value and an ice alert code between 0 (absence of ice) and 3 (high risk), through a linear function of the weather model output parameters.