Proceedings of the 20th SIRWEC conference, Druskininkai, Lithuania (14-16th June 2022)

SIRWEC (The Standing International Road Weather Commission) exists to encourage meteorologists, weather forecasters, highway engineers, road masters and others, who are interested in road weather problems, to exchange ideas to make our roads safer to drive on in all weather conditions. Every two years SIRWEC conference is being organized to gather all of the road weather enthusiasts and encourage them to share new scientific discoveries they have accomplished, new products or technologies they have made or any other topic in road weather field

Dabarties ir ateities žiemos kelių orų sąlygų prognozavimas Lietuvoje (santrauka)

This thesis is about climate change impact to transportation system and mostly focused on road maintenance and traffic safety in winter. The impact of climate change is evaluated by creating specific road weather climate projections for 21st century of indices that represent meteorological road condition affecting phenomena. According to these projections, road and traffic conditions in winter will get better on average – there will be less blizzards, air temperature will be higher. However, winter road maintenance will remain challenging – there will be a higher probability for ice formation on roads and ensuring good road condition will be a demanding task. Winter road maintenance decision support systems (MDSS) are popular worldwide and are considered as a best tool for short- and long-term winter road maintenance task planning. This work proposes a type of MDSS for Lithuania that shall decrease the vulnerability to climate change of Lithuanian transportation system. Lithuanian MDSS could include methods that were already successfully applied in Lithuania – thermal mapping and numerical road weather forecasting. Both MDSS components are evaluated and verified in this work. In combination, these methods and MDSS technology in Lithuania would greatly benefit road maintenance professionals. Lithuanian MDSS shall help ensure good road conditions during winters and reduce the number of traffic accidents

Thermal Mapping in Flat Lowlands and Undulating Uplands – A Comparison of Results

Thermal mapping has been known as a reliable technique to analyse and even predict road surface temperature in a stretch of road, rather than just a single point (e.g. road weather station location). The method itself was developed in the 1980s, and as time progressed, the technique was improved and has become more applicable. Due to other methods, such as climate modelling, becoming widely accessible and more affordable to apply, thermal mapping started being pushed out to the background as an expensive alternative. The idea for this paper arose from thermal mapping applications to Lithuanian roads that produced inconclusive results in some research areas and raised the question of whether this technique applies to flatlands as effectively as to uplands. The Czech Republic was chosen as a country with an available database and environmentally different road network. Several stretches of road thermal mapping data were analysed and compared. It was concluded, that in flat landscapes altitude has lesser predictability value for road surface temperature than in undulating uplands. In addition, thermal mapping results appear to be more inconclusive in flatlands, compared to uplands. Nevertheless, thermal mapping is a good and reliable method for determining cold spots

An adapted accumulated winter season severity index (AWSSI) for Lithuanian winter evaluation

Winter severity evaluation has been a difficult task to crack for climatologists for decades. This task becomes even more burdensome once this evaluation needs to represent a certain application or task effectiveness, like winter road maintenance. Thus, the AccumulatedWinter Season Severity Index (AWSSI) has been calculated in hopes to get an accurate and objective index for winter road maintenance task difficulty assessment. After initial evaluation, it was noted, thatAWSSI performed a lot better than previously usedindices, thusit was decided to improve the methodology and make it a bit more suitable for Lithuanian climate, more applicable to Lithuanian RWIS network and less dependent to climate change.A several methodology changes were performed and an adaptation of AWSSI was created.The resulting adapted AWSSI is a great tool to determine winter severity for road maintenance. It was shownthat the index correlates well with performed winter road maintenance tasks and material usage. Thus, it can be used in various fields, e.g., long-term forecasts and planning, and currently is being used to determine a part of worker wages