Search

The object of this study is to examine the possibility of developing a model that can determine road surface adjustment times to new conditions after weather changes. Situations where the weather changes from clear to overcast conditions are studied in order to produce a worst-case scenario. One hypothesis tested is that the decrease in road surface temperature (RST) differences between shaded and sun-exposed stations on clear days can be used to determine the reduction in RST difference on days with weather changes. A relationship that describes the variation in RST difference as a function of time of day and season is developed. For clear days a fourth-order polynomial can describe the relationship between RST differences and time of day. The coefficient in the polynomial depends on maximal solar elevation. Validation of the model for clear days showed that the deviation between modelled and measured values varied between 0.3 and . It was also possible to use the clear day relationship to predict the decrease in RST differences for situations with weather changes, but during these situations the deviations between modelled and measured values were higher and also tended to show a positive bias. Copyright © 2001 Royal Meteorological Society

The sky view factor (SVF) is used in forest, road and urban climatology to characterise radiative properties. We now propose a method suitable for forest canopies using the raster based and commercially available software IDRISI. It uses quadratic pixels in rows and columns in a scanned equiangular fish-eye image. A threshold value is chosen to divide the image into sky and non-sky areas. The resulting image is then multiplied with a sky view weight image, where the weights of the pixels depend on the angular distance from zenith. The sum of pixel products gives the SVF. Quality analysis of the method is also performed. The choice of threshold value gives some uncertainties due to leaves reflecting sunlight. This error will be reduced by observing details (branches etc.) in the image and by choosing an overcast day for capturing the image. The precision range for SVF calculations will be better than 0.1.

In this study, thermal mapping along the road and recordings from field stations in the Swedish Road Weather Information System (RWIS) are analysed. The purpose is to explore how long it takes for air and road surface temperatures to adjust from clear to overcast conditions after a warm front arrival, and to see if there are any variations in reaction time between the two temperatures. The study also focuses on whether different sitings affect the adjustment time when the warm front arrives and if the time of arrival is important for the resulting temperature variations. The results show that weather preceding the front, temperature difference when the front arrives, arrival time of the front, wind speed and the occurrence of precipitation all have an effect on the adjustment time. Air temperature reacts faster to a weather change than the road surface temperature. During the evening the road surface temperature can still be affected by previous shading for up to four hours after a front arrival. When the total cloud cover increases above 4 oktas before noon there are no or small lags in reaction time between air and road surface temperature, since there is insufficient time to establish shading effects. Copyright © 2001 Royal Meteorological Society

The effect of screening on road surface temperatures is analysed using data from the Swedish road weather information system (RWIS) together with data from thermal mapping. The study deals with the analysis of temperature variations caused by shading of the road surface during clear daytime conditions and focuses on the relation between solar elevation and magnitude of road surface temperature differences between screened and sun-exposed areas. Also included is an analysis of how the temperature differences during the day affect the establishment of temperature variations after sunset and the time it takes after sunset for temperature differences caused by shading to decline. The results show that the magnitude of road surface temperature differences between sun exposed and screened sites (RSTdiff) that develop during clear day conditions can be attributed to solar elevation (β) and can be expressed by the equation: RSTdiff = −2.7 + 0.46(β). A relationship between the daily maximum temperature difference and the preservation of the screening effect after sunset is observed. The effect after sunset can be described by: RSTdiff = A − B h + C h2 − D h3 − E h4 + F h5, where h is the time in hours after sunset and A to F are constants related to the time of the year at the actual site. Copyright © 2000 Royal Meteorological Society

The objective of this paper is to focus on the influence of clouds and wind on air and road surface temperature variations between different types of local climate environments. The study area covers 160×130 km2 and includes 35 field stations in the Swedish Road Weather Information System (RWIS) and two synoptic weather stations. By combining data from the two sources, the spatial and temporal variations in air and road surface temperature have been analysed. In the first part of this paper the theoretical influence of different weather parameters is determined. In the empirical part of the study, a validation of the theoretical result is assessed using temperature and weather data from the study area. The results show that it is possible to calculate the temperature variations in relation to topographical siting and different weather factors. During day-time conditions, the effect of screening from the sun has a significant influence on the road surface temperature, even with cloudiness amounting to 4–6 octas, provided that the solar elevation is high. During night-time, the potential for pooling of cold air is determined by cloud cover and wind speed. When cloudy situations prevail during night-time, neutral stability is dominant resulting in a decrease with increasing altitude for both air and surface temperatures. Road surface temperatures, however, have a lower correlation with altitude than air temperature. The variation in surface temperature decreases with altitude is also larger and has a more even distribution than the air temperature decrease with altitude. Wind speed was not an important factor for the variation in surface temperature decrease with altitude, but insolation from the sun during day-time is one parameter to consider. Copyright © 2000 Royal Meteorological Society