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A nocturnal cooling rate model (NOCRAM) to simulate nocturnal air temperature at urban sites is presented. The model is designed for urban planners, practitioners and researchers who demand meteorological information for urban planning and research applications. The model is based on the concept of nocturnal cooling, progressing in two distinct phases, i.e. site-dependent cooling around sunset and site-independent cooling from about 1 or 2 h after sunset until sunrise. Cooling rates are usually determined predominantly by prevailing weather conditions (i.e. clearness of the sky and wind speed), followed by maximum daily air temperature and by sky view factors. Second phase cooling is chiefly determined by sky clearness and wind speed. The findings and statistical results from the analysis of observational data during warm months (May–September) from Gothenburg, Sweden, as well as from past studies, were used. The model requires standard meteorological variables (i.e. wind speed, incoming short-wave radiation, air temperature, relative air humidity, air pressure) at a reference station as well as geometrical information (i.e. the sky view factor of the site and the geographical co-ordinates of the reference meteorological station). The model simulates the characteristic development of cooling rates in the two phases at open sites and built-up sites with different sky view factors under a wide range of weather conditions in warm months. Using the modelled cooling rates, nocturnal air temperature is estimated easily with the accuracy of root mean square error (RMSE) ≤1.54 °C and R2 ≥0.78.

Site-specific meteorological forcing appropriate for applications such as urban outdoor thermal comfort simulations can be obtained using a newly coupled scheme that combines a simple slab convective boundary layer (CBL) model and urban land surface model (ULSM) (here two ULSMs are considered). The former simulates daytime CBL height, air temperature and humidity, and the latter estimates urban surface energy and water balance fluxes accounting for changes in land surface cover. The coupled models are tested at a suburban site and two rural sites, one irrigated and one unirrigated grass, in Sacramento, U.S.A. All the variables modelled compare well to measurements (e.g. coefficient of determination=0.97 and root mean square error=1.5°C for air temperature). The current version is applicable to daytime conditions and needs initial state conditions for the CBL model in the appropriate range to obtain the required performance. The coupled model allows routine observations from distant sites (e.g. rural, airport) to be used to predict air temperature and relative humidity in an urban area of interest. This simple model, which can be rapidly applied, could provide urban data for applications such as air quality forecasting and building energy modelling, in addition to outdoor thermal comfort.

Wind is a complex phenomenon and a critical factor in assessing climatic conditions and pedestrian comfort within cities. To obtain spatial information on near-ground wind speed, 3D computational fluid dynamics (CFD) modelling is often used. This is a computationally intensive method which requires extensive computer resources and is time consuming. By using a simpler 2D method, larger areas can be processed and less time is required. This study attempts to model the relationship between near-ground wind speed and urban geometry using 2.5D raster data and variable selection methods. Such models can be implemented in a geographic information system (GIS) to assess the spatial distribution of wind speed at street level in complex urban environments at scales from neighbourhood to city. Wind speed data, 2 m above ground, is obtained from simulations by CFD modelling and used as a response variable. A number of derivatives calculated from high-resolution digital surface models (DSM) are used as potential predictors. A sequential variable selection algorithm followed by all-possible subset regression was used to select candidate models for further evaluation. The results show that the selected models explain general spatial wind speed pattern characteristics but the prediction errors are large, especially so in areas with high wind speeds. However, all selected models did explain 90 % of the wind speed variability (R2 ≈ 0.90). Predictors adding information on width and height ratio and alignment of street canyons with respect to wind direction are suggested for improving model performance. To assess the applicability of any derived model, the results of the CFD model should be thoroughly evaluated against field measurements.

The effect of variations in land cover on mean radiant temperature (T mrt ) is explored through a simple scheme developed within the radiation model SOLWEIG. Outgoing longwave radiation is parameterised using surface temperature observations on a grass and an asphalt surface, whereas outgoing shortwave radiation is modelled through variations in albedo for the different surfaces. The influence of ground surface materials on T mrt is small compared to the effects of shadowing. Nevertheless, altering ground surface materials could contribute to a reduction in T mrt to reduce the radiant load during heat-wave episodes in locations where shadowing is not an option. Evaluation of the new scheme suggests that despite its simplicity it can simulate the outgoing fluxes well, especially during sunny conditions. However, it underestimates at night and in shadowed locations. One grass surface used to develop the parameterisation, with very different characteristics compared to an evaluation grass site, caused T mrt to be underestimated. The implications of using high temporal resolution (e.g. 15 minutes) meteorological forcing data under partly cloudy conditions are demonstrated even for fairly proximal sites.

We investigate the spatial characteristics of urban-like canopy flow by applying particle image velocimetry (PIV) to atmospheric turbulence. The study site was a Comprehensive Outdoor Scale MOdel (COSMO) experiment for urban climate in Japan. The PIV system captured the two-dimensional flow field within the canopy layer continuously for an hour with a sampling frequency of 30 Hz, thereby providing reliable outdoor turbulence statistics. PIV measurements in a wind-tunnel facility using similar roughness geometry, but with a lower sampling frequency of 4 Hz, were also done for comparison. The turbulent momentum flux from COSMO, and the wind tunnel showed similar values and distributions when scaled using friction velocity. Some different characteristics between outdoor and indoor flow fields were mainly caused by the larger fluctuations in wind direction for the atmospheric turbulence. The focus of the analysis is on a variety of instantaneous turbulent flow structures. One remarkable flow structure is termed 'flushing', that is, a large-scale upward motion prevailing across the whole vertical cross-section of a building gap. This is observed intermittently, whereby tracer particles are flushed vertically out from the canopy layer. Flushing phenomena are also observed in the wind tunnel where there is neither thermal stratification nor outer-layer turbulence. It is suggested that flushing phenomena are correlated with the passing of large-scale low-momentum regions above the canopy.

A method for measuring the two-dimensional distribution of wind velocity vectors near a surface exposed to solar radiation, by tracking brightness temperature images instead of particle images, is proposed. It is based on time-sequential thermography with the algorithm used for particle image velocimetry. This thermal image velocimetry (TIV) was tested on a full-scale building wall covered by polystyrene boards attached side-by-side over a vertically elongated area measuring 22.2 m by 2.73 m. A thermal infrared camera was installed 8 m from the test wall to capture the wall-surface temperature at 30 Hz frequency. A sonic anemometer was also installed 35 mm from the surface used for validation of the TIV. The advection velocity estimated from thermal infrared imagery had a linear relationship with the wind velocity measured by the sonic anemometer, irrespective of the wind speed and direction. This linear slope was multiplied by the advection velocity of the thermal infrared image to rescale it to the wind velocity, and the term ‘TIV velocity’ was then used. A histogram and power spectra of the TIV velocity showed quantitatively good agreement with the velocity measured by the sonic anemometer, except for the high-frequency region of the spectra, where the TIV velocity was overestimated compared with that of the sonic anemometer. The method was also tested on ground covered by artificial turf to demonstrate its application to a horizontal plane with a wider area, extending for more than 80 m by 60 m.