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During the Convective Storm Initiation Project experiment, which was conducted in summer 2005 in southern England, vertical velocity in the convective boundary layer (CBL) was measured simultaneously with a research aircraft and a wind lidar. The aircraft performed horizontal flight legs approximately parallel to the prevailing wind direction and centered over the lidar. This measurement setup allows for the comparing of CBL characteristics (CBL depth zi, integral length scale lw, spectral peak wavelength λm, and vertical velocity variance σ w 2 ) from temporal (lidar) and spatial (aircraft) measurements. For this, the lidar time series are transferred into space using the mean wind. While the statistics of the aircraft data are all based on the 34-km flight legs, the averaging interval for the lidar is either 1 h or a longer period that corresponds to the 34-km leg. Although the lw and λm values from aircraft and lidar measurements are in the same range (100–200 and 500–2000 m) and agree well on the average, the correlation for individual legs is very low (R2 < 0.17). One possible explanation is the large uncertainty that arises from the transfer of the lidar time series to space. For σ w 2 , the agreement between aircraft and lidar is better for individual legs (R2 ≥ 0.63), but the mean absolute difference in σ w 2 is about 2.5 times as large as the statistical error. We examine the nonstationarity and heterogeneity for the lidar and aircraft samples and can exclude these as the major sources for the large differences between lidar and aircraft data. [ABSTRACT FROM AUTHOR]

Abstract: To optimise the placement of small wind turbines in urban areas a detailed understanding of the spatial variability of the wind resource is required. At present, due to a lack of observations, the NOABL wind speed database is frequently used to estimate the wind resource at a potential site. However, recent work has shown that this tends to overestimate the wind speed in urban areas. This paper suggests a method for adjusting the predictions of the NOABL in urban areas by considering the impact of the underlying surface on a neighbourhood scale. In which, the nature of the surface is characterised on a 1km2 resolution using an urban morphology database. The model was then used to estimate the variability of the annual mean wind speed across Greater London at a height typical of current small wind turbine installations. Initial validation of the results suggests that the predicted wind speeds are considerably more accurate than the NOABL values. The derived wind map therefore currently provides the best opportunity to identify the neighbourhoods in Greater London at which small wind turbines yield their highest energy production. The model does not consider street scale processes, however previously derived scaling factors can be applied to relate the neighbourhood wind speed to a value at a specific rooftop site. The results showed that the wind speed predicted across London is relatively low, exceeding 4ms−1 at only 27% of the neighbourhoods in the city. Of these sites less than 10% are within 10km of the city centre, with the majority over 20km from the city centre. Consequently, it is predicted that small wind turbines tend to perform better towards the outskirts of the city, therefore for cities which fit the Burgess concentric ring model, such as Greater London, ‘distance from city centre’ is a useful parameter for siting small wind turbines. However, there are a number of neighbourhoods close to the city centre at which the wind speed is relatively high and these sites can only been identified with a detailed representation of the urban surface, such as that developed in this study. [Copyright &y& Elsevier]

We present one year of data from the first continuous measurements of carbon dioxide mixing ratio in central London. Measurements were made at an 87m tower site using the new Vaisala CARBOCAP GMP343 instrument, which was found to provide a compact and inexpensive method for mixing ratio monitoring, in an environment where conventional CO2 sensors could not be accommodated. Measurements were compared with a monitoring site outside London, showing that the city''s CO2 “dome” was an order of magnitude smaller than measured at lower levels in other cities. During the night time in the summer, the mixing ratio in central London was found to be significantly lower than at the rural site. This was thought to be explained by the proximity of biogenic sources to the rural sensor, differences between urban and rural mixing heights and/or the interception of a vertical mixing ratio gradient at two different measurement heights. Estimation of the CO2 loading of the air entering the city therefore proved problematic during the summer. As a result, we propose that monitoring of CO2 emission rate using this type of measurement may only be possible in the winter when the influence of these factors is minimal. [Copyright &y& Elsevier]

The aim of this work is to present experimentally evaluated effective roughnesses (zoe) of a partly forested landscape. Although the ratio of boundary-layer height to obstacle size was only of the order of 50, there still seemed to exist a height range of 75–200 m where surface-layer similarity was approximately valid. Attempts were made to use conventional wind profile analysis to evaluate zoe, but the small height range and the large number of variables initially led to unacceptable uncertainties. Fixing the displacement height zd, rather than fitting it, reduced the data scatter to an acceptable level. The profile-derived roughness lengths zop obtained in this way were in good agreement with previous work, and with an alternative roughness length estimate zof for which flux-derived profile parameters u* and θ* were used. This implies that the profile-derived roughnesses were consistent with the measured surface-layer momentum flux. Comparison of both roughness estimates also yielded an improved estimate of the displacement height. Besides this, the authors tested a landscape roughness evaluation method which makes use of the gustiness parameter Tu = σu/U in the surface layer. The results obtained by this method were in fair agreement with the profile-derived data. In previous work, the gustiness method was advocated because it could be used at relatively low levels, perhaps even within the roughness sub-layer. At the present measuring site, this was not the case as the gustiness method was only valid in an approximate way, and for a limited height range. [ABSTRACT FROM AUTHOR]

Various models for calculating the effective or area-averaged roughness length zoe have been tested for a partly forested area. Three types of model are considered: the tile approach for very large scales of inhomogeneity (> 20 km), drag models for very small scales (up to 1 km), and surface-layer methods such as the blending-height method for intermediate scales. Over partly forested areas, where both pressure effects and roughness sub-layer effects may become significant, small-scale models are expected be the most suitable type of model. The various model types were tested against new experimental data that were obtained over the partly forested Sherwood Forest area (UK). The best fit with the data was obtained with the blending-height method, rather than with the different small-scale models. This is remarkable as the surface-layer assumptions of the blending-height method were clearly violated: the calculated blending height was 7 m, as compared to the mean tree height of 20 m. Of the small-scale models, a sparse-canopy approach compared poorly with the experimental data. The drag models overestimated the area-averaged roughness to a lesser degree, but a major point of concern remains the choice of the model parameters. Therefore, suggestions are made for an improved choice of these parameters. [ABSTRACT FROM AUTHOR]