Nocturnal air and road surface temperature variations in complex terrain

Abstract

This paper is part of an ongoing project dealing with the modelling of local climate for predicting temperature variations and risks of road slipperiness under various synoptic conditions. Temperature recordings from mobile measurements taken along road stretches have been analysed to determine the influence of valleys on the variation in air and road surface temperatures. During clear, calm nights, the variation in air temperature between valley bottoms and surrounding areas can be related to geometric properties of valleys, such as depth and width. It is seen that temperature differences between valleys and surrounding areas increase with increasing depth and width. The prevailing wind speed has been found to be a major factor controlling the variation in temperature. The variation in air temperature is totally smoothed out in situations in which there is an ambient wind speed exceeding 3 ms-'. In the interval 2-3 ms-', the degree of wind exposure in valleys is of importance for the magnitude of the air temperature differences. Counter-radiation from clouds has been found to significantly reduce the intensity of cold air pools. Under partly cloudy situations (3-5 octas) with no wind, the temperature difference between valley bottoms and surrounding areas differs by approximately 6°C in comparison with clear, calm situations. The relationship between differences in air and road surface temperature has also been studied. In general, an increase in cold air pool intensity of 1°C lowers the road surface temperature by 0~4°C. KEY WORDS Topoclimate Valley Road surface temperature Cold air pool

Transforming Image-Objects into Multiscale Fields: A GEOBIA Approach to Mitigate Urban Microclimatic Variability within H-Res Thermal Infrared Airborne Flight-Lines

“…These included: (i) Splines [35], (ii) Nearest Neighborhood [36], (iii) Polynomial [37], (iv) Kriging [38], (v) Inverse Distance Weighted (IDW), (vi) Triangular Integrated Network (TIN) [39], and (vii) Radial Basis Function (RBF) [40]. Based on our visual and statistical assessment of the resulting surfaces, IDW produced the smoothest appearing surface based on locally varying values; which is consistent with the conceptual models of locally explicit, but regionally continuous microclimatic variability [29,30]. Therefore, we have used IDW interpolation for the remainder of this analysis.…”

“…This is because: (i) roads are relatively well distributed over modern urban environments, (ii) their primary construction materials are generally the same for different major road types within a given city, thus providing consistent thermal properties [28], and (iii) previous research has revealed a strong correlation between night-time air temperature and road surface temperature [29,30], from which we assume that the road temperature can be used to model urban microclimatic variability in terms of energy flux.…”

A simple height-based correction for temperature downscaling in complex terrain

“…Gustavsson, 1991, Gustavsson et al, 1998). The noticeable increase in scatter in Figure 4(b) is probably due to cold air pooling in stable night time conditions, which is more directly related to local topography than elevation above sea level (Bogren and Gustavsson, 1991;Gustavsson, 1999;Bogren et al, 2000). A more detailed study of observed night time γ as a function of cloud cover and wind was performed for the Devon stations by compiling γ values as implied by the slopes of plots such as Figures 4(a) and (b) constructed for nights in winter 2006-2007.…”

The use of sequential satellite images in forecasting road‐surface temperatures

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