Virve Karsisto, a researcher at the Finnish Meteorological Institute, a road weather modelling researcher of the Green InterTraffic project, investigated how road surface temperature observations can best be used to determine the initial state of a road weather prediction model. The more accurate the initial state of the model is, the better are the chances for the model to make a good forecast.
Traditionally, road weather stations have been the most important source of observations, but nowadays it is possible to obtain real-time observations from new sources such as cars. The quality of mobile measurements was investigated by comparing the road surface temperature measurements made with a vehicle mounted device to the road weather station measurements.
“The difference between mobile and road weather station measurements depended on whether the road surface was dry, wet or icy,” says Virve Karsisto. “For example, when there is ice on the surface, the optical device measures the temperature of the ice, not the actual road surface,” Karsisto explains.
The study developed a circumstance-based calibration equation to better match mobile observations with road weather station observations. Using calibrated mobile observations in the model initialization improved the forecasts compared to a theoretical situation where road surface temperature observations were not available. In contrast, forecasts using mobile observations were about as accurate as forecasts using observations from other road weather stations in an area with dense road weather station network.
Mobile observations were utilized in the road weather model by using a radiation correction method. The radiation correction method adjusts the amount of radiation received by the surface in the model so that the road surface temperature given by the model corresponds to the observed temperature. According to the study, the method can significantly improve road surface temperature forecasts.
“The radiation correction method makes it possible to improve the road weather forecast even if only one observation is available at the forecast point. Of course, the observation must be fresh enough”, Virve Karsisto sums up.
Virve Karsisto defended her doctoral dissertation entitled "Observing and forecasting road surface temperatures" on November 1, 2019 in the Faculty of Science, University of Helsinki. The opponent was professor Lee Chapman from University of Birmingham and professor Heikki Järvinen from the University of Helsinki served as the custos.
The dissertation is available at Helda: http://hdl.handle.net/10138/306438
More information: email@example.com November 2019