The impact of screening on road surface temperature

The impact of screening on road surface temperature Meteorol. Appl. 7, 97 104 (2000) J Bogren, T Gustavsson, M Karlsson and U Postgård, Earth Sciences Centre, Physical Geography, Göteborg University, Box 460, SE 405 30 Göteborg, Sweden 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 (RST diff ) that develop during clear day conditions can be attributed to solar elevation (β) and can be expressed by the equation: RST diff = 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: RST diff = A B h+c h 2 D h 3 E h 4 +F h 5, 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. 1. Introduction Winter road maintenance is an important field for local climatological research. Maintenance engineers require highly accurate short-period forecasts. During the last ten years different models for predicting ice and frost have been developed and both road maintenance engineers and meteorologists are now using them as a valuable technique for making decisions about winter road maintenance (Bogren, 1990; Thornes & Shao, 1992; Bogren & Gustavsson, 1994; Hertl & Schaffar, 1998). The acceptance and use of a road weather information system (RWIS) provides the maintenance engineers with advanced knowledge of temperature development. Information on where and when slippery road conditions are likely to occur is also provided. This information is a valuable tool for making decisions about where and when to take proper preventive action. A well-developed RWIS makes it possible to take preventive action against risk of slipperiness by effectively optimising the use of salt and other winter maintenance operations. Optimising salt usage is important as excessive use may lead to vehicle corrosion and problems with construction work. There is also a risk of soil and water resources being affected (Jutengren, 1995; Bäckman & Folkesson, 1996). In addition there is growing concern about the effects of frequent road salting on roadside vegetation development (D Itri, 1992; Brod, 1993). A RWIS can act as a very important tool in minimising salt usage. At present the Swedish RWIS consists of more than 600 field stations sited in different topographical and geographical environments. The system provides the road authorities and maintenance engineers with accurate information about air temperature, road surface temperature, humidity, wind and precipitation. From the RWIS it is also possible to receive forecasts of cloudiness, road surface temperature and dew point temperature. These forecasts are specially designed to give four-hour prediction of road conditions. Traditionally these forecasts are designed individually for each station in the RWIS. Recent research and model development within the field of applied climatology at Göteborg University has shown that by using a Local Climatological Model (LCM) it is possible to calculate a temperature pattern along a stretch of road, and hence increase the available information (Bogren et al., 1992; Gustavsson & Bogren, 1993). Knowledge about local climate and how temperature variations along roads affect the risk of icy conditions is a key factor in improving early detection. This knowledge is also crucial for the different models used for maintenance today. Variations in road surface temperature (RST) along a road are, to a great extent, determined by climatological and weather related parameters where microclimatological factors in particular have a great impact. Topographical aspects, different types of road construction materials and different radiation conditions contribute to the risk of temperature variations. Previous studies on the influence of climatological factors on RST show that large temperature variations can occur over short distances (Bogren & Gustavsson, 1990). The largest temperature variations are particularly pronounced during clear 97

J. Bogren, T. Gustavsson, M. Karlsson and U. Postgård weather since these conditions provide the potential for large variations in radiation components in the energy balance. During clear calm nights the pooling of cool air is an additional factor creating large temperature variations (Bogren & Gustavsson, 1991). When clear daytime conditions prevail the effect of shading significantly affects the temperature variations and thus the risk of slipperiness. This is especially marked during spring and autumn (Bogren, 1991). One problem with daytime forecasting of road surface temperatures is that large temperature differences occur when comparing screened and sun-exposed locations. To be able to predict the surface temperature at screened locations and to calculate the temperature patterns for entire stretches of road, the impact of screening must be known. It is essential to be able to calculate the potential differences between sun-exposed and screened locations during the day to make a reliable forecast of RST. Another requirement is to include the lag effects due to screening when calculating RST after sunset. The magnitude of the screening impact is dependent on several factors, the most important being the amount of incoming solar radiation (itself dependent on the time of the day and the season). The object of this study is to analyse temperature variations caused by shading of the road surface during clear daytime conditions. The analysis will focus on the following factors: (a) the relationship between solar elevation and temperature differences between screened and sunexposed areas; (b) the significance of temperature differences between screened and sun-exposed areas during the day for the establishment of temperature variations after sunset; (c) the time it takes after sunset for the temperature difference caused by shading to decline. conditions every 30 minutes which means that the temporal resolution is high. Thermal mapping (mobile temperature recording) gives information about the temperature pattern along entire stretches of road where data is collected every 10 metres at a specific measuring point. Specification of the instruments and levels for measurements are given in Table 1. Data from RWIS have been used for analysing the road surface temperature differences (RST diff ) between sunexposed and screened areas on clear days in terms of solar elevation. RWIS data have also been used for analysing the relation between RST diff during the day and that prevailing after sunset, based on data from 165 separate recordings. The data used are for the period October to April 1994 1997. The establishment of temperature variations during the day and after sunset together with the lag effect are also verified by thermal mapping. The RWIS stations used in this study present different types of screening objects with varying orientation shading the road surface; a nearby, open and well-exposed site is used as a control (Table 2). The thermal mapping used in this study was performed during clear daytime conditions (cloudiness < 4 oktas) from February April 1992 in the county of Halland and from February April 1994 and December 1994 April 1995 in the county of Skaraborg. The thermal mapping has been performed in such a way that coverage of open and forested sites within a short distance is obtained. This is important in order to reduce the influence of variations in regional climate and weather on the RST. From the thermal maps it is pos- An analysis of the magnitude of the factors controlling the temperature variations caused by screening objects along the road will form a valuable input for improvement of the present forecast models. It is also fundamental as a criterion in the LCM for stretch-wise temperature information. 2. Methods and data The analysis of the impact of screening on RST variations is based on data from two sources: (a) field stations in the RWIS and (b) thermal mapping from the study area in south-west Sweden (Figure 1). Data from the RWIS provides continuous information about the RST together with information about atmospheric conditions (air temperature, humidity, wind and precipitation) at different sensor locations. The stations record 98 Figure 1. Map of the study area, south-west Sweden.

Table 1. Instrument specifications for the measuring equipment The Impact of screening on road surface temperatures Parameter Level Time constant Accuracy Range Sampling Instrument (m) interval RWIS station Air temperature 2.0 10 s ±0.5 C 40 to +60 C 30 min Rotronic Mp300 Humidity 2.0 <20 s ±2% 0 to 100% 30 min Rotronic Mp300 Wind speed 5.0 Threshold = 0.4 m s 1 30 min Vaisala,WAA15 Wind direction 5.0 Threshold = 0.3 m s 1 30 min Vaisala,WAV15 Road Surface 0 30 min Pt100 temperature Mobile measurement Road surface 0 1 s ±0.3 C 25 to +75 C Every 10 min Heimann temperature KT 15 SMD sible to detect how the influence of various orientations, geometry and size of the screening objects affects the RST and how the temperature pattern is repeated throughout the measuring period. The thermal mapping routes in the county of Halland mainly follow a west east direction on Roads 25, 26 and 150, starting in the flat open coastal area and progressing into the elevated and forested eastern part. In the county of Skaraborg the thermal mapping of Road 47 has been used for the analysis since it has a northwest southeast orientation characterised by an open undulating topography in the north-west part and dense forests in the south-east part (Figure 1). 3. Results 3.1. Screening The impact of screening on road surface temperature is illustrated in Figure 2. The RSTs which are plotted in the diagram represent four different station locations: one open and well exposed and three that are screened during different periods of the day (morning, noon and afternoon). The recording is from the beginning of March when the solar elevation reaches a maximum of 27 above the horizon at latitude 58 N. It is obvious from the curves that the effect of screening has a great influence on the RST depending on when it occurs during the day. When a screening effect is well established around noon, a difference of 10 C is evident at 14.00 h (local time). Another important feature of the magnitude of the screening effect is that the drop in temperature is almost immediate when a site is screened, as happens, for example, when a screening object shades from the south-west to produce an afternoon screening effect. The change from being sun-exposed to screened results in an immediate decrease in surface temperature, the RST dropping 7.5 C in less than one hour. Within a very short period of time large RST differences can be established along a stretch of road thus creating potentially hazardous road conditions. It can be assumed that the RST differences established during the day create a temperature deficit that continues after sunset. Although the difference declines during the afternoon it has the potential to create a temperature lag effect after sunset. 3.2. Solar elevation road surface temperature variations The assessment of the relationship between solar elevation and RST diff between sun-exposed and screened areas is derived from the comparison of maximum RST diff and the maximum daily solar elevation for the period investigated (October April). The criterion for inclusion of a screened site is that the shade on the road surface is well established at noon (1200 1500 h). Solar elevation (β) varies according to: sin β = sin ϕ sin δ + cos ϕ cos δ cos h where ϕ is the latitude of the site, δ is the solar declination and h is the hour angle. The declination can be described by a good approximation as a function of the day of the year N: δ = 23.4 cos[360(n+10)/365] Maximum solar elevation (β max ) thus varies according to: β max = (90 ϕ) ± δ At latitude 58 N the β max varies from 9 in December to about 40 in March. These conditions make it interesting to consider the RST diff between screened and sun-exposed sites as a function of solar elevation. In an earlier study by Bogren (1991), it was stated that the relationship between solar elevation and RST diff can be predicted by the equation: RST diff =-1.47+0.47 β 99

J. Bogren, T. Gustavsson, M. Karlsson and U. Postgård Table 2. Site characteristics of the RWIS Station Altitude Orientation of Site characteristics (m asl) the road Screened sites 1601 95 24 Road rock cut on both east and west sides of the road. 1603 125 5 Screened by deciduous trees lined on both sides close to the road. The station is sited on the western side of the road. 1608 5 34 Dense coniferous forest on both side of the road. 1622 250 112 Road rock cut combined with hillside, screening from south to west. 1516 75 85 Road rock cut and dense forest towards south and west screening the road surface. 1517 105 60 Line of coniferous forest in combination with road rock cut on the south-eastern side of the road. 1308 90 95 Dense coniferous forest in combination with hillside giving screening form south and south west. Reference sites 1601 95 Small valley surrounded by open arable land. Remote sensor for road surface temperature in road rock cut 150 m to the south. 1620 230 Open well exposed area. 1522 5 Large well exposed open area. 1307 10 Open flat area, well exposed. Figure 2. Screening effect at RWIS stations, located in latitude 58 o N, with different orientations shading the road at different times of the day. Data from 8 March 1996. Figure 3. Observed relation between maximum solar elevation and maximum RST diff during clear daytime conditions. See Table 2 for site characteristics. However, by having access to a more comprehensive set of data it can be concluded from the analysis that it is necessary to modify this equation. In the study area, seven different pairs of screened sun-exposed locations were used for establishing such a relationship, so allowing the addition of more data to the previous formulae. Figure 3 illustrates the relationship between solar elevation and maximum RST diff. From analysis of the data it is obvious that solar elevation can be used to predict the maximum RST diff during clear conditions. The relationship can be expressed by the equation: RST diff = 2.7+0.46 β (1) From this it can be seen that during December/January, when solar elevation reaches just 9 above the horizon, 100 the temperature difference is quite small, only 1.4 C. Later, towards the end of March when the solar elevation (β) is 35, the RST difference increases to more than 13 C (Table 3). To verify this relationship and to transfer it to stretchwise temperature information, thermal mapping tests were carried out along Roads 25, 26 and 150 in the county of Halland on the Swedish west coast. These roads have a pronounced west to east orientation and the surrounding vegetation alternates between open sun-exposed areas and dense forested areas. The screening characteristics make it most suitable for this kind of analysis since the potential for input of screening is high. Table 4 shows the variation in maximum RST diff, recorded by the thermal mapping, between sun exposed and shaded areas on 5 February, 4 March and 30 March for these stretches. A comparison between

The Impact of screening on road surface temperatures Table 3. Seasonal variation in solar elevation and calculated RST diff at latitude 58 N during clear day conditions. Date Maximum solar Calculated maximum elevation β max RST diff 1 October 29 10.7 15 October 24 8.3 1 November 18 5.6 15 November 14 3.7 1 December 11 2.4 15 December 9 1.4 1 January 9 1.4 15 January 11 2.4 1 February 15 4.2 15 February 20 6.5 1 March 25 8.8 15 March 30 11.1 1 April 35 13.4 recorded and calculated values using equation (1), shows a fairly good agreement since the absolute difference ranges between 0.1 C and 3.1 C and the mean error for the nine occasions is 1.0 C (see Table 4). The distribution and magnitude of the screening effect, recorded along a road stretch by thermal mapping, is illustrated by Road 25 (shown in Figure 4). The first 7- km stretch is bounded by open fields which are then succeeded by forest. In the forested part, several open glades cause breaks in the shade on the road surface. From the thermal mapping performed at noon on three separate occasions during winter along Road 25, it is clear that there are three main screening effects. (a) There is a distinct and immediate drop in the RST within a very short distance in screened areas. (b) There is a reoccurrence of the shadow pattern throughout the season in those areas where the forest is high and dense. (c) There is an increase in the RST diff as a function of solar elevation as the season proceeds. 3.3. RST difference after sunset Analysis of the RST differences that develop during the day and their effect after sunset reveals the temperature deficit at screened sites several hours after sunset is prolonged. Depending on the magnitude of the RST diff during the day, the temperature difference may be prolonged for several hours. Figure 5 illustrates the effect of varied magnitudes of RST diff during the day and the differences after sunset at station 1620 compared with 1622 (see Figure 1 for the locations). The lines in the graph represent 1 January, 15 February and 1 April and are expressed as functions of the respective time of the season. It is obvious that a relatively large magnitude of Figure 4. Thermal mapping during clear day conditions at noon along Road 25 for (a) 5 February, (b) 4 March and (c) 30 March, 1992. The first 7-km stretch is characterised by open fields while forests intersected by glades dominate the rest of the route. The RST is plotted as the difference from the areas with full sun-exposure. RST diff during the day is required to produce a significant difference after sunset. During January, a RST diff of about 2 C is not enough for it to continue after sunset. Not until February is RST diff discernible after sunset. In mid-february, for example, the RST diff during the day is 6.5 C, which results in a 2 C difference at sunset and a 1.5 C difference four hours later. It can be assumed that temperature differences that are detected after sunset in the screened areas are dependent on the magnitude of the incoming solar radiation during the day. Although a large temperature difference develops during the day between sun exposed and 101

J. Bogren, T. Gustavsson, M. Karlsson and U. Postgård Table 4. Variations in maximum RST differences between screened and sun-exposed areas. A comparison of results from thermal mapping and calculated values. Date Observed maximum RST diff Calculated Absolute difference ( C) maximum RST diff (observed calculated) ( C) ( C) Road 25 Road 26 Road 150 Road 25 Road 26 Road 150 5 February 6.2 4.8 5.6 4.9 1.3 0.1 0.7 4 March 8.8 9.8 11.1 9.5 0.7 0.3 1.6 30 March 14.8 10.1 13.3 13.2 1.6 3.1 0.1 screened areas, the difference after sunset is relatively small. According to the measurements plotted in Figure 5, the screening effect is very small (less than 2 C) during December and January. It takes until mid-february for the solar elevation to reach a height sufficient enough to produce a large enough daytime temperature difference for that difference to remain after sunset. When the RST diff increases to 7 C during the middle of the day (4.5 hours before sunset) a 2 3 C difference in magnitude is maintained after sunset. In April, when the solar elevation produces a midday difference of 13 C, a 5 C difference remains at sunset. The results indicate that screening effects after sunset must be considered during early autumn and late spring. The reduction of the RST diff after sunset is quite slow provided that RST diff is maintained after sunset. The difference of 5 C seen immediately after sunset in April is reduced by 1 C during the first hour, but the difference still remains four hours after sunset. A case study for verification of the temperature pattern along a stretch of road with screened areas as well as exposed areas has been carried out along Road 47 in the county of Skaraborg (Figure 6). The road has a mainly north-west to south-east orientation which means that objects on the southern side cast a shadow pattern on the road surface from midday onwards through the afternoon. The first 16 km of this stretch of road is mainly open but then becomes screened by dense forest. Thermal mapping was carried out during clear calm weather on 27 March at (a) sunset, (b) 1 h 30 min after sunset and (c) 3 h after sunset. When the (a) measurements were taken at sunset there was a pronounced drop in RST when the vehicle entered the forested section of the road in the eastern part. The magnitude of the temperature drop was, at this time, 6 C where the shadow pattern was dense. When the (b) measurements were taken 1 h 30 min after sunset the magnitude of the temperature change was 3.5 C, and the (c) measurements after 3 hours showed a drop of 2.5 C in the screened section. When combining the information from the thermal mapping measurements with the RWIS recordings it can be seen that they are in agreement. 102 Figure 5. Variation in magnitude of the RST diff during the day and differences after sunset. Differences between station 1620 and station 1622 are used for the calculation of the curves. The temperature difference at and after sunset can be calculated using data obtained from the relationship between station 1620 and 1622 (illustrated by the plot in Figure 5). Using values for three different periods, the expression for 1 January, 15 February and 1 April can be written as follows: RST diff = A B h + C h 2 D h 3 E h 4 + F h 5 where h is the time in hours after sunset and A to F are constants related to the time of the year. The actual numbers of the constants can be related to site specific conditions. 4. Conclusions The conclusions that can be drawn from this study are as follows. (a) It is clear that solar elevation during the day determines the potential for development of road surface temperature differences between screened and exposed areas. (b) This difference can be calculated using equation (1). (c) There is a correlation between of the RST diff which develops during the day and the temperature differences at and after sunset.

The Impact of screening on road surface temperatures Figure 6. Thermal mapping along Road No 47 performed at (a) sunset, (b) 1 h 30 min after sunset and (c) 3 h after sunset on 27 March 1995. The progressing solar elevation situation in the April case means that the effect after sunset is very well marked, thus indicating a pronounced maximum difference during the day. During weather conditions characterised by cold clear settled weather with light winds, the effect caused by the shading of the road surface is especially important. The screening effect also favours the formation of hoar frost. The position and extent of the shading is crucial since there needs to be both an obstruction of incoming short-wave radiation and a maintenance of relatively large net outgoing long-wave radiation. This also means that the conditions along the roads can change due to tree growth or constructions that can alter the shading pattern. 5. Discussion The importance of taking the screening effect into consideration when dealing with modelling of road surface temperatures is obvious. The measurements and the results presented in this study of temperature variations between screened and sun-exposed sites show that they are of considerable magnitude especially during spring and autumn. The influence of daytime RST differences on the RST after sunset is important not only for modelling the temperature pattern for stretches of road but also for the accurate development of site-specific forecasts. For further studies it would be interesting to analyse data from latitudes lower than 56 N, with particular consideration given to the impact of solar elevation on RST diff and the temperature after sunset. Site-specific models for prediction of RST and correction of local climatological deviations have been dealt with in previous studies (Thornes & Shao, 1991; Sass, 1992; Shao et al. 1993; Bogren & Gustavsson, 1994; Shao & Lister, 1995; Jacobs & Raatz, 1996). However, the idea of making RST data valid for entire stretches of road demands that the effects of local topography on temperatures is treated and included in a systematic and dynamic way. One approach in dealing with modelling of stretch-wise temperatures is the use of a local climatological model (LCM). The LCM developed at Göteborg University can be described as a dynamical model, which considers the variety of topography and changes in weather conditions along stretches of road. Another area where the knowledge of local climatological effects such as screening or pooling of cold air is important is in applying RST information to aid the safety of road users. At present RST and air temperature data are presented on electronic signs at a few selected sites along the roads. However, it is essential to make drivers aware that this temperature information is site specific and that totally different conditions may occur within a very short distance. A solution to this problem could be to present temperature variations along stretches of road thus providing more diversified information according to variations in local climate. Possible future developments include the presentation of information about road conditions on computer screens in vehicles or displayed on variable message signs along roads. Acknowledgements This research has been financially supported by the Swedish National Road Administration (SNRA). The study is part of the project Applied road climatology for increased traffic safety (Grant: Winter project no. 263-52/5110). 103

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