Temperature differences in the air layer close to a road surface

Transcription

1 Meteorol. Appl. 8, (2001) Temperature differences in the air layer close to a road surface Jörgen Bogren, Torbjörn Gustavsson and Maria Karlsson, Laboratory of Climatology, Physical Geography, Department of Earth Sciences, University of Göteborg, Box 460, SE Göteborg, Sweden In this study, profiles of temperature and humidity (<250 cm above the road and 5 m into the surroundings) have been used to examine the development of temperature differences in the air layer close to the road. Temperature, humidity and wind profiles were measured, together with net radiation and observations of road surface state, at a test site at Road 45, Surte, Sweden. Measured temperature differences were compared with present weather, preceding weather, surface status, wind direction and other parameters thought to be important for the development of temperature differences. The results showed that large temperature differences (1 3 C between 250 cm and 10 cm above the road) occurred when there was a high risk of slipperiness caused by hoarfrost, snow or ice on the road. The temperature differences between different levels were associated with the exchange of humidity and temperature between the air layer and the road surface. The 10 cm level reflected the surface processes well. Higher levels were influenced by the surroundings because of turbulence and advection. This study emphasises the need for measurements to be taken at a height and place that reflects the processes at the road surface. 1. Introduction Road climate research spans a wide range of subjects that all, in some way, concern surface temperatures and slipperiness on the road surface. Over the past fifteen years, most road climate research has concentrated on the development and improvement of models to predict the state of the road surface. The method and input data differ between models. (a) Rayer (1987), Parmenter & Thornes (1986) and Sass (1992, 1997) use numerical calculations of heat conduction or energy balance based on meteorological data, such as air temperature, wind speed, humidity, cloud data, etc. (b) Shao & Lister (1996) and Jensen (1985) use numerical calculations as well but the model is designed so that the measured data at road weather stations, road temperature, air temperature, wind speed, wind direction and precipitation are sufficient as input data. (c) Some models use statistics from road station data and mobile measurements to construct regression equations for road temperature (Roodenburg, 1984). (d) Bogren et al. (1992) and Gustavsson & Bogren (1993) use an empirical formula to extrapolate the temperature from road weather stations for different sections of the road and different weather conditions. In the models where road station data are used, the parameters are usually measured and recorded at a road station network. The measuring stations are situated at the side of the road in various environments that have a high risk of slipperiness during different weather conditions. The location of the measuring sensor is also important in road climate studies. The accuracy of the forecast depends not only on the quality of the model but also on the accuracy of the measuring sensors. The field stations should cover different environments with a high risk of slipperiness during different weather situations, and the sensor should be installed at a height and place that is representative of the climate at the road (see Bogren & Gustavsson, 1989). The questions to be answered are: Is the location representative for the road climate? Is the measuring equipment recording a local climate that is not valid for the road surface? For practical reasons the measuring equipment is usually situated a couple of metres from the road at the meteorological standard measuring height. A study by Chen et al. (1998) showed that the temperature gradient in the air layers close to the road surface can be large during certain weather situations. In a study on road slipperiness during warm air advection, Gustavsson & Bogren (1990) showed that large temperature differences occur between the road surface and the air layer above the road surface. When estimating the state of the road surface it is important to be aware of how the temperature gradient in the air layer close to the road surface develops dur- 385

2 J Bogren, T Gustavsson and M Karlsson ing different weather situations. Since the calculations of dew point in the RWiS (Road Weather information System) are based on measurements taken at 2 m, large temperature differences in the air layer can result in misleading predictions of when hoar-frost will form on the road surface. In order to increase understanding of the development of temperature differences above a road surface, a number of parameters such as regional weather, recent weather, surface status and time of day were measured and analysed. The aim of this study was to: (a) investigate the temperature differences between the location of road weather stations and the air layer above the road surface; (b) study temperature differences between the air layer above the road surface and the surrounding air during different weather situations; (c) study the factors which influence the development of the recorded temperature differences. 2. Method 2.1. Study area The observations presented in this paper were recorded during winter and spring, Measurements were taken at the Swedish National Road Administration test site at Road 45 in the county of Västra Götaland (12 E, 58 N). The test site is situated on a four-lane highway at Surte and consists of an asphalt plane approximately 30 m long and 10 m wide in contact with one lane of the highway. The road runs northwards along the east side of the Göta river valley (approximately 1 km wide) with hills and forest to the east and the Göta river and agricultural land running parallel to the road to the west. Temperature data received from the SMHI (Swedish Meteorological and Hydrological Institute) weather station in Säve, 4 km from the test site, are displayed in Table 1. This gives a general description of the temperature during the two measuring seasons. On average, the measuring period 1996/97 was colder than normal except for February and March, whereas the measuring period 1997/98 was warmer than normal. However, deviations from the normal mean are not larger than would be expected from year to year. Although the mean temperature was above 0 C for some months, several days with frost were recorded for the period December to March. Figure 1 shows the number of days with frost and precipitation during the measuring season and gives an indication of the number of days when there was risk of slipperiness on the road surface Instrumentation The test site is equipped with a monitoring system with sensors situated at 0.3, 0.9 and 2.0 m. Between October and May, temperature, humidity, wind speed and wind direction are measured at each of these heights. The surface temperature is measured with a probe in the middle of the slow speed lane. Sensors are also installed at depths of 0.05, 0.10, 0.15, 0.20 and 0.30 m for measurement of heat flow in the roadbed. Apart from the original instrumentation the test site was also equipped with extra sensors for this project. A denser measuring profile provided the temperature at five levels above the road surface (0.1, 0.4, 1.0, 1.5 and 2.5 m), humidity at three levels (0.1, 1.0 and 2.5 m) and net radiation at one level (see Table 2). The temperature gradient was also measured a few metres from the road, in a profile with two levels. The extra equipment took measurements every 10 seconds and stored an average in a logger (Campbell Cr10) every 10 minutes. An RWiS station measuring air temperature, humidity, wind speed, wind direction, road surface temperature and precipitation is also situated at the test site. Measuring levels and instrument data are shown in Table 2. Before and after each measuring season the temperature and humidity instruments were calibrated and intercompared. Figure 2 shows how the test site and measuring profiles are located in relation to the road. Table 1. Temperatures recorded at the SMHI station at Säve. Month 386 Normal mean temperature ( o C) Temperature ( o C) 1996/97 Temperature ( o C) 1997/ Mean Minimum Mean Minimum December January February March April May

3 Temperature differences in the air layer close to a road surface Figure 1. Number of days with frost (air temperature 0 C) and number of days with precipitation during the two measuring seasons. Table 2. Instrument specifications for measuring equipment. Parameter Level Time Accuracy Range Sampling Instrument constant frequency Test site Air temperature 0.3, 0.9, 2.0 m 10 s ±0.5 C 40 to +60 C 30 min Rotronic Mp300 Humidity 0.3, 0.9, 2.0 m <20 s ±2% 0 100% 30 min Rotronic Mp300 Wind speed 0.3, 0.9, 2.0, 5.0 m Threshold = 0.4 m s 1 30 min Vaisala,WAA15 Wind direction 5.0 m Threshold = 0.3 m s 1 30 min Vaisala,WAV15 Road temperature 0, 5, 10, 15, 30 min Pt100 20, 30, 50, 100 cm Road mast Temperature 0.1, 0.4, 1.0, 1.5, <10 s ±0.1 C 10min Pt m Net radiation s 10 min Campbell Q7 Humidity 0.1, 1.0, 2.5 m 15 s (90%) ±0.5% 0 100% 10 min Vaisala, HMP 243 Surroundings Temperature 1.0, 2.5 m <10 s ±0.1 C 10 min Pt Analyses Measurements were taken during the period December 1996 to May 1997 and the period December 1997 to May This resulted in a total of 200 days of data. The recorded data were analysed in order to identify weather situations in which large temperature differences occurred in the air layer close to the road surface. Statistics for the whole dataset and for the case studies were used in the analyses. The whole dataset has been analysed with regard to the development of temperature differences between the different levels. Because the focus is on those days where there is a risk of slipperiness, the statistical analyses have only been performed on days with temperatures between 10 C and +5 C. In order to assess the importance of prevailing and preceding weather, the dataset has been sorted into nine weather classes according to cloud and wind data. These weather classes have been chosen to represent weather situations ranging from clear and calm to 387

4 J Bogren, T Gustavsson and M Karlsson Figure 2. The position of the measuring profiles in relation to the road. cloudy and windy weather situations. In this way it becomes possible to identify when large temperature differences can be expected and how they are related to wind and cloudiness. The classification of weather data into weather classes and the frequency of each class are shown in Table Temperature gradients Both the road surface temperature and the air temperature at 2 m change in a similar way, with only small differences between them, during cloudy and windy situations. However, large differences can occur during changing weather or clear, calm weather. Furthermore, such situations occur frequently enough to warrant investigation. Figure 3 shows an example of a weather situation with large temperature differences between the air and the road surface. This occurred on January 1995 when a warming occurred at the test site, and the figure shows the development of dew point, air and road surface temperatures. The weather, observed at the SMHI station in Säve, was mostly clear with wind speeds of 3 5 m s 1 (10 m above ground). At the test site the wind speed was 1 3 m s 1 (5 m above ground). The ground was covered with 9 cm of fresh snow which had fallen the day before. Air and road surface temperatures were almost the same before the warming started. A temperature difference of about 3 C was established when the warming began. According to the dew point temperature, calculated from the 2 m level, hoar frost should theoretically form on the road surface during this situation. However, this ought not to be inferred without reference to the temperature gradient below 2 m or observations at the site. Temperature differences in the air layer close to the road surface must be known if the development of slipperiness is to be accurately predicted. The problem is Table 3. Weather classes, classified on the basis of wind and cloud data from Säve (4 km west of the test site). Weather class Cloud Wind speed Frequency of measuring (oktas) (m s 1 ) Number of observations period (%) 388 Day Night Day Night > > >

5 Temperature differences in the air layer close to a road surface Figure 3. Development of road surface and air temperatures measured at an RWiS station (Road Weather information System) during a warming situation from 24 to 25 January Dew point is calculated from the temperature and humidity at 2 m. Figure 4. Development of the temperature profile over 2 hours on 29 January The temperature profile is shown every 20 minutes and temperature is measured at 10, 40, 100, 150 and 250 cm above the road surface. further illustrated in Figure 4 where the temperature profile above the road during a cooling situation is shown. The figure shows the temperature differences that can occur in the air layer below a height of 250 cm. The temperature gradient changes from near zero, when the cooling starts, to a difference of 1.3 C between 250 cm and 10 cm above the road. The objective of this study is to establish how often these temperature differences develop, the size of the temperature differences close to the road surface, and the parameters that are important for the development of a large temperature difference. 4. Statistical analysis of temperature differences during different weather situations Large temperature gradients developed on several occasions between 10 cm and 250 cm above the road. A distribution of the temperature differences, between 10 cm and 250 cm above the road, ranges from 3.6 to 2 C for 99.9% of cases (extremes excluded). The corresponding figures for temperature differences between the road and its surroundings are 2.6 to 2.1 C at the 100 cm level and 2.2 to 1.1 C for the 250 cm level. As noted above, the dataset was classified according to wind and cloud data into nine weather types (Table 3). This enabled the weather type to be determined for occasions when large temperature differences develop. Figure 5 shows the distribution of temperature differences for each weather class for daytime and nighttime. The results are exemplified by the temperature differences recorded between 250 cm and 10 cm above the road (R250 R10) and also by the temperature differences between the road and its surroundings at the 100 cm and 250 cm levels (R100 S100 and R250 S250). The distribution within each weather class is shown with the median value together with the percentile and the 1 99 percentile. In Figure 5 it can be seen that the temperature difference, between the air layer above the road and the air layer above the surroundings, decreases with increasing wind speed and cloudiness. Increasing wind speed results in more turbulent mixing of the air and only small temperature variations. Increasing cloudiness decreases the incoming and outgoing radiation, which also results in small temperature variations. The temperature differences between various environments decrease with height and the smallest temperature differences are found at 250 cm. However, the decreasing trend with increasing cloudiness and wind speed is not clearly seen between the different levels above the road, indicating that other factors are more important in the development of temperature differences above the road surface. 5. Wind direction roughness and humidity sources Temperature variations during the different weather situations shown in the sections 3 and 4 could be the result of differences in humidity and temperature of the areas surrounding the test site. These areas comprise built-up area, forest, agricultural land and the Göta River with its wetlands. These surroundings, with their varying roughness and humidity sources, influence the air passing the test site. With certain wind directions, the differences in roughness and humidity of the surroundings compared with the road could be one cause of the temperature differences between levels in the air layer above the road. Grimmond (1994) and Schmid et al. (1991) classified urban areas according to their surface characteristics and used this to see how different source areas affected the parameters measured at their 389

6 J Bogren, T Gustavsson and M Karlsson Figure 5. Distribution of temperature differences for selected weather classes during night for (a) R250 S250, (b) R100 S100 and (c) R250 R10. (d), (e), (f) as (a), (b), (c) but for daytime. field tower. They highlighted the importance of knowing the surface characteristics of the surroundings in order to understand the variation in energy fluxes that can occur at a specific site. The area within a circle of 1 km radius around the test site was classified into nine sectors according to humidity content, roughness and land use. Temperature differences at the test site were thereafter compared with situations when the wind was blowing from these different areas. The nine areas are shown in Table 4 together with the corresponding wind direction, frequency of occasions when the wind came from this area, and temperature differences between 250 cm and 10 cm above the road. Regardless of land use, the result shows that large positive temperature differences occurred when the wind came from northerly to easterly directions. In southern Sweden these wind directions indicate either cold air masses from the north or high pressure areas, often resulting in clear, calm weather. The result therefore indicates that the temperature differences seem to be 390 more related to the weather situation than the humidity sources, thermal capacity and roughness of the areas surrounding the site. The roughness and humidity of the surroundings areas are, however, important for the development of temperature differences at the test site but it is necessary to construct a more detailed classification of the surrounding areas to see their influence. 6. Weather conditions during situations with large temperature gradients A detailed study of the weather conditions prevailing when large temperature gradients were recorded was performed to investigate the factors required for the development of such air temperature differences. Situations with temperature differences larger than 1 C, between R250 and R10, for more than 1 hour were chosen for the detailed study. The following parameters were chosen for each situation: date, temperature gradient in the road bed, cloudiness, wind speed, wind direction, preceding weather, temperature change, ambient air temperature, humidity and surface status.

7 Temperature differences in the air layer close to a road surface Table 4. Wind directions classified on the basis of roughness, humidity source and land use, and the temperature differences associated with this wind direction. Main land use Corresponding Percentage Range of wind direction situations temperature (deg.) difference R250 R10 ( C) Road (north) 358 to to +1.7 Road (south) 174 to to +0.2 Buildings 2 to to +1.6 Buildings and forest 30 to to +1.6 Forest, rock face 110 to to +0.9 Wetland, reeds (north) 350 to to +0.8 Wetland, reeds (south) 180 to to +1.1 Cultivated area and Göta River 194 to to to 350 Göta River, reeds 182 to to to 340 These parameters were compared with the time with temperature differences larger than 1 C and maximum temperature difference. Temperature differences larger than 1 C lasting more than 1 hour occurred on 28 occasions during the period studied. The occasions in April and May with a negative temperature gradient were excluded because only those occasions with a positive temperature gradient (i.e. lower temperatures close to the road surface) are of interest for this study. The results showed that the 28 occasions could be divided into three typical weather conditions: (a) Clear, calm weather with significant night-time cooling > 1 C h 1. (b) Calm conditions at the test site during the passage of a warm front >1 C h 1. (c) Situations with snow or ice on the road surface and ambient temperature 0 C. Table 5 shows the weather conditions for the three categories when temperature differences develop. The maximum temperature difference and the duration of the temperature difference are similar for categories (a) and (b). The largest differences develop when there is snow or ice on the road surface, and the temperature difference also persists for a longer period of time under these conditions. Although it is possible to distinguish three weather categories when large temperature differences develop, there are also occasions when these conditions do not produce large temperature differences. Figure 6 shows examples of the three categories compared with similar weather conditions when temperature differences are small. The figure shows the development of ambient temperature and the temperature difference between R250 and R10. In Figure 6(a) two cooling situations with clear, calm weather are shown. The wind direction was southerly, humidity was near 100% and the temperature difference between the road surface and at 30 cm in the road bed varied from 0 C around sunset to 7 C in the morning hours, for both situations. Despite the fact that the weather conditions were so similar, a large temperature difference was only established on January. The temperature difference increases when the cooling starts, and occurs in pulses thereafter. A second increase in temperature difference occurs at midnight. The cause for these temperature differences is dealt with in the next section. Figure 6(b) shows two situations when a warm front passes the area. Both situations are characterised by Table 5. Weather conditions during situations with large negative temperature gradient in the air layer close to the road surface: (a) cooling situation, ( b) passages of warm front, and (c) snow or ice on road surface. Max T a = maximum temperature difference between R250 and R10; W Class and PW Class = weather situation (based on the classification in Table 3) for each event and for the days preceding the event; C/W = cooling/warming. Weather Period Duration Max DT a W Class PW Class Wind speed Temperature Ambient air Total C/W condition (number of (h) ( C m 1 ) (m s 1 ) change temperature occasions) ( C h 1 ) ( C) ( C) (a) Dec Mar (14) < to 0 10 to to 11.5 (b) Nov Feb (6) , 4 9 < to to to +12 (c) Dec Mar (8) <2.0 0 to to

8 J Bogren, T Gustavsson and M Karlsson Figure 6. Temperature development and weather type during situations with large temperature differences compared with similar situations with small temperature differences. (a) Cooling, January 1998 and January (b) Passage of warm front, February 1998 and January (c) Snow on road surface, 3 5 March Figures 6(a) and 6(b) it can be seen that large temperature differences occur in pulses of minutes. Since temperatures were recorded every 10 minutes the pulses might actually be shorter than is shown in the figure. In Figure 6(c) only one example is shown since all situations with snow on the road surface and ambient temperature >0 C (i.e. melting snow) resulted in large temperature differences. The temperature difference starts to develop when the ambient temperature rises above 0 C and the snow starts to melt. The temperature difference develops because energy is required from the lowest air layers to melt the snow. clear weather followed by cloudy, calm weather at the passage of the warm front. The wind direction changes from northerly to southerly at the passage, humidity is close to 100% and wind speed less than 1.5 m s 1. The temperature difference in the roadbed changes from 6 C to 0 C. A temperature difference is established on January due to the passage of the warm front whereas on February the temperature differences decrease at the passage of the warm front. In both 392 The results in Figures 6(a) and 6(b) show that the temperature gradient in the air layer close to the road surface develops differently during apparently similar weather conditions. A comparison of the days with large temperature differences with protocols of the surface status showed that hoar frost was present each time a large temperature difference developed. Large temperature differences are clearly one of the factors important for hoar frost to develop at the road surface. A detailed study of a few hours during January 1998 when hoar frost formed on the road surface is

9 Temperature differences in the air layer close to a road surface Figure 7. (a) Temperature difference R250 R10, (b) temperature at 10, 100 and 250 cm, (c) net radiation at 100 cm and (d) absolute humidity at 10, 100 and 250 cm for January shown in Figure 7. The development of a temperature difference between R250 and R10 is shown together with the development of temperature and absolute humidity at 10 cm, 100 cm and 250 cm above the road and net radiation at 100 cm. It can be seen in Figure 7 that the development of temperature differences is closely linked to the exchange of water vapour in the lower air layers. The increase in temperature difference starts when warmer and more humid air is brought down to the surface i.e. when the temperature and humidity increase at 10 cm. The air is thereafter cooled by the surface, dew point is reached and hoar frost is deposited on the road surface, which results in a lowering of absolute humidity at 10 cm. This process is then repeated in the form of pulses of increasing/decreasing temperature (see Figure 7). This exchange in temperature and humidity between the road surface and air layers above is not seen as clearly in the higher levels where more turbulence and advection from other areas affect the air. Figure 8 shows the 10-minute change in absolute humidity plotted against the 10-minute temperature change at 10 cm and 250 cm above the road on January when hoar frost was formed on the road surface. The temperature and humidity changes are well correlated at the 10 cm level. At this level an increase in temperature is simultaneous with an increase in humidity (i.e. warm and humid air is transported down from the air layers above the road). The decrease in temperature and humidity is associated with deposition of hoar frost on the road surface. Energy is released when hoar frost is deposited but the amount is too small to be apparent from the temperature readings taken every 10 minutes. The 10-minute changes at 250 cm above the road are generally smaller due to greater turbulence and advection. This indicates that the measurements of temperature and humidity at 10 cm reflect the processes at the surface better than at the 250 cm level and that large temperature differences in the air layer close to the road surface are important for the development of hoar frost on the road surface. 7. Conclusions This study has shown that large temperature differences in the air layer close to the road surface are present during situations with high risk of slipperiness (i.e. there is hoar frost, snow or ice on the road surface). This result further confirms the need to measure tem- 393

10 J Bogren, T Gustavsson and M Karlsson most common during clear and partly clear weather conditions with weak winds. The differences varied from 0.5 to +1.7 C at night and from 1.2 to +1.4 C during the day. (b) The temperature difference between the road and its surroundings decreased with increasing cloudiness and wind speed. It also decreased with height above the surface. (c) Temperature differences were not influenced to any great degree by differences in roughness, humidity and thermal capacity of the surrounding areas but rather by weather situations typical of certain wind directions. (d) The situations when large temperature differences develop in the air layer close to the road surface can be divided into three weather types: cooling situations during clear, calm weather; advection of warm air during the passage of fronts; and situations with snow or ice on the road surface. Large temperature differences thus occur during situations with a high risk of slipperiness. (e) The development of large temperature differences is associated with the exchange of temperature and humidity close to the road surface. At 10 cm above the road, changes in temperature and humidity are well correlated, whereas at higher levels turbulence and advection have a large influence and temperature and humidity readings do not reflect the processes at the road surface. Figure 8. Changes in absolute humidity plotted every 10 minutes against the corresponding change in temperature at (a) 10 cm and (b) 250 cm above the road on January perature at a place and a height that will be representative of the processes occurring at the road surface. Further studies will focus on the amount of hoar frost that is developed during different weather situations, and whether the deposited amount can be derived from the parameters presently measured at an RWiS station or if additional parameters or measuring levels are necessary for the correct prediction of hoar frost on the road surface. Several important conclusions can be drawn from these results of this study. (a) The statistical analyses of temperature gradients show that large temperature differences, measured between 250 cm and 10 cm above the road, were 394 The results from this study shows that the real situation is very complex compared with what is often assumed in theoretical discussions. As Chen et al. (1999) state, the influence of the road surface on the boundary layer close to the ground has implications for the complexity of the model dealing with calculations of the vertical temperature profiles. A further study will focus on the possibilities of using observational data to establish a parametric model for the vertical eddy fluxes in the atmosphere above a road surface. Acknowledgements Thanks to Professor Sven Lindqvist for his valuable comments, to Hans Alter for his help with the technical equipment, and to Susan Cornell for linguistic revision. This research has been funded by the Swedish National Road Administration. Grants have also been received from the Swedish Society of Anthropology and Geography (SSAG), Anna Ahrenberg Foundation, Hierta Retzius Foundation, Lars Hierta Foundation and Adlerbertska Foundation. References Bogren, J., Gustavsson, T. & Lindqvist, S. (1992) A description of a local climatological model used to predict temperature variations along stretches of road. Meteorol. Mag., 121:

11 Temperature differences in the air layer close to a road surface Chen, D., Gustavsson, T. & Bogren, J. (1999) The applicability of similarity theory to a road surface. Meteorol. Appl., 6: Gustavsson, T. & Bogren, J. (1989) Modeling of local climate for prediction of road slipperiness. Phys. Geog., 10: Gustavsson, T. & Bogren, J. (1990) Road slipperiness during warm air advection. Meteorol. Mag., 119: Gustavsson, T. & Bogren, J. (1993) Evaluation of a local climatological model test carried out in the county of Halland, Sweden. Meteorol. Mag., 122: Grimmond, S. (1994) Surface description for urban climate studies: A GIS-based methodology. Geocarto International, 1: Jensen, N. O. (1985) Micrometeorological techniques applied to the prediction of road icing. In Proc.of Second International Road Weather Conference, Copenhagen, Parmenter, B. S. & Thornes, J. E. (1986) The use of a computer model to predict the formation of ice on road surfaces. Research Report 71, Transport and Road Research Laboratory, Department of Transport, Crowthorne, Berkshire RG11 6AU. Rayer, P. J. (1987) The Meteorological Office forecast road surface temperature model. Meteorol. Mag., 116: Roodenburg, J. (1984) Forecasting road surface minimum temperatures. Meteorol. Mag., 113: Sass, B. H. (1992) A numerical model for prediction of road temperature and ice. J. Appl. Meteorol., 31: Sass, B. H. (1997) A numerical forecasting system for the prediction of slippery roads. J. Appl. Meteorol., 36: Schmid, H. P., Cleugh, H. A., Grimmond, C. S. B. & Oke, T. R. (1991) Spatial variability of energy fluxes in suburban terrain. Bound. Layer Meteorol., 54: Shao, J. & Lister, P. J. (1996) An automated nowcasting model of road surface temperature and state for winter road maintenance. J. Appl. Meteorol., 35: